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
Anyscale
Software Development
San Francisco, California 24,687 followers
Scalable compute for AI and Python
About us
Scalable compute for AI and Python Anyscale enables developers of all skill levels to easily build applications that run at any scale, from a laptop to a data center.
- Website
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https://anyscale.com
External link for Anyscale
- Industry
- Software Development
- Company size
- 51-200 employees
- Headquarters
- San Francisco, California
- Type
- Privately Held
- Founded
- 2019
Products
Anyscale
AIOps Platforms
The Anyscale Platform offers key advantages over Ray open source. It provides a seamless user experience for developers and AI teams to speed development, and deploy AI/ML workloads at scale. Companies using Anyscale benefit from rapid time-to-market and faster iterations across the entire AI lifecycle.
Locations
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Primary
San Francisco, California 94105, US
Employees at Anyscale
Updates
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The 2nd annual #TiDB Future App Hackathon is here! 🎉 You can register now at https://lnkd.in/giW4gJx9 This year's event features more than $30k in prizes and you will have an opportunity to build an amazing #ai application with the new TiDB #vectorsearch. Don't miss out on this incredible opportunity to push the boundaries of what's possible! A huge thank you to our sponsors: Amazon Web Services (AWS), Anyscale, Dify, Jina AI, Lepton AI, LlamaIndex, and NPi AI
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🚀 Follow along this week as we highlight some of the features we shipped over the past quarter! Up first: Anyscale Replica Compaction. Anyscale’s Replica Compaction optimizes resource scheduling in Ray Serve, solving resource fragmentation and enhancing efficiency. Why it matters: Resource fragmentation happens when scaling leads to uneven utilization across nodes. As traffic decreases, previously needed nodes become underutilized, leading to increased cost and poor efficiency. Ray Serve scales each model independently, leading to this issue. Solution: Replica Compaction automatically migrates replicas into fewer nodes, optimizing resource use and reducing costs with zero downtime. Results: On an Anyscale Service with multiple LLMs (Mistral, Mixtral, Llama3), efficiency increased by 10.7% (measured by Tokens / GPU Second). We found instance seconds declined by 3.7% despite an 11.2% traffic increase. Learn more in our blog: https://lnkd.in/e5WjVSFH Get started today: https://bit.ly/3Y6qHrx
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It was great to see everyone at the Ray in Financial Services Meetup in New York 🏙 A big thank you to all the community members who made it possible. 👏 We discussed Ray and it's use cases, got a hands on look at running parallel experiments with cpus and gpus, and shared more on the upcoming roadmap. Looking forward to our next meetup - training day in New York this July 31st! Register here:https://lnkd.in/ePbX2KYs
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Join us on 7/25 for a conversation with our CEO, Krishna Gade, and Anyscale CEO, Robert Nishihara, on Productionizing GenAI at Scale. Enterprises are harnessing the full potential of #GenAI across various facets of their operations for enhancing productivity, driving innovation, and gaining a competitive edge. However, scaling production GenAI deployments can be challenging due to the need for evolving #AI infrastructure, approaches, and processes that can support advanced GenAI use cases. Attend this #AIExplained to learn: 🔷 Challenges in reliability issues in backend and frontend systems affecting GenAI production environments 🔷 Insights into the AI infrastructure necessary for enterprise-scale GenAI deployments 🔷 Emerging practices in productionizing GenAI, including #multimodal AI advancements 📅 Register now: https://lnkd.in/gA8HuUnR
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Mira Murati, CTO of OpenAI, will be a keynote speaker for Ray Summit 2024! 🎉 Known for her work on ChatGPT, DALL-E, and GPT-4, Mira advocates for ethical AI aligned with human values. Join us and learn from her groundbreaking work and vision for the future of AI 🚀 Register here: https://t.co/VTdE4cbXB9
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We’ve recently contributed FP8 support to vLLM in collaboration with Neural Magic -- with this feature, you can see up to a 1.8x reduction in inter-token latency, with >99% accuracy preservation! A common concern with FP8 is whether users will experience accuracy degradation. To address this, Neural Magic has produced many checkpoints for key models with >99% accuracy preservation across a wide range of benchmarks (https://lnkd.in/gTimN5dZ), including: - Llama3-70b - Mixtral 8x7b - Llama3-8b You can easily try this out on vLLM, and read more about the feature here -- https://lnkd.in/gzKJqerB
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🌟 It's not too late! 🌟 Join us tonight, July 9th, from 5:30 - 8:30pm in NYC for the Ray in Financial Services Meetup. Don’t miss out on discovering how Ray powers AI in finance and networking with industry peers Sign up here: https://lu.ma/vrlylh28 We hope to see you there!
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🚨Last chance!🚨 Tomorrow, July 9th, 5:30 - 8:30pm in NYC, join the Ray in Financial Services Meetup. Discover how Ray powers AI in finance, explore AI-driven use cases, get insights into the Ray 3.0 roadmap, and network with industry peers🤝 Minimal spots left, sign up here: https://lu.ma/vrlylh28
Ray in Financial Services · Luma
lu.ma
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Harrison Chase will be speaking at this year's #RaySummit! 🙌 Learn more about building LLM applications including agentic applications from the cofounder of LangChain, the open-source framework and toolkit helping developers innovate. 🚀 Register Today: https://lnkd.in/gmpMH_Wi
Anyscale | Ray Summit 2024
raysummit.anyscale.com