444 summarised stories about Large Language Models, each linking back to the original source. Browse all topics →
TechCrunch 1 month ago 50 ● 4 sources
PrismML released Bonsai 2 27B, a compressed reasoning large language model designed to run on PCs and smartphones. The model compresses Qwen3.8 27B down to 5.9 GB, matching 98% of Qwen’s aggregate benchmark scores. As a result, LLMs can be deployed with much lower memory use while aiming to preserve performance, with the company planning next releases targeting several-hundred-billion parameters.
Ptidej Team Blog 1 month ago 43
The article argues that understanding why language models work requires studying the training process rather than only analyzing a finished model. The key example is that image-classifier category-specific neurons were targeted during training and the model got better. It changes the focus for interpretability and debugging by treating training traces like version history and using randomness across runs as evidence rather than noise.
Rohan Bansal 1 month ago 31
A researcher trained a 4B open-weights language model to generate PostgreSQL query plans and evaluate them against PostgreSQL’s own default planning choices. The model achieved 81% faster query plans than Postgres. As a result, supervised fine-tuning plus agentic reinforcement learning can steer Postgres toward lower-latency plans without changing Postgres’s cost model.
Trending Topics 1 month ago 39
Z.ai says its GLM-5.3-Flash model helped create the inference infrastructure it and its related system run on. Z.ai built that production inference service on a cluster of more than 100,000 Chinese-made AI accelerators and claims the model reached production readiness in less than two weeks. The company reports faster throughput (about 3x), improved hardware efficiency and per-token cost, and partial automation of engineering via an “Infra Agent,” while still saying true recursive self-improvement has not been reached.
Scientific American 1 month ago 32
Levent Alpöge and Ava Howell used Anthropic’s Claude to produce elliptic curves with rational points of rank at least 31. The work reported rank at least 31 solutions within just a few days. As a result, AI-generated examples added two higher-rank elliptic curves to a field where progress had been slow for years.
Futura-Sciences 1 month ago 26
Talkie, a large language model trained only on pre-1930 public-domain English text, was built to see how an AI with a frozen 1930 mindset responds to modern events.
The Batch 45 ● 2 sources
OpenAI launched GPT-6 Astra, a vision-language model positioned for top leaderboard performance and offered with cyber-defense safeguards limited to selected organizations. OpenAI says it trained Astra on more than 100,000 GPUs, its largest run yet. Pricing, access tiers, and tool-safety behavior in ChatGPT and the API changed around the new model, including token-based rates and stricter handling of flagged tool actions.
Last Week in AI 1 month ago 16 ● 3 sources
OpenAI published an internal-model proof claiming it resolved the Navier–Stokes Millennium Prize problem, triggering a mix of credit disputes and further scrutiny. It said the effort used 300 billion output tokens and culminated with an OpenAI publication on September 8. As a result, the Clay Mathematics Institute still lists the problem as unsolved pending review, and Anthropic’s CEO and US/EU lawmakers escalated calls to slow advanced AI development and strengthen regulation while concerns about misuse grew.
Allen Institute (AI2) 1 month ago 21
Soham Padia used Olmo 3 to build Steering Arena, a crowdsourced “game” that submitted text prompts to test whether text steering reliably produces prosocial behavior in the model.
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18 October 2026
DeepSeek kept one foot on the gas. Its updated DeepSeek-V4.1-Flash-1017 went live across web, mobile, and the existing deepseek-flash API model ID, with the same pricing while it improves performance: DeepSWE v1.1 resolution rises to 77% of tasks from 74.2%, and DeepSeek says it finishes work faster. It also bundled something more practical than another benchmark brag—an accompanying developer search API backed by its own engine, with Terminal-Bench 4.0 moving from 31.2 to 42.3 and billing that stays at $0.30 per million input tokens and $1.20 per million output tokens. The subtext for builders is familiar: as agent workflows spread, retrieval cost and reliability matter as much as raw model IQ.
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