Latest / Today’s AI News / ChatGPT Images 2.0 Reclaims Number One, Meta Logs Employee Keystrokes, Google’s Research Agent

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ChatGPT Images 2.0 Reclaims Number One, Meta Logs Employee Keystrokes, Google’s Research Agent · Today’s AI News

• 0:00
  Imagine trying to paint a masterpiece while blindfolded.
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  I mean, for the longest time that is exactly how AI image
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  generators used to work. Oh yeah, completely flying
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  blind. Right, they just threw pixels at
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  a canvas, but today the blindfold is off.
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  The AI has a sketchbook, a reference library, and a massive
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  eraser. Welcome back to today's AI News,
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  brought to you by 9X Productions.
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  Glad to be here for this one, it is a big week.
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  It really is. Our mission for this deep dive
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  is to look at a massive leap in AI reasoning, the somewhat
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  controversial ways companies are gathering data to fuel it, and
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  how you can actually use these exact tools to take control of
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  your daily workflow. Yeah, we're moving from theory
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  to some very intense practical applications.
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  Today. Exactly.
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  So let's start with the biggest development.
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  Open AI just dropped ChatGPT images two point O and look, if
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  you follow this space, you know Google's Nano Banana 2 has been
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  sitting comfortably at the number one spot on the Arena AI
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  leaderboard for a while. It was the undisputed
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  heavyweight, yeah. But that run is totally over
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  images 2 point O dethroned it and by a wide margin.
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  It swept every category. I mean, Sam Altman even compared
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  this upgrade to going from GPT 3 to GPT 5 all at once.
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  OK, let's unpack this because the specs are wild.
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  We're talking 2K resolution natively, generating up to 8
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  images at once, and supporting aspect ratios from like 3.1
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  ultra wide to 1.3 tall. And it actually nails
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  multilingual text rendering now, which, you know, used to just be
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  absolutely gibberish. Totally, but the specs aren't
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  even the main story here. It's the fact that the model
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  quote UN quote thinks before it generates the older generators
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  were just like a reflex action, right?
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  Right. What's fascinating here is how
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  the self checking mechanism changes the workflow.
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  Instead of acting like a slot machine where you pull a lever
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  and get 50 bad variations, it acts as its own art director.
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  Wait, really? Like it critiques itself.
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  Exactly. It plans out the image, searches
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  the web for references, drafts it, and then self checks for
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  errors like did I give this person 6 fingers?
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  Did I misspell the French text on this sign?
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  Oh, wow. So it uses that digital eraser
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  we talked about? Yeah.
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  It spots the hallucination and corrects it before delivering
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  the final result to you. So does this mean the whole
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  prompt engineering guessing game is just dead?
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  Pretty much you don't have to speak the machines quirky
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  language which anymore you just state your intent and the AI's
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  internal reasoning handles the execution.
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  That is a massive shift. But you know, while Open AI is
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  applying this thinking to visual creation, Google is pushing that
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  exact same autonomous reasoning into complex data analysis.
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  Right. They just dropped deep research
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  and deep research Max. Powered by a Gemini 3.1 Pro.
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  Yeah, replacing their December preview.
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  Yeah, and it is a beast. Max is currently beating models
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  like Opus 4.6 and GPT 5.4 in both retrieval and reasoning
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  benchmarks. It's the output that blew my
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  mind. It's not just a chat window.
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  It generates comprehensive research reports with native
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  charts and infographics pulling from the open web, uploaded
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  files or private data through MCP servers.
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  Yeah, the model context protocol, that is the key right
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  there. They're already partnering with
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  Pitchbook, S&P and FactSet to pipe paid financial data
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  directly in. But wait, so is this the end of
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  the entry level analyst? That is the $1,000,000 question.
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  I mean turning high level research into a simple priced
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  API call. Does that democratize knowledge
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  for us, or does it just automate human jobs away?
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  If we connect this to the bigger picture, you have to look at how
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  industries train experts. The pipeline always relied on
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  junior staff doing the foundational data gathering.
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  Now every major vertical is about to realize which parts of
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  those research workflows just became automatable.
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  So The Apprentice level work just vanishes.
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  Yeah, essentially it is a huge structural disruption.
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  Which brings us to a really dark reality.
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  Because to build these reasoning agents that replace human tasks,
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  AI companies need to learn exactly how humans operate on
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  computers in the first place. Right, they need the behavioral
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  data. And here's where it gets really
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  interesting. Meta has launched this model
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  capability initiative MCI and they are literally logging their
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  U employees keystrokes, screenshots and mouse activity
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  on work laptops. It's an unprecedented scale of
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  capture. They are heavily targeting
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  developers tracking activity in Viscode, their internal Meta
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  mate tool, Google Chat, Gmail and the CTO Andrew Bosworth sent
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  an internal memo explicitly stating there is no option to
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  opt out. Yeah, that memo definitely
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  ruffled some feathers. And the timing?
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  This logging started a month before roughly 8000 Meta
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  staffers are scheduled to be laid off on May 20th.
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  The optics are terrible, but technically speaking there is a
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  reason for it. They are trying to bridge the
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  gap between a language model and an action model.
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  Right, because an AI might know how to write an e-mail, but it
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  needs to know how to physically navigate the UI to send it like
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  we're human mouse hovers or how we backspace to fix a typo.
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  Exactly. It needs the human friction.
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  It's just like how Robotics Lab spent years recording humans
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  grabbing and stacking boxes to train physical robots.
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  Meta is applying that exact physical playbook to digital
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  office workers. It is the exact same playbook.
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  Human computer interaction data is the new oil.
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  But this raises an important question about the dystopian
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  ethics here. Not kidding.
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  You are balancing the trade off between building better models
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  and implementing total, inescapable surveillance of a
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  workforce, especially a workforce facing imminent
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  layoffs. It's heavy, it really is.
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  But let's sort of flip the script here, because while Big
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  Tech is monitoring workflows from the top down, you can
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  actually use these new AI capabilities to design your own
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  highly personalized daily workflow.
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  This is where the technology actually feels empowering for
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  the user. Let's talk about building a
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  command center with Claude Live Artifacts.
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  You can build a daily command center in Claude, Co work so you
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  don't have to individually open Slack, e-mail, calendar, and
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  docs all day. Yeah, the context switching is a
• 6:00
  productivity killer. So Step 1, you literally prompt
• 6:04
  Claude to interview you. You tell to ask about your
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  KPI's, your connected apps, and what you specifically count as
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  an urgent priority. I love that part because it
• 6:12
  learns your personal mental model first.
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  Exactly. Then Step 2 and 3, you ask it to
• 6:18
  build a modular live artifact dashboard based on that
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  interview. Give it a today view, this week,
• 6:24
  this month and it automatically applies priority labels like
• 6:28
  Urgent Review, FYI or Blocked. And it does all this securely,
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  without absorbing your company's private slack data into its core
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  training weights. Right.
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  And then Step 4 is the magic trick.
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  You add dedicated action buttons right into the bass board, like
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  a button that says plan my day or draft replies.
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  You are taking action directly from a custom interface, yeah?
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  And the pro tips are great, you can tell it to add a dark mode,
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  smooth animations and archive button or even manual override
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  so you keep control. So what does this all mean for
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  the listener? It represents A broader paradigm
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  shift. For decades we've had to adapt
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  our brains to fit rigid enterprise software.
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  Now we are shifting away from switching between dozens of apps
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  to operating out of a single intelligent AI generated command
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  center that adapts to us. It's tailored entirely to how
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  you work. It is incredible.
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  It really is. Well, let's jump into the quick
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  hits and everything else in AI today, because as these powerful
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  new agents hit the market, the ripple effects are definitely
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  speeding up across the industry. Well, lab shakeups alone this
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  week are wild. Totally.
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  Former Open AIVP Jerry Toric just launched Core Automation.
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  Their mission is to build an AI to build.
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  AI, which tells you exactly where the architecture is
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  headed, Yeah. Meanwhile, Meta just poached 3
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  more members from Mira Marotti's Thinking Machines lab.
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  That brings their total to seven from that team alone.
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  It is an absolute talent war right now.
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  Then we have some massive new tool releases.
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  Google just open source design dot MD.
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  It's a file format that lets agents understand a project's
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  brand and accessibility rules so they don't mess up your designs.
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  That is super practical for developers.
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  An aggress released Deepmax, an agentic search tool that tops
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  its rivals and runs 20 times faster.
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  Oh, and Genspark launched build is powered by Cloud Opus 4.7.
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  Yeah, the Vibe coding tool. Exactly, you literally generate
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  apps just from text prompts. Just pure vibe coding, but with
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  all this easy creation, there's a lot of noise.
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  These are just reported that 75,000 AI tracks are public to
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  their platform every single day. That number is just staggering.
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  It's 44% of their total daily uploads, but, and here's the
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  kicker, they only draw 1 to 3% of actual streams and 85% of
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  them are labeled as fraudulent. Wow.
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  I mean I was in absolute shock at that statistic.
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  Are we just entering an era where the Internet is totally
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  flooded with AI slop? Like making the advanced
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  reasoning and search we just talked about absolutely
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  necessary just to filter out the garbage.
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  Your theory is completely valid. Look, as generation cost dropped
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  to basically 0, the true value of AI in the ecosystem is going
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  to shift entirely to curation, filtering, and proving
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  authenticity. You literally need an AI to save
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  you from the AI. Pretty much, yeah.
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  Well, let's bring this deep dive back down to earth, because
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  despite the massive scale of Google and Meta, the most
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  exciting AI developments are actually happening in the
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  community. The niche individual use cases
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  are always the best part. I love this story.
• 9:25
  Matthew S from the UK used Claude to build his own custom
• 9:29
  exercise tracking app. He took the code, exported it to
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  Bolt and made it a live web app. Because none of the existing
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  apps on the market mapped his specific routine, right?
• 9:39
  Right, and they didn't award his streaks properly, so he just
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  built a custom interface with four sections and he hard coded
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  it so it only triggers a daily streak when all of his specific
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  targets are met. That is brilliant.
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  It ties right back to the Ginsburg vibe, code coding and
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  the clot artifacts we talked about.
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  Coding just isn't a barrier anymore.
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  Anyone can solve their highly specific niche problems in
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  minutes. And that is the ultimate promise
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  of AI. You are democratizing creation
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  so the software molds perfectly to the individual rather than
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  forcing the individual to mold to the software.
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  It really is a beautiful thing. It is, but before we wrap up I
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  want to leave you with one final, slightly mind bending
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  thought that connects everything we talked about today.
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  Oh boy, lay it on me. So if Meta is aggressively
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  tracking human keystrokes to train their AI, and humans are
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  increasingly using AI to automate their workflows and
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  eliminate their own keystrokes, what happens in five years when
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  the AI is just logging the keystrokes of other AI's?
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  Oh wow, that is a brain Bender. It's just machines studying
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  machines in an endless loop. It actually makes that
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  blindfolded painter metaphor from the start seem almost
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  quaint. The blindfold is definitely off
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  and it feels like the AI is starting to paint the rest of
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  the world for us. It really does.
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  Well, if you want to keep making sense of this wild new world
• 10:59
  with us, please make sure you hit subscribe so you stay
• 11:01
  updated. And if you enjoyed today's deep
• 11:03
  dive, please rate the show with five stars.
• 11:06
  It really helps us out. Thank you so much for hanging
• 11:08
  out with us, and we'll see you back for tomorrow's episode.