Anyscale

Excited to announce Brandon Leonardo, Co-founder of Instacart, as a keynote speaker at Ray Summit! Brandon will share insights on scaling tech, AI innovations, and building resilient systems. Don’t miss this chance to learn from a leading tech mind! Sign up here: https://lnkd.in/gWTKRzwc

🚀 See how Handshake cut their LLM GPU costs by 50% with Anyscale. Discover how they: 💰 Reduced LLM GPU costs by 50% or more. 📈 Seamlessly scaled large language models (LLMs) without compromising performance. ⏱ Enhanced operational efficiency, enabling faster development cycles. Check out the full story here: https://lnkd.in/gSiKJDaY

🚀 Have you seen the Anyscale newsletter? Get the scoop on new features, products, & webinars. What's new in July: 🟢Ray Summit 2024: Join us September 30 - October 2, with speakers from OpenAI and Meta. 🟢Community Spotlight: See how Pinterest, Dreamfold, and SewerAI are leveraging Ray and Anyscale. 🟢Product Updates: Explore new features like cost-saving replica compaction, new user interface, and enhanced elastic training. And much more! See how companies are tackling AI challenges with Anyscale & Ray, plus stay up-to-date with all things AI 🙌 Read more here: https://lnkd.in/g5gYc7K9

💥 Another feature update💥 Excited to announce Anyscale Job Queues Job Queues deliver improved utilization and simplified cluster management by running multiple concurrent jobs on a single cluster. • Users submit jobs to a specified queue, Anyscale automatically prioritizes and schedules them. • Jobs are executed based on their queue position, with limits on concurrent jobs per cluster. • Jobs run to completion, including retries, repeating until all jobs in the queue are completed or errored. Read full details here: https://lnkd.in/g3VfuApt And watch how it works below:

🚀 Exciting news! Anyscale and MongoDB are empowering enterprises to build, deploy, and scale AI-enriched applications with the launch of the MongoDB AI Applications Program (MAAP.) We’re thrilled to be part of this ecosystem and to help enterprises take advantage of AI. hashtag #MAAPLaunch

📣 Meta-Llama-3.1-405B is now available on Anyscale! 📣 Get started and deploy yourself here: https://lnkd.in/gfywap9J

🚀 Excited to announce Elastic Distributed Training is now on Anyscale! 🔍 With Elastic Training, you’ll see up to 60% lower cloud costs using spot instances and faster training with uninterrupted progress, even as computational resources come and go during training. Elastic training adjusts to dynamic computational resources during the training process. Training can recover from spot instances preemptions and hardware failures. Instead of waiting potentially hours for a fixed number of GPUs to be available, training can continue on the resources that are already available. ⚒ You can try this out on Anyscale with minimal code changes. This includes a simple one line code change to specify (min_workers, max_workers) as a tuple instead of a fixed worker group size and adding checkpointing. Read more in our announcement: https://lnkd.in/gK64MEiS

Introducing the Anyscale LLM Router template. This notebook helps you build your own LLM Router to optimize LLM applications and save up to 2X on LLM applications. The LLM router dynamically sends queries to the most cost-efficient LLM while maintaining quality and latency. In Gen AI and LLMs, model size, quality, inference speed, and cost vary widely. Some models can be 200X more expensive than others. Using a single model can lead to expensive queries or low-quality responses. LLM Routing ensures you get the best balance of cost and performance. With the template, you can easily start training your own LLM Router and optimize your LLM Applications to reduce costs. Click to learn more: https://lnkd.in/gZK73Z8s Let us know your results 👇

We’ve recently introduced the Anyscale Unified Log Viewer, which simplifies and streamlines the debugging and optimization of distributed Ray applications! Key features include: • Structured logging with actor, instance, and request attributes for effective searching across the cluster • UI and log persistence • Comprehensive search and filtering capabilities • Scalable to 100s of GB of logs and thousands of nodes Check out the video: https://lnkd.in/gwr5hsTf  🛠️ To get started, log in to Anyscale, run your Ray application, and navigate to the new log viewing section in your dashboard. Start debugging and optimizing with ease! 🌟 Read more in our announcement: https://lnkd.in/gpbEvr2h

Python's default logging library has a lot of advantages, but logs are often very unstructured, which adds complexity for downstream parsing, querying, managing, and exporting. We're excited to announce Structured Logging is now available on Anyscale. Logs are now in machine-readable JSON format, simplifying filtering, searching, and analyzing. No more messy text logs and writing regex to debug. Read more in our announcement: https://lnkd.in/gUt9e7sV Try on Anyscale: https://bit.ly/3Y2BnHJ