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Google's new Gemini Embedding model now leads the MTEB benchmark. But it is facing fierce competition from closed and open source rivals.Read More

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A DeepMind study finds LLMs are both stubborn and easily swayed. This confidence paradox has key implications for building AI applications.Read More

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A new AI model learns to "think" longer on hard problems, achieving more robust reasoning and better generalization to novel, unseen tasks.Read More

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Katanemo Labs' new LLM routing framework aligns with human preferences and adapts to new models without retraining.Read More

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Sakana AI's new inference-time scaling technique uses Monte-Carlo Tree Search to orchestrate multiple LLMs to collaborate on complex tasks.Read More

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Mixus's "colleague-in-the-loop" model blends automation with human judgment for safe deployment of AI agents.Read More

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Forecasting is a fundamentally new capability that is missing from the current purview of generative AI. Here's how Kumo is changing that.Read More

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MIT researchers developed SEAL, a framework that lets language models continuously learn new knowledge and tasks.Read More

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Why is Google hiding Gemini's reasoning traces? The decision sparks a debate over black-box models versus the need for transparency.Read More

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A robot powered by V-JEPA 2 can be deployed in a new environment and successfully manipulate objects it has never encountered before.Read More

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Anthropic's open-source circuit tracing tool can help developers debug, optimize, and control AI for reliable and trustable applications.Read More

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By combining fine-tuning and in-context learning, you get LLMs that can learn tasks that would be too difficult or expensive for either methodRead More

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Mem0's architecture is designed to LLM memory and enhance consistency for more reliable agent performance in long conversations.Read More