Discussions, reviews, and comparisons of specific AI models (like Gemini, Claude, etc.) and the platforms where they can be accessed or utilized.
Watch or Listen on YouTube Tongyi DeepResearch: A Guide To The AI Agent Automating Web Research Introduction You can spend weeks wiring a retrieval stack, then watch it wobble under load. Or you can get answers grounded in your own docs in a single afternoon. That is the promise of Gemini File Search, and it … Read more
Watch or Listen on YouTube Reinforcement Learning AI: Predictive Scaling Laws for LLMs Introduction If you’ve ever tried to scale an RL run and felt like you were flying by instrument in a storm, you’re not alone. For years, Reinforcement Learning AI has delivered flashes of brilliance, then slipped into instability right when the stakes … Read more
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
Kimi K2 Thinking: A Hands On Review Of The 1T Agentic AI Introduction The open-source race just grew a spine. Kimi K2 Thinking is not a parlor trick that copies syntax and calls it intelligence. It plans, checks its own work, and drives tools like a sober engineer. After several days of coding, research, 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
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
Mastering AI Agent Development: A Professional’s Guide to Context Engineering Introduction You built an agent that mostly works, and then it stopped. It forgets its goals, picks the wrong tool, and debugging turns into spelunking through logs. That’s not just bad luck. It’s context engineering, or the lack of it, showing up as brittle behavior. … Read more