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Z.ai just released GLM-5.3. GLM-5.3 runs on the same 743B base model as GLM-5.2. Every reported gain comes from scaled post-training: more task environments, more environment types, longer training. The results land in two places. Coding jumps most on the longest-horizon benchmarks, with Terminal-Bench 3.0 moving from 4.6 to 28.3. Cybersecurity moved further than Z.ai […]
Cactus Compute has released Needle 2, an open 45M-parameter model for tool calling, device use, and structured extraction. The entire model ships as a single 14MB binary that runs a full session in about 28MB of RAM. Weights are trained and deployed at CQ2-bit using Cactus Quants, and the model is sealed inside the company’s
Google has released Gemini 3.7 Flash, the newest model in its Flash tier, three weeks after Gemini 3.6 Flash. The model card describes it as a refinement of 3.6 Flash with algorithmic improvements to the core reasoning foundation — not a new pretraining run. It accepts text, images, audio, and video across a 1M-token context
Okta says identity-scoped Model Context Protocol (MCP) tool lists can reduce AI agent token costs. Each model call made by an AI agent can include schemas, names, descriptions and parameters for every tool exposed by a MCP server. Okta calls the resulting prompt overhead the “tool tax”: tokens consumed as a model considers tools, including
Okta targets AI agent token costs with MCP scoping Read More »
Dyna Robotics has released Dyna-2, a world-action model for robot manipulation. It was pre-trained on more than one million hours of egocentric human video. That is roughly 170 years of continuous waking experience. Robot learning has been bottlenecked by action-labelled data, which teleoperation must deliberately produce. Dyna-2 tests whether ordinary human video can substitute. The
SpaceXAI just released Grok 4.6. The release is a post-training upgrade over Grok 4.5 rather than a larger base model. SpaceXAI held the foundation constant and spent the improvement on a longer supplemental training run, regenerated supervised fine-tuning trajectories, and reinforcement learning in agentic environments. Agents that stay on a task across many steps without
How we built a Digital Twin of an Organization, powered by Claude, from prototype to production. The Challenge Our Client Came to Us With Organizations invest millions in transformation initiatives like new systems, restructured teams, AI adoption, without a complete picture of how they actually operate today. Process knowledge lives in documents that go stale,
Why it matters: See how a semantic knowledge graph for LLM agents slashes hallucinations, adds memory, and lifted answer accuracy from 17 to 54 percent in tests.
NVIDIA introduced open technologies for building always-on AI agents from systems of specialized models. Two artifacts shipped together. Nemotron 3.5 Lightning is a lightweight, customizable open model built for high-volume agentic tasks, and NeMo Switchyard is an open source routing library that directs each step of an agent workflow to the most capable and efficient
Why it matters: Domain-specific vs general AI agents: real accuracy, cost, and ROI data plus named enterprise deployments to help you pick the right agent.
