8/ OpenAI's "Strawberry" proves an important point: AI can be both fast and thoughtful. By focusing on improving reasoning capabilities, OpenAI is reshaping how businesses interact with AI.
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OpenAI’s Strawberry model thinks before responding for accuracy
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2/ To address this, OpenAI developed "Strawberry": A model that "thinks" before responding. This approach aims to enhance accuracy and depth of responses, removing barriers for businesses seeking more thoughtful AI interactions.
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OpenAI’s competition: perception that AI lacks reasoning depth.
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1/ In 2023, AI chatbots became a staple for businesses worldwide. OpenAI realized that their competition wasn't just other AI companies, but also the perception that AI lacks depth in reasoning.
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Strawberry: an AI that reasons to transform business exchanges
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Think AI can't reason? Not anymore. OpenAI's about to change the game with "Strawberry". Here's how this new AI model could revolutionize your business interactions. Follow the :
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New SuperNova Training Pipeline and Llama-3.1-SuperNova-Lite Model
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Blog post:
https://
blog.arcee.ai/arcee-supernov
a-training-pipeline-and-model-composition/
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Model on HF:
https://
huggingface.co/arcee-ai/Llama
-3.1-SuperNova-Lite
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Arcee SuperNova: Llama-3.1-70B fine-tune with 405B distillation
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Arcee releases Arcee-SuperNova, better fine-tune of Llama-3.1-70B! versions: 70B and 8B Trained by distilling logits from Llama-3.1-405B Used a clever compression method to reduce dataset weight from 2.9 Petabytes down to 50GB (may share it in a paper) Not all
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HuggingFace Model Updates: Fixed Version Released
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Those are two HF models: the first uploaded version, and then a "fixed" version (confirmed by someone from the team).
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Reflection 70B: New Open Source AI at Center of Controversies
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[#Article] Open source AI: Just unveiled, Reflection 70B at the center of controversies https://actuia.com/actualite/ia-open-source-tout-juste-devoile-reflection-70b-au-coeur-des-controverses/
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Reflection-70B API and Model Reliability Issues Exposed
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Maybe Reflection-70B really works. But that doesn't change the fact that people massively shared something that didn't. The API was wrong. The HF model was wrong (see my own benchmarks ↓).
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Philschmid’s space to compare LLM prices
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In a similar vein, check out @_philschmid
's great space to compare LLM prices across providers: