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Semantic search improves our agent's accuracy across all frontier models, especially in large codebases where grep alone falls short. Learn more about our results and how we trained an embedding model for retrieving code.

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880,914 görüntüleme • 7 ay önce •via X (Twitter)

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We are excited to launch our two models Pharia-1-LLM-7B-control and Pharia-1-LLM-7B-control-aligned. Both models and the code used to train them are now publicly available and open-sourced for non-commercial research and educational use. Read our model blog post here: Learn more about our open-source codebase Scaling: #writtenbyalephalpha
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We are excited to launch our two models Pharia-1-LLM-7B-control and Pharia-1-LLM-7B-control-aligned. Both models and the code used to train them are now publicly available and open-sourced for non-commercial research and educational use. Read our model blog post here: Learn more about our open-source codebase Scaling: #writtenbyalephalpha

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AI has huge potential to change how we work and live. That was clear at Montreal’s ALL IN Conference. But we also need to make sure our AI ecosystem can develop responsibly – and that’s what our new code of conduct does. Learn more about the code here:
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AI has huge potential to change how we work and live. That was clear at Montreal’s ALL IN Conference. But we also need to make sure our AI ecosystem can develop responsibly – and that’s what our new code of conduct does. Learn more about the code here:

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Today, we announced our earnings results for Q3 2024. This quarter, we delivered $1.37B in revenue and our community grew to 443M DAU! Learn more at
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Today, we announced our earnings results for Q3 2024. This quarter, we delivered $1.37B in revenue and our community grew to 443M DAU! Learn more at

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Search just got an upgrade! Our new Advanced Search lets you set your location, apply updated filters, and customize your search between tournaments, leagues, and hubs much faster than before. Learn about this and more in our new Balance Patch article below!
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Search just got an upgrade! Our new Advanced Search lets you set your location, apply updated filters, and customize your search between tournaments, leagues, and hubs much faster than before. Learn about this and more in our new Balance Patch article below!

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New Generation Model! 🚨 We're introducing the Mistral model to our expanding lineup of generation models. Mistral brings efficient performance and strong language understanding capabilities to our platform. Initial testing shows promising results in code comprehension and generation tasks, making it a valuable addition to development workflows. While we continue to optimize its implementation, early benchmarks demonstrate consistent and reliable outputs across various programming tasks.
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New Generation Model! 🚨 We're introducing the Mistral model to our expanding lineup of generation models. Mistral brings efficient performance and strong language understanding capabilities to our platform. Initial testing shows promising results in code comprehension and generation tasks, making it a valuable addition to development workflows. While we continue to optimize its implementation, early benchmarks demonstrate consistent and reliable outputs across various programming tasks.

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Introducing our Hosted Firecrawl MCP 🔥 Near-instant setup for web scraping, crawling, and search across all major model providers like Gemini, Claude, and OpenAI who all support MCP. Perfect for IDE workflows, agents, and more. Just plug in your API key and go 👇
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Introducing our Hosted Firecrawl MCP 🔥 Near-instant setup for web scraping, crawling, and search across all major model providers like Gemini, Claude, and OpenAI who all support MCP. Perfect for IDE workflows, agents, and more. Just plug in your API key and go 👇

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We're excited to introduce Arcee.ai's Trinity Large model. An open 400B parameter Mixture of Experts model, delivering frontier-level performance with only 13B active parameters. Trained in collaboration between Arcee, Datology and Prime Intellect.
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We're excited to introduce Arcee.ai's Trinity Large model. An open 400B parameter Mixture of Experts model, delivering frontier-level performance with only 13B active parameters. Trained in collaboration between Arcee, Datology and Prime Intellect.

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Many of you asked for code & weights for π₀, we are happy to announce that we are releasing π₀ and pre-trained checkpoints in our new openpi repository! We tested the model on a few public robots, and we include code for you to fine-tune it yourself.
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Many of you asked for code & weights for π₀, we are happy to announce that we are releasing π₀ and pre-trained checkpoints in our new openpi repository! We tested the model on a few public robots, and we include code for you to fine-tune it yourself.

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Introducing exa-code, a big step towards eliminating LLM code hallucination. We indexed 1B+ docs pages, Github repos, StackOverflow posts, and more. Given a query, exa-code initiates a hybrid search over this data, chunks it, and returns a concatenated, token-efficient string. In our code hallucination eval, exa-code outperforms every popular web search tool (including Exa!). Available for free: How we built it:
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Introducing exa-code, a big step towards eliminating LLM code hallucination. We indexed 1B+ docs pages, Github repos, StackOverflow posts, and more. Given a query, exa-code initiates a hybrid search over this data, chunks it, and returns a concatenated, token-efficient string. In our code hallucination eval, exa-code outperforms every popular web search tool (including Exa!). Available for free: How we built it:

Exa

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We trained our Large Sensor Model (LSM) on over 40 million hours of de-identified multimodal sensor data from 165K users to demonstrate how it could improve performance in wearable tasks like exercise and activity recognition. Here’s what we found →
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We trained our Large Sensor Model (LSM) on over 40 million hours of de-identified multimodal sensor data from 165K users to demonstrate how it could improve performance in wearable tasks like exercise and activity recognition. Here’s what we found →

Google AI

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1/ Happy to share VADER: Video Diffusion Alignment via Reward Gradients. We adapt foundational video diffusion models using pre-trained reward models to generate high-quality, aligned videos for various end-applications. Below we generated a short movie using VADER 😀, we used ChatGPT to write a script and an off-the-shelf AI music generator to generate the sound. Our code & weights are open-sourced:
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1/ Happy to share VADER: Video Diffusion Alignment via Reward Gradients. We adapt foundational video diffusion models using pre-trained reward models to generate high-quality, aligned videos for various end-applications. Below we generated a short movie using VADER 😀, we used ChatGPT to write a script and an off-the-shelf AI music generator to generate the sound. Our code & weights are open-sourced:

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Accidentally ran an accuracy test on our MicroFactory robotic arm. I had to disassemble the base for some improvements. To keep testing consistent for our already-trained models, I quickly built an improvised setup to recreate the previous calibration. After removing and reinstalling the motors, I was able to restore their position within 0.002°. Positioning repeatability was at least 0.01 mm at 300 mm reach. This isn’t a full accuracy test — a proper one would require more planes and indicators with resolution at least an order of magnitude better than the measured values. But anyway, this accuracy is sufficient for all of our assembly tasks.
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Accidentally ran an accuracy test on our MicroFactory robotic arm. I had to disassemble the base for some improvements. To keep testing consistent for our already-trained models, I quickly built an improvised setup to recreate the previous calibration. After removing and reinstalling the motors, I was able to restore their position within 0.002°. Positioning repeatability was at least 0.01 mm at 300 mm reach. This isn’t a full accuracy test — a proper one would require more planes and indicators with resolution at least an order of magnitude better than the measured values. But anyway, this accuracy is sufficient for all of our assembly tasks.

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Video understanding is the next frontier, but not all videos are alike. Models now reason over youtube clips and feature films, but what about the everyday spaces we—and our future AI assistants—navigate and experience? Introducing Thinking in Space, our latest study exploring how multimodal LLMs see, remember and recall spaces. 🧵[1/n]
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Video understanding is the next frontier, but not all videos are alike. Models now reason over youtube clips and feature films, but what about the everyday spaces we—and our future AI assistants—navigate and experience? Introducing Thinking in Space, our latest study exploring how multimodal LLMs see, remember and recall spaces. 🧵[1/n]

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We now have an easy overview of all open-source models supported in our API You can find pricing, context limits, supported features, and more
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We now have an easy overview of all open-source models supported in our API You can find pricing, context limits, supported features, and more

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From day one of our Administration, President Biden and I have worked to build an America where every person has the opportunity to thrive. Learn more about our accomplishments at

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September is an important month for blood and platelet donation: ❤️ #BloodCancerAwarenessMonth 💛 #ChildhoodCancerAwarenessMonth ❤️ #SickleCellAwarenessMonth Keep your eyes on our page to learn more about each of these and how you can support our mission to save more lives.

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Working with multiple models in Chat? The model picker in VS Code is now organized by provider, making it easier to browse, search, and switch between models. You'll also see provider names next to your recent models for quicker recognition. 💡 Tip: Use /models for quick access.
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Working with multiple models in Chat? The model picker in VS Code is now organized by provider, making it easier to browse, search, and switch between models. You'll also see provider names next to your recent models for quicker recognition. 💡 Tip: Use /models for quick access.

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Our first-quarter 2025 results demonstrate the strength of our operations and our steady progress toward a more secure and sustainable energy future Learn more #AramcoResults #aramco
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Our first-quarter 2025 results demonstrate the strength of our operations and our steady progress toward a more secure and sustainable energy future Learn more #AramcoResults #aramco

aramco

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Searching for files in large projects has never been easier 🚀 Check out the real-time search results for the #vscode project, which has thousands of files (and yes, we use Visual Studio Code to write Visual Studio Code). You can easily switch between fuzzy matching and continuous matching too!
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Searching for files in large projects has never been easier 🚀 Check out the real-time search results for the #vscode project, which has thousands of files (and yes, we use Visual Studio Code to write Visual Studio Code). You can easily switch between fuzzy matching and continuous matching too!

Visual Studio Code

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Gemini Embedding 2 is now generally available in the Gemini API and Vertex AI! Start building with our first natively multimodal embedding model, now equipped with the stability and optimizations required for production apps.
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Gemini Embedding 2 is now generally available in the Gemini API and Vertex AI! Start building with our first natively multimodal embedding model, now equipped with the stability and optimizations required for production apps.

Google AI Developers

813,214 görüntüleme • 1 ay önce