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Why Your AI Projects Fail (You Can't Fire AI) · Private Equity Data Guy

• 0:00
  Seasonality
• 0:02
  is
• 0:03
  incredibly
• 0:04
  important.
• 0:05
  And
• 0:06
  this
• 0:06
  is
• 0:06
  obvious
• 0:07
  if
• 0:07
  you
• 0:07
  think
• 0:07
  about
• 0:07
  it,
• 0:08
  even
• 0:08
  for
• 0:08
  a
• 0:08
  couple
• 0:08
  of
• 0:08
  seconds,
• 0:09
  right.
• 0:09
  When
• 0:09
  do
• 0:09
  you
• 0:10
  want
• 0:10
  to
• 0:10
  stock
• 0:10
  shovels
• 0:11
  and
• 0:11
  snowblowers
• 0:12
  in
• 0:12
  your
• 0:12
  store?
• 0:13
  It's
• 0:14
  when
• 0:14
  it's
• 0:15
  right
• 0:15
  before
• 0:15
  snowing
• 0:16
  season.
• 0:16
  There's
• 0:16
  a
• 0:17
  joke
• 0:17
  that
• 0:18
  whenever
• 0:18
  something
• 0:19
  in
• 0:19
  AI
• 0:20
  gets
• 0:20
  solved,
• 0:20
  they
• 0:21
  call
• 0:21
  it
• 0:21
  machine
• 0:21
  learning.
• 0:22
  Left
• 0:22
  my
• 0:22
  spouse
• 0:23
  because
• 0:23
  my
• 0:23
  AI
• 0:24
  girlfriend
• 0:24
  was
• 0:24
  like,
• 0:25
  better,
• 0:25
  stuff
• 0:25
  like
• 0:25
  that,
• 0:26
  right?
• 0:26
  Yeah,
• 0:26
  she
• 0:26
  told
• 0:26
  me
• 0:27
  to.
• 0:28
  As
• 0:28
  an
• 0:28
  employee,
• 0:28
  you
• 0:28
  still
• 0:29
  need
• 0:29
  to
• 0:29
  be
• 0:29
  responsible
• 0:30
  for,
• 0:30
  for,
• 0:31
  or
• 0:31
  accountable
• 0:31
  for
• 0:32
  what
• 0:32
  comes
• 0:32
  out
• 0:33
  of
• 0:33
  that
• 0:33
  AI.
• 0:33
  I've
• 0:34
  joked
• 0:34
  that,
• 0:34
  you
• 0:34
  know,
• 0:35
  there
• 0:35
  are
• 0:35
  these
• 0:35
  articles
• 0:36
  you
• 0:36
  can
• 0:36
  read
• 0:36
  online
• 0:37
  that
• 0:37
  says
• 0:37
  in
• 0:37
  the
• 0:38
  future
• 0:38
  you're
• 0:38
  going
• 0:38
  to
• 0:38
  have
• 0:39
  10,000
• 0:39
  AI
• 0:40
  coworkers
• 0:40
  or,
• 0:41
  you
• 0:41
  know,
• 0:41
  10,000
• 0:42
  AIs
• 0:42
  are
• 0:42
  going
• 0:42
  to,
• 0:43
  you
• 0:43
  know,
• 0:43
  you're
• 0:43
  going
• 0:43
  to
• 0:43
  be
• 0:44
  the
• 0:44
  manager
• 0:44
  of
• 0:44
  a
• 0:44
  thousand
• 0:45
  AIs.
• 0:45
  The
• 0:46
  problem
• 0:46
  is
• 0:47
  I
• 0:47
  can't
• 0:48
  fire
• 0:48
  any
• 0:48
  of
• 0:49
  those
• 0:49
  AIs.
• 0:49
  I
• 0:49
  can't
• 0:50
  put
• 0:50
  those
• 0:50
  AIs
• 0:51
  on
• 0:51
  a
• 0:51
  performance
• 0:52
  plan
• 0:52
  or
• 0:52
  a
• 0:52
  coaching
• 0:53
  plan.
• 0:53
  You're
• 0:54
  listening
• 0:54
  to
• 0:54
  the
• 0:54
  Transformed
• 0:55
  with
• 0:55
  Data
• 0:55
  podcast
• 0:56
  with
• 0:56
  Graham
• 0:56
  Crawford,
• 0:57
  CEO
• 0:58
  of
• 0:58
  Crawford
• 0:58
  McMillan.
• 0:59
  Graham
• 0:59
  is
• 1:00
  here
• 1:00
  to
• 1:00
  share
• 1:00
  something
• 1:00
  he's
• 1:01
  genuinely
• 1:01
  passionate
• 1:02
  about.
• 1:02
  He's
• 1:02
  going
• 1:02
  to
• 1:02
  show
• 1:03
  you
• 1:03
  how
• 1:03
  data
• 1:03
  can
• 1:04
  completely
• 1:04
  change
• 1:04
  the
• 1:05
  outcome
• 1:05
  for
• 1:05
  both
• 1:05
  people
• 1:06
  and
• 1:06
  businesses.
• 1:07
  In
• 1:07
  each
• 1:07
  episode,
• 1:07
  he
• 1:08
  sits
• 1:08
  down
• 1:08
  with
• 1:08
  real
• 1:09
  people
• 1:09
  who've
• 1:09
  done
• 1:09
  incredible
• 1:10
  things
• 1:10
  with
• 1:10
  data.
• 1:11
  But
• 1:11
  don't
• 1:11
  worry,
• 1:12
  these
• 1:12
  aren't
• 1:12
  your
• 1:13
  typical
• 1:13
  dry
• 1:13
  case
• 1:14
  studies.
• 1:14
  Graham
• 1:15
  and
• 1:15
  his
• 1:15
  guests
• 1:15
  bring
• 1:15
  you
• 1:16
  stories
• 1:16
  about
• 1:16
  leaders
• 1:17
  and
• 1:17
  innovators
• 1:17
  who
• 1:18
  saw
• 1:18
  something
• 1:18
  in
• 1:18
  their
• 1:18
  data
• 1:19
  that
• 1:19
  sparked
• 1:19
  a
• 1:19
  brand
• 1:20
  new
• 1:20
  reality.
• 1:21
  These
• 1:21
  are
• 1:21
  changes
• 1:22
  that
• 1:22
  tore
• 1:22
  through
• 1:22
  entire
• 1:23
  industries,
• 1:24
  upended
• 1:24
  company
• 1:25
  cultures,
• 1:25
  and
• 1:25
  sometimes
• 1:26
  even
• 1:26
  changed
• 1:27
  lives.
• 1:28
  So
• 1:28
  whether
• 1:28
  you're
• 1:28
  a
• 1:28
  data
• 1:29
  enthusiast
• 1:29
  or
• 1:30
  just
• 1:30
  curious
• 1:31
  about
• 1:31
  how
• 1:31
  to
• 1:31
  find
• 1:31
  the
• 1:32
  truth
• 1:32
  in
• 1:32
  your
• 1:32
  data,
• 1:33
  join
• 1:33
  Graham
• 1:34
  as
• 1:34
  he
• 1:34
  discovers
• 1:35
  how
• 1:35
  data
• 1:35
  becomes
• 1:35
  more
• 1:36
  than
• 1:36
  just
• 1:36
  numbers.
• 1:37
  It
• 1:38
  becomes
• 1:38
  the
• 1:38
  spark
• 1:38
  that
• 1:39
  ignites
• 1:39
  real,
• 1:40
  meaningful
• 1:40
  change.
• 1:41
  Let's
• 1:42
  get
• 1:42
  started.
• 1:42
  Thanks
• 1:43
  for
• 1:43
  listening.
• 1:43
  Most
• 1:44
  AI
• 1:44
  and
• 1:44
  machine
• 1:45
  learning
• 1:45
  projects
• 1:45
  don't
• 1:46
  fail
• 1:46
  because
• 1:46
  the
• 1:46
  models
• 1:47
  are
• 1:47
  bad.
• 1:48
  They
• 1:48
  fail
• 1:48
  because
• 1:49
  no
• 1:49
  one
• 1:49
  connects
• 1:50
  math
• 1:50
  to
• 1:50
  the
• 1:50
  messy
• 1:51
  reality
• 1:51
  of
• 1:51
  human
• 1:52
  behavior.
• 1:52
  Scott
• 1:52
  Golda
• 1:53
  has
• 1:53
  spent
• 1:53
  his
• 1:53
  career
• 1:54
  fixing
• 1:54
  that
• 1:54
  disconnect.
• 1:55
  He's
• 1:55
  a
• 1:56
  sociologist
• 1:56
  by
• 1:56
  training,
• 1:57
  now
• 1:57
  senior
• 1:58
  director
• 1:58
  of
• 1:58
  Data
• 1:58
  Science
• 1:58
  at
• 1:59
  the
• 1:59
  Home
• 1:59
  Depot,
• 1:59
  where
• 2:00
  his
• 2:00
  team
• 2:00
  powers
• 2:01
  the
• 2:01
  algorithms
• 2:01
  behind
• 2:02
  one
• 2:02
  of
• 2:02
  the
• 2:02
  world's
• 2:03
  top
• 2:03
  five
• 2:03
  E
• 2:04
  commerce
• 2:04
  platforms.
• 2:05
  Before
• 2:05
  that,
• 2:05
  he
• 2:06
  helped
• 2:06
  scale
• 2:06
  data
• 2:06
  science
• 2:07
  at
• 2:07
  Capital
• 2:07
  One.
• 2:07
  In
• 2:08
  this
• 2:08
  episode,
• 2:08
  Scott
• 2:09
  breaks
• 2:09
  down
• 2:09
  how
• 2:10
  to
• 2:10
  build
• 2:10
  data
• 2:10
  teams
• 2:11
  that
• 2:11
  blend
• 2:11
  academic
• 2:12
  depth
• 2:12
  with
• 2:12
  real
• 2:13
  world
• 2:13
  traction
• 2:14
  and
• 2:14
  what
• 2:14
  it
• 2:14
  really
• 2:14
  takes
• 2:15
  to
• 2:15
  make
• 2:15
  machine
• 2:15
  learning
• 2:16
  and
• 2:16
  AI
• 2:17
  trustworthy
• 2:18
  at
• 2:18
  scale.
• 2:18
  So
• 2:19
  let's
• 2:19
  get
• 2:19
  into
• 2:19
  it.
• 2:19
  Here's
• 2:20
  Scott
• 2:20
  Golder.
• 2:20
  Welcome,
• 2:21
  Scott.
• 2:21
  Thank
• 2:21
  you
• 2:21
  so
• 2:22
  much
• 2:22
  for
• 2:22
  coming
• 2:22
  on.
• 2:22
  Graham.
• 2:23
  Thank
• 2:23
  you
• 2:23
  so
• 2:23
  much
• 2:23
  for
• 2:23
  having
• 2:23
  me.
• 2:24
  Home
• 2:24
  Depot
• 2:25
  really
• 2:25
  is
• 2:25
  one
• 2:25
  of
• 2:26
  the
• 2:26
  top
• 2:26
  five
• 2:26
  E
• 2:27
  commerce
• 2:27
  platforms.
• 2:27
  There's
• 2:28
  so
• 2:28
  many
• 2:28
  questions
• 2:29
  I
• 2:29
  could
• 2:29
  ask
• 2:29
  about
• 2:30
  it.
• 2:30
  But
• 2:30
  I
• 2:30
  want
• 2:31
  to
• 2:31
  start
• 2:31
  with
• 2:31
  your
• 2:32
  background
• 2:33
  and
• 2:33
  this
• 2:33
  blend
• 2:33
  of
• 2:34
  academia
• 2:35
  with
• 2:35
  business
• 2:35
  results.
• 2:36
  How
• 2:36
  do
• 2:37
  you
• 2:38
  come
• 2:38
  up
• 2:38
  with
• 2:39
  the
• 2:39
  right
• 2:39
  blend
• 2:39
  of
• 2:40
  academic
• 2:40
  curiosity
• 2:41
  and
• 2:42
  business
• 2:42
  reality
• 2:42
  when
• 2:43
  you're
• 2:43
  putting
• 2:43
  data
• 2:43
  science
• 2:44
  teams
• 2:44
  together?
• 2:44
  Yeah,
• 2:45
  it
• 2:45
  took
• 2:45
  me
• 2:46
  a
• 2:46
  long
• 2:46
  time
• 2:47
  to
• 2:47
  realize
• 2:47
  this,
• 2:48
  frankly,
• 2:48
  but
• 2:49
  I've
• 2:49
  observed
• 2:50
  that
• 2:50
  the
• 2:50
  deeper
• 2:51
  the
• 2:51
  academic
• 2:52
  background
• 2:53
  may
• 2:53
  be,
• 2:53
  not
• 2:54
  the
• 2:54
  better
• 2:55
  fit
• 2:55
  as
• 2:56
  a
• 2:56
  data
• 2:56
  scientist.
• 2:58
  So
• 2:58
  I
• 2:58
  have
• 2:59
  been
• 2:59
  privileged
• 3:00
  to
• 3:00
  work
• 3:00
  with
• 3:00
  a
• 3:01
  very
• 3:01
  large
• 3:01
  number
• 3:02
  of
• 3:03
  data
• 3:03
  scientists
• 3:04
  over
• 3:04
  time
• 3:04
  who
• 3:04
  have
• 3:05
  a
• 3:05
  wide
• 3:05
  range
• 3:07
  of
• 3:07
  academic
• 3:08
  backgrounds.
• 3:08
  And
• 3:09
  that's
• 3:09
  not
• 3:09
  just
• 3:10
  the
• 3:10
  disciplines
• 3:10
  that
• 3:11
  they've
• 3:11
  been
• 3:11
  trained
• 3:11
  in,
• 3:11
  but
• 3:12
  really
• 3:12
  how
• 3:13
  long
• 3:13
  they
• 3:13
  have
• 3:13
  spent
• 3:14
  in
• 3:14
  their
• 3:14
  academic
• 3:15
  career.
• 3:15
  So
• 3:16
  some
• 3:16
  people
• 3:16
  have
• 3:18
  finished
• 3:18
  their
• 3:18
  undergrad
• 3:19
  and
• 3:19
  had
• 3:20
  a
• 3:20
  whole
• 3:20
  bunch
• 3:20
  of
• 3:20
  professional
• 3:21
  experience
• 3:22
  and
• 3:22
  they're
• 3:22
  amazing
• 3:23
  data
• 3:23
  scientists.
• 3:24
  Typically
• 3:24
  what
• 3:25
  I
• 3:25
  see
• 3:25
  is
• 3:25
  people
• 3:25
  have
• 3:27
  some
• 3:27
  sort
• 3:27
  of
• 3:27
  masters
• 3:28
  in
• 3:29
  technical
• 3:29
  discipline.
• 3:30
  And
• 3:30
  then
• 3:31
  of
• 3:31
  course
• 3:31
  there
• 3:31
  are
• 3:31
  people
• 3:31
  who
• 3:32
  have
• 3:33
  spent
• 3:34
  years
• 3:34
  getting
• 3:34
  PhDs
• 3:35
  in
• 3:36
  wide
• 3:36
  variety
• 3:36
  of
• 3:37
  disciplines.
• 3:37
  So
• 3:38
  you
• 3:38
  mentioned
• 3:39
  earlier,
• 3:39
  I'm
• 3:40
  a
• 3:40
  sociologist
• 3:41
  and
• 3:41
  my
• 3:41
  background
• 3:42
  before
• 3:42
  that
• 3:42
  was
• 3:42
  actually
• 3:43
  in
• 3:43
  linguistics
• 3:43
  and
• 3:44
  computer
• 3:44
  science,
• 3:45
  which
• 3:46
  the
• 3:46
  linguistics
• 3:47
  part
• 3:47
  of
• 3:47
  it
• 3:47
  is
• 3:47
  mostly
• 3:48
  good
• 3:48
  for,
• 3:49
  you
• 3:49
  know,
• 3:49
  boring
• 3:49
  cocktail
• 3:50
  party
• 3:50
  conversations
• 3:51
  and
• 3:51
  stuff
• 3:51
  like
• 3:52
  that
• 3:52
  at
• 3:52
  this
• 3:52
  point.
• 3:53
  But
• 3:54
  I've
• 3:54
  seen
• 3:54
  data
• 3:55
  scientists
• 3:56
  have,
• 3:56
  you
• 3:56
  know,
• 3:56
  more
• 3:56
  traditional
• 3:57
  backgrounds
• 3:58
  in
• 3:58
  statistics
• 3:58
  and
• 3:59
  computer
• 3:59
  science
• 3:59
  and
• 3:59
  things
• 4:00
  like
• 4:00
  that.
• 4:00
  A
• 4:00
  lot
• 4:00
  of
• 4:01
  physics,
• 4:01
  a
• 4:02
  lot
• 4:02
  of
• 4:02
  biology.
• 4:03
  I
• 4:03
  joke.
• 4:04
  I
• 4:04
  have
• 4:04
  had
• 4:04
  people
• 4:04
  on
• 4:04
  my
• 4:05
  teams
• 4:05
  who
• 4:05
  are
• 4:06
  literally
• 4:06
  former
• 4:07
  rocket
• 4:07
  scientists.
• 4:08
  Wow.
• 4:08
  And
• 4:09
  just
• 4:09
  wide
• 4:09
  varieties
• 4:10
  of
• 4:11
  different
• 4:11
  kinds
• 4:12
  of
• 4:12
  backgrounds,
• 4:12
  which
• 4:13
  is
• 4:13
  great
• 4:13
  because
• 4:14
  the
• 4:14
  conversations
• 4:14
  you
• 4:15
  can
• 4:15
  have
• 4:15
  at
• 4:15
  lunch
• 4:15
  together
• 4:16
  are
• 4:16
  terrific
• 4:17
  and
• 4:17
  you
• 4:18
  always
• 4:18
  tend
• 4:18
  to
• 4:18
  learn
• 4:19
  something
• 4:19
  new
• 4:20
  from
• 4:20
  those
• 4:20
  people.
• 4:21
  But
• 4:22
  one
• 4:23
  of
• 4:23
  the
• 4:23
  things
• 4:23
  I
• 4:23
  have
• 4:24
  observed,
• 4:24
  maybe
• 4:25
  this
• 4:25
  is
• 4:25
  very
• 4:25
  data
• 4:25
  scientist
• 4:26
  of
• 4:26
  me,
• 4:27
  is
• 4:27
  there
• 4:28
  is
• 4:28
  not
• 4:29
  a
• 4:30
  statistical
• 4:30
  relationship
• 4:31
  between,
• 4:32
  between
• 4:33
  whether
• 4:33
  someone,
• 4:34
  say,
• 4:34
  has
• 4:34
  a
• 4:35
  PhD
• 4:36
  and
• 4:37
  is
• 4:37
  a
• 4:37
  great
• 4:37
  data
• 4:37
  scientist.
• 4:38
  In
• 4:39
  both
• 4:39
  of
• 4:39
  the
• 4:40
  companies
• 4:41
  that
• 4:41
  I've
• 4:41
  been
• 4:41
  part
• 4:41
  of
• 4:42
  in
• 4:42
  the
• 4:42
  past
• 4:42
  decade,
• 4:43
  I've
• 4:44
  taken
• 4:45
  my
• 4:45
  performance
• 4:46
  management
• 4:47
  data
• 4:48
  and
• 4:49
  the
• 4:49
  one
• 4:49
  binary
• 4:50
  variable
• 4:51
  right.
• 4:51
  Of
• 4:51
  PhD
• 4:52
  non
• 4:52
  PhD
• 4:53
  to
• 4:54
  try
• 4:54
  to
• 4:54
  see
• 4:54
  if
• 4:54
  there's
• 4:55
  a
• 4:55
  statistically
• 4:55
  significant
• 4:56
  difference
• 4:57
  in
• 4:57
  performance
• 4:58
  between
• 4:58
  PhDs
• 4:59
  and
• 4:59
  non
• 4:59
  PhDs.
• 5:00
  And
• 5:00
  I
• 5:01
  found
• 5:01
  it
• 5:01
  not
• 5:01
  to
• 5:01
  be
• 5:01
  the
• 5:01
  case.
• 5:02
  The
• 5:02
  null
• 5:03
  hypothesis
• 5:03
  there,
• 5:03
  right,
• 5:04
  that
• 5:04
  difference
• 5:05
  between
• 5:05
  those
• 5:05
  two
• 5:05
  groups
• 5:06
  is
• 5:06
  zero,
• 5:07
  turns
• 5:07
  out
• 5:08
  to
• 5:08
  be
• 5:08
  supported.
• 5:09
  And
• 5:10
  what
• 5:10
  I
• 5:11
  do
• 5:11
  think
• 5:11
  matters,
• 5:13
  and
• 5:13
  this
• 5:13
  is
• 5:13
  why
• 5:13
  I
• 5:13
  think
• 5:13
  it,
• 5:14
  you
• 5:14
  know,
• 5:14
  can
• 5:14
  be
• 5:14
  anti
• 5:15
  correlated
• 5:15
  in
• 5:15
  some
• 5:16
  cases,
• 5:16
  is
• 5:17
  simply
• 5:17
  put,
• 5:18
  you
• 5:18
  have
• 5:18
  to
• 5:18
  fall
• 5:18
  in
• 5:18
  love
• 5:18
  with
• 5:19
  the
• 5:19
  problem,
• 5:20
  not
• 5:20
  the
• 5:20
  solution.
• 5:22
  And
• 5:22
  I
• 5:23
  have
• 5:23
  observed
• 5:24
  that
• 5:24
  people
• 5:25
  with
• 5:25
  great
• 5:26
  methodological
• 5:27
  depth
• 5:28
  will
• 5:28
  sometimes
• 5:29
  fall
• 5:29
  in
• 5:29
  love
• 5:29
  with
• 5:29
  their
• 5:29
  methodologies
• 5:31
  and
• 5:32
  yeah,
• 5:32
  maybe
• 5:32
  that
• 5:33
  approach
• 5:34
  that
• 5:34
  you
• 5:34
  took
• 5:34
  is
• 5:34
  not
• 5:35
  the
• 5:35
  right
• 5:35
  approach.
• 5:35
  And
• 5:36
  this
• 5:36
  is
• 5:36
  why
• 5:36
  having
• 5:36
  a
• 5:36
  diverse
• 5:37
  team
• 5:37
  in
• 5:37
  terms
• 5:37
  of
• 5:37
  the
• 5:37
  disciplinary
• 5:38
  backgrounds
• 5:38
  is
• 5:38
  really
• 5:39
  important,
• 5:39
  right?
• 5:39
  It's
• 5:40
  because
• 5:40
  people
• 5:40
  can
• 5:41
  recommend
• 5:41
  lots
• 5:41
  of
• 5:42
  different
• 5:42
  methodologies
• 5:43
  to
• 5:43
  attack
• 5:44
  the
• 5:44
  same
• 5:45
  kind
• 5:45
  of
• 5:45
  problem,
• 5:46
  but
• 5:46
  you
• 5:47
  have
• 5:47
  to
• 5:47
  love
• 5:47
  the
• 5:47
  problem.
• 5:48
  That
• 5:48
  means
• 5:48
  learning
• 5:49
  everything
• 5:49
  that
• 5:49
  you
• 5:49
  can
• 5:50
  about
• 5:50
  the
• 5:50
  problem.
• 5:51
  That
• 5:51
  means
• 5:51
  spending
• 5:52
  time
• 5:53
  with
• 5:53
  your
• 5:53
  business
• 5:53
  partner.
• 5:54
  That's
• 5:55
  cliche,
• 5:55
  right?
• 5:56
  Spend
• 5:56
  time
• 5:56
  with
• 5:56
  your
• 5:56
  business
• 5:56
  partner,
• 5:57
  but
• 5:57
  it's
• 5:57
  not
• 5:57
  just
• 5:58
  talking
• 5:59
  to
• 5:59
  them.
• 6:00
  I
• 6:00
  think
• 6:00
  it's
• 6:01
  great
• 6:01
  when
• 6:01
  you
• 6:01
  can
• 6:01
  shadow
• 6:02
  them.
• 6:02
  Right.
• 6:03
  So
• 6:04
  I
• 6:04
  love
• 6:04
  when
• 6:05
  data
• 6:05
  scientists
• 6:06
  sit
• 6:06
  next
• 6:07
  to
• 6:08
  the
• 6:09
  people
• 6:09
  who
• 6:09
  are
• 6:10
  part
• 6:10
  of
• 6:10
  the
• 6:10
  business
• 6:10
  team
• 6:11
  that
• 6:11
  they're
• 6:11
  working
• 6:11
  with
• 6:12
  and
• 6:13
  look
• 6:13
  at
• 6:13
  the
• 6:13
  documents
• 6:14
  that
• 6:14
  they're
• 6:14
  creating,
• 6:15
  look
• 6:15
  at
• 6:15
  the
• 6:16
  phone
• 6:16
  calls
• 6:17
  they're
• 6:17
  on,
• 6:17
  go
• 6:17
  to
• 6:18
  meetings
• 6:18
  with
• 6:18
  them
• 6:18
  if
• 6:19
  you
• 6:19
  can,
• 6:19
  learn
• 6:20
  as
• 6:20
  much
• 6:20
  as
• 6:20
  you
• 6:21
  can
• 6:21
  about
• 6:21
  doing
• 6:22
  their
• 6:22
  job
• 6:23
  as
• 6:23
  is
• 6:23
  possible.
• 6:25
  Because
• 6:26
  inevitably
• 6:26
  it's
• 6:26
  going
• 6:27
  to
• 6:27
  be
• 6:27
  more
• 6:27
  complicated
• 6:28
  than
• 6:28
  you
• 6:29
  think
• 6:29
  it
• 6:29
  is.
• 6:30
  I've
• 6:30
  worked
• 6:30
  with
• 6:30
  some
• 6:32
  really
• 6:32
  solid
• 6:33
  scientists
• 6:33
  in
• 6:33
  the
• 6:34
  past
• 6:34
  who
• 6:35
  has
• 6:35
  said,
• 6:35
  oh,
• 6:35
  well,
• 6:36
  if
• 6:36
  you
• 6:36
  just
• 6:36
  model
• 6:36
  it
• 6:37
  as
• 6:37
  of
• 6:37
  this,
• 6:37
  and
• 6:38
  you
• 6:38
  know,
• 6:38
  this
• 6:38
  sort
• 6:39
  of
• 6:39
  thing,
• 6:39
  then
• 6:39
  the
• 6:40
  graph
• 6:40
  is
• 6:40
  going
• 6:40
  to
• 6:40
  look
• 6:40
  something
• 6:41
  like
• 6:41
  this
• 6:41
  and
• 6:42
  dang
• 6:42
  if
• 6:42
  it
• 6:42
  doesn't.
• 6:43
  But
• 6:44
  on
• 6:44
  the
• 6:44
  other
• 6:44
  hand,
• 6:45
  you're
• 6:45
  solving
• 6:46
  a
• 6:46
  simplified
• 6:46
  version
• 6:47
  of
• 6:47
  a
• 6:47
  problem
• 6:47
  or
• 6:48
  a
• 6:48
  toy
• 6:48
  version
• 6:49
  of
• 6:49
  a
• 6:49
  problem
• 6:50
  that
• 6:51
  is
• 6:51
  very
• 6:51
  different
• 6:52
  from,
• 6:52
  you
• 6:52
  know,
• 6:53
  the
• 6:53
  problem
• 6:53
  that
• 6:53
  you're
• 6:53
  actually
• 6:53
  supposed
• 6:54
  to
• 6:54
  solve.
• 6:54
  Obviously
• 6:54
  you
• 6:54
  want
• 6:55
  to
• 6:55
  have
• 6:55
  appropriate
• 6:55
  abstractions
• 6:56
  and
• 6:56
  things
• 6:56
  like
• 6:57
  that,
• 6:57
  but
• 6:57
  I
• 6:58
  mean,
• 6:58
  retail
• 6:58
  is
• 6:59
  very
• 6:59
  complicated,
• 7:00
  Supply
• 7:01
  chains
• 7:01
  are
• 7:01
  complicated,
• 7:02
  Accounting
• 7:03
  is
• 7:03
  complicated.
• 7:04
  Credit,
• 7:05
  as
• 7:05
  we
• 7:06
  know
• 7:06
  from
• 7:06
  our
• 7:06
  time
• 7:06
  in
• 7:06
  the
• 7:06
  banking
• 7:07
  industry,
• 7:07
  is
• 7:08
  incredibly
• 7:08
  complicated.
• 7:09
  But
• 7:10
  ensuring
• 7:10
  that
• 7:11
  you're
• 7:11
  solving
• 7:11
  the
• 7:11
  right
• 7:12
  problem
• 7:12
  is
• 7:13
  the
• 7:13
  key
• 7:13
  to
• 7:14
  it.
• 7:14
  And
• 7:16
  being
• 7:16
  flexible
• 7:16
  as
• 7:16
  to
• 7:16
  what
• 7:17
  methodology
• 7:18
  you
• 7:18
  bring
• 7:18
  to
• 7:19
  bear
• 7:19
  is
• 7:19
  important
• 7:20
  as
• 7:20
  well.
• 7:21
  One
• 7:21
  of
• 7:21
  the
• 7:21
  things
• 7:21
  I
• 7:21
  recommend
• 7:22
  data
• 7:22
  scientists
• 7:23
  do,
• 7:23
  and
• 7:24
  I
• 7:24
  recommend
• 7:24
  business
• 7:24
  people
• 7:25
  who
• 7:25
  are
• 7:25
  working
• 7:25
  with
• 7:25
  data
• 7:26
  scientists
• 7:26
  do,
• 7:27
  is
• 7:27
  produce
• 7:27
  the
• 7:27
  artifact
• 7:28
  first.
• 7:29
  Some
• 7:29
  great
• 7:29
  advice
• 7:30
  I
• 7:30
  got
• 7:30
  years
• 7:30
  ago
• 7:30
  for
• 7:31
  giving
• 7:32
  data
• 7:32
  driven
• 7:32
  presentations
• 7:34
  works
• 7:34
  really
• 7:34
  well
• 7:35
  here
• 7:35
  too,
• 7:35
  which
• 7:35
  is
• 7:36
  build
• 7:36
  the
• 7:36
  presentation
• 7:37
  first,
• 7:37
  figure
• 7:38
  out
• 7:38
  your
• 7:38
  outline,
• 7:39
  your
• 7:39
  story,
• 7:39
  flow,
• 7:40
  things
• 7:40
  like
• 7:40
  that
• 7:41
  before
• 7:42
  you've
• 7:42
  actually
• 7:42
  done
• 7:43
  the
• 7:43
  analytical
• 7:43
  work,
• 7:44
  and
• 7:44
  then
• 7:44
  work
• 7:45
  backwards
• 7:45
  from
• 7:45
  that
• 7:46
  because
• 7:46
  otherwise
• 7:47
  you
• 7:47
  can
• 7:47
  produce
• 7:47
  a
• 7:48
  whole
• 7:48
  bunch
• 7:48
  of
• 7:49
  figures
• 7:49
  and
• 7:50
  analyses
• 7:50
  and
• 7:51
  side
• 7:51
  analyses
• 7:52
  that
• 7:52
  don't
• 7:52
  actually
• 7:53
  fit
• 7:53
  into
• 7:53
  your
• 7:54
  main
• 7:54
  narrative.
• 7:54
  And
• 7:55
  this
• 7:55
  works
• 7:55
  well
• 7:55
  when
• 7:56
  you're
• 7:56
  giving
• 7:56
  an
• 7:56
  artifact
• 7:57
  to
• 7:58
  a
• 7:58
  business
• 7:58
  person.
• 7:58
  I
• 7:59
  need
• 7:59
  to
• 7:59
  give
• 7:59
  you
• 7:59
  the
• 8:00
  list
• 8:00
  of
• 8:00
  the
• 8:00
  top
• 8:01
  10
• 8:02
  product
• 8:03
  categories
• 8:03
  that
• 8:04
  are
• 8:04
  likely
• 8:05
  to
• 8:05
  do
• 8:05
  the
• 8:05
  following
• 8:06
  thing
• 8:07
  in
• 8:07
  the
• 8:07
  following
• 8:07
  quarter
• 8:08
  or
• 8:08
  something
• 8:08
  like
• 8:09
  that,
• 8:09
  produce
• 8:10
  that
• 8:10
  artifact,
• 8:11
  then
• 8:11
  do
• 8:11
  your
• 8:12
  own
• 8:12
  mini
• 8:12
  UX
• 8:12
  testing.
• 8:13
  So
• 8:13
  people
• 8:14
  talk
• 8:14
  about,
• 8:14
  which
• 8:15
  is
• 8:15
  great.
• 8:15
  I
• 8:15
  think
• 8:15
  data
• 8:16
  as
• 8:16
  A
• 8:16
  product.
• 8:17
  Right.
• 8:17
  How
• 8:17
  do
• 8:17
  you
• 8:17
  create
• 8:18
  a
• 8:19
  data
• 8:19
  set
• 8:19
  that
• 8:19
  is
• 8:20
  usable
• 8:20
  and
• 8:21
  well
• 8:21
  managed
• 8:21
  and
• 8:22
  well
• 8:22
  supported
• 8:22
  and
• 8:23
  versioned
• 8:23
  and
• 8:23
  all
• 8:24
  those
• 8:24
  good
• 8:24
  things
• 8:24
  that
• 8:25
  you
• 8:25
  can
• 8:25
  give
• 8:25
  to
• 8:25
  analysts
• 8:26
  downstream?
• 8:27
  I
• 8:27
  like
• 8:27
  to
• 8:27
  think
• 8:27
  about
• 8:28
  data
• 8:28
  science
• 8:28
  as
• 8:29
  a
• 8:29
  product
• 8:29
  too.
• 8:30
  Right.
• 8:30
  Is
• 8:30
  what
• 8:31
  is
• 8:31
  this
• 8:32
  data
• 8:32
  science
• 8:33
  analysis
• 8:34
  doing
• 8:36
  in
• 8:37
  a
• 8:37
  downstream
• 8:37
  process?
• 8:38
  What
• 8:38
  is
• 8:38
  it
• 8:39
  plugging
• 8:39
  into?
• 8:40
  Ensure
• 8:40
  that
• 8:40
  it's
• 8:41
  going
• 8:41
  to
• 8:41
  be
• 8:41
  usable
• 8:42
  there.
• 8:42
  The
• 8:42
  same
• 8:42
  way
• 8:43
  in
• 8:43
  UX
• 8:43
  design
• 8:44
  you
• 8:44
  do,
• 8:44
  you
• 8:44
  know,
• 8:44
  wizard
• 8:45
  of
• 8:45
  Oz
• 8:45
  tests
• 8:46
  and
• 8:46
  you
• 8:46
  do
• 8:46
  high
• 8:47
  fidelity
• 8:47
  mocks
• 8:48
  and
• 8:48
  all
• 8:48
  that
• 8:48
  kind
• 8:49
  of
• 8:49
  stuff.
• 8:49
  Do
• 8:50
  that
• 8:50
  with
• 8:50
  the
• 8:50
  data
• 8:50
  science
• 8:51
  report
• 8:51
  first
• 8:52
  so
• 8:52
  that
• 8:52
  you
• 8:52
  build
• 8:52
  the
• 8:52
  analysis
• 8:53
  that
• 8:53
  actually
• 8:53
  results
• 8:54
  in
• 8:54
  that
• 8:54
  thing.
• 8:54
  You
• 8:54
  definitely
• 8:55
  caught
• 8:55
  my
• 8:55
  attention
• 8:55
  with
• 8:55
  wizard
• 8:56
  of
• 8:56
  Oz
• 8:56
  test.
• 8:56
  Is
• 8:57
  that
• 8:57
  like
• 8:57
  clicking
• 8:57
  your
• 8:57
  heels
• 8:58
  together
• 8:58
  three
• 8:58
  times
• 8:58
  or
• 8:59
  following
• 8:59
  the
• 8:59
  yellow
• 8:59
  record?
• 9:00
  It
• 9:00
  is.
• 9:01
  Well,
• 9:01
  now
• 9:01
  we're
• 9:01
  getting
• 9:01
  a
• 9:02
  little
• 9:02
  bit
• 9:02
  out
• 9:02
  of
• 9:02
  my
• 9:03
  depth.
• 9:03
  It
• 9:03
  is
• 9:04
  essentially
• 9:04
  when
• 9:05
  you
• 9:05
  have
• 9:05
  a
• 9:06
  human
• 9:07
  pretending
• 9:08
  to
• 9:09
  be
• 9:09
  the
• 9:10
  piece
• 9:10
  of
• 9:10
  software.
• 9:11
  Ah,
• 9:12
  behind
• 9:12
  the
• 9:12
  curtain.
• 9:12
  I
• 9:13
  see,
• 9:13
  click
• 9:13
  a
• 9:13
  button
• 9:14
  and
• 9:14
  something
• 9:15
  changes.
• 9:15
  And
• 9:16
  it's
• 9:16
  not
• 9:16
  because
• 9:16
  the
• 9:16
  software
• 9:17
  changed
• 9:17
  it,
• 9:18
  it's
• 9:18
  because
• 9:18
  the
• 9:19
  experimenter
• 9:20
  manually
• 9:20
  changed
• 9:21
  it
• 9:21
  in
• 9:21
  order
• 9:22
  to.
• 9:22
  It's
• 9:23
  basically
• 9:23
  how
• 9:23
  you
• 9:23
  test
• 9:23
  a
• 9:23
  new
• 9:24
  design
• 9:24
  before
• 9:24
  you've
• 9:24
  actually
• 9:25
  built
• 9:25
  out
• 9:25
  the
• 9:25
  software
• 9:25
  that
• 9:26
  implements
• 9:26
  it.
• 9:26
  I
• 9:27
  got
• 9:27
  it.
• 9:27
  That
• 9:27
  makes
• 9:27
  sense.
• 9:27
  That
• 9:28
  makes
• 9:28
  sense.
• 9:28
  And
• 9:28
  data
• 9:29
  is
• 9:29
  a
• 9:29
  product.
• 9:29
  Absolutely
• 9:30
  right.
• 9:31
  Whether
• 9:31
  it's
• 9:31
  analysts
• 9:32
  or
• 9:32
  product
• 9:33
  people
• 9:33
  or
• 9:33
  even
• 9:33
  the
• 9:34
  customers
• 9:35
  that
• 9:35
  are
• 9:36
  the
• 9:36
  ultimate
• 9:36
  consumers
• 9:37
  of
• 9:37
  what
• 9:37
  you're
• 9:37
  building,
• 9:38
  you
• 9:38
  want
• 9:38
  them
• 9:38
  to
• 9:39
  be
• 9:39
  able
• 9:39
  to
• 9:39
  use
• 9:40
  whatever
• 9:40
  you're
• 9:40
  providing
• 9:41
  them
• 9:41
  to
• 9:41
  make
• 9:42
  a
• 9:42
  decision,
• 9:43
  to
• 9:43
  inform,
• 9:43
  a
• 9:44
  decision
• 9:44
  to
• 9:44
  adjust
• 9:45
  a
• 9:45
  strategy,
• 9:45
  to
• 9:45
  change
• 9:46
  an
• 9:46
  approach
• 9:46
  to
• 9:46
  something.
• 9:47
  I
• 9:48
  was
• 9:49
  wondering
• 9:49
  before
• 9:50
  we
• 9:50
  came
• 9:50
  on
• 9:50
  all
• 9:50
  of
• 9:51
  the
• 9:51
  wonderful
• 9:51
  problems
• 9:52
  that
• 9:52
  you
• 9:52
  might
• 9:52
  seek
• 9:53
  to
• 9:53
  solve
• 9:54
  for
• 9:54
  the
• 9:54
  customers
• 9:55
  of
• 9:55
  Home
• 9:55
  Depot.
• 9:56
  I
• 9:56
  think
• 9:56
  there
• 9:56
  are
• 9:56
  some
• 9:56
  obvious
• 9:57
  ones
• 9:57
  in
• 9:57
  my
• 9:57
  mind
• 9:57
  about
• 9:58
  recommending
• 9:59
  the
• 9:59
  right
• 9:59
  products
• 9:59
  to
• 10:00
  them,
• 10:00
  making
• 10:00
  it
• 10:00
  as
• 10:00
  easy
• 10:01
  as
• 10:01
  possible
• 10:01
  for
• 10:01
  them
• 10:01
  to
• 10:02
  find
• 10:02
  what
• 10:02
  they're
• 10:03
  looking
• 10:03
  for.
• 10:03
  You
• 10:03
  mentioned
• 10:04
  logistics
• 10:04
  which
• 10:04
  I
• 10:04
  hadn't
• 10:05
  thought
• 10:05
  of.
• 10:05
  Like
• 10:05
  making
• 10:06
  sure
• 10:06
  the
• 10:06
  right
• 10:06
  products
• 10:06
  are
• 10:06
  in
• 10:07
  the
• 10:07
  right
• 10:07
  place
• 10:07
  at
• 10:07
  the
• 10:07
  right
• 10:07
  time
• 10:08
  for
• 10:08
  the
• 10:08
  right
• 10:08
  people
• 10:08
  to
• 10:08
  buy.
• 10:10
  What
• 10:10
  are
• 10:10
  some
• 10:10
  of
• 10:11
  the
• 10:11
  other
• 10:12
  interesting
• 10:12
  work
• 10:13
  that
• 10:13
  your
• 10:13
  team
• 10:13
  does
• 10:13
  behind
• 10:13
  the
• 10:14
  scenes
• 10:14
  to
• 10:14
  kind
• 10:14
  of
• 10:14
  validate
• 10:15
  the
• 10:15
  experience
• 10:15
  of
• 10:16
  the
• 10:16
  customers?
• 10:17
  One
• 10:18
  of
• 10:18
  the
• 10:18
  reasons
• 10:18
  that
• 10:19
  I
• 10:19
  came
• 10:19
  to
• 10:20
  the
• 10:20
  Home
• 10:20
  Depot
• 10:20
  is
• 10:21
  because
• 10:21
  I
• 10:21
  am
• 10:21
  a
• 10:22
  lifelong
• 10:22
  DIYer
• 10:24
  and
• 10:24
  maker
• 10:25
  and
• 10:25
  I
• 10:26
  was
• 10:26
  a
• 10:26
  weekly
• 10:27
  customer
• 10:28
  long
• 10:28
  before
• 10:29
  I
• 10:29
  was
• 10:29
  ever
• 10:30
  an
• 10:31
  employee.
• 10:32
  And
• 10:32
  it
• 10:33
  makes
• 10:33
  my
• 10:34
  job
• 10:34
  tremendously
• 10:35
  fun
• 10:36
  and
• 10:36
  it
• 10:36
  also
• 10:37
  gives
• 10:37
  me
• 10:37
  incredible
• 10:38
  customer
• 10:39
  empathy.
• 10:40
  And
• 10:41
  one
• 10:41
  of
• 10:41
  the
• 10:41
  things
• 10:41
  that
• 10:42
  we
• 10:42
  do
• 10:42
  to
• 10:42
  build
• 10:43
  customer
• 10:44
  empathy
• 10:45
  is
• 10:46
  everybody
• 10:46
  spends
• 10:46
  time
• 10:47
  in
• 10:47
  the
• 10:47
  stores.
• 10:48
  I
• 10:48
  don't
• 10:49
  have
• 10:49
  them
• 10:49
  hanging
• 10:49
  up
• 10:49
  here,
• 10:50
  but
• 10:50
  sometimes
• 10:50
  I
• 10:50
  have
• 10:50
  my
• 10:51
  aprons
• 10:51
  hanging
• 10:51
  up
• 10:51
  here
• 10:52
  and
• 10:52
  I
• 10:53
  put
• 10:53
  on
• 10:53
  the
• 10:53
  orange
• 10:54
  apron
• 10:54
  and
• 10:54
  go
• 10:55
  in
• 10:55
  the
• 10:55
  store
• 10:55
  and
• 10:55
  help
• 10:56
  people
• 10:56
  find
• 10:56
  the
• 10:56
  things
• 10:57
  that
• 10:57
  they
• 10:57
  need
• 10:58
  several
• 10:58
  times
• 10:58
  a
• 10:59
  year.
• 11:01
  Because
• 11:01
  not
• 11:02
  every
• 11:02
  employee
• 11:03
  is
• 11:03
  a
• 11:04
  homeowner,
• 11:04
  is
• 11:05
  not
• 11:05
  a
• 11:05
  diy
• 11:06
  or
• 11:06
  many
• 11:06
  are.
• 11:07
  A
• 11:07
  surprising
• 11:08
  number
• 11:08
  are,
• 11:09
  but
• 11:09
  not
• 11:09
  everybody
• 11:10
  is
• 11:10
  right.
• 11:10
  And
• 11:10
  so
• 11:10
  the
• 11:10
  question
• 11:11
  is,
• 11:11
  how
• 11:11
  do
• 11:11
  you
• 11:11
  build
• 11:11
  that
• 11:12
  customer
• 11:12
  empathy?
• 11:13
  And
• 11:13
  it
• 11:13
  starts
• 11:13
  by
• 11:14
  getting
• 11:14
  people
• 11:14
  in
• 11:14
  the
• 11:14
  stores.
• 11:15
  And
• 11:16
  if
• 11:16
  you
• 11:16
  are
• 11:17
  somebody
• 11:17
  who's
• 11:17
  building
• 11:17
  product
• 11:18
  recommendation
• 11:18
  algorithms,
• 11:19
  you
• 11:19
  know,
• 11:20
  to
• 11:20
  say
• 11:20
  the
• 11:20
  data
• 11:20
  people.
• 11:21
  We
• 11:21
  often
• 11:21
  live
• 11:22
  in
• 11:22
  a
• 11:22
  pretty
• 11:23
  abstracted
• 11:24
  and
• 11:24
  antiseptic
• 11:25
  kind
• 11:26
  of
• 11:26
  world.
• 11:27
  And
• 11:27
  there's
• 11:27
  something
• 11:27
  really
• 11:28
  nice
• 11:28
  about,
• 11:29
  about
• 11:29
  touching
• 11:29
  reality
• 11:30
  and
• 11:30
  getting
• 11:31
  your
• 11:31
  hands
• 11:31
  dirty.
• 11:33
  I
• 11:33
  liked
• 11:33
  Joe.
• 11:34
  You
• 11:34
  mentioned
• 11:35
  Home
• 11:35
  Depot
• 11:36
  is
• 11:36
  one
• 11:36
  of
• 11:36
  the
• 11:36
  top
• 11:36
  five
• 11:37
  E
• 11:37
  commerce.
• 11:37
  It
• 11:38
  is.
• 11:38
  And
• 11:39
  in
• 11:39
  many
• 11:39
  of
• 11:40
  the
• 11:40
  others,
• 11:40
  you
• 11:41
  know,
• 11:41
  we
• 11:41
  have
• 11:41
  a
• 11:41
  slightly
• 11:42
  harder
• 11:42
  problem,
• 11:43
  I
• 11:43
  believe,
• 11:44
  because
• 11:44
  nobody
• 11:45
  is
• 11:45
  asking,
• 11:46
  how
• 11:46
  do
• 11:46
  I
• 11:46
  use
• 11:46
  these
• 11:47
  sweatpants?
• 11:48
  Right.
• 11:49
  But
• 11:49
  when
• 11:49
  you
• 11:49
  buy
• 11:49
  something
• 11:50
  at
• 11:50
  the
• 11:51
  Home
• 11:51
  Depot,
• 11:52
  um,
• 11:53
  it
• 11:53
  has
• 11:54
  to
• 11:55
  fit
• 11:55
  into
• 11:56
  whatever's
• 11:57
  going
• 11:57
  on
• 11:57
  in
• 11:57
  your
• 11:58
  home,
• 11:58
  whatever
• 11:58
  you're
• 11:58
  trying
• 11:58
  to
• 11:58
  attach
• 11:59
  it
• 11:59
  to.
• 11:59
  Things
• 12:00
  like
• 12:00
  that.
• 12:00
  Do
• 12:00
  I
• 12:00
  have
• 12:01
  the
• 12:01
  right
• 12:01
  size
• 12:01
  thing
• 12:02
  to
• 12:02
  connect
• 12:02
  this
• 12:03
  thing
• 12:03
  to?
• 12:03
  Is
• 12:04
  it
• 12:04
  actually
• 12:04
  going
• 12:04
  to
• 12:05
  fit?
• 12:05
  Is
• 12:05
  it
• 12:05
  the
• 12:05
  right
• 12:05
  materials?
• 12:06
  Is
• 12:06
  it
• 12:06
  a
• 12:06
  strong
• 12:07
  enough
• 12:07
  material?
• 12:08
  If
• 12:08
  we're
• 12:08
  selling
• 12:09
  you
• 12:09
  screws,
• 12:10
  those
• 12:10
  screws
• 12:11
  need
• 12:11
  to
• 12:12
  hold
• 12:12
  a
• 12:12
  certain
• 12:13
  amount
• 12:13
  of
• 12:13
  weight
• 12:13
  and
• 12:14
  stuff
• 12:14
  like
• 12:14
  that.
• 12:14
  And
• 12:15
  so
• 12:15
  ensuring
• 12:16
  product
• 12:16
  compatibility
• 12:17
  is,
• 12:17
  is
• 12:18
  really
• 12:18
  important.
• 12:19
  Ensuring
• 12:19
  that,
• 12:20
  you
• 12:20
  know,
• 12:21
  we're
• 12:21
  selling
• 12:21
  you
• 12:21
  the
• 12:21
  right
• 12:21
  thing
• 12:21
  for
• 12:22
  the
• 12:22
  job
• 12:22
  is
• 12:22
  really
• 12:23
  important.
• 12:23
  So
• 12:23
  recommendations
• 12:24
  for
• 12:25
  us
• 12:25
  is,
• 12:27
  you
• 12:27
  know,
• 12:27
  a
• 12:27
  really
• 12:27
  interesting
• 12:28
  and
• 12:28
  really
• 12:28
  complex
• 12:29
  problem.
• 12:29
  A
• 12:30
  lot
• 12:30
  of
• 12:30
  it
• 12:30
  starts
• 12:30
  with
• 12:30
  customer
• 12:31
  behavior.
• 12:32
  Right.
• 12:32
  So
• 12:34
  cliche.
• 12:34
  People
• 12:34
  who
• 12:35
  bought
• 12:35
  this
• 12:35
  also
• 12:35
  bought
• 12:36
  that.
• 12:36
  Right.
• 12:36
  Like
• 12:36
  that
• 12:37
  is
• 12:37
  a
• 12:38
  incredibly
• 12:39
  powerful
• 12:39
  signal
• 12:40
  of
• 12:41
  what
• 12:41
  people
• 12:41
  are
• 12:41
  going
• 12:42
  to
• 12:42
  end
• 12:42
  up
• 12:42
  wanting.
• 12:42
  But
• 12:42
  of
• 12:43
  course,
• 12:43
  there's
• 12:44
  a
• 12:44
  problem
• 12:44
  in
• 12:44
  recommender
• 12:45
  systems
• 12:45
  called
• 12:45
  the
• 12:46
  cold
• 12:46
  start
• 12:46
  problem.
• 12:47
  When
• 12:47
  a
• 12:48
  product
• 12:48
  is
• 12:48
  brand
• 12:49
  new
• 12:49
  and
• 12:49
  has
• 12:49
  never
• 12:50
  been
• 12:50
  purchased
• 12:50
  before,
• 12:51
  we'll
• 12:52
  know
• 12:52
  when
• 12:52
  it
• 12:52
  goes
• 12:52
  with.
• 12:53
  And
• 12:53
  there's
• 12:53
  all
• 12:53
  sorts
• 12:54
  of
• 12:54
  things
• 12:54
  you
• 12:54
  can
• 12:54
  do
• 12:54
  to
• 12:54
  get
• 12:54
  around
• 12:55
  that.
• 12:55
  You
• 12:55
  can
• 12:57
  look
• 12:57
  at
• 12:57
  the
• 12:57
  attributes
• 12:58
  of
• 12:58
  that
• 12:58
  item
• 12:59
  and
• 12:59
  say,
• 12:59
  well,
• 13:00
  maybe
• 13:00
  it's
• 13:00
  going
• 13:00
  to
• 13:00
  perform
• 13:01
  like
• 13:01
  other
• 13:01
  things
• 13:02
  that
• 13:02
  have
• 13:02
  similar
• 13:02
  attributes.
• 13:03
  So,
• 13:04
  you
• 13:04
  know,
• 13:04
  this
• 13:04
  is
• 13:05
  a
• 13:05
  widget.
• 13:05
  We've
• 13:06
  never
• 13:06
  sold
• 13:06
  this
• 13:06
  widget
• 13:07
  before,
• 13:07
  but
• 13:07
  we
• 13:07
  sell
• 13:08
  these
• 13:08
  other
• 13:08
  10
• 13:08
  widgets,
• 13:09
  so
• 13:09
  maybe
• 13:09
  this
• 13:09
  one
• 13:10
  is
• 13:10
  going
• 13:10
  to
• 13:10
  look
• 13:10
  sort
• 13:11
  of
• 13:11
  like
• 13:11
  that.
• 13:11
  And
• 13:12
  you
• 13:12
  can
• 13:12
  kind
• 13:12
  of
• 13:12
  bootstrap
• 13:13
  the
• 13:13
  process
• 13:14
  that
• 13:14
  way.
• 13:16
  Yeah.
• 13:17
  And
• 13:17
  we
• 13:17
  connect
• 13:17
  it
• 13:17
  directly
• 13:18
  to
• 13:19
  people's
• 13:21
  lived
• 13:21
  experiences.
• 13:22
  Right.
• 13:22
  Like
• 13:22
  the
• 13:22
  algorithm
• 13:23
  almost
• 13:24
  doesn't
• 13:25
  matter
• 13:25
  to
• 13:25
  them.
• 13:26
  But
• 13:26
  again,
• 13:27
  people
• 13:27
  who
• 13:27
  bought
• 13:28
  this
• 13:28
  also
• 13:28
  bought
• 13:28
  that
• 13:29
  is
• 13:29
  a
• 13:29
  pretty
• 13:29
  clear
• 13:29
  indicator
• 13:30
  of
• 13:30
  why
• 13:31
  we
• 13:31
  are
• 13:32
  recommending
• 13:32
  this
• 13:32
  to
• 13:32
  you.
• 13:33
  Other
• 13:33
  things
• 13:34
  from
• 13:34
  this
• 13:34
  brand
• 13:35
  is
• 13:35
  a
• 13:36
  pretty
• 13:36
  clear
• 13:37
  statement.
• 13:37
  About
• 13:37
  why
• 13:38
  we're
• 13:38
  recommending
• 13:38
  this
• 13:38
  to
• 13:38
  you.
• 13:39
  I
• 13:39
  have
• 13:39
  a
• 13:41
  product
• 13:41
  partner
• 13:41
  who's
• 13:41
  fond
• 13:42
  of
• 13:42
  saying
• 13:42
  you
• 13:42
  can't
• 13:42
  just
• 13:42
  show
• 13:43
  people
• 13:43
  stuff.
• 13:43
  You
• 13:43
  have
• 13:43
  to
• 13:44
  tell
• 13:44
  them
• 13:44
  why
• 13:44
  you're
• 13:44
  showing
• 13:45
  them
• 13:45
  that
• 13:45
  stuff.
• 13:45
  And
• 13:46
  I
• 13:46
  think
• 13:46
  that
• 13:46
  is
• 13:48
  really
• 13:49
  words
• 13:49
  that
• 13:49
  I
• 13:49
  live
• 13:49
  by.
• 13:50
  Yeah,
• 13:50
  I
• 13:51
  like
• 13:51
  that
• 13:51
  ethos.
• 13:52
  I
• 13:52
  was
• 13:52
  thinking,
• 13:52
  actually,
• 13:53
  maybe
• 13:53
  I've
• 13:53
  got
• 13:53
  you
• 13:53
  and
• 13:53
  your
• 13:54
  team
• 13:54
  to
• 13:54
  thank
• 13:54
  for
• 13:54
  this.
• 13:56
  The
• 13:57
  house
• 13:57
  next
• 13:57
  door
• 13:57
  to
• 13:58
  me
• 13:58
  is
• 13:58
  no
• 13:58
  longer
• 13:59
  a
• 13:59
  house.
• 13:59
  It's
• 13:59
  now
• 13:59
  a
• 13:59
  large
• 13:59
  hole
• 14:00
  in
• 14:00
  the
• 14:00
  ground
• 14:00
  that's
• 14:00
  currently
• 14:01
  getting
• 14:01
  filled
• 14:01
  with
• 14:01
  concrete.
• 14:03
  And
• 14:03
  one
• 14:03
  of
• 14:03
  the
• 14:04
  offshoot
• 14:05
  outcomes
• 14:06
  from
• 14:06
  that
• 14:06
  is
• 14:07
  prevalence
• 14:08
  of
• 14:08
  mice
• 14:09
  in
• 14:09
  and
• 14:09
  around
• 14:09
  my
• 14:09
  property.
• 14:10
  And
• 14:10
  I
• 14:10
  think
• 14:10
  the
• 14:10
  pest
• 14:10
  control
• 14:10
  guy
• 14:11
  said
• 14:11
  to
• 14:11
  me,
• 14:11
  actually,
• 14:12
  this
• 14:12
  is
• 14:13
  normal.
• 14:13
  Like
• 14:13
  when
• 14:13
  groan
• 14:14
  gets
• 14:14
  disturbed
• 14:14
  at
• 14:15
  a
• 14:15
  scale
• 14:15
  like
• 14:15
  this,
• 14:15
  then
• 14:16
  rodents
• 14:17
  will
• 14:17
  typically
• 14:17
  seek
• 14:18
  cover
• 14:19
  elsewhere.
• 14:21
  And
• 14:21
  that's
• 14:21
  been
• 14:21
  the
• 14:21
  case
• 14:22
  for
• 14:22
  me.
• 14:22
  So
• 14:22
  my
• 14:23
  wife
• 14:23
  and
• 14:23
  I,
• 14:23
  with.
• 14:25
  Somewhat
• 14:26
  of
• 14:26
  a
• 14:26
  grimace
• 14:26
  on
• 14:26
  our
• 14:27
  faces,
• 14:27
  went
• 14:28
  into
• 14:28
  the
• 14:28
  Home
• 14:28
  Depot
• 14:29
  last
• 14:29
  weekend
• 14:29
  in
• 14:29
  search
• 14:30
  of
• 14:30
  some
• 14:31
  mousetraps.
• 14:32
  And
• 14:32
  lo
• 14:32
  and
• 14:33
  behold,
• 14:33
  it
• 14:33
  was
• 14:33
  the
• 14:33
  first
• 14:33
  thing
• 14:34
  in
• 14:34
  front
• 14:34
  of
• 14:34
  us
• 14:34
  since
• 14:34
  we
• 14:34
  walked
• 14:35
  in.
• 14:36
  There
• 14:36
  was
• 14:36
  the
• 14:36
  display
• 14:37
  right
• 14:37
  there.
• 14:37
  And
• 14:37
  I
• 14:37
  assume
• 14:38
  at
• 14:38
  this
• 14:38
  time
• 14:38
  of
• 14:39
  year,
• 14:39
  it's
• 14:39
  getting
• 14:39
  colder.
• 14:40
  So
• 14:40
  even
• 14:40
  if
• 14:40
  you're
• 14:41
  not
• 14:41
  having
• 14:41
  a
• 14:41
  house
• 14:41
  knocked
• 14:42
  down
• 14:42
  next
• 14:42
  to
• 14:42
  you,
• 14:43
  the
• 14:43
  rodents
• 14:44
  are
• 14:44
  also
• 14:45
  seeking
• 14:45
  cover.
• 14:46
  So
• 14:46
  I
• 14:47
  guess
• 14:47
  your
• 14:47
  team
• 14:47
  feeds
• 14:47
  into
• 14:48
  that
• 14:48
  sort
• 14:48
  of
• 14:48
  what's
• 14:49
  at
• 14:49
  the
• 14:49
  front,
• 14:49
  because
• 14:50
  in
• 14:50
  July,
• 14:50
  in
• 14:50
  May,
• 14:51
  it's
• 14:51
  the
• 14:51
  grills.
• 14:52
  Right.
• 14:53
  Seasonality
• 14:54
  is
• 14:55
  incredibly
• 14:57
  important.
• 14:58
  And
• 14:58
  this
• 14:58
  is
• 14:59
  obvious
• 14:59
  if
• 14:59
  you
• 15:00
  think
• 15:00
  about
• 15:00
  it,
• 15:00
  even
• 15:00
  for
• 15:00
  a
• 15:01
  couple
• 15:01
  of
• 15:01
  seconds.
• 15:01
  Right.
• 15:01
  When
• 15:02
  do
• 15:02
  you
• 15:02
  want
• 15:02
  to
• 15:02
  stock
• 15:03
  shovels
• 15:03
  and
• 15:03
  snowblowers
• 15:04
  in
• 15:05
  your
• 15:05
  store?
• 15:05
  It's
• 15:06
  when
• 15:07
  it's
• 15:07
  right
• 15:07
  before
• 15:08
  snowing
• 15:08
  season.
• 15:09
  And
• 15:09
  when
• 15:09
  do
• 15:09
  you
• 15:09
  want
• 15:10
  to
• 15:10
  get
• 15:10
  that
• 15:11
  grass
• 15:11
  seed
• 15:11
  and
• 15:12
  weed
• 15:12
  control
• 15:13
  stocked?
• 15:13
  It's
• 15:15
  right
• 15:15
  before
• 15:15
  the
• 15:15
  beginning
• 15:16
  of
• 15:16
  the
• 15:16
  spring
• 15:16
  and
• 15:17
  stuff
• 15:17
  like
• 15:17
  that.
• 15:17
  So
• 15:18
  it
• 15:18
  turns
• 15:18
  out
• 15:18
  this
• 15:19
  is
• 15:19
  a
• 15:19
  very
• 15:20
  seasonal,
• 15:21
  cyclical
• 15:23
  business
• 15:23
  in.
• 15:24
  In
• 15:24
  that
• 15:25
  way.
• 15:25
  And.
• 15:28
  Yeah,
• 15:29
  meeting
• 15:29
  people
• 15:31
  at
• 15:31
  the
• 15:32
  right
• 15:32
  time
• 15:32
  is
• 15:33
  really
• 15:33
  important.
• 15:34
  And
• 15:34
  this
• 15:34
  varies
• 15:35
  geographically,
• 15:36
  too,
• 15:36
  Right.
• 15:36
  You
• 15:37
  know,
• 15:37
  even
• 15:37
  though
• 15:38
  I
• 15:38
  don't
• 15:38
  know
• 15:38
  exactly
• 15:39
  when
• 15:39
  it
• 15:39
  is,
• 15:39
  but,
• 15:40
  you
• 15:40
  know,
• 15:40
  say,
• 15:41
  November
• 15:41
  might
• 15:41
  be
• 15:41
  when
• 15:41
  you
• 15:42
  want
• 15:42
  to
• 15:42
  start
• 15:42
  putting
• 15:42
  out
• 15:43
  the
• 15:43
  snow
• 15:43
  shovels.
• 15:44
  Well,
• 15:45
  maybe
• 15:45
  you
• 15:45
  want
• 15:45
  to
• 15:46
  do
• 15:46
  that
• 15:46
  up
• 15:46
  in
• 15:47
  Boston,
• 15:47
  but
• 15:47
  you
• 15:47
  don't
• 15:47
  want
• 15:47
  to
• 15:48
  do
• 15:48
  that
• 15:48
  down
• 15:48
  in
• 15:48
  Miami,
• 15:49
  Right?
• 15:49
  No,
• 15:49
  sure.
• 15:51
  Geography
• 15:52
  is
• 15:52
  really
• 15:52
  important.
• 15:54
  Yeah.
• 15:55
  All
• 15:55
  sorts
• 15:55
  of
• 15:55
  things
• 15:55
  that
• 15:55
  we
• 15:55
  take
• 15:56
  into
• 15:56
  consideration.
• 15:57
  Yeah,
• 15:58
  it
• 15:58
  definitely
• 15:58
  felt
• 15:58
  like
• 15:58
  a
• 15:59
  blessing
• 15:59
  because
• 15:59
  I
• 15:59
  think
• 15:59
  I
• 16:00
  walk
• 16:00
  in
• 16:00
  the
• 16:00
  door
• 16:00
  and
• 16:00
  I
• 16:00
  think
• 16:02
  you
• 16:02
  can
• 16:02
  see
• 16:03
  the
• 16:03
  labels
• 16:03
  on
• 16:04
  all
• 16:04
  the
• 16:04
  aisles
• 16:05
  up
• 16:05
  and
• 16:05
  across.
• 16:07
  But
• 16:07
  I
• 16:07
  was
• 16:07
  walking
• 16:08
  and
• 16:08
  thinking,
• 16:08
  how
• 16:08
  am
• 16:09
  I
• 16:09
  going
• 16:09
  to
• 16:09
  find
• 16:09
  these
• 16:09
  tiny
• 16:09
  mousetraps
• 16:11
  in
• 16:11
  this
• 16:11
  huge
• 16:11
  store?
• 16:12
  So
• 16:12
  it
• 16:13
  felt
• 16:13
  like
• 16:14
  that
• 16:14
  felt
• 16:14
  like
• 16:14
  a
• 16:15
  real
• 16:15
  gift
• 16:15
  to
• 16:15
  me.
• 16:15
  Can
• 16:16
  we
• 16:16
  talk
• 16:16
  about
• 16:16
  AI,
• 16:16
  machine
• 16:17
  learning?
• 16:18
  Everybody
• 16:18
  wants
• 16:19
  to.
• 16:19
  Everybody
• 16:19
  wants
• 16:20
  to.
• 16:21
  I
• 16:22
  imagine
• 16:22
  it's.
• 16:23
  I
• 16:23
  know
• 16:23
  machine
• 16:24
  learning
• 16:24
  has
• 16:24
  been
• 16:24
  a
• 16:24
  part
• 16:24
  of
• 16:25
  data
• 16:25
  science
• 16:25
  for
• 16:25
  a
• 16:26
  while
• 16:26
  and
• 16:27
  I'm
• 16:27
  sure
• 16:27
  AI
• 16:27
  is
• 16:27
  very
• 16:28
  much
• 16:29
  on
• 16:29
  the
• 16:30
  scene
• 16:30
  now.
• 16:32
  It's
• 16:32
  easy
• 16:32
  to.
• 16:32
  You
• 16:32
  can
• 16:32
  read
• 16:33
  a
• 16:33
  lot
• 16:33
  about
• 16:33
  how
• 16:33
  inexact
• 16:34
  AI
• 16:34
  can
• 16:35
  be.
• 16:35
  So
• 16:35
  in
• 16:35
  what
• 16:35
  ways?
• 16:36
  In
• 16:37
  ways
• 16:37
  that
• 16:37
  I
• 16:37
  might
• 16:37
  understand.
• 16:38
  Have
• 16:39
  you
• 16:39
  begun
• 16:39
  to
• 16:39
  look
• 16:39
  at
• 16:40
  using
• 16:40
  AI
• 16:41
  safely
• 16:41
  as
• 16:41
  part
• 16:41
  of
• 16:43
  a
• 16:43
  rigorous
• 16:43
  discipline
• 16:44
  such
• 16:44
  as
• 16:44
  data
• 16:44
  science?
• 16:45
  I
• 16:45
  find
• 16:46
  AI
• 16:47
  to
• 16:48
  be
• 16:49
  a
• 16:50
  unhelpful
• 16:52
  name
• 16:53
  for
• 16:54
  this
• 16:54
  thing
• 16:54
  and
• 16:54
  I
• 16:54
  think
• 16:55
  people
• 16:55
  have
• 16:55
  probably
• 16:56
  been
• 16:56
  thinking
• 16:56
  that
• 16:56
  for
• 16:57
  60,
• 16:57
  70
• 16:58
  years.
• 17:00
  There's
• 17:00
  a
• 17:01
  joke
• 17:01
  that
• 17:02
  whenever
• 17:02
  something
• 17:03
  in
• 17:03
  AI
• 17:04
  gets
• 17:04
  solved,
• 17:04
  they
• 17:05
  call
• 17:05
  it
• 17:05
  machine
• 17:05
  learning.
• 17:06
  And
• 17:06
  so
• 17:07
  AI
• 17:07
  is,
• 17:08
  you
• 17:08
  know,
• 17:08
  only
• 17:09
  that
• 17:09
  subset
• 17:09
  of
• 17:10
  problems
• 17:10
  that
• 17:10
  hasn't
• 17:10
  been
• 17:11
  solved
• 17:11
  yet,
• 17:11
  which
• 17:12
  has
• 17:12
  actually
• 17:12
  changed
• 17:12
  in
• 17:12
  the
• 17:13
  past
• 17:13
  couple
• 17:13
  of
• 17:13
  years
• 17:13
  right
• 17:13
  now
• 17:14
  because
• 17:14
  I
• 17:14
  think
• 17:14
  AI
• 17:15
  has
• 17:15
  become
• 17:16
  a,
• 17:17
  it's
• 17:17
  a
• 17:18
  marketing
• 17:18
  term
• 17:18
  or
• 17:19
  a.
• 17:20
  Yeah,
• 17:21
  it
• 17:21
  is
• 17:21
  inexact
• 17:22
  in,
• 17:22
  in
• 17:22
  how
• 17:23
  it's
• 17:23
  used.
• 17:24
  And
• 17:25
  conventionally
• 17:25
  what
• 17:25
  we
• 17:25
  need
• 17:26
  is
• 17:26
  these
• 17:26
  large
• 17:26
  language
• 17:26
  models,
• 17:27
  right?
• 17:27
  These
• 17:27
  models
• 17:28
  that
• 17:28
  are
• 17:28
  trained
• 17:28
  on
• 17:29
  large
• 17:29
  amounts
• 17:29
  of
• 17:30
  text
• 17:30
  from
• 17:30
  the
• 17:30
  Internet
• 17:31
  and
• 17:32
  people
• 17:32
  have
• 17:33
  snarkily
• 17:34
  criticized
• 17:34
  them
• 17:35
  as
• 17:36
  glorified
• 17:38
  autocomplete.
• 17:39
  Right.
• 17:39
  Like
• 17:40
  basically
• 17:40
  it's
• 17:40
  just
• 17:40
  predicting
• 17:41
  the
• 17:41
  next
• 17:41
  word
• 17:41
  in
• 17:42
  your
• 17:42
  thing.
• 17:42
  And
• 17:42
  that's
• 17:42
  indeed.
• 17:43
  Yeah,
• 17:43
  that's
• 17:43
  a
• 17:43
  little
• 17:44
  bit
• 17:44
  unfair.
• 17:45
  I
• 17:45
  mean,
• 17:46
  methodologically,
• 17:47
  mathematically,
• 17:48
  like,
• 17:49
  sure,
• 17:49
  there's,
• 17:49
  there's
• 17:50
  something
• 17:50
  to
• 17:50
  that
• 17:50
  and
• 17:51
  you
• 17:51
  can
• 17:51
  have
• 17:51
  all
• 17:51
  sorts
• 17:51
  of
• 17:52
  discussions
• 17:52
  about,
• 17:52
  well,
• 17:53
  whether
• 17:53
  there's
• 17:53
  some
• 17:54
  emergent
• 17:54
  behaviors
• 17:55
  that
• 17:55
  make
• 17:55
  it
• 17:56
  be
• 17:56
  greater
• 17:57
  than
• 17:57
  the
• 17:57
  sum
• 17:58
  of
• 17:58
  its
• 17:58
  parts
• 17:58
  and
• 17:58
  stuff
• 17:59
  like
• 17:59
  that.
• 18:00
  I
• 18:00
  try
• 18:00
  not
• 18:00
  to
• 18:01
  get
• 18:01
  wrapped
• 18:01
  around
• 18:02
  that
• 18:03
  axle
• 18:03
  too
• 18:03
  much.
• 18:04
  What
• 18:04
  I
• 18:05
  try
• 18:05
  to
• 18:05
  do
• 18:06
  is
• 18:07
  focus
• 18:08
  on
• 18:08
  the
• 18:09
  extent
• 18:09
  to,
• 18:09
  whether
• 18:09
  or
• 18:09
  not
• 18:09
  it's
• 18:10
  useful.
• 18:10
  Right.
• 18:12
  I
• 18:13
  think
• 18:13
  that
• 18:14
  LLMs
• 18:15
  are
• 18:15
  really
• 18:16
  good
• 18:16
  at
• 18:17
  summarization
• 18:19
  and
• 18:19
  are
• 18:19
  really
• 18:20
  good
• 18:21
  at
• 18:22
  obviously
• 18:24
  generation
• 18:25
  of
• 18:25
  text
• 18:25
  is.
• 18:26
  It's
• 18:26
  where
• 18:27
  they
• 18:27
  can
• 18:27
  go
• 18:27
  haywire.
• 18:28
  Right.
• 18:28
  And
• 18:28
  so
• 18:28
  the
• 18:28
  things
• 18:28
  that
• 18:29
  you
• 18:29
  read
• 18:29
  in
• 18:29
  the
• 18:30
  news
• 18:30
  about.
• 18:32
  I
• 18:32
  fell
• 18:33
  in
• 18:33
  love
• 18:33
  with
• 18:33
  the
• 18:33
  AI
• 18:34
  and
• 18:34
  you
• 18:34
  know,
• 18:35
  left
• 18:35
  my
• 18:36
  spouse
• 18:36
  because
• 18:36
  my
• 18:36
  AI
• 18:37
  girlfriend
• 18:37
  was
• 18:38
  like,
• 18:38
  better
• 18:38
  stuff
• 18:39
  like
• 18:39
  that,
• 18:39
  right?
• 18:39
  Yeah,
• 18:39
  she
• 18:40
  told
• 18:40
  me
• 18:40
  to.
• 18:41
  Yeah,
• 18:41
  like
• 18:41
  that
• 18:42
  stuff's
• 18:42
  really
• 18:42
  off
• 18:42
  the
• 18:42
  rails
• 18:43
  and
• 18:43
  there's
• 18:43
  some
• 18:43
  probably
• 18:44
  really
• 18:44
  interesting
• 18:44
  like
• 18:46
  other
• 18:46
  psychology
• 18:46
  conversations
• 18:47
  you
• 18:47
  can
• 18:47
  have
• 18:48
  about
• 18:48
  that.
• 18:48
  But
• 18:48
  like
• 18:49
  the
• 18:49
  generation
• 18:50
  part
• 18:50
  is
• 18:50
  where,
• 18:50
  where
• 18:51
  I
• 18:51
  think
• 18:51
  things
• 18:51
  go.
• 18:53
  Get
• 18:54
  a
• 18:54
  little
• 18:54
  riskier
• 18:55
  because
• 18:55
  of
• 18:55
  just
• 18:55
  how
• 18:56
  open
• 18:56
  ended
• 18:57
  it
• 18:57
  is.
• 18:57
  Summarization
• 18:59
  is
• 18:59
  a
• 18:59
  lot
• 19:00
  less
• 19:00
  risky
• 19:01
  because
• 19:01
  you're
• 19:02
  dealing
• 19:02
  inherently
• 19:03
  just
• 19:03
  with
• 19:03
  the
• 19:03
  information
• 19:04
  that
• 19:04
  you're
• 19:05
  providing
• 19:05
  to
• 19:05
  it
• 19:06
  and
• 19:06
  putting.
• 19:06
  A
• 19:07
  fence
• 19:07
  around
• 19:07
  it.
• 19:07
  Right?
• 19:08
  Yeah,
• 19:08
  exactly.
• 19:09
  Exactly.
• 19:09
  And
• 19:10
  so
• 19:10
  I
• 19:10
  have
• 19:10
  found
• 19:11
  those
• 19:11
  use
• 19:12
  cases
• 19:13
  to
• 19:13
  be
• 19:14
  not
• 19:14
  just
• 19:14
  the
• 19:15
  safer
• 19:15
  ones,
• 19:16
  but
• 19:16
  the
• 19:16
  ones
• 19:17
  that
• 19:18
  you're
• 19:18
  just
• 19:18
  plain
• 19:19
  work
• 19:19
  better.
• 19:19
  I
• 19:19
  think
• 19:20
  any
• 19:20
  AI
• 19:21
  powered
• 19:22
  customer
• 19:22
  experience
• 19:23
  or
• 19:23
  even
• 19:23
  internal
• 19:24
  business
• 19:24
  process
• 19:25
  lives
• 19:26
  or
• 19:26
  dies
• 19:26
  based
• 19:26
  on
• 19:26
  the
• 19:27
  quality
• 19:27
  of
• 19:27
  the
• 19:27
  data.
• 19:28
  And
• 19:29
  one
• 19:29
  of
• 19:29
  the
• 19:29
  more
• 19:29
  prominent
• 19:30
  ones
• 19:31
  is
• 19:32
  Google's
• 19:33
  AI
• 19:34
  summaries.
• 19:34
  Right.
• 19:34
  So
• 19:35
  now
• 19:35
  if
• 19:35
  you
• 19:35
  search
• 19:35
  for
• 19:36
  something
• 19:36
  in
• 19:36
  Google,
• 19:36
  you
• 19:36
  get
• 19:37
  a
• 19:37
  little
• 19:37
  AI
• 19:37
  summary
• 19:38
  at
• 19:39
  the
• 19:39
  top.
• 19:40
  And
• 19:41
  as
• 19:41
  of
• 19:42
  right
• 19:42
  now,
• 19:43
  they're
• 19:43
  not
• 19:43
  great.
• 19:44
  Right?
• 19:44
  Like
• 19:44
  they,
• 19:45
  I
• 19:45
  feel
• 19:45
  like
• 19:45
  they're
• 19:46
  very
• 19:46
  hit
• 19:46
  or
• 19:46
  miss.
• 19:47
  Yeah,
• 19:47
  they
• 19:47
  put
• 19:48
  some,
• 19:48
  there's
• 19:48
  some
• 19:48
  interesting
• 19:49
  links
• 19:49
  they
• 19:49
  put
• 19:49
  in
• 19:50
  there.
• 19:50
  And
• 19:50
  the
• 19:50
  interesting
• 19:50
  thing
• 19:51
  about
• 19:51
  that
• 19:51
  for
• 19:51
  me
• 19:51
  as
• 19:52
  a
• 19:52
  student
• 19:52
  of
• 19:53
  Google's
• 19:55
  business
• 19:55
  value
• 19:55
  proposition
• 19:56
  is
• 19:57
  actually
• 19:57
  really
• 19:57
  cannibalizes
• 19:58
  the
• 19:59
  huge
• 19:59
  business
• 19:59
  they
• 19:59
  have
• 20:00
  of
• 20:00
  people
• 20:00
  paying
• 20:00
  to
• 20:00
  be
• 20:01
  number
• 20:01
  one
• 20:01
  in
• 20:01
  the
• 20:01
  search
• 20:01
  results.
• 20:03
  So
• 20:03
  it's
• 20:04
  a
• 20:04
  really
• 20:04
  interesting
• 20:04
  choice
• 20:04
  for
• 20:05
  me
• 20:05
  to
• 20:05
  know.
• 20:05
  I'll
• 20:06
  watch
• 20:06
  with
• 20:06
  interest
• 20:06
  how
• 20:06
  that
• 20:07
  goes.
• 20:07
  But
• 20:07
  yeah,
• 20:07
  you're
• 20:08
  right,
• 20:09
  that
• 20:09
  summary
• 20:09
  can
• 20:09
  be
• 20:09
  a
• 20:09
  bit
• 20:10
  all
• 20:10
  over
• 20:10
  the
• 20:10
  place
• 20:11
  and
• 20:12
  credit
• 20:13
  to
• 20:13
  them.
• 20:13
  There's
• 20:13
  typically
• 20:14
  diverse
• 20:14
  sources
• 20:14
  in
• 20:14
  there,
• 20:15
  but
• 20:15
  that
• 20:15
  can
• 20:15
  result
• 20:15
  in
• 20:16
  contradictions
• 20:17
  within
• 20:17
  the
• 20:17
  same
• 20:17
  summary.
• 20:18
  Exactly
• 20:18
  right.
• 20:19
  Because
• 20:19
  they're
• 20:19
  not
• 20:19
  using
• 20:20
  the
• 20:20
  most
• 20:20
  intelligent
• 20:21
  models
• 20:21
  that
• 20:21
  can
• 20:22
  do
• 20:22
  the
• 20:22
  backtracking
• 20:22
  and
• 20:23
  rewriting
• 20:23
  and
• 20:23
  things
• 20:23
  like
• 20:24
  that
• 20:24
  because
• 20:25
  they're
• 20:25
  trying
• 20:25
  to
• 20:25
  do
• 20:25
  it
• 20:25
  at
• 20:25
  scale
• 20:26
  and.
• 20:26
  I
• 20:27
  imagine
• 20:27
  speed
• 20:28
  as
• 20:28
  well.
• 20:28
  Exactly.
• 20:30
  That's
• 20:30
  a
• 20:30
  really
• 20:32
  good
• 20:33
  point
• 20:33
  and
• 20:33
  segue
• 20:34
  that
• 20:34
  the
• 20:35
  speed
• 20:36
  and
• 20:37
  cost
• 20:38
  of
• 20:39
  these
• 20:39
  models
• 20:40
  as
• 20:41
  it
• 20:41
  stands
• 20:41
  today
• 20:41
  at
• 20:42
  least
• 20:42
  dictates
• 20:43
  where
• 20:44
  they
• 20:44
  will
• 20:44
  and
• 20:45
  will
• 20:45
  not
• 20:45
  be
• 20:46
  feasible.
• 20:46
  Right.
• 20:47
  So
• 20:47
  if
• 20:47
  you
• 20:48
  are
• 20:48
  trying
• 20:49
  to
• 20:50
  integrate
• 20:51
  AI
• 20:52
  into,
• 20:53
  you
• 20:53
  know,
• 20:53
  every
• 20:54
  page
• 20:54
  on
• 20:54
  a
• 20:55
  highly
• 20:55
  trafficked
• 20:55
  site
• 20:56
  or
• 20:56
  something
• 20:57
  like
• 20:57
  that,
• 20:57
  you've
• 20:58
  got
• 20:58
  to
• 20:58
  think
• 20:58
  about
• 20:58
  whether
• 20:58
  that's
• 20:59
  cost
• 20:59
  effective.
• 20:59
  You've
• 21:00
  got
• 21:00
  to
• 21:00
  think
• 21:00
  about
• 21:00
  whether
• 21:01
  that's
• 21:01
  going
• 21:01
  to
• 21:01
  be
• 21:03
  operating
• 21:03
  at
• 21:03
  the
• 21:04
  speed
• 21:04
  at
• 21:04
  which
• 21:05
  your
• 21:05
  user
• 21:06
  wants
• 21:06
  to
• 21:07
  operate.
• 21:07
  I
• 21:07
  mean,
• 21:07
  imagine
• 21:08
  every
• 21:08
  time
• 21:08
  you
• 21:08
  clicked
• 21:09
  on
• 21:09
  a
• 21:10
  link,
• 21:10
  you
• 21:10
  had
• 21:11
  to
• 21:11
  wait
• 21:11
  another
• 21:11
  10
• 21:11
  seconds
• 21:12
  for
• 21:12
  some
• 21:12
  text
• 21:12
  to
• 21:13
  get
• 21:13
  generated
• 21:13
  or
• 21:13
  something
• 21:14
  like
• 21:14
  that.
• 21:14
  Right.
• 21:14
  So
• 21:15
  you
• 21:15
  have
• 21:15
  to
• 21:15
  think
• 21:16
  about
• 21:17
  whether
• 21:17
  it's
• 21:18
  appropriate
• 21:18
  or
• 21:18
  not
• 21:19
  appropriate
• 21:19
  for
• 21:20
  a
• 21:21
  given
• 21:21
  experience
• 21:22
  and
• 21:23
  thinking
• 21:24
  about
• 21:25
  internal
• 21:25
  business
• 21:26
  processes
• 21:27
  for
• 21:27
  a
• 21:27
  second.
• 21:29
  Businesses
• 21:30
  arrive
• 21:31
  on.
• 21:33
  Accountability
• 21:35
  and
• 21:36
  on.
• 21:36
  It's
• 21:37
  the
• 21:37
  word
• 21:37
  I'm
• 21:37
  grasping
• 21:38
  for
• 21:39
  expectation.
• 21:40
  Right.
• 21:41
  So
• 21:42
  is
• 21:43
  something
• 21:43
  repeatable.
• 21:45
  Auditable,
• 21:46
  those
• 21:47
  kinds
• 21:47
  of
• 21:47
  things?
• 21:48
  If
• 21:48
  I
• 21:50
  as
• 21:50
  an
• 21:50
  employee
• 21:51
  of
• 21:52
  some
• 21:52
  company
• 21:53
  have
• 21:53
  an
• 21:53
  AI
• 21:54
  that
• 21:54
  I'm
• 21:54
  using
• 21:55
  to
• 21:55
  help
• 21:55
  me
• 21:55
  make
• 21:56
  some
• 21:56
  kind
• 21:56
  of
• 21:56
  decision,
• 21:58
  I
• 21:59
  as
• 21:59
  an
• 21:59
  employee
• 21:59
  still
• 22:00
  need
• 22:00
  to
• 22:00
  be
• 22:00
  responsible
• 22:01
  for
• 22:01
  or
• 22:02
  accountable
• 22:02
  for
• 22:03
  what
• 22:03
  comes
• 22:03
  out
• 22:04
  of
• 22:04
  that
• 22:04
  AI.
• 22:04
  I've
• 22:05
  joked
• 22:05
  that
• 22:06
  there
• 22:06
  are
• 22:06
  these
• 22:06
  articles
• 22:07
  you
• 22:07
  can
• 22:07
  read
• 22:07
  online
• 22:08
  that
• 22:08
  says
• 22:08
  in
• 22:08
  the
• 22:09
  future
• 22:09
  you're
• 22:09
  going
• 22:09
  to
• 22:09
  have
• 22:10
  10,000
• 22:10
  AI
• 22:11
  co
• 22:11
  workers
• 22:11
  or
• 22:12
  10,000
• 22:13
  AIs
• 22:13
  are
• 22:13
  going
• 22:13
  to,
• 22:14
  you
• 22:14
  know,
• 22:14
  you're
• 22:14
  going
• 22:14
  to
• 22:14
  be
• 22:15
  the
• 22:15
  manager
• 22:15
  of
• 22:15
  a
• 22:15
  thousand
• 22:16
  AIs.
• 22:16
  The
• 22:17
  problem
• 22:17
  is
• 22:18
  I
• 22:18
  can't
• 22:19
  fire
• 22:19
  any
• 22:19
  of
• 22:20
  those
• 22:20
  AIs.
• 22:20
  I
• 22:20
  can't
• 22:21
  put
• 22:21
  those
• 22:21
  AIs
• 22:22
  on
• 22:22
  a
• 22:22
  performance
• 22:23
  plan
• 22:23
  or
• 22:23
  a
• 22:23
  coaching
• 22:24
  plan.
• 22:26
  They're,
• 22:26
  they're
• 22:27
  just
• 22:27
  software.
• 22:28
  So
• 22:28
  the
• 22:28
  human,
• 22:29
  ultimately,
• 22:30
  no
• 22:30
  matter
• 22:30
  how
• 22:30
  much
• 22:30
  AI
• 22:31
  you're
• 22:31
  using,
• 22:32
  some
• 22:33
  human
• 22:33
  ultimately
• 22:33
  needs
• 22:34
  to
• 22:34
  be
• 22:34
  responsible
• 22:34
  for
• 22:35
  a
• 22:35
  given
• 22:35
  decision.
• 22:36
  I
• 22:37
  still
• 22:37
  think
• 22:37
  human
• 22:37
  in
• 22:38
  the
• 22:38
  loop
• 22:39
  again,
• 22:39
  at
• 22:39
  least
• 22:39
  today,
• 22:40
  right.
• 22:40
  Things
• 22:40
  are
• 22:40
  changing
• 22:41
  so
• 22:41
  fast,
• 22:41
  you
• 22:41
  know,
• 22:42
  who
• 22:42
  knows
• 22:42
  where
• 22:43
  we'll
• 22:43
  end
• 22:43
  up
• 22:44
  even
• 22:44
  in
• 22:44
  the
• 22:44
  short
• 22:44
  term.
• 22:45
  But
• 22:46
  today,
• 22:46
  at
• 22:46
  least,
• 22:46
  I
• 22:46
  think
• 22:47
  human
• 22:47
  in
• 22:47
  the
• 22:47
  loop
• 22:47
  is
• 22:48
  incredibly
• 22:48
  important.
• 22:49
  Right.
• 22:49
  Like
• 22:50
  using
• 22:50
  the
• 22:50
  AI
• 22:51
  to
• 22:51
  make
• 22:51
  the
• 22:51
  human
• 22:52
  do
• 22:53
  more,
• 22:53
  do
• 22:53
  better,
• 22:54
  do
• 22:54
  faster
• 22:55
  is
• 22:56
  great,
• 22:56
  but
• 22:57
  that
• 22:57
  human
• 22:57
  judgment
• 22:58
  is
• 22:58
  not,
• 22:58
  we're
• 22:59
  not
• 22:59
  yet
• 22:59
  ready
• 22:59
  to
• 22:59
  replace
• 23:00
  that
• 23:00
  level
• 23:00
  of
• 23:00
  human
• 23:00
  judgment.
• 23:01
  Not
• 23:01
  because
• 23:01
  the
• 23:01
  judgment
• 23:02
  of
• 23:02
  the
• 23:02
  machine
• 23:02
  isn't
• 23:02
  that
• 23:03
  good,
• 23:03
  but
• 23:03
  because
• 23:03
  our
• 23:04
  organizations
• 23:05
  are
• 23:06
  not
• 23:06
  structured
• 23:07
  to
• 23:08
  imbue
• 23:09
  AIs
• 23:09
  with
• 23:09
  accountability.
• 23:10
  Yeah.
• 23:11
  And
• 23:12
  the
• 23:13
  warning
• 23:14
  signs
• 23:14
  that
• 23:14
  point
• 23:15
  for
• 23:15
  that
• 23:15
  being
• 23:15
  the
• 23:15
  correct
• 23:16
  approach
• 23:16
  are
• 23:16
  everywhere.
• 23:17
  And
• 23:18
  you
• 23:18
  don't
• 23:18
  really
• 23:18
  need
• 23:18
  to
• 23:19
  look
• 23:19
  that
• 23:19
  far
• 23:20
  to
• 23:20
  see
• 23:20
  them.
• 23:23
  I've
• 23:23
  answered
• 23:24
  questions
• 23:24
  from
• 23:24
  people
• 23:24
  before
• 23:25
  as
• 23:25
  a
• 23:25
  fellow
• 23:26
  data
• 23:26
  professional
• 23:27
  of
• 23:27
  this
• 23:28
  kind
• 23:28
  of
• 23:28
  expectation
• 23:29
  that
• 23:29
  people
• 23:29
  have
• 23:30
  that
• 23:31
  we're
• 23:31
  already
• 23:31
  in
• 23:31
  this
• 23:32
  position
• 23:32
  where
• 23:32
  you
• 23:32
  can
• 23:33
  take
• 23:33
  an
• 23:33
  entire
• 23:33
  enterprise
• 23:34
  data
• 23:34
  warehouse,
• 23:35
  here's
• 23:35
  all
• 23:35
  the
• 23:35
  data
• 23:36
  about
• 23:36
  the
• 23:37
  company,
• 23:38
  and
• 23:39
  just
• 23:40
  put
• 23:40
  some
• 23:41
  NLP
• 23:42
  interface
• 23:42
  on
• 23:42
  the
• 23:42
  front
• 23:42
  where
• 23:44
  any
• 23:44
  human
• 23:44
  can
• 23:44
  ask
• 23:45
  questions.
• 23:46
  And
• 23:46
  as
• 23:47
  I
• 23:47
  always
• 23:47
  say,
• 23:48
  how
• 23:48
  do
• 23:48
  you
• 23:48
  know
• 23:49
  what
• 23:49
  question
• 23:49
  to
• 23:49
  ask,
• 23:50
  number
• 23:51
  one.
• 23:51
  And
• 23:51
  then
• 23:51
  are
• 23:52
  you
• 23:52
  going
• 23:52
  to
• 23:52
  trust
• 23:52
  that
• 23:53
  whatever
• 23:53
  model
• 23:53
  you're
• 23:53
  talking
• 23:54
  to
• 23:54
  understands
• 23:55
  the
• 23:55
  context
• 23:56
  and
• 23:56
  the
• 23:56
  rationale
• 23:56
  and
• 23:57
  the
• 23:57
  specifics
• 23:57
  of
• 23:57
  the
• 23:57
  question
• 23:58
  in
• 23:58
  the
• 23:58
  way
• 23:58
  that
• 23:58
  you
• 23:58
  intend
• 23:59
  them?
• 24:00
  And
• 24:00
  then
• 24:01
  when
• 24:01
  the
• 24:01
  answer
• 24:01
  comes
• 24:01
  back,
• 24:02
  how
• 24:02
  are
• 24:02
  you
• 24:02
  going
• 24:02
  to,
• 24:03
  how
• 24:03
  are
• 24:03
  you
• 24:03
  going
• 24:03
  to
• 24:03
  check
• 24:03
  that
• 24:03
  it's,
• 24:04
  that
• 24:05
  it's
• 24:05
  correct?
• 24:05
  Like
• 24:05
  there's
• 24:06
  so
• 24:06
  many,
• 24:06
  there's
• 24:07
  so
• 24:07
  many
• 24:07
  issues
• 24:07
  that
• 24:08
  can,
• 24:08
  that
• 24:08
  can,
• 24:09
  that
• 24:09
  can
• 24:09
  go
• 24:09
  wrong.
• 24:10
  And
• 24:10
  great
• 24:11
  data
• 24:11
  governance,
• 24:11
  metadata,
• 24:12
  humans
• 24:13
  in
• 24:13
  the
• 24:13
  loop
• 24:14
  using
• 24:14
  analysts
• 24:14
  and
• 24:15
  the
• 24:15
  power
• 24:15
  that
• 24:16
  they
• 24:16
  bring.
• 24:17
  And
• 24:17
  I
• 24:17
  always
• 24:17
  say,
• 24:17
  like
• 24:17
  when
• 24:17
  people
• 24:18
  ask
• 24:18
  if
• 24:18
  the
• 24:18
  data
• 24:19
  analysis
• 24:20
  job
• 24:21
  is
• 24:21
  under
• 24:22
  any
• 24:22
  threat,
• 24:22
  I
• 24:23
  always
• 24:23
  point
• 24:23
  back
• 24:23
  to
• 24:23
  that
• 24:24
  first
• 24:24
  point
• 24:24
  I
• 24:24
  made,
• 24:25
  like
• 24:25
  someone
• 24:25
  needs
• 24:26
  to
• 24:26
  know
• 24:26
  the
• 24:26
  right
• 24:26
  question
• 24:27
  to
• 24:27
  ask.
• 24:27
  And
• 24:27
  there's
• 24:28
  a
• 24:28
  whole
• 24:28
  bunch
• 24:28
  of
• 24:29
  skill
• 24:29
  learning
• 24:29
  and
• 24:30
  experience
• 24:30
  and
• 24:30
  expertise
• 24:31
  that
• 24:31
  goes
• 24:31
  into
• 24:31
  understanding
• 24:32
  the
• 24:32
  right
• 24:32
  question
• 24:33
  to
• 24:33
  ask
• 24:33
  before
• 24:33
  you
• 24:34
  even
• 24:34
  get
• 24:34
  to
• 24:34
  the,
• 24:35
  you
• 24:35
  know,
• 24:35
  company
• 24:35
  defining
• 24:36
  insight
• 24:36
  that's
• 24:37
  going
• 24:37
  to
• 24:37
  give
• 24:38
  you
• 24:38
  the
• 24:38
  record
• 24:38
  next
• 24:39
  quarter
• 24:39
  or
• 24:39
  whatever.
• 24:40
  It
• 24:40
  might
• 24:40
  be
• 24:41
  so
• 24:41
  very
• 24:42
  much
• 24:42
  behind
• 24:43
  the,
• 24:44
  behind
• 24:45
  the
• 24:45
  human
• 24:45
  in
• 24:45
  the
• 24:45
  loop
• 24:46
  on
• 24:46
  that
• 24:46
  and
• 24:46
  beyond
• 24:48
  stock
• 24:48
  photography,
• 24:49
  I
• 24:49
  can't
• 24:49
  think
• 24:49
  yet
• 24:49
  of
• 24:50
  an
• 24:50
  industry
• 24:50
  that's
• 24:50
  completely
• 24:52
  being
• 24:52
  killed
• 24:52
  by
• 24:52
  AI.
• 24:52
  And
• 24:53
  I'm
• 24:53
  sure
• 24:53
  there's
• 24:53
  still
• 24:53
  some
• 24:53
  stock
• 24:54
  photographers
• 24:54
  going
• 24:54
  at
• 24:54
  it
• 24:55
  out
• 24:55
  there
• 24:55
  and
• 24:55
  adding
• 24:56
  some
• 24:56
  human
• 24:57
  uniqueness.
• 25:00
  To
• 25:00
  what
• 25:00
  they
• 25:00
  do
• 25:00
  with
• 25:00
  it.
• 25:01
  What
• 25:01
  AI
• 25:01
  experiences
• 25:02
  have
• 25:03
  you
• 25:03
  come
• 25:03
  across
• 25:03
  from
• 25:04
  in
• 25:05
  your
• 25:05
  life
• 25:05
  as
• 25:05
  a
• 25:05
  consumer.
• 25:07
  Beyond
• 25:08
  your
• 25:08
  work
• 25:08
  at
• 25:09
  Home
• 25:09
  Depot?
• 25:09
  Are
• 25:10
  there
• 25:10
  any,
• 25:11
  including
• 25:12
  tools
• 25:12
  you
• 25:12
  may
• 25:12
  have
• 25:12
  used
• 25:13
  for
• 25:13
  any
• 25:13
  personal
• 25:14
  projects?
• 25:14
  Are
• 25:14
  there
• 25:15
  any
• 25:15
  standout
• 25:15
  experiences
• 25:16
  that
• 25:17
  you've
• 25:17
  had
• 25:17
  where
• 25:17
  the
• 25:17
  data
• 25:18
  is
• 25:18
  good,
• 25:18
  well
• 25:18
  fenced,
• 25:19
  well
• 25:19
  guarded?
• 25:20
  Are
• 25:20
  there
• 25:20
  any
• 25:21
  shockingly
• 25:21
  bad
• 25:21
  ones?
• 25:22
  And
• 25:22
  we
• 25:22
  talked
• 25:22
  about
• 25:22
  Google
• 25:23
  already,
• 25:23
  but
• 25:23
  are
• 25:23
  there
• 25:23
  any
• 25:23
  others
• 25:24
  that
• 25:24
  you've
• 25:24
  had?
• 25:25
  Yeah,
• 25:26
  the
• 25:26
  two
• 25:26
  things
• 25:26
  that
• 25:27
  I
• 25:27
  use
• 25:27
  the
• 25:28
  most
• 25:28
  in
• 25:28
  my
• 25:29
  personal
• 25:29
  life
• 25:30
  are
• 25:30
  ChatGPT
• 25:32
  and
• 25:32
  Cursor.
• 25:35
  Yeah,
• 25:36
  it
• 25:37
  is
• 25:37
  really
• 25:38
  fun
• 25:39
  to
• 25:40
  be
• 25:41
  able
• 25:41
  to
• 25:42
  use
• 25:42
  it
• 25:43
  for
• 25:43
  like
• 25:43
  side
• 25:44
  projects
• 25:44
  and
• 25:45
  you
• 25:45
  know,
• 25:46
  little
• 25:46
  things
• 25:46
  that
• 25:47
  I'm
• 25:47
  tinkering
• 25:47
  with
• 25:48
  here
• 25:48
  and
• 25:48
  there
• 25:49
  for
• 25:49
  its
• 25:50
  code
• 25:50
  completion
• 25:51
  capabilities,
• 25:52
  for
• 25:52
  its
• 25:53
  ability
• 25:53
  to
• 25:54
  build,
• 25:54
  you
• 25:54
  know,
• 25:55
  really
• 25:55
  a
• 25:55
  scaffold
• 25:55
  of
• 25:56
  a
• 25:56
  project.
• 25:57
  And
• 25:58
  that's
• 25:59
  another
• 25:59
  one
• 25:59
  where
• 26:00
  the
• 26:01
  hype
• 26:02
  cycle.
• 26:02
  You
• 26:02
  get
• 26:03
  very
• 26:03
  polarized
• 26:04
  opinions
• 26:05
  on
• 26:05
  AI
• 26:06
  powered
• 26:07
  coding.
• 26:08
  And
• 26:09
  I
• 26:09
  can
• 26:09
  speak
• 26:09
  only
• 26:10
  from
• 26:10
  personal
• 26:10
  experience
• 26:11
  here.
• 26:11
  I
• 26:11
  feel
• 26:11
  like
• 26:11
  it
• 26:11
  makes
• 26:12
  me
• 26:12
  ten
• 26:12
  times
• 26:12
  more
• 26:12
  effective.
• 26:13
  Right.
• 26:14
  I
• 26:14
  can
• 26:15
  spend
• 26:15
  an
• 26:16
  hour
• 26:17
  just
• 26:18
  thinking
• 26:18
  with
• 26:19
  a
• 26:19
  side
• 26:19
  project
• 26:19
  after
• 26:20
  the
• 26:20
  kids
• 26:20
  go
• 26:20
  to
• 26:20
  bed
• 26:21
  and
• 26:22
  it's
• 26:22
  as
• 26:23
  though
• 26:23
  I
• 26:23
  did
• 26:24
  a
• 26:25
  10
• 26:25
  hour
• 26:25
  workday
• 26:26
  on
• 26:26
  it
• 26:26
  or
• 26:26
  something
• 26:27
  like
• 26:27
  that.
• 26:28
  Now
• 26:28
  I
• 26:29
  have
• 26:30
  minimal
• 26:31
  and
• 26:31
  that's
• 26:32
  even
• 26:32
  generous,
• 26:32
  you
• 26:33
  know,
• 26:33
  web
• 26:33
  design
• 26:34
  skills.
• 26:34
  And
• 26:35
  my
• 26:36
  web
• 26:36
  design
• 26:37
  technology,
• 26:38
  you
• 26:38
  know,
• 26:38
  keeping
• 26:39
  up
• 26:39
  to
• 26:39
  datedness,
• 26:40
  stopped
• 26:40
  probably
• 26:41
  about
• 26:41
  15
• 26:41
  years
• 26:41
  ago.
• 26:42
  So
• 26:42
  I
• 26:42
  don't
• 26:43
  know,
• 26:43
  react
• 26:44
  and
• 26:44
  I
• 26:45
  don't
• 26:45
  know,
• 26:45
  you
• 26:46
  know,
• 26:46
  a
• 26:46
  bunch
• 26:46
  of
• 26:46
  the
• 26:46
  other
• 26:46
  modern
• 26:47
  web
• 26:47
  frameworks.
• 26:48
  I
• 26:48
  can
• 26:48
  read
• 26:49
  code.
• 26:49
  So
• 26:50
  if
• 26:50
  it
• 26:50
  generates
• 26:50
  code
• 26:51
  for
• 26:51
  me,
• 26:52
  I
• 26:52
  can
• 26:52
  read
• 26:52
  it
• 26:52
  and
• 26:53
  I
• 26:53
  can
• 26:53
  debug
• 26:53
  it
• 26:53
  and
• 26:54
  stuff
• 26:54
  like
• 26:54
  that.
• 26:55
  But
• 26:55
  I've
• 26:56
  been
• 26:56
  able
• 26:56
  to
• 26:56
  build,
• 26:56
  you
• 26:57
  know,
• 26:57
  little
• 26:58
  side
• 26:58
  web.
• 26:58
  I
• 26:58
  built
• 26:58
  myself
• 26:59
  a
• 26:59
  flashcard
• 26:59
  app,
• 26:59
  right.
• 27:00
  Which
• 27:00
  I
• 27:00
  think
• 27:00
  basically
• 27:01
  everybody
• 27:02
  does.
• 27:02
  I
• 27:02
  have
• 27:02
  been
• 27:03
  about
• 27:04
  150
• 27:04
  days
• 27:05
  in
• 27:05
  of
• 27:05
  doing
• 27:06
  Chinese
• 27:06
  on
• 27:06
  Duolingo,
• 27:07
  which
• 27:07
  has
• 27:07
  been
• 27:07
  super
• 27:07
  fun.
• 27:08
  Wow.
• 27:08
  And
• 27:09
  I
• 27:09
  needed
• 27:10
  a
• 27:10
  way
• 27:11
  of
• 27:11
  just
• 27:11
  flashcarding
• 27:12
  myself
• 27:13
  of
• 27:13
  which
• 27:13
  characters
• 27:14
  I've
• 27:14
  learned.
• 27:15
  And
• 27:15
  I
• 27:15
  wrote
• 27:15
  a
• 27:16
  prompt
• 27:16
  like
• 27:16
  a
• 27:17
  two
• 27:17
  paragraph
• 27:17
  prompt,
• 27:18
  gave
• 27:18
  it
• 27:18
  to
• 27:19
  cursor,
• 27:19
  it
• 27:19
  built
• 27:20
  the
• 27:20
  front
• 27:20
  end,
• 27:20
  it
• 27:20
  built
• 27:21
  the
• 27:21
  backend,
• 27:22
  it
• 27:22
  imported
• 27:23
  my
• 27:23
  CSV
• 27:24
  of
• 27:24
  characters
• 27:25
  and
• 27:26
  built
• 27:26
  a
• 27:26
  little
• 27:26
  database
• 27:27
  backend
• 27:27
  to
• 27:28
  keep
• 27:28
  track
• 27:28
  of
• 27:28
  which
• 27:28
  things
• 27:29
  I
• 27:29
  got
• 27:29
  right
• 27:29
  and
• 27:29
  which
• 27:29
  things
• 27:30
  I
• 27:30
  got
• 27:30
  wrong
• 27:30
  and
• 27:30
  stuff
• 27:31
  like
• 27:31
  that.
• 27:31
  I
• 27:31
  mean,
• 27:32
  in
• 27:32
  15
• 27:32
  minutes
• 27:32
  I
• 27:33
  was
• 27:33
  up
• 27:33
  and
• 27:33
  running
• 27:33
  with
• 27:34
  a
• 27:35
  little
• 27:35
  app
• 27:36
  which
• 27:36
  was,
• 27:36
  was
• 27:37
  super
• 27:37
  cool.
• 27:38
  And
• 27:39
  I
• 27:39
  think
• 27:39
  what
• 27:39
  that's
• 27:39
  going
• 27:40
  to
• 27:40
  do
• 27:40
  is
• 27:41
  change
• 27:41
  what
• 27:42
  it
• 27:42
  means
• 27:42
  for
• 27:42
  like
• 27:43
  designers
• 27:43
  and
• 27:43
  product
• 27:44
  people
• 27:44
  and
• 27:45
  even
• 27:45
  engineers.
• 27:46
  Like,
• 27:47
  instead
• 27:47
  of
• 27:48
  mocking
• 27:48
  something
• 27:48
  up
• 27:49
  in,
• 27:49
  you
• 27:50
  know,
• 27:50
  what
• 27:50
  are
• 27:50
  the
• 27:50
  different
• 27:50
  apps
• 27:51
  people
• 27:51
  use
• 27:51
  to
• 27:51
  make?
• 27:51
  Like
• 27:52
  High
• 27:52
  Fidelity.
• 27:53
  Oh
• 27:53
  yeah,
• 27:53
  the
• 27:54
  Balsamiq
• 27:54
  was
• 27:55
  one
• 27:55
  that
• 27:55
  I've
• 27:55
  seen
• 27:55
  before.
• 27:56
  Yeah,
• 27:56
  yeah,
• 27:56
  all
• 27:57
  those
• 27:57
  things.
• 27:57
  Right.
• 27:57
  So
• 27:58
  the
• 27:58
  next
• 27:58
  generation
• 27:59
  of
• 27:59
  that
• 27:59
  I'm
• 27:59
  sure
• 28:00
  is
• 28:00
  going
• 28:00
  to
• 28:00
  be,
• 28:01
  well,
• 28:01
  here's
• 28:01
  this
• 28:01
  clickable
• 28:02
  thing
• 28:02
  that
• 28:02
  actually
• 28:02
  does
• 28:03
  stuff
• 28:03
  and
• 28:03
  you
• 28:03
  know,
• 28:03
  maybe
• 28:04
  it's
• 28:04
  not
• 28:04
  going
• 28:04
  to
• 28:04
  be
• 28:04
  the
• 28:04
  prime
• 28:04
  time
• 28:05
  thing
• 28:05
  that
• 28:05
  you
• 28:05
  end
• 28:06
  up
• 28:06
  shipping
• 28:06
  with
• 28:06
  all
• 28:06
  the
• 28:07
  robustness
• 28:07
  and
• 28:08
  latency
• 28:09
  and
• 28:09
  security
• 28:09
  and
• 28:09
  all
• 28:10
  the
• 28:10
  things
• 28:10
  that
• 28:10
  you
• 28:10
  want
• 28:10
  actual
• 28:11
  software
• 28:11
  to
• 28:11
  have,
• 28:12
  but
• 28:12
  man,
• 28:12
  does
• 28:13
  it
• 28:13
  get
• 28:13
  you
• 28:13
  from
• 28:13
  an
• 28:13
  idea
• 28:14
  to
• 28:14
  something
• 28:15
  tangible
• 28:15
  really
• 28:15
  quickly.
• 28:16
  So
• 28:17
  that's
• 28:17
  been
• 28:18
  really
• 28:19
  fun.
• 28:19
  And
• 28:19
  then
• 28:19
  the
• 28:20
  others,
• 28:20
  I
• 28:20
  just
• 28:20
  use
• 28:20
  ChatGPT
• 28:21
  a
• 28:21
  lot.
• 28:21
  I
• 28:22
  was
• 28:22
  playing
• 28:22
  chess
• 28:22
  with
• 28:22
  my
• 28:22
  10
• 28:23
  year
• 28:23
  old
• 28:23
  the
• 28:23
  other
• 28:23
  day
• 28:24
  and
• 28:24
  we
• 28:24
  had
• 28:24
  a
• 28:24
  disagreement
• 28:25
  about
• 28:25
  whether
• 28:25
  a
• 28:26
  certain
• 28:26
  move
• 28:26
  was
• 28:26
  legal
• 28:27
  or
• 28:27
  not.
• 28:28
  And
• 28:28
  I
• 28:28
  took
• 28:28
  a
• 28:29
  picture
• 28:29
  of
• 28:29
  the
• 28:29
  board
• 28:30
  and
• 28:30
  I
• 28:31
  sent
• 28:31
  it
• 28:31
  to
• 28:31
  ChatGPT
• 28:32
  and
• 28:32
  is
• 28:33
  like,
• 28:33
  is
• 28:34
  the
• 28:35
  bishop
• 28:35
  allowed
• 28:35
  to
• 28:36
  take
• 28:36
  this
• 28:37
  piece
• 28:37
  under
• 28:37
  this
• 28:37
  circumstance?
• 28:38
  I
• 28:38
  forget
• 28:38
  exactly
• 28:39
  what
• 28:39
  it
• 28:39
  was.
• 28:39
  And
• 28:40
  it
• 28:40
  went
• 28:40
  through
• 28:40
  its
• 28:40
  reasoning
• 28:41
  steps
• 28:41
  and
• 28:41
  it's
• 28:41
  like,
• 28:42
  oh,
• 28:42
  you
• 28:42
  took
• 28:42
  a
• 28:42
  picture
• 28:42
  of
• 28:43
  the
• 28:43
  board
• 28:43
  this
• 28:43
  way.
• 28:43
  I
• 28:43
  need
• 28:44
  to
• 28:44
  rotate
• 28:44
  it
• 28:44
  horizontally.
• 28:45
  And
• 28:45
  then
• 28:45
  you're
• 28:45
  probably
• 28:46
  talking
• 28:46
  about
• 28:47
  this
• 28:47
  bishop
• 28:47
  and
• 28:47
  this
• 28:48
  piece
• 28:48
  and
• 28:48
  like,
• 28:48
  no,
• 28:49
  you
• 28:49
  are
• 28:49
  not
• 28:49
  able
• 28:49
  to
• 28:50
  do
• 28:50
  this
• 28:50
  piece
• 28:50
  because
• 28:50
  even
• 28:51
  though
• 28:51
  it
• 28:52
  looks
• 28:52
  like
• 28:52
  you
• 28:52
  can
• 28:52
  move
• 28:52
  here,
• 28:53
  it
• 28:53
  turns
• 28:53
  out
• 28:53
  because
• 28:54
  this
• 28:54
  other
• 28:54
  guy
• 28:54
  is
• 28:54
  over
• 28:55
  here,
• 28:55
  you
• 28:55
  can't
• 28:55
  do
• 28:55
  it.
• 28:56
  And
• 28:56
  it
• 28:56
  resolved
• 28:56
  the
• 28:56
  argument
• 28:57
  and
• 28:57
  it
• 28:57
  blew
• 28:58
  my
• 28:59
  mind
• 28:59
  because,
• 29:01
  well,
• 29:01
  the
• 29:01
  multimodal
• 29:02
  ness
• 29:02
  of
• 29:02
  it,
• 29:02
  right?
• 29:03
  So
• 29:03
  there
• 29:03
  was
• 29:03
  an
• 29:03
  image,
• 29:04
  there
• 29:04
  was
• 29:05
  some
• 29:05
  text.
• 29:06
  It
• 29:06
  had
• 29:06
  to
• 29:06
  look
• 29:07
  at
• 29:07
  the
• 29:07
  image,
• 29:07
  understand
• 29:08
  the
• 29:08
  image
• 29:08
  in
• 29:09
  the
• 29:09
  context
• 29:09
  of
• 29:09
  the
• 29:10
  text
• 29:10
  and
• 29:10
  then
• 29:11
  figure
• 29:11
  out
• 29:11
  what
• 29:12
  to
• 29:12
  do.
• 29:12
  And
• 29:13
  it
• 29:13
  was
• 29:13
  amazing.
• 29:13
  And
• 29:13
  I've
• 29:14
  done
• 29:14
  this
• 29:14
  with,
• 29:15
  oh,
• 29:15
  one
• 29:15
  of
• 29:15
  the
• 29:15
  trees
• 29:15
  in
• 29:15
  my
• 29:16
  backyard
• 29:16
  had
• 29:17
  a
• 29:17
  weird
• 29:17
  growth
• 29:18
  on
• 29:18
  it
• 29:18
  and
• 29:18
  I
• 29:18
  took
• 29:18
  a
• 29:19
  picture
• 29:19
  of
• 29:19
  it
• 29:19
  and
• 29:19
  I
• 29:19
  was
• 29:19
  like,
• 29:20
  what's
• 29:20
  wrong
• 29:20
  with
• 29:20
  my
• 29:21
  tree?
• 29:21
  And
• 29:22
  it
• 29:22
  said,
• 29:22
  oh,
• 29:23
  it
• 29:23
  looks
• 29:23
  like
• 29:23
  this
• 29:23
  is
• 29:23
  this
• 29:24
  kind
• 29:24
  of
• 29:24
  holly
• 29:25
  tree
• 29:25
  and
• 29:25
  it
• 29:25
  probably
• 29:26
  has
• 29:26
  this
• 29:26
  kind
• 29:27
  of
• 29:27
  disease.
• 29:28
  I
• 29:28
  did
• 29:28
  this
• 29:28
  on
• 29:28
  vacation
• 29:29
  once
• 29:29
  in
• 29:30
  the
• 29:30
  Caribbean
• 29:30
  as
• 29:30
  well.
• 29:31
  And
• 29:31
  I
• 29:31
  took
• 29:31
  a
• 29:31
  picture
• 29:31
  of
• 29:32
  a
• 29:32
  tree
• 29:33
  that
• 29:33
  I
• 29:33
  said,
• 29:34
  what
• 29:34
  kind
• 29:34
  of
• 29:34
  tree
• 29:35
  is
• 29:35
  this?
• 29:36
  It
• 29:36
  said,
• 29:36
  well,
• 29:36
  based
• 29:36
  on
• 29:37
  the
• 29:37
  fact
• 29:37
  that
• 29:37
  you're
• 29:37
  located
• 29:38
  on
• 29:38
  such
• 29:38
  and
• 29:38
  such
• 29:39
  an
• 29:39
  island
• 29:39
  because,
• 29:39
  you
• 29:40
  know,
• 29:40
  grab
• 29:40
  the
• 29:40
  latitude,
• 29:41
  longitude
• 29:41
  off
• 29:41
  of
• 29:41
  the
• 29:42
  photo,
• 29:42
  you
• 29:43
  know,
• 29:43
  it's
• 29:43
  probably
• 29:43
  this
• 29:44
  kind
• 29:44
  of
• 29:44
  tree
• 29:44
  which
• 29:45
  is
• 29:45
  characterized
• 29:45
  by
• 29:46
  leaves
• 29:46
  that
• 29:47
  have
• 29:47
  these
• 29:47
  particular
• 29:48
  shapes
• 29:48
  on
• 29:49
  them.
• 29:49
  And
• 29:50
  I
• 29:50
  mean,
• 29:50
  it's
• 29:51
  a
• 29:51
  bit.
• 29:51
  It
• 29:52
  can
• 29:52
  be
• 29:52
  amazing,
• 29:54
  right?
• 29:55
  And
• 29:55
  when
• 29:55
  it's
• 29:55
  bad,
• 29:56
  it's
• 29:56
  bad,
• 29:56
  right?
• 29:57
  Like
• 29:57
  that's
• 29:57
  why
• 29:57
  I
• 29:57
  say
• 29:57
  these
• 29:58
  things
• 29:58
  kind
• 29:58
  of
• 29:58
  live
• 29:58
  or
• 29:58
  die
• 29:59
  based
• 29:59
  on
• 29:59
  the
• 29:59
  quality
• 30:00
  of
• 30:00
  the
• 30:00
  output.
• 30:01
  So
• 30:02
  obviously
• 30:02
  they're,
• 30:03
  they're
• 30:03
  not
• 30:03
  as
• 30:03
  smart
• 30:04
  as,
• 30:05
  you
• 30:05
  know,
• 30:05
  humans
• 30:06
  in
• 30:06
  the
• 30:06
  common
• 30:06
  sense
• 30:07
  sense,
• 30:08
  but
• 30:09
  the
• 30:09
  amount
• 30:09
  of
• 30:09
  knowledge
• 30:10
  that
• 30:10
  they
• 30:10
  can
• 30:10
  bring
• 30:11
  to
• 30:11
  bear
• 30:11
  is
• 30:12
  incredible.
• 30:13
  So
• 30:13
  on
• 30:13
  the,
• 30:14
  on
• 30:14
  the
• 30:14
  software
• 30:14
  engineering
• 30:15
  front,
• 30:15
  right,
• 30:15
  it's
• 30:16
  like
• 30:16
  sometimes
• 30:17
  you're
• 30:17
  handing
• 30:17
  a
• 30:18
  task
• 30:18
  off
• 30:18
  to
• 30:18
  the
• 30:18
  most
• 30:19
  junior
• 30:19
  developer
• 30:20
  in
• 30:20
  the
• 30:20
  world
• 30:20
  who
• 30:20
  knows
• 30:21
  absolutely
• 30:21
  nothing.
• 30:22
  Other
• 30:22
  times
• 30:22
  it's
• 30:23
  like
• 30:23
  you're
• 30:23
  handing
• 30:23
  a
• 30:23
  task
• 30:24
  off
• 30:24
  to
• 30:24
  the
• 30:24
  most,
• 30:25
  you
• 30:25
  know,
• 30:25
  seasoned
• 30:26
  old
• 30:26
  graybeard
• 30:26
  who
• 30:27
  knows
• 30:27
  everything.
• 30:29
  And
• 30:29
  sometimes
• 30:29
  it's
• 30:30
  somewhere
• 30:30
  in
• 30:30
  the
• 30:30
  middle.
• 30:30
  It's
• 30:31
  somewhere
• 30:31
  in
• 30:31
  the
• 30:31
  middle.
• 30:31
  It's.
• 30:32
  Yeah,
• 30:32
  I've
• 30:33
  had
• 30:33
  a
• 30:33
  few,
• 30:34
  a
• 30:34
  few
• 30:34
  similar
• 30:35
  experiences
• 30:35
  similarly
• 30:36
  know
• 30:37
  how
• 30:37
  to
• 30:37
  code,
• 30:37
  don't
• 30:38
  know
• 30:38
  react.
• 30:39
  And
• 30:40
  I've
• 30:40
  had
• 30:40
  some
• 30:41
  fun
• 30:42
  personal
• 30:42
  projects
• 30:42
  where
• 30:43
  I'll
• 30:43
  have
• 30:44
  v0
• 30:45
  I
• 30:45
  use
• 30:46
  generate
• 30:46
  a
• 30:46
  front
• 30:47
  end
• 30:47
  and
• 30:47
  then
• 30:47
  import
• 30:47
  the
• 30:48
  React
• 30:48
  code
• 30:48
  into
• 30:48
  a
• 30:49
  cursor.
• 30:49
  And
• 30:50
  the
• 30:50
  feature
• 30:50
  I
• 30:50
  love
• 30:51
  of
• 30:51
  cursor
• 30:51
  is
• 30:53
  it'll
• 30:53
  tell
• 30:53
  you
• 30:53
  what
• 30:53
  the
• 30:54
  code
• 30:54
  is
• 30:54
  for.
• 30:56
  And
• 30:56
  you
• 30:56
  know,
• 30:57
  I
• 30:57
  have
• 30:57
  the
• 30:57
  logical
• 30:58
  mind
• 30:58
  of
• 30:58
  a
• 30:58
  programmer,
• 30:59
  but
• 30:59
  if
• 30:59
  you
• 30:59
  don't
• 30:59
  know
• 30:59
  the
• 31:00
  language,
• 31:00
  it
• 31:00
  sometimes
• 31:00
  helps
• 31:01
  to
• 31:01
  see
• 31:01
  that
• 31:02
  construct
• 31:02
  and
• 31:02
  see
• 31:02
  it
• 31:03
  break
• 31:03
  down.
• 31:04
  The
• 31:04
  same
• 31:04
  with
• 31:05
  SQL.
• 31:06
  Could
• 31:07
  I
• 31:07
  write
• 31:07
  a
• 31:07
  two
• 31:08
  page
• 31:08
  SQL
• 31:08
  query
• 31:09
  from
• 31:09
  scratch
• 31:09
  that
• 31:10
  was
• 31:10
  precise.
• 31:11
  No,
• 31:12
  but
• 31:13
  can
• 31:13
  I
• 31:13
  get
• 31:13
  halfway
• 31:14
  there
• 31:14
  and
• 31:14
  then
• 31:14
  say
• 31:15
  finish
• 31:15
  this
• 31:15
  off
• 31:15
  and
• 31:16
  then
• 31:16
  manually
• 31:16
  be
• 31:16
  the
• 31:16
  human
• 31:17
  in
• 31:17
  the
• 31:17
  loop
• 31:17
  and
• 31:17
  check
• 31:17
  the
• 31:17
  logic
• 31:18
  afterwards?
• 31:18
  Yes,
• 31:18
  I
• 31:18
  can
• 31:18
  also
• 31:19
  do
• 31:19
  that.
• 31:19
  So.
• 31:22
  I
• 31:22
  find
• 31:22
  it
• 31:22
  incredibly
• 31:23
  powerful
• 31:24
  for
• 31:24
  those
• 31:24
  instances.
• 31:25
  And
• 31:25
  then
• 31:26
  with
• 31:26
  your
• 31:27
  picture
• 31:27
  thing.
• 31:27
  My
• 31:27
  wife
• 31:28
  and
• 31:28
  I
• 31:28
  were
• 31:28
  in
• 31:28
  Indiana
• 31:29
  in
• 31:29
  August
• 31:30
  and
• 31:31
  there
• 31:31
  were
• 31:31
  a
• 31:31
  lot
• 31:31
  of
• 31:31
  fields
• 31:32
  and
• 31:32
  it
• 31:32
  seemed
• 31:32
  to
• 31:33
  be
• 31:33
  just
• 31:33
  two
• 31:33
  types
• 31:33
  of
• 31:33
  crop.
• 31:34
  One
• 31:34
  of
• 31:34
  them
• 31:34
  was
• 31:34
  corn.
• 31:34
  That
• 31:35
  was
• 31:35
  easy.
• 31:35
  Like
• 31:35
  everyone
• 31:36
  knows
• 31:36
  what
• 31:36
  corn
• 31:36
  looks
• 31:36
  like.
• 31:36
  I
• 31:37
  know
• 31:37
  what
• 31:37
  corn
• 31:37
  looks.
• 31:38
  It
• 31:38
  was
• 31:38
  a
• 31:38
  dangling
• 31:38
  off
• 31:39
  the
• 31:39
  other
• 31:39
  one,
• 31:39
  but
• 31:39
  then
• 31:39
  there
• 31:39
  was
• 31:40
  this
• 31:40
  other
• 31:40
  one.
• 31:42
  And
• 31:42
  it
• 31:42
  maybe
• 31:42
  was
• 31:43
  like
• 31:43
  2ft
• 31:44
  tall,
• 31:45
  very
• 31:45
  sort
• 31:45
  of
• 31:45
  neat,
• 31:46
  dark
• 31:46
  green
• 31:46
  leaves,
• 31:47
  fields
• 31:48
  and
• 31:48
  fields
• 31:48
  and
• 31:48
  fields
• 31:48
  of
• 31:48
  it.
• 31:49
  And
• 31:49
  we
• 31:49
  had
• 31:49
  no
• 31:49
  idea
• 31:49
  and
• 31:50
  we
• 31:50
  even
• 31:50
  went
• 31:50
  up
• 31:50
  to
• 31:50
  the
• 31:50
  plants
• 31:50
  and
• 31:51
  we
• 31:51
  couldn't
• 31:51
  quite
• 31:51
  work
• 31:51
  it
• 31:51
  out.
• 31:52
  GPT
• 31:53
  knew
• 31:53
  exactly.
• 31:53
  Same
• 31:54
  thing.
• 31:54
  Like
• 31:54
  it
• 31:54
  knew
• 31:54
  where
• 31:55
  we
• 31:55
  were.
• 31:57
  You're
• 31:57
  in
• 31:57
  Indiana,
• 31:58
  there's
• 31:58
  only
• 31:58
  two
• 31:59
  world
• 31:59
  crops
• 31:59
  that
• 31:59
  are
• 31:59
  growing
• 31:59
  around
• 32:00
  there,
• 32:00
  corn
• 32:01
  and
• 32:01
  soybeans.
• 32:03
  There
• 32:03
  were
• 32:04
  acres
• 32:04
  and
• 32:04
  acres
• 32:05
  of
• 32:05
  soybeans.
• 32:05
  I
• 32:05
  never
• 32:06
  knew
• 32:06
  Indiana,
• 32:06
  Indiana
• 32:07
  had
• 32:07
  a,
• 32:09
  a
• 32:09
  soybean
• 32:09
  thing
• 32:10
  going
• 32:10
  on.
• 32:11
  But
• 32:11
  it's.
• 32:13
  I
• 32:13
  want
• 32:13
  to
• 32:13
  pick
• 32:13
  up
• 32:13
  on
• 32:14
  the
• 32:14
  point
• 32:14
  you
• 32:14
  made
• 32:14
  about
• 32:14
  sometimes
• 32:15
  as
• 32:15
  a
• 32:15
  junior
• 32:15
  developer,
• 32:16
  sometimes
• 32:16
  it's
• 32:17
  a
• 32:17
  kind
• 32:17
  of.
• 32:17
  It
• 32:17
  can
• 32:17
  be
• 32:18
  a
• 32:18
  master,
• 32:18
  a
• 32:19
  master
• 32:19
  developer.
• 32:19
  And
• 32:19
  some
• 32:20
  of
• 32:20
  that
• 32:20
  integration
• 32:20
  work
• 32:20
  that
• 32:21
  you
• 32:21
  talked
• 32:21
  about
• 32:21
  in
• 32:21
  terms
• 32:21
  of
• 32:22
  building
• 32:22
  a
• 32:22
  database,
• 32:22
  getting
• 32:23
  linking
• 32:23
  the
• 32:23
  back
• 32:23
  end
• 32:24
  to
• 32:24
  the
• 32:24
  front
• 32:24
  end,
• 32:24
  that's
• 32:24
  where
• 32:25
  I
• 32:25
  find
• 32:25
  most
• 32:25
  people
• 32:26
  fall
• 32:26
  down
• 32:26
  with
• 32:26
  their
• 32:26
  AI
• 32:27
  personal
• 32:27
  projects
• 32:28
  who
• 32:28
  can't
• 32:28
  code.
• 32:29
  Like
• 32:29
  sticking
• 32:30
  it
• 32:30
  all
• 32:30
  together
• 32:30
  and
• 32:31
  getting
• 32:31
  the
• 32:31
  database
• 32:31
  to
• 32:31
  understand
• 32:32
  what's
• 32:32
  happening
• 32:32
  on
• 32:32
  the
• 32:32
  front
• 32:33
  end
• 32:33
  is,
• 32:34
  is
• 32:35
  tricky
• 32:36
  still
• 32:37
  for
• 32:37
  some
• 32:37
  of
• 32:38
  today's
• 32:39
  app.
• 32:40
  But
• 32:41
  I
• 32:41
  think
• 32:41
  it's
• 32:41
  safe
• 32:41
  to
• 32:41
  say
• 32:42
  that
• 32:42
  most
• 32:42
  junior
• 32:43
  development
• 32:43
  tests
• 32:44
  it's
• 32:44
  easy
• 32:44
  to
• 32:44
  do.
• 32:45
  So
• 32:45
  I
• 32:45
  worry
• 32:46
  it
• 32:46
  creates
• 32:46
  a
• 32:46
  supply
• 32:47
  issue.
• 32:47
  I
• 32:47
  still
• 32:48
  see
• 32:48
  like
• 32:49
  wizened
• 32:49
  integration
• 32:50
  engineers
• 32:50
  and
• 32:51
  experienced
• 32:52
  software
• 32:52
  engineers
• 32:53
  in
• 32:53
  super
• 32:53
  high
• 32:54
  demand.
• 32:54
  But
• 32:55
  it
• 32:55
  worries
• 32:55
  me
• 32:56
  a
• 32:56
  bit
• 32:56
  that.
• 32:58
  The
• 32:59
  more
• 32:59
  organizations
• 33:00
  use
• 33:01
  AI
• 33:01
  or
• 33:01
  able
• 33:02
  to
• 33:02
  use
• 33:02
  AI
• 33:02
  for
• 33:02
  junior
• 33:03
  software
• 33:03
  engineering
• 33:03
  tasks,
• 33:03
  the
• 33:04
  less
• 33:04
  opportunity
• 33:04
  it
• 33:04
  creates
• 33:05
  for
• 33:05
  junior
• 33:05
  software
• 33:05
  engineers
• 33:06
  who
• 33:06
  of
• 33:06
  course
• 33:06
  become
• 33:07
  the
• 33:07
  future
• 33:07
  senior
• 33:07
  software
• 33:08
  engineers.
• 33:08
  So.
• 33:10
  Again,
• 33:11
  just
• 33:11
  a
• 33:11
  personal
• 33:12
  hypothesis
• 33:12
  and
• 33:12
  I've
• 33:12
  not
• 33:13
  seen
• 33:13
  any
• 33:13
  of
• 33:13
  it
• 33:13
  play
• 33:13
  out,
• 33:14
  but
• 33:15
  I
• 33:15
  wonder
• 33:16
  what
• 33:16
  happens
• 33:16
  in
• 33:16
  the
• 33:17
  future.
• 33:17
  My
• 33:17
  hope
• 33:17
  is
• 33:17
  that
• 33:18
  everyone
• 33:18
  becomes
• 33:18
  more
• 33:19
  kind
• 33:19
  of
• 33:19
  multi
• 33:20
  skilled
• 33:21
  generalist
• 33:23
  and
• 33:23
  more
• 33:23
  valuable.
• 33:24
  I
• 33:24
  don't
• 33:24
  know
• 33:25
  any
• 33:25
  thoughts.
• 33:25
  I,
• 33:26
  I
• 33:26
  don't
• 33:27
  know
• 33:27
  that
• 33:29
  everyone
• 33:29
  being
• 33:29
  more
• 33:30
  generalist
• 33:30
  is
• 33:32
  the
• 33:32
  way
• 33:32
  I
• 33:33
  would
• 33:33
  quite
• 33:33
  put
• 33:33
  it.
• 33:34
  So
• 33:34
  I
• 33:35
  do
• 33:35
  completely
• 33:36
  agree
• 33:36
  with
• 33:37
  the
• 33:38
  dynamics
• 33:38
  of
• 33:38
  the
• 33:38
  situation
• 33:39
  that
• 33:39
  you're
• 33:39
  describing.
• 33:40
  Right.
• 33:40
  Is,
• 33:41
  and
• 33:41
  I
• 33:42
  just
• 33:42
  from
• 33:42
  what
• 33:43
  I've
• 33:43
  read
• 33:43
  in
• 33:44
  the
• 33:44
  news,
• 33:44
  right.
• 33:45
  Is
• 33:45
  demand
• 33:46
  for
• 33:47
  junior
• 33:48
  engineers,
• 33:48
  entry
• 33:49
  level
• 33:49
  people
• 33:49
  is
• 33:50
  down
• 33:51
  while
• 33:51
  demand
• 33:52
  for
• 33:52
  senior
• 33:52
  people
• 33:52
  remains
• 33:53
  high.
• 33:53
  Yes,
• 33:54
  we
• 33:54
  are.
• 33:55
  The
• 33:55
  industry
• 33:56
  is
• 33:56
  eating
• 33:57
  its
• 33:57
  seed
• 33:57
  corn.
• 33:58
  Right.
• 33:58
  So
• 33:59
  if
• 33:59
  you
• 33:59
  don't
• 34:00
  grow
• 34:01
  the
• 34:02
  experts
• 34:03
  of
• 34:03
  the
• 34:03
  future,
• 34:05
  then
• 34:05
  there
• 34:05
  won't
• 34:05
  be
• 34:06
  any.
• 34:06
  Right.
• 34:06
  And
• 34:06
  if
• 34:06
  you
• 34:07
  take
• 34:07
  away
• 34:07
  the
• 34:07
  junior
• 34:08
  opportunities
• 34:09
  today,
• 34:10
  yeah,
• 34:11
  you're
• 34:11
  keeping
• 34:11
  people
• 34:11
  from
• 34:12
  getting
• 34:12
  into
• 34:12
  that
• 34:12
  path
• 34:13
  to
• 34:13
  be
• 34:13
  the,
• 34:13
  the
• 34:14
  experts
• 34:14
  in
• 34:14
  the
• 34:14
  future.
• 34:15
  So
• 34:16
  I
• 34:16
  worry
• 34:16
  that
• 34:17
  we're.
• 34:19
  High
• 34:19
  on
• 34:20
  a
• 34:21
  artificially
• 34:22
  large
• 34:23
  supply
• 34:23
  of
• 34:25
  engineers
• 34:26
  right
• 34:26
  now.
• 34:26
  That
• 34:26
  won't
• 34:26
  be
• 34:27
  the
• 34:27
  case
• 34:27
  in
• 34:27
  the
• 34:27
  future.
• 34:28
  Depending
• 34:28
  on
• 34:28
  the
• 34:28
  day
• 34:29
  I
• 34:29
  might
• 34:29
  go
• 34:29
  glass
• 34:29
  half
• 34:30
  full
• 34:30
  on
• 34:30
  it
• 34:30
  and
• 34:30
  instead
• 34:31
  say
• 34:31
  actually
• 34:32
  basic
• 34:32
  software
• 34:32
  engineering
• 34:33
  just
• 34:33
  became
• 34:34
  more
• 34:34
  accessible
• 34:34
  to
• 34:35
  way
• 34:35
  more
• 34:35
  people
• 34:35
  than
• 34:35
  it
• 34:35
  ever
• 34:36
  was
• 34:36
  before.
• 34:37
  And
• 34:37
  it's
• 34:37
  less
• 34:37
  technical.
• 34:40
  Less
• 34:40
  technical
• 34:41
  a
• 34:41
  procedure
• 34:41
  to
• 34:42
  take.
• 34:42
  Like
• 34:43
  you
• 34:43
  don't
• 34:43
  have
• 34:43
  to
• 34:43
  start
• 34:43
  from
• 34:43
  a
• 34:43
  command
• 34:44
  line
• 34:44
  anymore
• 34:44
  like
• 34:44
  I
• 34:44
  used
• 34:45
  to
• 34:46
  back
• 34:46
  in
• 34:46
  college.
• 34:47
  So
• 34:47
  it
• 34:47
  feels
• 34:47
  instantly
• 34:48
  more
• 34:48
  accessible.
• 34:48
  So
• 34:49
  maybe
• 34:50
  the
• 34:50
  doors
• 34:51
  are.
• 34:51
  I
• 34:51
  think
• 34:51
  every
• 34:52
  generation
• 34:52
  feels
• 34:52
  that
• 34:53
  way
• 34:53
  though,
• 34:53
  right.
• 34:54
  I
• 34:54
  think
• 34:54
  that
• 34:55
  the
• 34:56
  people
• 34:57
  who
• 34:57
  were
• 34:57
  writing
• 34:58
  in
• 34:58
  C
• 34:58
  when
• 34:59
  they
• 34:59
  were
• 34:59
  young
• 34:59
  were
• 34:59
  made
• 35:00
  fun
• 35:00
  of
• 35:00
  because
• 35:00
  they
• 35:01
  weren't
• 35:01
  writing
• 35:02
  in
• 35:02
  machine
• 35:02
  code.
• 35:03
  And
• 35:03
  the
• 35:03
  people
• 35:03
  who
• 35:04
  were
• 35:04
  writing
• 35:05
  java
• 35:06
  in
• 35:06
  the
• 35:07
  90s
• 35:07
  and
• 35:07
  2000s
• 35:08
  were
• 35:08
  being
• 35:09
  made
• 35:09
  fun
• 35:09
  of
• 35:09
  because
• 35:10
  they
• 35:10
  weren't
• 35:10
  writing
• 35:11
  in
• 35:11
  C.
• 35:11
  Right.
• 35:12
  It's
• 35:12
  like
• 35:12
  whoever
• 35:13
  was
• 35:13
  at
• 35:14
  the
• 35:14
  level
• 35:14
  of
• 35:15
  abstraction
• 35:16
  just
• 35:16
  before
• 35:16
  you
• 35:17
  is
• 35:18
  going
• 35:18
  to
• 35:18
  criticize
• 35:18
  you
• 35:19
  for
• 35:19
  being
• 35:20
  at
• 35:20
  a
• 35:20
  greater
• 35:20
  level
• 35:20
  of
• 35:21
  abstraction.
• 35:21
  The
• 35:22
  one
• 35:22
  thing
• 35:22
  that's
• 35:22
  done
• 35:22
  back
• 35:22
  to
• 35:22
  your
• 35:23
  point
• 35:23
  about
• 35:23
  making
• 35:23
  things
• 35:23
  real,
• 35:24
  and
• 35:24
  I
• 35:24
  think
• 35:24
  about
• 35:25
  this
• 35:25
  from
• 35:25
  a
• 35:25
  product
• 35:26
  perspective,
• 35:27
  a
• 35:27
  paper
• 35:28
  prototype
• 35:28
  is
• 35:29
  all
• 35:29
  well
• 35:29
  and
• 35:29
  good,
• 35:29
  but
• 35:30
  if
• 35:30
  you
• 35:30
  can
• 35:30
  put
• 35:30
  together
• 35:31
  a
• 35:31
  functional
• 35:32
  or
• 35:32
  seemingly
• 35:32
  functional
• 35:33
  front
• 35:33
  end,
• 35:33
  even
• 35:33
  if
• 35:33
  there's
• 35:33
  no
• 35:34
  backend
• 35:34
  behind
• 35:34
  it,
• 35:35
  it's
• 35:36
  easier
• 35:36
  to
• 35:36
  sort
• 35:36
  of
• 35:37
  test
• 35:37
  products
• 35:38
  with
• 35:38
  users
• 35:39
  than
• 35:39
  it
• 35:39
  ever
• 35:40
  has
• 35:40
  been
• 35:40
  before.
• 35:41
  But
• 35:42
  that
• 35:42
  coupled
• 35:43
  with
• 35:43
  the
• 35:43
  large
• 35:43
  language
• 35:44
  models,
• 35:44
  focus
• 35:44
  on
• 35:45
  words
• 35:46
  and
• 35:46
  repeatable
• 35:46
  patterns
• 35:47
  and
• 35:48
  predicting.
• 35:49
  One
• 35:49
  of
• 35:49
  the
• 35:49
  things
• 35:49
  I've
• 35:50
  seen
• 35:50
  people
• 35:50
  train
• 35:51
  LLMs
• 35:51
  really
• 35:51
  effectively
• 35:52
  on
• 35:52
  is
• 35:52
  marketing,
• 35:52
  sales
• 35:53
  and
• 35:53
  marketing.
• 35:54
  And
• 35:54
  I've
• 35:55
  certainly
• 35:55
  observed
• 35:55
  in
• 35:56
  the
• 35:56
  world
• 35:56
  of
• 35:57
  wide
• 35:58
  company
• 35:58
  to
• 35:58
  SaaS
• 35:58
  platform
• 35:59
  type
• 36:00
  areas,
• 36:00
  the
• 36:01
  people
• 36:01
  have
• 36:02
  become
• 36:02
  on
• 36:02
  average
• 36:03
  a
• 36:03
  lot
• 36:03
  better
• 36:03
  at
• 36:03
  sales
• 36:03
  and
• 36:04
  marketing,
• 36:04
  but
• 36:04
  on
• 36:04
  average
• 36:05
  not
• 36:05
  a
• 36:05
  lot
• 36:05
  better
• 36:05
  at
• 36:06
  delivery
• 36:06
  of
• 36:06
  value
• 36:07
  and
• 36:07
  focus
• 36:07
  on
• 36:07
  solving
• 36:08
  the
• 36:08
  problems
• 36:08
  that
• 36:08
  actually
• 36:09
  matter.
• 36:10
  It'll
• 36:10
  be
• 36:10
  interesting
• 36:11
  to
• 36:11
  see
• 36:11
  how
• 36:11
  that
• 36:11
  evolves.
• 36:12
  And
• 36:12
  of
• 36:12
  course
• 36:13
  you
• 36:13
  need
• 36:13
  the
• 36:14
  is
• 36:15
  a
• 36:15
  different
• 36:15
  type
• 36:15
  of
• 36:15
  data,
• 36:16
  but
• 36:16
  you
• 36:17
  still
• 36:17
  need
• 36:17
  data
• 36:18
  to
• 36:18
  back
• 36:18
  up
• 36:18
  a
• 36:18
  hypothesis
• 36:19
  that
• 36:19
  a
• 36:19
  product
• 36:20
  is
• 36:20
  worth
• 36:21
  having.
• 36:21
  And
• 36:22
  certainly
• 36:22
  my
• 36:22
  experiences
• 36:23
  were
• 36:23
  flooded
• 36:23
  with
• 36:24
  many
• 36:24
  products
• 36:24
  out
• 36:25
  there.
• 36:25
  Back
• 36:25
  to
• 36:25
  your
• 36:25
  original
• 36:26
  point
• 36:26
  about
• 36:26
  how
• 36:27
  you
• 36:27
  operate.
• 36:28
  If
• 36:28
  you're
• 36:28
  not
• 36:28
  connected
• 36:29
  to
• 36:29
  the
• 36:29
  humans
• 36:30
  who
• 36:30
  have
• 36:30
  a
• 36:31
  need
• 36:31
  or
• 36:31
  the
• 36:31
  business
• 36:32
  that
• 36:32
  is
• 36:32
  trying
• 36:32
  to
• 36:32
  drive
• 36:33
  value,
• 36:33
  it's
• 36:33
  now
• 36:34
  possible
• 36:34
  to
• 36:34
  create
• 36:34
  a
• 36:34
  product
• 36:35
  very
• 36:35
  quickly
• 36:35
  that's
• 36:36
  of
• 36:36
  no
• 36:36
  use
• 36:36
  whatsoever
• 36:38
  to
• 36:38
  anybody.
• 36:39
  And
• 36:39
  recall
• 36:40
  that
• 36:40
  these
• 36:40
  LLMs,
• 36:41
  the
• 36:42
  L
• 36:42
  is
• 36:42
  for
• 36:43
  second
• 36:43
  L,
• 36:43
  at
• 36:44
  least
• 36:44
  is
• 36:44
  for
• 36:44
  language.
• 36:45
  Right.
• 36:45
  These
• 36:45
  things
• 36:45
  are
• 36:46
  designed
• 36:46
  to
• 36:46
  manipulate
• 36:48
  words,
• 36:49
  not
• 36:49
  numbers.
• 36:50
  And
• 36:51
  so
• 36:51
  I've
• 36:53
  heard
• 36:53
  some
• 36:53
  very
• 36:54
  seasoned
• 36:54
  data
• 36:55
  scientists
• 36:55
  and
• 36:56
  statisticians
• 36:56
  point
• 36:57
  out
• 36:57
  that
• 36:58
  your
• 36:59
  optimization
• 36:59
  models,
• 37:00
  your
• 37:00
  forecasting
• 37:01
  models,
• 37:02
  these
• 37:02
  things
• 37:03
  are
• 37:04
  still
• 37:04
  very
• 37:06
  much
• 37:06
  in
• 37:06
  need
• 37:06
  of
• 37:07
  expert
• 37:08
  statisticians
• 37:09
  building
• 37:09
  them.
• 37:10
  Right.
• 37:10
  Like
• 37:11
  anything
• 37:11
  that
• 37:11
  involves.
• 37:14
  Yeah,
• 37:15
  numbers
• 37:15
  is
• 37:16
  just
• 37:16
  something
• 37:16
  that
• 37:16
  LLMs
• 37:17
  by
• 37:17
  their
• 37:18
  very
• 37:18
  nature
• 37:19
  are
• 37:19
  not
• 37:19
  going
• 37:19
  to
• 37:19
  be
• 37:20
  good
• 37:20
  at.
• 37:20
  Yeah,
• 37:21
  I
• 37:21
  see.
• 37:22
  And
• 37:22
  I
• 37:22
  know
• 37:23
  in
• 37:23
  a
• 37:23
  large
• 37:23
  enterprise
• 37:24
  this
• 37:24
  nightmare
• 37:24
  will
• 37:25
  never
• 37:25
  come
• 37:25
  to
• 37:25
  fruition,
• 37:25
  but
• 37:26
  I
• 37:26
  see
• 37:26
  the,
• 37:26
  the
• 37:27
  nightmare
• 37:27
  flying
• 37:27
  around
• 37:28
  out
• 37:28
  there
• 37:28
  of
• 37:29
  CEOs
• 37:30
  saying
• 37:30
  oh,
• 37:31
  forget
• 37:31
  the
• 37:31
  data.
• 37:31
  I
• 37:31
  just,
• 37:32
  let's,
• 37:32
  let's
• 37:32
  get
• 37:32
  AI
• 37:33
  and
• 37:33
  AI
• 37:33
  will
• 37:35
  make
• 37:35
  smart
• 37:35
  intelligent
• 37:36
  guesses.
• 37:36
  Even
• 37:36
  if
• 37:36
  my
• 37:36
  data
• 37:37
  quality
• 37:37
  is
• 37:37
  really
• 37:37
  bad,
• 37:37
  AI
• 37:38
  will
• 37:38
  fix
• 37:38
  it.
• 37:38
  And
• 37:39
  it's,
• 37:39
  and
• 37:39
  you
• 37:39
  know,
• 37:40
  I
• 37:40
  shudder
• 37:40
  at
• 37:41
  some
• 37:41
  of
• 37:41
  the
• 37:42
  potential
• 37:42
  mishaps
• 37:43
  that
• 37:43
  will
• 37:43
  come
• 37:43
  off
• 37:44
  of
• 37:45
  the
• 37:45
  back
• 37:45
  of
• 37:45
  that.
• 37:45
  So
• 37:46
  it
• 37:46
  all
• 37:46
  goes
• 37:46
  back
• 37:47
  to
• 37:47
  what
• 37:47
  you're
• 37:47
  talking
• 37:47
  about
• 37:48
  in
• 37:48
  terms
• 37:48
  of.
• 37:48
  I
• 37:49
  will
• 37:49
  use
• 37:50
  a
• 37:51
  very
• 37:51
  appropriately
• 37:52
  home
• 37:52
  improvement
• 37:53
  related
• 37:53
  metaphor
• 37:54
  for
• 37:54
  that.
• 37:55
  Your
• 37:56
  home
• 37:56
  is
• 37:56
  built
• 37:56
  on
• 37:56
  a
• 37:57
  foundation
• 37:58
  and
• 37:58
  if
• 37:59
  you
• 37:59
  have
• 37:59
  cracks
• 38:00
  in
• 38:00
  your
• 38:00
  foundation,
• 38:01
  there
• 38:02
  is
• 38:02
  nothing
• 38:02
  that
• 38:03
  you
• 38:03
  can
• 38:03
  do
• 38:03
  to
• 38:04
  shore
• 38:04
  up
• 38:04
  the
• 38:05
  structure
• 38:06
  that
• 38:06
  will
• 38:07
  paper
• 38:07
  over
• 38:08
  or
• 38:08
  gloss
• 38:09
  over
• 38:10
  the
• 38:10
  underlying
• 38:11
  foundation
• 38:11
  problems.
• 38:12
  Right.
• 38:13
  So.
• 38:14
  You
• 38:15
  know,
• 38:15
  data
• 38:15
  governance,
• 38:16
  data
• 38:16
  management
• 38:17
  are
• 38:18
  as
• 38:18
  essential
• 38:18
  as
• 38:19
  ever.
• 38:20
  That
• 38:20
  is
• 38:20
  the
• 38:21
  foundation
• 38:21
  on
• 38:21
  which
• 38:21
  your
• 38:22
  data
• 38:22
  ecosystem
• 38:23
  is
• 38:23
  built.
• 38:23
  Your
• 38:24
  data
• 38:24
  will
• 38:24
  never
• 38:25
  be
• 38:26
  useful
• 38:27
  for
• 38:27
  AI
• 38:28
  if
• 38:28
  it's
• 38:29
  not
• 38:29
  just
• 38:29
  useful
• 38:30
  as
• 38:30
  data.
• 38:31
  And
• 38:31
  so
• 38:32
  all
• 38:32
  those
• 38:32
  fundamentals
• 38:33
  of
• 38:33
  ensuring
• 38:34
  your
• 38:34
  data
• 38:35
  is
• 38:35
  well
• 38:36
  cataloged
• 38:36
  and
• 38:37
  well
• 38:37
  organized
• 38:37
  and
• 38:38
  well
• 38:38
  governed
• 38:38
  all
• 38:39
  apply
• 38:39
  just
• 38:39
  as
• 38:40
  much
• 38:40
  as
• 38:40
  they
• 38:40
  ever
• 38:40
  did
• 38:40
  and
• 38:41
  probably
• 38:41
  more.
• 38:41
  So,
• 38:42
  yeah,
• 38:42
  this
• 38:42
  should
• 38:42
  be
• 38:43
  the
• 38:43
  golden
• 38:43
  period
• 38:44
  for
• 38:44
  data
• 38:44
  governance
• 38:45
  and
• 38:45
  I'm
• 38:45
  not
• 38:45
  sure
• 38:45
  the
• 38:45
  whole
• 38:46
  world
• 38:46
  has
• 38:46
  quite
• 38:46
  cottoned
• 38:47
  onto
• 38:47
  that
• 38:47
  yet.
• 38:47
  And
• 38:48
  maybe
• 38:48
  there's
• 38:48
  a
• 38:48
  few
• 38:48
  failed
• 38:49
  AI
• 38:49
  projects
• 38:49
  that
• 38:50
  need
• 38:50
  to
• 38:50
  happen
• 38:50
  out
• 38:50
  there
• 38:51
  before
• 38:52
  we
• 38:52
  all
• 38:52
  get
• 38:52
  there,
• 38:52
  but
• 38:54
  absolutely
• 38:55
  the
• 38:56
  solidity
• 38:56
  of
• 38:57
  those
• 38:57
  foundations.
• 39:00
  Suitably
• 39:00
  on
• 39:00
  my
• 39:00
  behalf
• 39:01
  as
• 39:01
  well
• 39:01
  seen
• 39:01
  as
• 39:01
  those
• 39:01
  literal
• 39:02
  foundations
• 39:02
  being
• 39:03
  poured
• 39:04
  next
• 39:05
  door
• 39:05
  to
• 39:05
  me
• 39:05
  right
• 39:05
  now
• 39:06
  at
• 39:07
  the
• 39:07
  expense
• 39:07
  of
• 39:07
  the
• 39:07
  mice.
• 39:10
  You
• 39:10
  know,
• 39:11
  will
• 39:11
  have
• 39:11
  to
• 39:12
  be
• 39:12
  spot
• 39:12
  on
• 39:12
  and
• 39:13
  correct.
• 39:13
  Otherwise
• 39:13
  the,
• 39:14
  the
• 39:14
  house
• 39:14
  will
• 39:14
  always
• 39:15
  be
• 39:15
  shaking.
• 39:15
  All
• 39:16
  right,
• 39:16
  Scott,
• 39:16
  hi,
• 39:18
  thanks
• 39:18
  so
• 39:18
  much
• 39:18
  for,
• 39:19
  for
• 39:20
  coming
• 39:20
  on.
• 39:20
  You
• 39:20
  know,
• 39:20
  I've,
• 39:21
  you
• 39:21
  know,
• 39:21
  I've
• 39:21
  known
• 39:21
  each
• 39:21
  other
• 39:22
  for
• 39:22
  a
• 39:22
  long
• 39:22
  time.
• 39:23
  I
• 39:23
  always
• 39:23
  enjoy
• 39:24
  chatting
• 39:24
  with
• 39:24
  you
• 39:24
  about
• 39:26
  all
• 39:26
  of
• 39:26
  the
• 39:27
  latest
• 39:27
  advancements
• 39:28
  and
• 39:29
  I'm
• 39:29
  sure.
• 39:32
  Home
• 39:32
  Depot
• 39:32
  is
• 39:32
  very
• 39:33
  lucky
• 39:33
  to
• 39:33
  have
• 39:33
  you
• 39:34
  and
• 39:34
  the
• 39:34
  amazing
• 39:34
  team
• 39:34
  that
• 39:34
  I'm
• 39:35
  sure
• 39:36
  you're
• 39:36
  building
• 39:36
  there.
• 39:37
  And
• 39:38
  thanks
• 39:38
  again
• 39:38
  for.
• 39:40
  Providing
• 39:41
  great
• 39:41
  service
• 39:41
  to
• 39:41
  all
• 39:41
  the
• 39:42
  customers,
• 39:42
  including
• 39:42
  me,
• 39:43
  who
• 39:43
  go
• 39:43
  in.
• 39:44
  Even
• 39:44
  if
• 39:44
  I'm
• 39:44
  only
• 39:45
  a
• 39:45
  part
• 39:45
  time
• 39:46
  diyist,
• 39:47
  I
• 39:48
  think
• 39:48
  my
• 39:49
  wife
• 39:49
  would
• 39:49
  certainly
• 39:49
  love
• 39:49
  me
• 39:50
  to
• 39:50
  spend
• 39:50
  more
• 39:50
  time
• 39:50
  with
• 39:51
  you
• 39:51
  all.
• 39:52
  I'm
• 39:52
  always
• 39:52
  happy
• 39:53
  to
• 39:53
  help
• 39:53
  you
• 39:53
  find
• 39:53
  the
• 39:53
  mousetraps.
• 39:54
  Yeah,
• 39:55
  it
• 39:55
  did,
• 39:55
  but
• 39:56
  this
• 39:56
  was
• 39:56
  really
• 39:56
  fun.
• 39:57
  Thank
• 39:57
  you
• 39:58
  so
• 39:58
  much
• 39:58
  for
• 39:58
  having
• 39:58
  me
• 39:58
  on.
• 39:59
  It
• 39:59
  is
• 40:00
  always
• 40:00
  great
• 40:00
  to
• 40:00
  see
• 40:01
  you
• 40:01
  and
• 40:02
  yeah,
• 40:03
  this
• 40:03
  is
• 40:03
  a
• 40:03
  really
• 40:03
  nice,
• 40:04
  really
• 40:04
  nice
• 40:05
  time.
• 40:05
  Cool.
• 40:06
  Take
• 40:06
  care,
• 40:06
  Scott.
• 40:06
  I'll
• 40:07
  speak
• 40:07
  to
• 40:07
  you
• 40:07
  soon.
• 40:07
  Thanks
• 40:08
  for
• 40:08
  tuning
• 40:08
  in
• 40:08
  to
• 40:08
  Transformed
• 40:09
  with
• 40:09
  Data.
• 40:10
  If
• 40:10
  today's
• 40:11
  conversation
• 40:11
  gave
• 40:11
  you
• 40:11
  even
• 40:12
  one
• 40:12
  insight,
• 40:12
  one
• 40:13
  aha
• 40:13
  moment,
• 40:13
  or
• 40:14
  one
• 40:14
  new
• 40:14
  idea
• 40:14
  to
• 40:15
  take
• 40:15
  action
• 40:15
  on,
• 40:16
  do
• 40:16
  me
• 40:16
  a
• 40:16
  favor,
• 40:17
  subscribe,
• 40:18
  leave
• 40:18
  a
• 40:18
  review
• 40:18
  and
• 40:19
  share
• 40:19
  this
• 40:19
  with
• 40:19
  someone
• 40:19
  who's
• 40:20
  ready
• 40:20
  to
• 40:20
  level
• 40:20
  up
• 40:20
  up
• 40:21
  until
• 40:21
  next
• 40:22
  time.
• 40:22
  Keep
• 40:22
  asking
• 40:23
  the
• 40:23
  right
• 40:23
  questions,
• 40:24
  keep
• 40:24
  challenging
• 40:24
  the
• 40:25
  status
• 40:25
  quo
• 40:25
  and
• 40:26
  keep
• 40:26
  transforming
• 40:27
  with
• 40:27
  data.