Learn more here: https://
cerebras.ai/press-release/
cerebras-demonstrates-trillion-parameter-model-training-on-a-single-cs-3-system
… https://
cerebras.ai/blog/introduci
ng-gigagpt-gpt-3-sized-models-in-565-lines-of-code
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GENERATIVE AI
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Cerebras Trains Trillion-Parameter Models on Single CS-3
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Cerebras-GPT vs Megatron: Simplifying GPU Training Architecture
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Nvidia is very proud of Megatron – it lets you train across thousands of GPUs! But it's 20K lines of code to manage the cluster. Cerebras-GPT is 500 lines of code. One block of memory. One logical accelerator. No distributed computing. Everyone who's used it calls it magic.
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ChatGPT integrated into Apple Intelligence and Siri: Apple-OpenAI strategy
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#ChatGPT arrives in #AppleIntelligence and #Siri → https://youtu.be/Ks1sbFyWrNc In this video, we discuss the features and especially the (brilliant) strategy of @Apple with @OpenAI and #AI
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The Rapid Adoption of Generative AI in the Workplace
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The Rapid Adoption of Generative AI
#AI #AIio #BigData #ML #NLU #Futureofwork @Kevin_Jackson @sallyeaves @schmarzo @kdnuggets @akwyz @BrettKing @TechNative @MiaD -
Llama 3.3 70B Now Available on SambaNova Cloud
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🚨 Llama 3.3 70B, now available on SambaNova Cloud! @AIatMeta
— SambaNova (@SambaNovaAI) 11 décembre 2024
✅ Context length of 64K tokens
✅ Perfect for building Agents with other models
✅ Need higher rate limits? Just ask us
Try it out 👇Llama 3.3 70B, now available on SambaNova Cloud! @AIatMeta Context length of 64K tokens Perfect for building Agents with other models Need higher rate limits? Just ask us Try it out
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ContextCite: Tracing AI Sources and Detecting Hallucinations
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If the AI generates an inaccurate fact, users can trace the error back to its original source & understand the model’s reasoning. If the AI hallucinates an answer, ContextCite can indicate that the information didn’t come from any real source at all.
— MIT CSAIL (@MIT_CSAIL) 11 décembre 2024
The tool could be valuable… pic.twitter.com/D8ViuL2cjXIf the AI generates an inaccurate fact, users can trace the error back to its original source & understand the model’s reasoning. If the AI hallucinates an answer, ContextCite can indicate that the information didn’t come from any real source at all. The tool could be valuable
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ContextCite helps verify AI assistant claims with source citations
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Existing AI assistants sometimes provide source links, but users would have to tediously review the article to spot any mistakes. ContextCite can help directly find the specific sentence that a model used, making it easier to verify claims & spot mistakes.
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MIT ContextCite tool improves chatbot answer reliability verification
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How can we really know if a chatbot is giving a reliable answer? MIT CSAIL’s "ContextCite" tool can ID the parts of external context used to generate any particular statement from a language model, improving trust by helping users easily verify the statement:
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Data Scaling Limitations in AI Model Improvement Questioned
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Shared some hot takes with @reckless on Decoder this week (not all of them AGI-related!), and one of the most important: I don't think data will be a limitation on model improvement and scaling anytime soon. Why I think we still have big gains ahead: 1. The more computation you