#MachineLearning for Streaming Data with #Python — build practical online Machine Learning solutions: http://
amzn.to/40ztysN v/ @PacktDataML ————
#DataScience #ML #AI #StreamAnalytics #EdgeComputing #Edge #EdgeAI #TimeSeries #IoT #IIoT #DataScientist #AnomalyDetection
MACHINE LEARNING
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Practical Machine Learning for Streaming Data with Python
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Real-time world model generation from text and image prompts
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In our research lab, we are building “real-time dreaming” – the ability to generate fully playable video worlds prompted from any text or image.
— Roblox (@Roblox) 5 février 2026
Our real-time, action conditioned world model (currently running internally at 16fps at 832x480p) is trained on a combination of data,… pic.twitter.com/R5CKJkFuh2In our research lab, we are building “real-time dreaming” – the ability to generate fully playable video worlds prompted from any text or image. Our real-time, action conditioned world model (currently running internally at 16fps at 832x480p) is trained on a combination of data, including proprietary Roblox 3D avatar/world interaction data. World models are different from multiplayer engines in that they store state and memory in video latents. Roblox is multiplayer, and we are actively researching optimal ways to simultaneously store state for thousands of players, and keep them in sync with their environment. Our world model leverages database technology which stores all user interactions on Roblox in a vector format that can be used to re-render video and interaction from any camera angle. We see several immediate uses for our Roblox world model. We will use it side-by-side text, image and video prompts as a way to launch auto-generation of immersive worlds. In Roblox Studio, a creator could walk around and use prompts to “paint” a world and then convert it into a 3D representation or direct to Roblox native as a way for many people to play simultaneously. All of this comes alive as we explore the notion of a “Dream Theater” – where one user is dreaming, while others watch and prompt them. 2/4 Community note: The beginning of the video has stolen assets/design from Clair Obscur: Expedition 33 by Sandfall Interactive. The environment is the Flying Waters area and the girl in the video is Maelle. store.steampowered.com/app/1903340/Cl… expedition33.wiki.fextralife.com/Flying+Waters clair-obscur.fandom.com/wiki/Maelle
→ View original post on X — @shiqi_yang_147, 2026-02-05 01:28 UTC
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Tinker Community Achievements: Models, Infrastructure, Research Roundups
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Since Tinker launched, our community has used it to train state-of-the-art models, build infrastructure, and publish novel research. We will be highlighting this creative work in regular roundups, and hope to inspire your own Tinkering as well.
→ View original post on X — @soumithchintala, 2026-02-04 21:14 UTC
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Neural Architecture Search: Automating AI Model Design
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NAS: The AI That Designs AI 🏗️
— Satya Mallick (@LearnOpenCV) 4 février 2026
Stop guessing your model’s architecture. Neural Architecture Search (NAS) automates the hunt for the perfect model by balancing accuracy with hardware limits like speed and memory. 🚀#AI #MachineLearning #NAS #AutoML #DeepLearning #DataScience… pic.twitter.com/yE2Hyg5Z6MNAS: The AI That Designs AI Stop guessing your model’s architecture. Neural Architecture Search (NAS) automates the hunt for the perfect model by balancing accuracy with hardware limits like speed and memory. #AI #MachineLearning #NAS #AutoML #DeepLearning #DataScience
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Physical AI Era: Dassault and NVIDIA Pioneer Virtual Twins
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Physical AI is here. 🤝
— NVIDIA (@nvidia) 4 février 2026
Grounded in physics. Driven by intelligence.
Together, @Dassault3DS and NVIDIA are pioneering a new era of virtual twins that learn, simulate, and evolve.
🔗 https://t.co/SrTMcT6ndb pic.twitter.com/AtTBHFN4MzPhysical AI is here. Grounded in physics. Driven by intelligence. Together, @Dassault3DS and NVIDIA are pioneering a new era of virtual twins that learn, simulate, and evolve. https://
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Voxtral Transcribe 2: Impressive Real-Time Speech-to-Text Demo
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The demo on https://t.co/ozhOG8iPeH is worth a try – ignore the "No microphone found" message, clicking "Record" and allowing your browser to use a microphone fixes that. It transcribes very accurately in almost real-time. It's really impressive. https://t.co/LOJUsT2sPW
— Simon Willison (@simonw) 4 février 2026The demo on huggingface.co/spaces/mistra… is worth a try – ignore the "No microphone found" message, clicking "Record" and allowing your browser to use a microphone fixes that. It transcribes very accurately in almost real-time. It's really impressive. Mistral AI (@MistralAI) Introducing Voxtral Transcribe 2, next-gen speech-to-text models by @MistralAI. State-of-the-art transcription, speaker diarization, sub-200ms real-time latency. Details in 🧵 — https://nitter.net/MistralAI/status/2019068826097213953#m
→ View original post on X — @guillaumelample, 2026-02-04 18:29 UTC
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Voxtral Mini 4B Realtime: Fast Streaming ASR with vLLM Support
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Congrats to @MistralAI on releasing Voxtral Mini 4B Realtime! 🎉 Day-0 support in vLLM! A 4B streaming ASR model achieving <500ms latency while matching offline model accuracy, supporting 13 languages. vLLM's new Realtime API `/v1/realtime` provides audio streaming – optimized for voice assistants, live subtitles, and meeting transcription! Thanks to the close collaboration between the vLLM community and @MistralAI for making this production-grade support possible 🤝 📑Model & Usage: huggingface.co/mistralai/Vox… Mistral AI (@MistralAI) Voxtral Realtime is built for voice agents and live applications. Its natively streaming architecture delivers latency configurable to sub-200ms. And at 480ms, it stays within 1-2% WER of our offline model. We release the model as open weights under Apache 2.0. — https://nitter.net/MistralAI/status/2019068828257333466#m
→ View original post on X — @guillaumelample, 2026-02-04 17:51 UTC
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Voxtral Mini Transcribe 2: High-Performance Affordable Batch Transcription
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Voxtral Mini Transcribe 2 handles batch transcription with the best price-performance of any transcription API: 4% WER on FLEURS at $0.003/min. Includes speaker diarization, context biasing, and word-level timestamps across 13 languages.
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Voxtral Realtime: Ultra-Fast Open Source Streaming Voice Model
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Voxtral Realtime is built for voice agents and live applications. Its natively streaming architecture delivers latency configurable to sub-200ms. And at 480ms, it stays within 1-2% WER of our offline model. We release the model as open weights under Apache 2.0.
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Google DeepMind’s Project Genie Advances World Models Research
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— Google AI (@GoogleAI) 4 février 2026
Project Genie is a great way to experiment and get a feel for world models and this exciting research frontier. I've been having fun exploring interactions that are usually quite hard to simulate with physics engines x.com/GoogleDeepMind…