How good is a model if you let it just keep doing more and more test-time compute? Maybe the sky's the limit.
COMPUTING
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NVIDIA explains AI Grid basics for telecom networks
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Earlier this year we announced that telecom leaders are building AI grids using NVIDIA AI infrastructure to optimize inference on distributed networks
— NVIDIA (@nvidia) 9 juin 2026
But what actually is an AI Grid?
In this video, Amogh Dendukuri takes us back to basics. Watch now to see him break down the… pic.twitter.com/JMgh8YXq9FEarlier this year we announced that telecom leaders are building AI grids using NVIDIA AI infrastructure to optimize inference on distributed networks But what actually is an AI Grid? In this video, Amogh Dendukuri takes us back to basics. Watch now to see him break down the
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ChatGPT update now available on mobile and web
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And we wake up to another chatgpt update!
— Futurepedia – Learn to Leverage AI (@futurepedia_io) 9 juin 2026
Now on mobile and web 👇 https://t.co/rOwuozZBZGAnd we wake up to another chatgpt update! Now on mobile and web
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Siri runs on custom Google Gemini model costing $1 billion annually
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5/ Siri runs on a custom Google Gemini model, reported at around $1 billion a year.
The numbers come from Bloomberg, not Apple. The deal is real. -
Arcee AI replaces AWS S3 with Hugging Face for all its models
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Super excited to announce that @arcee_ai is the first major US AI lab to replace AWS S3 with Hugging Face for ALL their models and datasets, public AND private. Multi-million dollar partnership to support American open-source AI, let's
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Apple’s new 20B on-device AFM 3 for iPhone 17 Pro
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Apple's new foundation models are genuinely exciting. The standout is AFM 3 Core Advanced, a 20-billion (!) parameter model that runs entirely on-device. Read that again. 20-billion, on-device, iPhone 17 Pro. It pulls this off by keeping the full model in flash memory and
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Cross-referencing answers between models to get more from each
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.@nlarusstone from @benchling on how they cross-check answers between models to get more out of each one. pic.twitter.com/kL0ZVnvgQt
— LangChain (@LangChain) 9 juin 2026@nlarusstone from @benchling on how they cross-reference answers between models to get more out of each.
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PGA Championship tests AI and simultaneous connections without slowdowns
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Stadiums. Hospitals. Campuses. The architecture problem is the same everywhere: how do you run AI and thousands of simultaneous connections without one system slowing down another? The PGA Championship just ran that experiment live, in front of the world. Watch the full
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Misunderstanding about harness/CLI despite quality models
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I really don't understand what they are doing with their harness/CLI. The models are apparently good.
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TensorFlow vs PyTorch: Choosing Your ML Framework
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#TensorFlow Vs #PyTorch: Choosing Your ML Framework. #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #Python #RStats #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode https://
geni.us/TensorFlow-Vs-
PyTorch
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