HAI associate director @AmyZegart is a recognized expert on AI, U.S. intelligence, and national security. Her book “Spies, Lies, and Algorithms” explores how technological advancements have transformed the landscape of American intelligence-gathering. 6/n https://
hai.stanford.edu/news/amy-zegar
t-integrating-ai-realm-national-security
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RESEARCH
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AI Expert Amy Zegart on Intelligence and National Security
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Stanford Professor Studies Robot Learning and Intelligent Behavior Development
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Assistant prof. @chelseabfinn studies the capability of robots and other agents to develop broadly intelligent behavior through learning and interaction. She runs the IRIS lab @Stanford whose work was featured in the @nytimes
: https://
nytimes.com/2021/07/20/tec
hnology/ai-education-neural-networks.html
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Vision-Language-Action Learning in Robotics: Progress Discussion
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TY David for a very fun discussion about the state of the art in robotics, including new developments in robot vision-language-action learning, and why progress is not exponential!
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Breakthrough AI Technology Impresses Industry in 2026
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In the world of AI, it’s getting harder and harder to impress people. Tech that was mind blowing a year ago is already taken for granted.
— Matt Wolfe (@mreflow) 13 mars 2024
THIS 👇 is something truly impressive! https://t.co/5ZJlqLb9WgIn the world of AI, it’s getting harder and harder to impress people. Tech that was mind blowing a year ago is already taken for granted. THIS is something truly impressive!
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Knowledge Graphs for RAG: Advanced Data Retrieval Course
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Our new short course, Knowledge Graphs for RAG, is now available! Knowledge graphs are a data structure that is great at capturing complex relationships between data of multiple types. By enabling more sophisticated retrieval of text than similarity search alone, knowledge graphs… pic.twitter.com/vdJDrldsLE
— Andrew Ng (@AndrewYNg) 13 mars 2024Our new short course, Knowledge Graphs for RAG, is now available! Knowledge graphs are a data structure that is great at capturing complex relationships between data of multiple types. By enabling more sophisticated retrieval of text than similarity search alone, knowledge graphs
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AI Companies Neglect Language and Reasoning Benchmarks for Software Optimization
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There are so few benchmarks the AI companies compete on outside of software and general knowledge benchmarks. They also fine tune obsessively to optimize software. Language, turn-taking, logical reasoning, lack of hallucinations, and other critical issues get less clear focus.
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AI Development Bias: Software Engineers Overlook Marketing, Education, Law
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The Law of the Hammer is an issue in AI. The people who build AI are software engineers, and they obsess over the degree to which LLMs can (or cannot) automate software. Meanwhile, entire swathes of larger industries exposed to AI (marketing, education, law) get much less focus.
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Rise of LLMs: Vector Embeddings and Vector Databases in AI
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The rise of #LLMs has made vector embeddings and #VectorDB immensely popular and useful, particularly in #AI, #GenerativeAI, and #LLMOps applications. @bindureddy from @abacusai explains in this “RAG – Vector Retrieval – Comprehensive Study”…
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Humanoid Robot Demo Shows Impressive Visual Language Reasoning
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Things stood out to me in order: > The voice kind of sounded like @adcock_brett at first
> This demo really shows how "humanoid" the robot is from the smoothness and slight stutters
> The visual + language reasoning is faster than I expected but still too slow for a full -
Consciousness-Inspired Abstractions Improve RL Generalization
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Consciousness-Inspired Spatio-Temporal Abstractions for Better Generalization in Reinforcement Learning Zhao et al.: https://
arxiv.org/abs/2310.00229 #ArtificialIntelligence #DeepLearning #MachineLearning