ray @raydistributed
The AI framework trusted by OpenAI, Uber, and Airbnb. Created and developed by @anyscalecompute. docs.ray.io Joined August 2019-
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Ray Summit Training Day is back Nov 3 in SF š One full day. Six expert-led sessions. Built for engineers who want to go deeper with Ray. ā” Seats go fastālast year we had a waitlist. š Register now: na2.hubs.ly/H01jJPq0
At Ray Summit 2025, @amog Kamsetty @character_ai will walk through Rayman, their open-sourceāfirst post-training stack that powers rapid iteration on models serving tens of millions of users. Hereās what will be covered: - SFT and distillation at scale with Ray Data, Rayā¦
šØ THIS WEEK šØ In-person Ray Meetup on Multimodal Data + AI at our Anyscale HQ Learn how Ray Data + Anyscale power pipelines across text, image, audio & video ā from dev ā prod. š Sept 25, 5:30 PM | š 600 Harrison St Seats are almost full ā luma.com/hoy3vilo
Itās time you attended a conference led by teams running AI in production ā not marketing teams masquerading as engineers. If you think such a conference doesnāt exist, you havenāt been to Ray Summit š Itās the place to be for developers who care about what actually ships. Areā¦
Did you know you can add training to your Ray Summit 2025 conference pass? Ray Summit Training Day is a separate day of hands-on Ray learning, taught by our experts. Save your seat before itās too late ā anyscale.com/ray-summit/202ā¦ #RaySummit
ā”Bangalore Ray Community ā join our in-person meetup on Sept 26 with @InMobi! ā” Connect with industry peers and learn how Ray powers large scale AI & ML workloads. Agenda: ā¢ Internals of tasks, actors, and objects (Anyscale Team) ā¢ Scaling DNN training with Ray at InMobiā¦
Scaling multimodal AI ā across text, images, audio, and video ā is complex. At our next in-person Ray Meetup, youāll see how Ray Data and Anyscale make it easier to take workloads from dev to prod. Talks and Demos: š¹ Ray Data: streaming + fault-tolerant pipelines š¹ Anyscaleā¦
šØ Virtual Hands on Lab Alert šØ Seats are almost gone for our live Ray hands-on lab. Code alongside our instructor and see how Ray scales AI in production. In this interactive session, youāll learn how to: ā¢ Build distributed data pipelines ā¢ Run efficient batch inferenceā¦
šØAttention India Ray Community ā Ray Meetup in Bangalore, Sept 26šØ Ray isnāt just powering research - itās running large-scale AI systems in production. At the upcoming Ray Meetup with InMobi, practitioners will go deep on: The internals of tasks, actors, and objects in Rayā¦
šØWebinar AlertšØ Batch inference bottlenecks = idle GPUs + wasted resources. Join us live tomorrow (Sept 17) to see how Ray syncs CPU & GPU for faster, smoother distributed Python workloads. Save your spot š linkedin.com/events/7366213ā¦
Itās time you attended a conference led by teams running AI in production ā not marketing teams masquerading as engineers. If you think such a conference doesnāt exist, you havenāt been to Ray Summit š Itās the place to be for developers who care about what actually ships. Areā¦
New feature for Ray Serve users! We are excited to announce support for custom request routing and a prefix-aware request router in Ray 2.49 - making LLM serving faster and more efficient. On benchmark workload we see: ā” 60% reduction in time-to-first-token (TTFT) ā” 40%+ā¦
New feature for Ray Serve users! We are excited to announce support for custom request routing and a prefix-aware request router in Ray 2.49 - making LLM serving faster and more efficient. On benchmark workload we see: ā” 60% reduction in time-to-first-token (TTFT) ā” 40%+ā¦
Have you signed up for Ray Summit Training Day? Itās a full day of hands-on training taught by Ray experts. Training fills up first every year, and last year, we had a waiting list. Sign up today before training sells out ā anyscale.com/ray-summit/202ā¦
Excited to host our next in-person Ray Meetup: Multimodal Data + AI at Anyscale HQ in SF! Weāll discuss how to scale multimodal workloadsātext, images, audio, video ā with Ray Data for high-throughput, GPU-efficient processing (with streaming execution + fault tolerance) andā¦
Scaling batch inference is tricky āĀ especially when CPU preprocessing and GPU model execution fall out of sync. The result? Bottlenecks, idle GPUs, and wasted compute. On September 17, join us live to see how Rayās open-source framework streamlines CPUāGPU coordination forā¦
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