435 stories
A practical guide to what changed, the benchmarks that matter, the cost controls developers should not miss, and one hands-on demo worth building. Anthropic has just released Claude Sonnet 5.5. It is the middle child of the Claude family, and the one most people will actually use.
AI agent guardrails are relatively straightforward to evaluate when an agent only generates text. The decision gets more complicated as soon as the agent can...
Journalist Garrison Lovely discusses his reporting from inside the AI industry, exploring the beliefs driving AGI development and making the case for halting the race to replace human labor.
AI agents are already talking to each other at scale. The standards bodies are mobilizing. Where is the layer that matters most: the conditions and boundaries envelope?
Learn how AI agents turn goals into executable tasks, choose planning strategies, validate results, and replan safely when reality changes.
Checking in on Opus 5.5 ~1 week after launch. It's the #1 model in share of spend and share of tokens among Anthropic models on OpenRouter Switching from Opus 5 has been particularly rapid
The best AI employee platforms for small business in 2026, ranked on price, capabilities, and limits: Construct, CellCog, Manus, Lindy, Sintra, and more.
Since launching a year ago, the Microsoft Research Asia — Singapore lab has established a strong foundation, deepened collaboration across government, academia, and industry, and explored how frontier AI research can create real-world value.
For the first time, an OCR model reads Indian languages as fluently as English documents. Sarvam Vision 2.1 breaks a long-standing trade-off. Indian businesses had to choose between structural document parsing and script recognition. Never both. Finance teams automating invoices faced this.
AI phone agent pricing hides three cost layers enterprise buyers never see. Avoid budget surprises with our full 2026 vendor breakdown.
AGENTS.md best practices for multi-agent setups: root, scope, and role layers, subagent context rules, handoff contracts, and what to delete before adding.
A deterministic, MCP-first coordination protocol for multi-agent coding — unusually honest about its own limits, and exactly the plumbing a fleet-of-agents future needs.
Nathan Labenz and Prakash Narayanan review key AI developments with five experts, discussing multi-agent coordination risks, AI safety funding bottlenecks, GPU compute markets, sensor foundation models, and robotic drug testing.
Agentic Context Learning or ACE is a learning paradigm that lets an AI agent improve across tasks by editing the context it reads, while leaving model weights unchanged.
RAG retrieves. Agents act. I built both separately, connected them explicitly, and ran the same nine tasks through all three systems. The post RAG Isn't an Agent — I Built the Layer Between Retrieval and Action appeared first on Towards Data Science.
A quiet day lets us discuss the work behind the scenes - now open for business!
Copilot Studio, Agentforce, Gemini Enterprise, n8n, Zapier Agents, Relevance AI, Lindy, Gumloop, CrewAI and Caddi, compared on who builds, runtime, pricing and fit for regulated back-office work.
Recent advancements in video diffusion demonstrate remarkable high-fidelity generation with models that can render realistic scenes in seconds. However, while diffusion models generate high-fidelity video clips, transforming them into coherent long storytelling engines remains challenging.
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