There’s also always the specter of rate limiting for most (all?) AI company, but remember, OpenAI has a cap for API spending. And OAI feels largely geared toward a conversational experience, while 11L can satisfy a wide set of use cases across many industries.
GENERATIVE AI
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Snorkel AI’s 7B Model Ranks 2nd on AlpacaEval 2.0
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We are making big strides towards programmatic alignment! Using a reward model w/ DPO, Snorkel AI ranked 2nd on the AlpacaEval 2.0 LLM leaderboard using only a 7B model! Hear from the researcher behind this achievement at our Enterprise LLM Summit tomorrow! #SnorkelAI #AI #LLMs
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Dolly Zoom Effect Now Available in Runway Gen-2
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Learn to create a dolly zoom effect with Multi Motion Brush.
— Runway (@runwayml) 24 janvier 2024
Available now for Gen-2 at https://t.co/ekldoIsP34 pic.twitter.com/jgHzm1kRw4Learn to create a dolly zoom effect with Multi Motion Brush. Available now for Gen-2 at http://
runwayml.com -
New features for managing personal data in ChatGPT and Custom GPTs
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It will be possible to see what GPT learned about you and remove this information. There is also a dropdown which only has a ChatGPT option as of now but it looks like you will be able to browse and manage the same for Custom GPTs
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ChatGPT Developing New Personalisation Memory Management Options
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ChatGPT is working on an option to manage Personalisation memory
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Voltron Data Acquires Claypot for Real-Time AI Applications
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Claypot AI is joining Voltron Data! AI starts from data. By joining forces, we can further help companies leverage both batch and real-time data for AI applications, on top of Voltron Data’s GPU-native distributed engine Theseus. https://
venturebeat.com/data-infrastru
cture/exclusive-voltron-data-acquires-claypot-to-unlock-real-time-ai-with-modular-data-systems/
… For AI, GPUs are mostly -
Key Research Topics for Improving RAG Accuracy in LLM Applications
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A good custom LLM application typically involves RAG and while naive RAG is easy to implement, it rarely performs well. Here are key areas research topics in RAG that are essential for increasing accuracy of custom LLM apps In-Context Learning – LLMs do poorly when you send a
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LangChain QA with RAG and Advanced Retrieval Techniques
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two pages id check out: QA with RAG, a page covering lot of different concept related to this use case: https://
python.langchain.com/docs/use_cases
/question_answering/
… Retrieval: a page covering advanced retrieval techniques: https://
python.langchain.com/docs/modules/d
ata_connection/retrievers/
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Kit Kat’s AI Break Study: Marketing or Misinformation?
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Kit Kat Canada just used a @GoogleDeepMind study to advertise chocolate.
— Allie K. Miller (@alliekmiller) 24 janvier 2024
Because if AI performs better after a break, maybe you need one too 🍫
(Friendly reminder that LLMs are not truth tellers and reducing hallucinations does not mean you should trust the output blindly.) pic.twitter.com/HufEma2UmDKit Kat Canada just used a @GoogleDeepMind study to advertise chocolate. Because if AI performs better after a break, maybe you need one too (Friendly reminder that LLMs are not truth tellers and reducing hallucinations does not mean you should trust the output blindly.)
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Fine-Tuning Foundation Models: New Safety Risks Emerge
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When users of foundation models customize them through a process called fine-tuning, new safety risks emerge. Read the HAI Policy Brief: