Latest / Elon Musk Podcast / Google is teaching AI to take your money - AI Update

Transcript

Google is teaching AI to take your money - AI Update · Elon Musk Podcast

• 0:00
  Welcome to AI Update, where we explore the latest advancements
• 0:03
  in artificial intelligence with insights into Open AI, Google,
• 0:07
  Gemini, generative AI, machine learning, and more.
• 0:11
  Now let's learn together. I'm your host, Will Walden.
• 0:14
  So how is Google DeepMind making its robots smarter with Gemini?
• 0:20
  And what new methods are they using to train these robots?
• 0:23
  Now imagine we're in a sci-fi movie like The Matrix, but
• 0:26
  instead of fighting machines, we're making them more
• 0:29
  intelligent and efficient, which is bad for us and for the
• 0:33
  humans. But Google DeepMind is
• 0:36
  leveraging its latest AI advancements to revolutionize
• 0:39
  robot training and efficiency so they can actually help us
• 0:43
  humans. Now they've introduced a cutting
• 0:46
  edge AI training method known as Gemini 1.5 Pro.
• 0:51
  This approach uses vision through video tours to train
• 0:55
  robots, enhancing their ability to maintain, navigate, and
• 0:59
  complete various tasks. And by utilizing this method,
• 1:03
  robots can learn more effectively from real world
• 1:06
  scenarios, thereby improving their operational efficiency and
• 1:10
  adaptability. Another significant development
• 1:13
  by Google Deepmine is the introduction of Jest, the joint
• 1:17
  example selection training. This method aims to optimize the
• 1:21
  AI training process, significantly reducing computing
• 1:25
  costs and also energy consumption.
• 1:28
  With reported 13 fold increase in performance and A10 fold
• 1:32
  improvement and power efficiency, Jest represents a
• 1:35
  major step forward in the economics of AI development.
• 1:40
  Now the innovation of Jest is particularly important given the
• 1:43
  ongoing discussions about the environmental impact and the
• 1:46
  high costs associated with AI data centers.
• 1:49
  And by reducing these barriers just could facilitate broader
• 1:53
  access to AI tech and accelerate advancements, especially in
• 1:56
  areas like e-commerce and multilingual support.
• 2:00
  Now it's important for these evolving AI methods.
• 2:05
  Now, new training methods for large language models are
• 2:07
  essential due to the rapidly evolving nature of data and the
• 2:11
  increasing demand for models that can adapt on the fly to new
• 2:14
  information and contexts. And since the inception of
• 2:17
  machine learning, AI training methods have evolved
• 2:21
  significantly. Traditional supervised learning
• 2:24
  methods relied on labeled data sets, while more recent
• 2:28
  approaches include unsupervised learning and reinforcement
• 2:31
  learning. These methods allow models to
• 2:34
  identify patterns in unlabeled data and learn through trial and
• 2:38
  error. Now, the GIST method differs
• 2:40
  from traditional AI training techniques by focusing on entire
• 2:43
  branches of data rather than individual data points.
• 2:47
  Initially, it creates a smaller AI model to assess data quality
• 2:51
  from high quality sources and ranks the batches accordingly.
• 2:55
  These rankings are then compared to a larger, lower quality data
• 2:59
  set to determine the most suitable batches for training a
• 3:02
  large model. Now, the innovative approach
• 3:04
  that's happening here ensures that the training process is
• 3:08
  more effective and more efficient.
• 3:10
  It reduces time and resources as well of the practical
• 3:14
  implications of just extend beyond general adaptability with
• 3:17
  potential applications in various specialized domains such
• 3:21
  as healthcare and also in finance.
• 3:24
  New methods are crucial for language models to respond
• 3:28
  accurately to questions about niche or about sensitive topics.
• 3:33
  This includes areas dealing with highly sensitive information the
• 3:37
  traditional LLM training algorithms might not handle
• 3:40
  appropriately, and several emerging approaches and AI
• 3:43
  training could significantly impact online commerce.
• 3:47
  One such method is reinforcement learning from human feedback, or
• 3:51
  RLHF, which fine tunes models based on user interactions.
• 3:56
  This technique could enhance recommendation systems,
• 3:59
  providing more personalized and relevant product offerings.
• 4:03
  Another promising technique is a parameter efficient fine tuning.
• 4:07
  It's PEFT, which allows AI models to adapt efficiently to
• 4:12
  specific tasks. Now, this method could be
• 4:15
  particularly beneficial for online retailers during peak
• 4:18
  sales periods, optimizing their algorithms for better
• 4:21
  performance and more money. You know, ensuring the language
• 4:25
  models can provide accurate responses in multiple languages
• 4:29
  is a critical aspect of AI development, especially for
• 4:32
  global e-commerce. Many companies mistakenly
• 4:35
  believe their AI systems can effectively translate content
• 4:38
  across different languages, but this often leads to
• 4:40
  inaccuracies, particularly with industry specific jargon.
• 4:45
  To tackle the issue, though, some organizations are
• 4:47
  developing new multilingual AI training approaches.
• 4:50
  Language IO, for instance, has implemented a retrieval,
• 4:54
  augmented generation, or RAG process influenced by
• 4:58
  multilingual strategies. This approach aims to enhance
• 5:01
  the accuracy of multilingual support in e-commerce settings.
• 5:07
  Now, advancements in AI training methods could transform online
• 5:10
  shopping by offering better product suggestions, improved
• 5:14
  customer support, and more efficient business operations.
• 5:18
  AI that comprehends multiple languages can help companies
• 5:21
  expand their footprint globally and improve customer
• 5:25
  satisfaction. So you would get repeat
• 5:27
  customers. And faster AI training methods
• 5:30
  might lead to quicker deployment of AI for various business
• 5:33
  tasks, such as better inventory management and enhance customer
• 5:37
  service chat bots. This has enabled businesses to
• 5:40
  operate more smoothly and respond to customer needs more
• 5:43
  effectively. Now, with more accurate AI that
• 5:47
  can communicate in multiple languages, businesses could
• 5:50
  enter new markets more efficiently and provide local
• 5:53
  services without relying on human translators.
• 5:56
  This capability could significantly enhance their
• 5:59
  global reach and customer service quality.
• 6:02
  Now, improved training approaches can enhance online
• 6:06
  commerce by enabling more accurate, context aware
• 6:09
  multilingual support. It leads to better customer
• 6:12
  experiences, reduced language barriers, and potentially
• 6:16
  increasing revenue. Now all that said, Google's
• 6:20
  DeepMind enhancements with Gemini AI and Jest are an
• 6:24
  important stride for AI and for commerce.
• 6:27
  They promise to make AI systems more efficient, adaptable, and
• 6:31
  capable for multi legal support, potentially transforming
• 6:35
  e-commerce and various sectors in the near future.
• 6:44
  Hey, thank you so much for listening today.
• 6:46
  I really do appreciate your support.
• 6:48
  If you could take a second and hit this subscribe or the follow
• 6:51
  button on whatever podcast platform that you're listening
• 6:53
  on right now, I greatly appreciate it.
• 6:56
  It helps out the show tremendously and you'll never
• 6:58
  miss an episode. And each episode is about 10
• 7:01
  minutes or less to get you caught up quickly.
• 7:04
  And please, if you want to support the show even more, go
• 7:07
  to patreon.com/stage Zero. And please take care of
• 7:12
  yourselves and each other, and I'll see you tomorrow.