442 summarised stories about Large Language Models, each linking back to the original source. Browse all topics →
MarkTechPost 10 hours ago 21
DeepSeek released DeepSeek-V4.1-Flash-1017, a new checkpoint of its V4.1-Flash model that is live via its website, app, and API. It scored 77.0 on DeepSWE v1.1. DeepSeek also opened its Search and Fetch APIs to all developers, enabling cheaper agent coding plus a first-party web layer under one API key.
Latent Space 11 hours ago 18 ● 27 sources
Muse released its Muse Spark Open and Reflection Beam models alongside multiple frontier and decision-model updates covered in this AINews roundup. Muse Spark Open is an 816B-total, 42B-active MoE with weights quantized so experts-only fit to about 530GB. As a result, open-weight licensing, pricing, and benchmark rankings shift across cost, agent performance, and inference hardware/serving notes.
MarkTechPost 11 hours ago 24 ● 4 sources
TypeSafe launched Jev, a decision-model that outputs labels/scores or yes/no probabilities without generating text, and within about 4 weeks at least 20 other Jev alternatives were shipped by companies and developers. Cloudflare’s Clef (27B) scored 94.20 on BANKING77 F1 versus Jev’s 79.74 in Cloudflare’s own run. Developers now have many more hosted and self-hostable decision-model options, with differences in licenses, hardware support, pricing, and some models claiming Jev SDK/API compatibility.
MarkTechPost 12 hours ago 49 ● 2 sources
StepFun released Step 5 Preview open-weight checkpoints, including FP8 and BF16, on Hugging Face and ModelScope. The model has 600B total parameters with 27B active per token and supports up to a 1M-token context. Developers can now self-host it for agentic coding and long-document/finance workflows, with specified data-center GPU requirements (4x B300 for FP8 or 8x B300 for BF16) instead of using only the API.
SiliconANGLE 18 hours ago 43 ● 3 sources
Microsoft’s AI research team detailed its MAI-Base-2 base model, which is built to be converted into full LLMs via additional training. The model has 2 trillion parameters and activates 80 billion per prompt, and it was trained for 38 days on 16,000 Nvidia GB200 chips with 50 trillion tokens. Microsoft says MAI-Base-2 is up to 12 times more hardware-efficient, will be licensed to “trusted partners” on Azure, and will be used to power a new line of LLMs.
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TLDRocket
17 October 2026
The big thread today is the messy middle between agent ambitions and the boring parts that make them safe and auditable. ServiceNow is positioning its AI Control Tower as the enterprise hub to discover, govern, and—crucially—control AI agents across models and clouds, while a field study of 15 large-enterprise customers (conducted September 15–21, 2026) presses on a key question: how strong is “technical runtime enforcement” and lifecycle evidence compared with other tools? ServiceNow’s answer is mostly commercial muscle—aiming for $1.5B in full-year AI ACV—but its guidance effectively says buyers should treat Control Tower as strongest for governance workflows and operational action, then verify where model validation evidence and real-time blocking are actually handled.
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