Meet #DBRX: a general-purpose LLM that sets a new... standard for efficient open source models. Use the DBRX model in your RAG apps or use the DBRX design to build your own custom LLMs and improve the quality of your GenAI applications.show more

DBRX by Databricks ...it's REALLY good!! The New MoE... 132b parameter model is open-source and costs $10 m to train. Thank you, Databricks, for your contribution to OS. Check out the full explanation and testing: 🎥👇show more

We’re excited to partner with OpenAI to launch their... new open source models natively on Databricks! gpt-oss sets a new standard of quality for open language models, supporting advanced reasoning with the transparency, flexibility and control enterprises need. Running on Databricks, the gpt-oss models connect securely to your data and scale with built-in governance, and expand what you can build and do with GenAI. Try both the 20B and 120B today in the Mosaic AI Playground.show more

The future of AI is open-source. And ollama is... the easiest way to build AI applications with open-source LLMs. Here's how to build a free, private RAG app using open-source tools. We'll use: - Ollama for LLMs and embedding models - PostgreSQL for data storage and retrieval - pgai Vectorizer for embedding creation and sync (I use Nomic for embeddings and tinnyllama as my LLM but you can substitute them for any models on Ollama)show more

🚨 Host Your Own Local LLM On The Abacus... AI SuperComputer Stop being sad about Fable and control your destiny by hosting your own LLM - host open source LLMs like Qwen and Gemma - create chat bots or always on APIs - message it via an always on agents Use SOTA models like GPT 5.5xHigh or Opus to create open-source LLM apps and gamesshow more

Introducing the 01 Developer Preview. Order or build your... own today: The 01 Light is a portable voice interface that controls your home computer. It can see your screen, use your apps, and learn new skills. This is only the beginning for 01— the open-source foundation for this new era of AI devices.show more

Run state-of-the-art RAG applications locally on your computer with... ollama and use all the fantastic open-source models like llama3, msk's awesome models, or Command R from Cohere With Verba 1.0, we put it all in your hands 🙌 Get on board for a wild open-source ride, we're bridging any moat as open-source is here to winshow more

RouteLLM: Choose the Best LLM for Your Query! Use... a single interface to access all state-of-the-art LLMs: - o1 for hard problems - Sonnet 3.5 for standard coding - GPT-4o for essays - Gemini Flash 2.0 for longer contexts Mix and match to use the best LLM for your query on ChatLLM.show more

Introducing the Warp CLI — a new way to... use Warp’s agents. Use the CLI to build custom integrations, use Warp on remote machines, trigger it when CI fails, or build your own Slack integrations:show more

It’s time to take your ideas seriously. You can... now build apps directly in Fuser: ↳ a design tool for your favorite effects ↳ a game that gets the group chat to meet IRL ↳ a photo diary of textures to use later Make it for you and your people. Go live in minutes.show more

What if LLMs could learn your habits and preferences... well enough (across any context!) to anticipate your needs? In a new paper, we present the General User Model (GUM): a model of you built from just your everyday computer use. 🧵show more

Weave is launching the number 1 prompt router in... the world. It enables you to get 70% more efficient use of your tokens. We analyzed millions of prompts and found that the vast majority don't need a frontier model. Weave Router fixes that. It analyzes your prompt and routes it to the highest quality model with the lowest cost (across open and closed source models). This all happens in your current workflow on Claude, Cursor or Codex so you don't have to change a thing. Early customers have seen an ~70% reduction in costs without any slowdowns. Source code available.show more

Artifacts, but 100% Open Source, Private & Local. Open... WebUI has released a game changer update---"Artifacts". Instead of proprietary LLMs, you can now use fully LOCAL and PRIVATE LLM via ollama to build apps! Here I use Qwen 2.5 32B to build a game of life app.show more

We’re launching Optima. Now anyone can create a custom... benchmark for their use case, leveraging Artificial Analysis’ leading research and platform Building and running benchmarks is difficult. We have distilled Artificial Analysis’ research and experience developing benchmarks into Optima, a new platform for benchmarking models on your own workloads and comparing performance, speed and cost efficiency. Optima allows you to find the best model for your task, or an equally performant alternative to your current setup at 10x lower cost or time per task. We’ve integrated Artificial Analysis' research and experience in benchmarks across the Optima workflow: ➤ Build benchmarks based on your own data and use cases: There are three ways to build a benchmark with Optima. Upload an existing evaluation dataset from your own files or Hugging Face, or import agent traces from platforms including Arize AI, Braintrust and langfuse.com. Install the Optima skill to build a benchmark using context from your coding environment and previous sessions. Or simply describe your use case and provide example inputs and outputs, and Optima will build the benchmark for you ➤ Run across the latest models: Run the same benchmark across leading models in a single click, and keep your leaderboard up to date as soon as new models are released ➤ Bring Artificial Analysis grading to your own benchmark: Evaluate responses against objective rubric criteria or using the same pairwise judging approach used for Artificial Analysis benchmarks including GDPval-AA and AA-Briefcase. For pairwise judging, select your preferred responses from a sample and Optima uses those preferences to rank models across your test set ➤ Compare performance, cost and time efficiency: Optima measures more than model performance. Cost per Task and Time per Task are tracked alongside benchmark scores, with category-level results and support for custom metrics, allowing you to compare the tradeoffs between models for your specific use case Ahead of launch, here are examples questions our beta testers answered with Optima: ➤ Which model can save me 10x the cost without a meaningful decrease in quality for my finance & accounting agent? ➤ Which model best matches the writing style of lawyers for my legal agent? ➤ Which model can best identify different elements in my custom image dataset? Optima is available today. Build your own benchmark atshow more

Today we're launching a new way to build apps... in AI Studio! 🚀 - Build directly in AI Studio and leverage Gemini without a key, for free! - Browse new sample apps that you can remix and make your own - Share with friends Check out the open source apps below, more to come!show more

Last week we launched Optima, a new platform for... benchmarking models on your own workloads and comparing performance, speed and cost efficiency Watch our new video walkthrough to see how to build and run your own benchmark with Optima, and find the best model for your use case Start building your benchmark today atshow more

Our Llama-3.1-Nemotron-70B-Instruct model is a leading model on the... 🏆 Arena Hard benchmark (85) from Arena. Arena Hard uses a data pipeline to build high-quality benchmarks from live data in Chatbot Arena, and is known for its predictive ability of Chatbot Arena Elo score as well as separability between helpful and less helpful models. Use our customized model Llama-3.1-Nemotron-70B to improve the helpfulness of LLM generated responses in your applications. 📥 Try on our API catalog: 📥 On GitHub: 📥 Or on Hugging Face:show more

New skill: /improve-animations Inspired by shadcn’s improve skill I... made one specifically for animations. Use your most capable model to audit animations in your project and hand the execution to cheaper models. Fable is available through July 12, so make good use out of it!show more

New short course on Reinforcement Learning from Human Feedback!... RLHF is one of the key techniques that led to the rise of modern LLMs. It is used to align LLMs with human preferences, to make them more honest, helpful and harmless, by (i) learning a reward function that mimics human preferences, as expressed in human-provided labels, then, (ii) tuning an LLM to generate outputs that receive a high reward. In this course, taught by Nikita Namjoshi, Developer Advocate for GenAI at Google Cloud, you'll learn the details of how RLHF works, including how to apply it to tune an LLM for your own applications. You'll also use an open source library to tune a base LLM to align with human preferences expressed in a training set, and evaluate the tuned model by comparing its responses before and after RLHF-tuning. Please sign up here!show more

Let's build a dashboard to evaluate and monitor your... Agentic and RAG apps! . . In this video, I'll guide you through creating an evaluation and observability pipeline for your AI apps using a 100% open-source tool! Tech Stack: - Comet's Opik to eval and monitor - LlamaIndex to build a RAG pipeline - Ragas for synthetic datagen You'll learn: - Setting up Opik - Building a RAG pipeline - Creating an eval dataset - Evaluating the RAG pipeline - Monitoring all activities during the process It's a hands on demo with code and step-by-step guide to do everything listed above. CometML's Opik is fully open-source, offering the most Pythonic and easiest way to monitor LLM apps. I have shared link to their repo in next tweet!show more