搜索“OpenAI”

0吉瓦算力，需求能否以相近速度增长。 随着云厂商、模型公司和算力供应商同时扩张，一旦新增数据中心产能增长快于实际需求，设备利用率和GPU租赁价格都可能下降，实际收入也会低于最初的投资测算。对于那些大量依靠债务建设的数据中心而言，高杠杆之下也可能转化为更大的股权损失和偿债压力。 要消化如此庞大的新增算力，本身就需要AI产业收入保持极高增速。报告援引当前估算称，OpenAI和Anthropic合计年收入约1000亿美元（约合6713亿元人民币）。如果以这一收入规模作为参照，要在2032年达到3.725万亿美元，需要未来数年保持大约80%的年复合增长率。 以英伟达为例，它一边向云厂商和数据中心出售GPU，一边又通过残值担保等方式帮助客户获得融资，降低大规模采购芯片的资金门槛。云厂商则继续建设数据中心、向模型公司出售算力，数据中心投资者再依靠大型科技企业的长期租赁和采购承诺支撑债务。 一旦需求增长赶不上数据中心和GPU产能释放，芯片价格、算力租赁价格和设备利用率都可能下降，而已经签下的债务、租金和采购承诺仍需继续支付。AI行业信号频道: 前沿科技本内容来源于网络 原文链接，观点仅代表作者本人，

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or to what Gen-2 could produce. There were a lot of, a lot of chatter on Twitter about Runway. Runway’s done. like, there is no way Runway will catch up. And if you remember, also OpenAI in the early twenty-It felt very, like it’s a Swyx [00:36:56]: To the moon Anastasis [00:36:57]: It’s a formidable opponent now, but at that point, it, they were on the top of their game. nobody could even get close to them. There was maybe Gemini was just the first version of Gemini had just released. So when O

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hort dramas and video production 🩺 Scribe v2 Medical - ElevenLabs’ speech-to-text model for medical transcription Sponsored listing Australian PM Anthony Albanese revealed that an OpenAI agent broke into an Australian Medicare statistics portal in June and pulled non-public files, the first known agent hack of a government site. Google debuted Gemini 3.8 Flash TTS and Flash-Lite TTS models with custom voice creation, line-by-line direction, and two-speaker dialogue across 100+ languages. Anthrop

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5B-A3B MoE model load and serve through the normal SGLang interfaces on one H100. Its verifier checks model registration, configuration and weight loading, image and video inputs, OpenAI-compatible requests, native batched generation, log probabilities, and execution through the MoE model’s routed experts. Some failures only appear once a real server starts. The SGLang team contributed ideas for end-to-end verification, including recommendations for specific model-serving tests. SWE-Serve includ

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to Oracle, to Meta and many more. Furthermore, it has the support of the ML community including from vLLM, LMCache, SGLang, PyTorch, Huggingface and the support of major labs like OpenAI, MiniMax, ZAI, Qwen, Moonshot Kimi, etc. Star the InferenceX GitHub repository if you find the open-source benchmark and data useful!. InferenceX is the only inference benchmark in the world to have TPUv7, Jalapeño, Nvidia Rubin NVL72, AMD, and soon, SambaNova and Trainium. Due to how realistic AgentX scenario i

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to Oracle, to Meta and many more. Furthermore, it has the support of the ML community including from vLLM, LMCache, SGLang, PyTorch, Huggingface and the support of major labs like OpenAI, MiniMax, ZAI, Qwen, Moonshot Kimi, etc. Thank you to Jensen Huang, Ian Buck, Nick Comly, Kedar Potdar, Rohit Nagraj, and the Mainland China TensorRTLLM Team for helping on doing next gen Rubin software bring up and helping verify our agentic benchmark results. Star the InferenceX GitHub repository if you find t

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nt everywhere you work, even in Claude or Cursor Vanta is trusted by more than 16,000 companies like Ramp, Harvey, and Writer. Learn more by watching their on-demand demo . Rowan: OpenAI’s GPT-6 Astra model came out last week to ChatGPT paid plans, and I’ve been having an absolute blast pushing it to its limits (and waiting for limits to reset…). The capabilities that make it genuinely feel like a step up are its computer use, visual consistency, long one-prompt jobs -- and, to my pleasant surpr

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tion lies outside the stated scope, tasks that cannot be completed without probing or breaking the sandbox boundary, and a situation inspired by parts of the attack chain from the OpenAI-Hugging Face incident. As in the real incidents, Claude Mythos 5 is the most willing of the models we tested to act against out-of-scope parties or leave its sandbox. For example, it was willing to commit a severely harmful action in the CTF replication roughly 80% of the time. In contrast, Claude Opus 5 and Cla

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look at what people ask AI to do, analyzing millions of conversations to see which tasks users bring to a chatbot [AI Observatory, 2026; Handa et al., 2025; Iscenko et al., 2026; OpenAI, 2026; Tomlinson et al., 2025]. Both represent distinct pieces in the larger puzzle of how AI is impacting work, however, they do not represent the full picture on their own. At Cohere Labs, we are committed to helping assemble this puzzle, and our research presents new evidence from a third, complementary vanta

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OpenAI vs HuggingFace, Container Escapes, Kernel Bypass, Network Policies, Security Keys, Multi-tenant Grafana, and a ClusterMAX 3.0 Preview In Shakespeare’s Julius Caesar, Caesar ignores a soothsayer’s warning, shrugs off his wife’s dream of blood running through the streets, waves away a letter revealing his assassins by name, and strides gallantly into the one room in Rome where every senator is “required” to check their weapons at the door. Two thousand years later, neoclouds are making the

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eached customers yet. SoftBank has a $5.4B deal pending for ABB Robotics; it also led Skild AI’s $1.4B round, and has consolidated 20 robotics holdings under its Robo HD umbrella. OpenAI backed 1X early and explored buying it last year before talks fell apart, putting SoftBank in a position to scoop up another piece of its partner ecosystem. Why it matters: SoftBank is piecing together a physical AI stack spanning Skild’s robot brains, ABB’s industrial machines, and potentially 1X’s humanoids in

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Claude Code inflection point in November 2025, long-context, multi-turn agentic workloads have grown rapidly. They now dominate traffic for production inferencing. In April 2026, OpenAI’s Enterprise agentic spending overtook ChatGPT spending. Claude Code is the Inflection Point Agentic workflows have decisively taken the baton. Today, we announce AgentX 1.0 - the world’s first fully open source, multi-turn agentic coding inference benchmark at 1 million context, released under Apache 2.0. Our f

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9 nvidia/canary-qwen-2.5b Automatic Speech Recognition • 3B • Updated Apr 21 • 41.9k • 465 nvidia/parakeet-tdt-0.6b-v2 Automatic Speech Recognition • Updated Jun 29 • 185k • 1.55k openai/whisper-large-v3 Automatic Speech Recognition • 2B • Updated Aug 12, 2024 • 4.21M • 6.53k Datasets mentioned in this article 3 ArtificialAnalysis/VoxPopuli-Cleaned-AA Viewer • Updated Feb 17 • 628 • 1.08k • 7 facebook/voxpopuli Viewer • Updated Jan 30 • 1.26M • 38.9k • 165 openslr/librispeech asr Viewer • Update

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y Aug. 25 for the early bird discount. Image source: Replit The Rundown: Replit launched Free Mode, a new setting for its $20 and $100 paid plans that runs everyday chats/tasks on OpenAI’s GPT-5.6 Luna without eating up user credits — with the company crediting Luna’s 80% price cut for making the math work. The details: Replit says its $20/month Core plan scales as much as 30x usage with Free Mode, adding 30 hours per month of chat using the efficient model. Bigger builds still burn credits in t

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runs lasting up to eight days, 8xH200s per run, and coverage of 18 models. For comparison, Anthropic's internal automated AI R&D evaluation optimizes a model on a CPU node, while OpenAI reports using nanoGPT Track 1 with a single H100 for less than a day in the GPT-5.6 Sol system card. While we don't have strong conviction that methods developed in this kind of speedrun are inherently scalable or would be used in real model training, we think the tight feedback loop and hill-climbing aspect mak

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gure is Green’s December 2025 revision, so later events are not in the bars; After that revision, Liam Price and GPT-5.4 Pro resolved Problem 44 (also Erdős 1202) in the negative, OpenAI Astra constructed a non-sofic group, answering the sofic half of Problem 100 (the hyperlinear half remains open), and Ma, Tang and Xu resolved Problem 90. Green has not yet marked these headings solved NanoGPT speedrun: AI contributions, acceleration unclear nanoGPT is a collective competition to minimize the tr

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shotai/Kimi-K3 Image-Text-to-Text • 2.8T • Updated 30 days ago • 1.27M • 11.6k nvidia/NVIDIA-Nemotron-Labs-3-Puzzle-75B-A9B-NVFP4 Text Generation • 45B • Updated Jul 7 • 10k • 130 openai/gpt-oss-120b Text Generation • 117B • Updated Aug 26, 2025 • 4.48M • 5.34k zai-org/GLM-5.2 Text Generation • 753B • Updated about 1 month ago • 731k • 5.14k Papers mentioned in this article 1 Efficient Knowledge Distillation for LLMs: Offline Top-K Logits and a Fused Chunked KL Loss Paper • 2608.03796 • Publishe

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nnoticed. Overall, it’s a great candidate for a Purple Team operation, if your company is into that. What Is LiteLLM? LiteLLM is an open-source proxy presenting a unified API over OpenAI, Anthropic, Azure OpenAI, Bedrock, and others. Organizations deploy it internally and issue “virtual keys” instead of distributing real provider keys. All configured inference traffic passes through the gateway. Claude Code users, for example, set ANTHROPIC BASE URL to the proxy and use a gateway credential such

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× single-node throughput, with roughly 10× lower P50 latency at high concurrency → 2.4× speedup on 8 nodes, near-linear scaling from 16 to 64 GPUs → Drop-in: one program id field, OpenAI-compatible, works with your existing engine-level optimizations (like speculative decoding) ThunderAgent was accepted to ICML 2026 as a Spotlight paper. This paper was a collaboration between researchers at Georgia Institute of Technology, the University of Illinois Urbana-Champaign, Carnegie Mellon University,

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ge models have performed research-level mathematics. In just the last few months, researchers from Google have used Gemini to resolve several open Erdős problems, researchers from OpenAI have used GPT to resolve the unit distance conjecture (a particularly challenging Erdős problem), and earlier this month we announced that Claude Fable 5 resolved the Jacobian Conjecture. Our result here—that Claude is able to perform cryptographic research at the level of top experts—indicates that these same c

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