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Conferences / Ray Summit

Ray Summit 2026

Aug 24–26, 2026 · San Francisco Marriott Marquis, San Francisco, CA, United States

Conference
Ray Summit Vendor & industry
Dates
Aug 24, 2026 – Aug 26, 2026
Venue
San Francisco Marriott Marquis
Place
San Francisco, CA, United States
Format
In person
Status
Past
Attendance
—
Site says only 'Three days. Hundreds of AI builders.' An aggregator's '3,000+ expected' figure is not used.
Website
anyscale.com
Recorded
24 sponsors · 21 speaker appearances
Notes
Training day 24 Aug, summit 25-26 Aug; co-located with the first vLLM Conference (hosted by Inferact), included in the Ray Summit pass. Registration via the Linux Foundation. Speakers: keynotes and featured session speakers only, from the event-week home page (full agenda in a JS-only LF session catalogue, not checked); affiliations from logo alt text (Krishna Toshniwal 'latitude', Volodymyr Kuleshov 'Inception lab', Shaowei Su 'MAI' as shown). Gold tier: one logo is labelled 'Nebius' twice; the second uses a Lila logo file and is recorded as Lila. No 2027 edition announced as of Nov 2026.

Ticket prices

TicketPriceValid untilNotesSource
Summit Pass (Day 1 + Day 2, incl. vLLM Conference)$400—Price shown on event-week page.web.archive.org
Summit + Training Pass$450—web.archive.org
Bundle Promo (5 passes, summit + training)$750—Shown as '$2250 $750' (struck-through list price).web.archive.org

Sponsors 24

Speakers and talks 21

SpeakerCompanyRoleTalkLinks
Andrew BeamLila SciencesKeynote——
Bryan CatanzaroNVIDIAKeynote——
Elvis NavamimicKeynote——
Felix HeideTorc RoboticsKeynote——
Ion StoicaAnyscaleKeynote——
Josh PayneNscaleKeynote——
Keerti MelkoteAnyscaleKeynote——
Liam FedusPeriodic LabsKeynote——
Robert NishiharaAnyscaleKeynote——
Simon MoInferactKeynote——
Vincent GonguetBedrockKeynote——
Aamir AnwarSpotifyFeaturedRay in Production: Engineering Lessons from Spotify's Hendrix Framework for Training LLMs—
Aleksandar DjuricRecursionFeaturedBuilding a Virtual Biology Platform on Ray: Multimodal AI Across Hybrid Anyscale at Recursion—
Andrew DaiElorianFeaturedWhy Current AI Cannot Truly See the World—
Edward HuMercorFeaturedTraining Frontier Knowledge Work Agents: A 397B Open Recipe with SkyRL—
Hanna van der VlisAdyenFeaturedTrillion-Token Pretraining: Building a Tabular Foundation Model for Payments—
Jack LiAppleFeaturedApple Maps on Ray: Batch Inference and LLM Evaluation at Scale—
Krishna ToshniwalLatitudeFeaturedPerformant Training for All Workstreams—
Serrana AguirregarayDiscordFeaturedScaling Machine Learning at Discord: Our Journey with Ray and Anyscale—
Shaowei SuMAIFeaturedRay and MAI-Thinking-1—
Volodymyr KuleshovInception LabsFeaturedDiffusion Large Language Models: Redefining the Token Efficiency Frontier—

Sources