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@MicronTech introduces GDDR7, its graphics memory chip for next-generation GPUs https://actuia.com/actualite/micron-technology-presente-gddr7-sa-puce-de-memoire-graphique-pour-les-gpu-nouvelle-generation/
… #AI #ArtificialIntelligence
AI HARDWARE
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Micron Technology Introduces GDDR7 for Next-Generation GPUs
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Humane AI Pin: Employee Fired for Voicing Launch Concerns
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“After that software engineer was fired for questioning if the AI pin would be ready for launch, the report describes a staff meeting where the founders "said the employee had violated policy by talking negatively about Humane."”
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Metis AI: Cost-Effective Edge Inference Computer Vision
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Want to cut costs on AI computer vision without losing performance? Watch our video to see how the Metis AI excels in edge inference and AI acceleration. Get the best performance-to-cost ratio in the market. Explore our Metis AI Evaluation Kits. https://t.co/XYy5Ncb30k#AI pic.twitter.com/uJGbRd3kxo
— Axelera AI (@AxeleraAI) 10 juin 2024Want to cut costs on AI computer vision without losing performance? Watch our video to see how the Metis AI excels in edge inference and AI acceleration. Get the best performance-to-cost ratio in the market. Explore our Metis AI Evaluation Kits. https://
tinyurl.com/244md3rf
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X Premium Users Monetize Neural Capacity via Grok Integration
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Well it all started when X premium users with Neuralink could get paid to let Grok use excess neural capacity…
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GPU Supply Distribution Among Major AI Labs
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5/ there is another factor—which is that the $100B is spread between multiple labs. the largest labs (Google, OpenAI, Meta, Anthropic, etc.) may only have 10-20% of the total GPU supply from NVDA (sidenote: Google is the hardest to track because they use TPUs as well as GPUs)
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GPU spending scale needed for hundred billion dollar model training
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6/ so we won't see what would happen if you spent $100B of GPUs on a model for a while because of how spread out the GPU distributions are. we'd likely need to see $500B of aggregate GPU spend to have an individual model trained on $100B of GPUs (wow!)
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100B GPU Investment: Will Next-Gen AI Models Justify NVIDIA Spending?
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1/ one of the biggest questions in AI today is: since GPT-4 was trained in fall 2022, we've collectively spent ~$100B on NVIDIA GPUs will the next generation of AI models' capabilities live up to that aggregate investment level? NVIDIA qtrly datacenter rev, by @Thomas_Woodside
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Nate Silver Confirms Significant Nvidia Holdings Betting on AI
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Nate Silver says 'I have a fair amount of Nvidia, so, I guess, yes,' when asked if he is long AI at the Manifest conference
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Hugging Face Pollen Robotics Open Source Household Chores Robot
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https://
venturebeat.com/ai/hugging-fac
e-and-pollen-robotics-show-off-first-project-an-open-source-robot-that-does-chores/
… "…train the robot to do a variety of household chores and safely interact with humans and dogs" understudied problem here imo (as a pet owner) -
NVIDIA NIM Deploys Fine-Tuned LoRA Adapters Mixed-Batch Inference
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Get a step-by-step on how #NVIDIANIM helps deploy and scale swarms of fine-tuned LoRA adapters to handle mixed-batch inference requests. Learn more about our strategic approach > https://
nvda.ws/4aNMSWh #LLM #benchmark