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MLPerf Training v6.1 adds an agentic reinforcement-learning workload that measures how quickly systems can teach a 397-billion-parameter language model to repair real software projects. The post MLPerf Training Introduces Its First LLM Post-Training Benchmark appeared first on MLCommons.
Some of the most interesting work being built with PyTorch starts in universities, research labs, student groups, and academic institutions. A new model architecture. A library created to support a...
OpenAI introduced GPT-6 Sol and Luna as faster, more affordable counterparts to GPT-6 Astra, bringing advances in coding, factuality, computer use, and professional tasks to lower-cost models.
Jev's first week brought a trusted monitor, computer-use agents, self-hosted clones, a benchmark and a joke chatbot: the slot each fills and which numbers hold.
The open-source alternatives to Jev are Laya, Kev, SemIf, Open-Jev and Nimble. They are four kinds of project, and here is what each one replaces.
TL;DR To achieve state-of-the-art performance at the frontier, vLLM is changing its internal implementation in ways that make it incompatible with fullgraph torch.compile. This may have consequences for users who...
TL;DR: This case study explores how Shopify compresses production failures into model weights every day, beats frontier-model quality, and cuts serving costs 96% by building a continual learning loop with...
This is a first for the “Apple of China” phone maker-turned-frontier lab: “The MiMo-V2.6 series includes two natively omnimodal models: MiMo-V2.6-Pro is our most capable model to date, while MiMo-V2.6-Flash strikes the best balance between intelligence, efficiency, and cost.
The early rapid expansion of AI capabilities that focused on frontier models was largely ushered into the world by a few powerful, US-based AI labs. Open-weight models released from labs in China, early on from DeepSeek, and later from Moonshot, Z.ai, and others, have in part disrupted that…
A large AI model can run on modest hardware only by reducing the memory it occupies, reducing the calculations it performs, or moving some work to slower hardware.
In this article, you will learn how LLM inference optimization works and which techniques to apply to make language models faster, cheaper, and more reliable...
Somewhere in your company's ServiceNow instance is the answer to the question an engineer asks at two in the morning: if this is broken, what else is about to break? Every fact needed to answer it has
You’re deploying a model on a system. It starts up, prompts are getting responses. Now the hard question: Is this fast? Your instincts might lead you to send...
PyTorch Day Japan 2026 will bring the open source AI community together in Tokyo on December 10 for a full day of technical talks and interactive discussions designed to foster...
AI News for 9/16/2026-9/17/2026. We checked 12 subreddits, 544 Twitters and no further Discords. AINews’ website lets you search all past issues. As a reminder, AINews is now a section of Latent Space. You can opt in/out of email frequencies!
When comparing Chinese AI vs ChatGPT, your decision comes down to cost versus security. If you need low API pricing, open weights, and fast coding assistance, Chinese AI models like DeepSeek lead the way. However, if your team...
Steve Yegge has been very popular and loud in his gung ho adoption of tokenmaxxing, so it is sobering to see him now shut down Gas Town and admit that despite spending many thousands a month on coding agent subscriptions… he only ever built Gas Town with it:
In this analysis, MLPerf Inference Working Group chairs Miro Hodak and Frank Han break down a record field of 30 submitters and 120 systems, the arrival of agentic and end-to-end benchmarks, and what the results signal about where inference engineering is headed.
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