Anthropic on Tuesday unveiled a suite of updates to its Claude Managed Agents platform at its second annual Code with Claude developer conference in San Francisco, introducing a new capability called “dreaming” that lets AI agents learn from their own past sessions and improve over time — a step toward the kind of self-correcting, self-improving …
Every LangChain pipeline your team hardcodes starts breaking the moment the query distribution shifts — and it always shifts. That bottleneck is what Sakana AI set out to eliminate. Researchers at Sakana AI have introduced the “RL Conductor,” a small language model trained via reinforcement learning to automatically orchestrate a diverse pool of worker LLMs. …
How Sakana trained a 7B model to orchestrate GPT-5, Claude Sonnet 4 and Gemini 2.5 Pro Read More »
Even as leading AI providers like OpenAI and Anthropic battle over the compute to train and release ever larger, more powerful models, other labs are going in a different direction — pursuing the development of smaller, more efficient models and often open sourcing them. The latest worth paying attention to comes from the lesser-known Palo …
Presented by Zeta Global The gap between what AI promises and what it delivers is not subtle. The same model can produce precise, useful output in one system and generic, irrelevant results in another. The issue is not the model. It’s the context. Most enterprise systems were not built for how AI operates. Data is …
Why AI breaks without context — and how to fix it Read More »
Picture this scenario: An Anthropic Skill scanner runs a full analysis of a Skill pulled from ClawHub or skills.sh. Its markdown instructions are clean, and no prompt injection is detected. No shell commands are hiding in the SKILL.md. Green across the board. The scanner never looked at the .test.ts file sitting one directory over. It …
Anthropic Skill scanners passed every check. The malicious code rode in on a test file. Read More »
In a world where a viral TikTok video can cause a brand to trend globally in mere hours, the traditional market research cycle — often spanning 12 weeks — is becoming a liability. The lag between a survey question and the answers from a wide (or targeted) pool of respondents has become a primary bottleneck …
There’s an app for nearly every imaginable user and use case these days, but one thing they all have in common is that they’re centered around one device: the smartphone. That changes today as Hugging Face, the 10-year-old New York City startup best known for being the go-to place online to host and use cutting-edge, …
As AI model providers increasingly move downstream, launching products and agents for specific enterprise applications and sectors like finance, one big question still remains: how will said AI agents be equipped with the proper context surrounding a task — who assigned it, which other stakeholders are involved, what data or discussions have taken place about …
Presented by Nutanix Across industries, organizations are focused on how to move from AI pilots, proofs of concept, and cloud-based experimentation to deploying it at scale — across real workloads, for real users, in real business environments. VentureBeat spoke with Tarkan Maner, president and chief commercial officer at Nutanix, and Thomas Cornely, EVP of product …
Scaling AI into production is forcing a rethink of enterprise infrastructure Read More »
A little-known Miami-based startup called Subquadratic emerged from stealth on Tuesday with a sweeping claim: that it has built the first large language model to fully escape the mathematical constraint that has defined — and limited — every major AI system since 2017. The company claims its first model, SubQ 1M-Preview, is the first LLM …