The latest breakthroughs in foundational models, reasoning capabilities, and prompt engineering from OpenAI, Anthropic, Google, and open-source challengers.
OpenAI just cracked open gpt-oss-120b and 20b, echoing GPT-2's 2019 shock. But smarter architectures and GPU tricks make them runnable at home—here's the deep architecture breakdown.
AI voices always had that robotic tell — the pause, the flat tone. Google's Gemini 3.1 Flash Live just erased it, rolling out today and arming devs to build undetectable chatbots.
Your LLM's gobbling RAM like it's free candy. Google's TurboQuant says hold my beer—6x compression, faster speeds, zero quality loss. Or so they claim.
Spending more compute at inference — not training — unlocks LLM reasoning gains that rival model upgrades. Here's the categorized playbook from recent papers.
Attention mechanisms in LLMs aren't static relics—they're battlegrounds for speed and scale. Sebastian Raschka's new gallery reveals the winners.
Next time your AI assistant spits out a response in seconds, thank the KV cache. It's quietly revolutionizing how we run massive language models without breaking the bank on compute.
Forget the scale obsession. 2025's LLM research zeroed in on reasoning and smarts. This curated July-Dec list shows exactly where the field's heading.
Sebastian dangles Chapter 1 like catnip for AI nerds. But does 'reasoning from scratch' crack the code — or just repackage old tricks?
Picture this: an AI not just spitting code, but navigating your repo, fixing bugs on the fly, remembering your last tweak. Coding agents aren't hype—they're the jetpack for LLMs.
Your next ChatGPT might 'think' like a human — or at least pretend to. But in the state of LLMs 2025, cheaper training via DeepSeek R1 promises open-source wins, while big labs chase the same old dollars.
Your next AI side hustle just got cheaper to prototype—if you've got the GPUs. Spring 2026 dumped 10 open-weight LLMs on us, but beneath the parameter counts, it's the same old convergence.
Claude Code just hit 4% of all public GitHub commits. That's the opening shot in what could become the SaaSpocalypse for software engineers.