Azmat
AI Mathematics: AlphaEvolve’s 67-Problem Stress Test Introduction If you care about AI mathematics, this is the moment when the conversation got serious. AlphaEvolve, an evolutionary coding agent, was set loose on sixty-seven real mathematical challenges across analysis, combinatorics, geometry, and number theory. It did not just rediscover known constructions. It found new ones, tightened bounds, … Read more
Nested Learning: Inside Google’s New Paradigm For Self Improving AI Introduction Nested Learning is a machine-learning paradigm from Google Research designed to improve continual learning: the ability of an AI model to acquire new knowledge and skills over time without catastrophically forgetting what it already learned. Instead of treating a model as one monolithic network … Read more
Kimi K2 Thinking: A Hands On Review Of The 1T Agentic AI Introduction Kimi K2 Thinking is Moonshot AI’s 1-trillion-parameter open-weight reasoning model, with 32 billion parameters activated per token and a 256K context window. In Moonshot’s published evaluations, it scored 44.9% on Humanity’s Last Exam with tools, 60.2% on BrowseComp and 71.3% on SWE-bench … Read more
AI News November 8 2025: The Weekly Pulse And Pattern Introduction This week’s cycle felt like watching a chess board wake up. Companies moved compute like queens, research labs opened new lanes in reasoning, and policymakers stared down safety gaps that are no longer theoretical. If you care about how intelligence gets built, deployed, and … Read more
AI News — Tongyi DeepResearch Update Introduction If you’ve ever tried to stitch together ten tabs, three PDFs, one spreadsheet, and a half-finished notebook into a clear answer, you know the bottleneck. It’s not the lack of information. It’s the plumbing. Tongyi DeepResearch turns that plumbing into a system, an AI research agent that reads, … Read more
AI Scientist: Inside Kosmos, the Autonomous AI that Does 6 Months of Research in a Day Introduction You do not hire a robot to stack beakers. You hire a mind that reads the literature, writes code, argues with itself, changes course, and ships a result. That is the promise of the modern AI scientist. Edison … Read more
Autoregressive Models CALM Next Vector Inference Introduction Every time you chat with an LLM, you’re watching autoregressive models at work. They’re powerful, yet they stall on a simple fact: they write one token at a time. That single habit slows everything down. If we want faster models without throwing endless compute at the problem, we … Read more