#EdgeAI is Key to Driving Innovative, Low-Power #AI Use Cases: https://
iotworldtoday.com/connectivity/w
hy-edge-ai-is-key-to-driving-innovative-low-power-use-cases
… In the era of AI everywhere, edge intelligence is not just a technical upgrade—it’s a strategic imperative: Intelligence at the Point of Data Collection! #IoT #IIoT #Edge #EdgeComputing #ML
MACHINE LEARNING
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Edge AI: Strategic Imperative for Innovative Low-Power Intelligence
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Digital Agents and Real-World Robots: Advancing AI Competence
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In the near term, I hope my research can help make digital agents more competent and helpful (e.g. make an automated travel planning or personal AI assistant possible). In the longer term, I hope my work plays some part in enabling real-world robots that can cook, clean, and do
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Gemini-Embedding-001 Tops MTEB Leaderboard with Cost-Effective Batch Mode
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🚀 Gemini-Embedding-001 is live
— Louis-François Bouchard 🎥🤖 (@Whats_AI) 15 juillet 2025
• Tops the MTEB leaderboard, ahead of OpenAI & Cohere
• Batch mode = 2× cheaper for large-scale RAG
• Pre-compute & cache embeddings for faster retrieval
• Text + code only (no image/audio… yet)
Pure value or oversold? Drop your verdict 👇… pic.twitter.com/RVhwuUhG00Gemini-Embedding-001 is live • Tops the MTEB leaderboard, ahead of OpenAI & Cohere
• Batch mode = 2× cheaper for large-scale RAG
• Pre-compute & cache embeddings for faster retrieval
• Text + code only (no image/audio… yet) Pure value or oversold? Drop your verdict -
AI vs ML vs DL vs GenAI vs LLM vs AI Agent Infographic
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Pretty Infographic — AI vs ML vs DL vs GenAI vs LLM vs AI Agent
— Kirk Borne (@KirkDBorne) 15 juillet 2025
Let me know if you think this is useful, or just eye candy.
Source: https://t.co/6pkGjZzyq2 pic.twitter.com/iB9H1gB8aFPretty Infographic — AI vs ML vs DL vs GenAI vs LLM vs AI Agent Let me know if you think this is useful, or just eye candy. Source: https://
linkedin.com/posts/prem-nat
arajan-ai_ai-vs-ml-vs-dl-vs-genai-vs-llm-vs-ai-agent-activity-7350864396476112896-YLlJ
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Explore Real-World AI Applications in Action
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Explore real-world AI in action: https://
nvda.ws/40HWdgb -
Deploying AI on Physical Robots and Simulations
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I've mostly deployed my work on physical, real-world robots (e.g. the Spot from @BostonDynamics
, or the Franka Emika Panda arm). A lot of my work has also included experiments in simulated household environments (e.g. https://
behavior.stanford.edu). More recently, I've been working on -
Matryoshka Quantization poster presentation at ICML2025
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Check out our #ICML2025 poster on Matryoshka Quantization tomorrow, being presented by @puranjay1412 on behalf of all the authors.
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JEPA Architecture: Exciting Research Direction at CSAIL
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I personally don't work on JEPA-related architectures, but it's certainly an exciting direction that I'm sure others in CSAIL/EECS are working on!
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Formalizing Hofstadter’s Strange Loop Beyond Recursion
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I agree: Hofstadter’s concept of the strange loop is not a specification that can be directly implemented, and recursion can be vexing but is not necessarily strange. Hofstadter is pointing at something interesting that is yet to be formalized.
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Using LLMs to Simulate Reinforcement Learning Environments
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Has anyone used LLMs to simulate RL environments? Seems like a huge opportunity.