Hien Luu

The Stanford Human-Centered AI Report is out. This is the 7th year that Stanford has published this report and it is a must-read if you're trying to keep track of the developments in this field. https://lnkd.in/gwsHtzsq

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Sharing my latest article on Overconfidence in State of the Art LLMs. Explore the challenges and limitations these models face in critical applications. #AI #MachineLearning #LLMs #ArtificialIntelligence #TechInsights #Innovation #EnterpriseSolutions #AIResearch

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Alphabet committed another $5 billion recently to Waymo's self-driving cars. A renewed vow of confidence. Per my post yesterday, fast growing additional compute and better AI architectures are changing self driving cars rapidly. Notably, some traditional car manufacturers pulled out investments in full self-driving cars. It didn't think the tech was going to be ready for decades to come, if ever. I think it may be a mistake given AI and compute grow exponentially, not linearly. As an example, it may take 20-40 years to achieve 1% of progress, then just 5-10 years for the remaining 99% (instead of 1,000s of years per our intuition) link in comments #AI #Transformers #waymo

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From where I sit in the SF Bay Area, cradle of innovation for at least the last 30 years, I'm a true believer in the promise of the #AI revolution. That said, I find it fascinating to consider views on the opposing side. I'm sharing below two opinion pieces from the last two weeks suggesting that the AI revolution is fundamentally overhyped and a bubble ripe for bursting, and that AI tools are actually not useful or transformative. Contrast this with venture capitalist Kai-Fu Lee's prognostication that 50% of white collar jobs will be displaced by #AI within three years, and that OpenAI and the other cutting edge movers in the space are headed to a trillion+ dollar valuation. Which side will win out? Where will we be by 2030 in the AI race? I'd love to hear your thoughts in the comments.

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What creative possibilities arise from generative AI vs predictive AI? "Generative AI generates original content, while predictive AI analyzes historical data to predict future outcomes." Discover how generative AI sparks creativity and predictive AI forecasts future trends in innovative ways.

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Ethical AI applies to inference as well as upstream data sources. Amazon is emphasizing structure and responsibility over unchecked innovation spanning from foundational models to consumer applications. It is good to see this mentality being adopted. https://buff.ly/445KcS0 #ArtificialIntelligence #AmazonAI #TechResponsibility

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And just like that, Waymo announced they have an end-to-end model for autonomous driving. Former CEO John Krafcik states: 1. there is long-term promise for an e2e approach (e.g., interpretable decision rationale is possible), but 2. big challenges remain (insufficient long-term memory to solve complex long-tail challenges, sensor fusion), so 3. it's going to be super hard for e2e-only companies (Wayve, Waabi, Tesla) to catch Waymo, which has the only safely working AI approach in the space & a huge on-going advantage: Alphabet AI adjacency/talent

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