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  4. Plants can speak using electricity, so this startup built an AI model to decipher their language
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Models & Releases

Plants can speak using electricity, so this startup built an AI model to decipher their language

Electric Plant has built an AI-powered translator to help humans listen to what plants are saying with the subtle electricity coursing through their stems.

Get smart on it

A startup has developed an AI model that interprets electrical signals flowing through plant stems to understand what plants need, such as water, nutrients, or light. Plants naturally communicate their conditions through electrical signals in their tissues, and the AI model can translate these signals across over 100 plant species to help farmers and growers make real-time adjustments to watering and fertilizer. The approach uses inexpensive sensors attached to plants that send data wirelessly to the cloud, where the AI processes it and returns actionable information. This technology could improve crop yields while reducing water use compared to traditional farming methods that rely on less precise tools like soil probes and satellite imagery.

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Models & ReleasesOpen story →

Mistral AI launches Voxtral 3, a full voice agent stack that listens, thinks, and talks in real time

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

Models & ReleasesOpen story →

Voxtral 3

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.

Models & ReleasesOpen story →

DeepSeek Open-Sources DeepInfer, the Inference Framework Behind DeepSeek-V4.1-Flash

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

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Nvidia launches new open models to run agents in the enterprise and on PCs

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.

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Meta and Apple team up to make Muse AI models run better on Macs

The new Muse Spark Open AI model can work on M5 Ultra Mac Studios. | Photo: Amelia Holowaty Krales / The Verge Meta announced the Muse Spark Open AI model today, claiming that it's the "most capable US open-weight model to date." But the company also says that it's the "the first model in its class" that can "run on your desktop using two Apple M5 Ultra Mac Studios with the latest MLX framework." Meta and Apple, typically rivals, worked together on the launch and are publicly su

Also reported by The Decoder, TechCrunch, SiliconANGLE and MarkTechPost

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Elevenlabs releases two new speech-to-speech models designed for real-time AI conversations

Elevenlabs' new Eleven Realtime speech-to-speech models combine speed and accuracy. The v1 Max variant scores 98.8 percent on the Big Bench Audio benchmark with a 0.57-second response time. Elevenlabs says no model on the Artificial Analysis leaderboard is both faster and more accurate. The article Elevenlabs releases two new speech-to-speech models designed for real-time AI conversations appeared first on The Decoder.