🍓OpenAI’s ‘Strawberry’, The Future of AI is Here!🧠

📸Meet Pixtral 12B, Mistral’s AI That Sees and Thinks!📝

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In Today's Blog:

• 🍓OpenAI’s ‘Strawberry’ The AI That Thinks Before It Speaks!🧠
  

• 🗣️Mistral Unleashes Pixtral 12B, The AI Model That Sees and Speaks!📸

• 🧬Chai-1, The AI Marvel Outshining AlphaFold in Drug Discovery!💊

• 🗣️Google’s AI NotebookLM Now Talks!📚

🍓OpenAI’s ‘Strawberry’ The AI That Thinks Before It Speaks!🧠

OpenAI is set to release a new AI model called “Strawberry” for ChatGPT in the next two weeks. This model is designed to enhance reasoning capabilities by “thinking” before responding, rather than providing immediate answers.

• 🍓OpenAI plans to release a new AI model called “Strawberry” for ChatGPT in two weeks. 
• 🧠Strawberry is unique because it can “think” before responding, unlike other conversational AIs.
• 📄The initial version will only handle text, not images, making it a text-focused AI.
• 🤔While part of ChatGPT, Strawberry will be a standalone offering, though details on its availability are still unclear.

      Read about it here: Link

🗣️Mistral Unleashes Pixtral 12B, The AI Model That Sees and Speaks!📸

French AI startup Mistral has released Pixtral 12B, its first multimodal model capable of processing both images and text. This 12-billion-parameter model, built on Mistral’s text model Nemo 12B, can handle tasks like image captioning and object counting.

• 📸French startup Mistral released Pixtral 12B, a multimodal model that processes both images and text.
• 💾Pixtral 12B has 12 billion parameters and is about 24GB in size, enhancing its problem-solving skills.
• 🔓The model is available for download on GitHub and Hugging Face under an Apache 2.0 license.
• 💬Pixtral 12B will soon be testable on Mistral’s chatbot and API platforms, Le Chat and Le Plateforme.

     Read more about it: Link

🧬Chai-1, The AI Marvel Outshining AlphaFold in Drug Discovery!💊

Chai Discovery, an AI startup backed by OpenAI and Thrive Capital, has introduced Chai-1, an advanced AI model designed to predict molecular structures, crucial for drug discovery. 

• 🧬Chai Discovery introduced Chai-1, an advanced AI model for predicting molecular structures, which is crucial for drug discovery.
• 🏆Chai-1 has outperformed Google DeepMind’s AlphaFold in certain benchmarks, making it a significant advancement in the field.
• 🌐The model is available for free through a web interface, and its code and tools are shared for non-commercial use to encourage further research.
• 💊Chai-1 excels in predicting interactions between proteins and small molecules, even with limited data, making it highly useful in practical scenarios.

     Read about it here: Link

🗣️Google’s AI NotebookLM Now Talks!📚

Google has introduced a new feature called Audio Overview for its AI note-taking app, NotebookLM. This feature allows users to listen to summaries and explanations of their uploaded documents, such as course readings or legal briefs.

• 🎧Google’s AI note-taking app, NotebookLM, now has an “Audio Overview” feature that explains complex topics out loud.
• 📚This feature helps users who prefer listening over reading to understand their documents better.
• 🗣️AI-generated virtual hosts use conversational speech patterns and metaphors to explain the material.
• 🌍The feature is currently in beta, available in English, and can be used in over 200 countries.

     Read about it here: Link

Other stuff

• 🚀 Apple Intelligence is Here! 🌟 Only for Devs & Beta Testers! 🧑 [Link] RECOMMENDED
• 💡 Tezi Raises $9M to Revolutionize HR with AI! 🤖 [Link] RECOMMENDED
• 🤝 Nvidia & Neura Team Up for Next-Gen Robots! 🤖 [Link] 
• 🏛️ OpenAI Backs AI Bills in Congress! 🤖 [Link] RECOMMENDED

Chess Dream: A deep neural network, trained to generate realistic (more or less) chess positions [Link]

Elicit: Analyze research papers at superhuman speed [Link]

🦓🦓 ZebraPose: Zebra Detection & Pose

MPI and Stuttgart unveil the first synthetic dataset that can be used for both detection and 2D pose estimation of zebras without applying any bridging strategies. Code, results, models, and the synthetic, training/validation data, including 104K manually labeled images open-sourced.