SiliconANGLE: AI startup doubleAI debuts Maxwell ‘code execution model’
Startup doubleAI today debuted Maxwell, a model that can optimize software code and generate mathematical proofs. Tel Aviv-based doubleAI, officially AA-I Technologies Ltd., is led by Chief Executive Officer Amnon Shashua, who earlier co-founded auto chip supplier Mobileye Global Inc. The company is backed by $220 million in funding from Nvidia Corp., Dell Technologies Inc. […] The post AI startup doubleAI debuts Maxwell ‘code execution model’ appeared first on SiliconANGLE.
An AI startup has debuted Maxwell, a model designed to optimize software code and generate mathematical proofs by analyzing how programs interact with data and underlying computer chips. The model works on a program's binary, or machine-generated translation, rather than source code, which means it can make applications more efficient without requiring developers to manually rewrite code. Maxwell has demonstrated capability across multiple domains, including rewriting software libraries to reduce hardware usage, improving data science toolkit performance by a factor of 38, and breaking a nearly 50-year chess record. The company plans to sell Maxwell to enterprises looking to lower their AI workloads' hardware demands, positioning it alongside competing models from other major AI developers that are also capable of automating research tasks.
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Mistral AI launched Voxtral 3, a new family of language models built for real-time voice agents. The system combines speech-to-text, text-to-speech, and a voice agent SDK, supports more than 50 languages, and lets agents tap into external tools during live conversations. It can run on your own infrastructure or through EU-hosted APIs to keep data under your control. The article Mistral AI launches Voxtral 3, a full voice agent stack that listens, thinks, and talks in real time appeared
Also reported by MarkTechPost

Voxtral 3: Mistral's voice agent SDK for real-time speech in 50+ languages — accurate transcription, emotional TTS, deep tool use. EU-hosted or self-deployed.

Recursive makes the case that the benefits of using AI to build AI outweigh the risks.

DeepSeek has open-sourced DeepInfer, the inference framework that runs its production services. The DeepSeek DeepInfer inference framework is the engine behind DeepSeek-V4.1-Flash. It ships under the Apache 2.0 license. DeepSeek also released deepseek-recipe, its MIT-licensed token encoding and decoding layer. For developers, this is a rare look at a frontier lab’s real serving stack. TL;DR Size / scope: 1 supported model (DeepSeek-V4.1-Flash), 1M-token context window per the model
Also reported by The Decoder and SiliconANGLE

Nvidia is leaning hard into the trend of enterprise companies wanting to run their own open models in their own data centers and also trying to make on-device, private AI agents a thing.

NVIDIA is expanding its family of open models across language, robotics, biology, and quantum computing, giving developers, researchers and enterprises what they need to build applications tailored to local languages and industries The portfolio includes the new NVIDIA Nemotron 3.5 Super VL and Nemotron 3.5 Bolt models; new NVIDIA Nemotron Retriever models for embedding, reranking and document parsing; the new NVIDIA Kumo family open weight foundation models and libraries for structured business