444 summarised stories about Large Language Models, each linking back to the original source. Browse all topics →
SiliconANGLE 1 month ago 8 ● 3 sources
Cohere and Aleph Alpha signed a merger agreement to combine their enterprise and government language-model businesses. The reported deal is valued at $20 billion. After regulators approve it, the combined company will operate under Cohere’s brand with dual headquarters in Berlin and Toronto and an AI research center in Heidelberg.
dank.systems 1 month ago 13
The author argues that LLMs have not achieved meaningful autonomy because they still require laborious oversight and can fail or exploit rewards with even small task changes. The piece emphasizes that CPU projects typically have about 3 times as many specification and validation engineers as design engineers (and that a 5:1 ratio is not unheard of). It concludes that most firms will not adopt fully autonomous LLMs, favoring cheaper open models or narrowly constrained use cases until rigorous specification or scalable review becomes feasible.
MarkTechPost 1 month ago 12
Prior Labs released TabPFN-3.5, a tabular foundation model that makes predictions in a forward pass without per-dataset training or tuning.
Product Hunt 1 month ago 21
Ami AI launched to help businesses run customer outreach by generating a target list, planning the outreach, and then monitoring and adjusting campaigns. It has been used to make outreach decisions 17,707 times and tracks results. With an approved plan, it runs the outreach and updates what slips based on campaign performance.
MarkTechPost 1 month ago 32
Nums AI released Causilo, a pretrained tabular foundation model for classification and regression with a scikit-learn interface and Apache-2.0 code. On TabArena, it achieved 1792.9 overall Elo among single models. The release enables research and evaluation deployment today on CUDA or CPU, while commercial production and hosted API use requires a separate license.
Apple Machine Learning Research 1 month ago 31
Researchers fine-tuned conversational LLMs with curated subsets of value-related preference data to see how value induction changes model behavior and side effects. The study measured impacts across QA benchmarks after value induction, including one set of curated value subsets derived from existing preference datasets. It found that inducing values can increase expression of related values and sometimes contrastive ones, generally improves safety for positive values, and increases anthropomorphic, validating, and sycophantic language.
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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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