| Feb. 2020 |
Ray Meetup, Jan 30, 2020, San Francisco: Three Talks |
fABgQ5hA4qI |
| Feb. 2020 |
Fast Scheduling using Ray's Python API (0.8) by Edward Oakes |
uwmAKk49oKY |
| Apr. 2020 |
Ray Community and the Ray Ecosystem |
M37hMsBcBnY |
| May. 2020 |
Decision-Making Side of Machine Learning by Michael I. Jordan |
B1f6UJlHxp0 |
| May. 2020 |
Ray Summit Connect, May 2020 - Q&A and Panel Discussion |
cIgc52qrqsk |
| May. 2020 |
Ray Summit Connect, May 2020 - Ion Stoica |
dl29iiRIBT8 |
| Jun. 2020 |
Enterprise Applications of Reinforcement Learning |
Ba06FzqFLNI |
| Jun. 2020 |
Ray Summit Connect, June 2020: Liam Li |
dZ2R2WoiPUA |
| Jun. 2020 |
Ray Summit Connect, June 2020: Meghana Ravikumar |
PT081ycB7Bs |
| Jun. 2020 |
Ray Summit Connect, June 2020: Panel Discussion |
UkpadfEizd8 |
| Jun. 2020 |
Ray Summit Connect, June 2020: Introduction and Richard Liaw |
PV2x1bsFwUU |
| Jul. 2020 |
Ray Summit Connect, July 2020: Anna Luo |
FRAiQxFxsng |
| Jul. 2020 |
Ray Summit Connect, July 2020: Q&A Panel Discussion |
t52LbnbQOAg |
| Jul. 2020 |
Ray Summit Connect, July 2020: Max Pumperla |
6g2k8NLNlvM |
| Jul. 2020 |
Ray Summit Connect, July 2020: Eric Liang |
W0TtPMcA3ck |
| Aug. 2020 |
PyBay 2020 - Anyscale Sponsorship Video |
bypJMOljqZQ |
| Aug. 2020 |
Ray Summit Connect, August 12, 2020 - Q&A |
TASDn66SddE |
| Aug. 2020 |
Ray Summit Connect, August 12, 2020 - Simon Mo |
c1Vo98aPWWo |
| Aug. 2020 |
Ray Summit Connect, August 12, 2020 - Ding Ding |
mhvY6elLtO0 |
| Aug. 2020 |
Ray Summit Connect, August 12, 2020 - Qingqing Mao |
FQ6ZfYcWJ-8 |
| Sep. 2020 |
Five Key Features for a Machine Learning Platform |
JpYEBVIje44 |
| Sep. 2020 |
Keynote: Anyscale Product Demo - Edward Oakes, Software Engineer, Anyscale |
8GTd8Y_JGTQ |
| Oct. 2020 |
AI In Production Key Challenges and Use Cases - Jonathan Berte Robovision |
jLHs3N2sdVg |
| Oct. 2020 |
Easy Access to SOTA NLP Models with Ray and Hugging Face - Thomas Wolf, Hugging Face |
u6st0oMvhfU |
| Oct. 2020 |
Leveraging Ray to Enhance Machine Learning Models in Finance - James Dunworth-Crompton Goldman Sachs |
c-1XT8S5hh0 |
| Oct. 2020 |
Ray Internals: A Peek at `ray.get` - Stephanie Wang, Anyscale |
a1kNnQu6vGw |
| Oct. 2020 |
Ray + Arize - Why you Need Model Observability - Aparna Dhinakaran, Arize AI |
1RYhjfOgRlQ |
| Oct. 2020 |
Project Zouwu: Scalable AutoML for Telco Time Series Analysis using Ray and Analytics Zoo- Ding Ding |
TQq7f_wgaMY |
| Oct. 2020 |
Keynote: The Future of Ray - Robert Nishihara, Anyscale |
bRMZ0AMssSE |
| Oct. 2020 |
Keynote: AlphaStar: How Google Infrastructure Made it Possible - Oriol Vinyals, Principal Scientist |
W-rIUmLbRk0 |
| Oct. 2020 |
Keynote: Scalable Python We Can Afford - Wes McKinney, Founder, Ursa Labs |
TflnJKLRj-M |
| Oct. 2020 |
Introducing Ray Serve: Scalable and Programmable ML Serving Framework - Simon Mo, Anyscale |
gV4YS4e1CXg |
| Oct. 2020 |
Adopting Ray @ LinkedIn - Jonathan Hung & Nitin Pasumarthy, LinkedIn |
0Z0Th9ySIfs |
| Oct. 2020 |
Building Complex Data Analytics Pipelines with Ray - Qingqing Mao, Dascena |
BHxqB7aDQ2U |
| Oct. 2020 |
The Java API and Cross Language Programming on Ray - Hao Chen, Ant Group |
AFHyIEIfQYw |
| Oct. 2020 |
What's New with Ray Libraries: Tune - Richard Liaw, Anyscale |
t94gNPREZUc |
| Oct. 2020 |
Advanced Ray RLlib: New Features and New Possibilities - Sven Mika, Anyscale |
Cc5IZrC_7Ok |
| Oct. 2020 |
Turbocharging State-of-the-art Natural Language Processing on Ray - David Talby, John Snow Labs |
fvdJRSQMtoc |
| Oct. 2020 |
Keynote: Machine Learning & A.I. At Uber - Zoubin Ghahramani, Chief Scientist & VP |
4XTv5qgugCk |
| Oct. 2020 |
AlphaDow: Reinforcement Learning for Industrial Production Scheduling - Adam Kelloway, Dow Chemical |
DQm3e7mMBt4 |
| Oct. 2020 |
Keynote : Modern App Development - Adrian Cockcroft, VP Cloud Architecture Strategy, AWS |
wYCLbLrEoqs |
| Oct. 2020 |
RLlib: Scalable RL for TensorFlow, PyTorch, and Beyond - Eric Liang, Anyscale |
FxW5egRmD3Y |
| Oct. 2020 |
Project Bonsai: How Microsoft is Using Ray and RLlib Inside a Machine Teaching Service |
yRowxgcrt_Q |
| Oct. 2020 |
Debugging and Observability for Distributed Ray Applications - SangBin Cho, Anyscale |
MHPDsuEiinw |
| Oct. 2020 |
Dask-on-Ray: Using Dask and Ray to Analyze Petabytes of Remote Sensing Data - Clark Zinzow |
kZCmqnBrUp4 |
| Oct. 2020 |
Keynote: AI for Financial Services - Manuela Veloso, Head of AI Research, J.P. Morgan |
tnmyBOUcaH8 |
| Oct. 2020 |
Keynote: Easier Machine Learning Thoughts From Scikit-Learn - Gaël Varoquaux, Research Director |
1s8RzWwMdqg |
| Oct. 2020 |
Using Ray On Large-scale Applications at Ant Group - Jiaying Zhou, Ant Group |
DN7Kg2gXn0k |
| Oct. 2020 |
Distributed Reinforcement Learning for Robotic Assembly - Rodger Luo, Autodesk Research |
FWIkJoKY8DA |
| Oct. 2020 |
Hyperparameter Tuning and Visualization in Deep Learning - Lukas Biewald, Weights & Biases |
2QX6jjMt1Eg |
| Oct. 2020 |
Keynote: Every Five Decades: A New Field of Engineering - Michael I. Jordan, Distinguished Professor |
ILhQvlFVKSA |
| Oct. 2020 |
Keynote: Artificial Innovation Accelerates Artificial Intelligence - David Patterson, Professor |
few75NRPDBs |
| Oct. 2020 |
Keynote: ML for Systems and Chip Design - Azalia Mirhoseini, Senior Research Scientist, Google Brain |
LQoFQ2AL9z4 |
| Oct. 2020 |
Information Gain Regulation in Reinforcement Learning with the Digital... - Géza Szabó & József Pető |
rY274PUS-pw |
| Oct. 2020 |
Keynote: Programming the Cloud as Easily as Your Laptop - Ion Stoica, Executive Chairman, Anyscale |
A1_-9S5dsgU |
| Oct. 2020 |
State Management in Distributed Online Learning with Ray - Edmon Begoli |
f1rGqAfgtI0 |
| Oct. 2020 |
Building a Python Web Service with Ray - Philipp Moritz, Anyscale |
A1dB-4FdFgQ |
| Oct. 2020 |
Keynote: A Secure Collaborative Learning Platform - Raluca Ada Popa, Computer Security Professor |
4kvTh4JIxp8 |
| Oct. 2020 |
Keynote: Building a Fusion Engine with Ray - Dr. Charles He, Chief Architect of Storage and Compute |
Wwv9YNlXx0Q |
| Oct. 2020 |
Ray: A General Purpose Serverless Substrate? - Eric Liang, Anyscale |
vzMXTpdJSuk |
| Oct. 2020 |
EfficientBERT: Trading off Model Size and Performance - Meghana Ravikumar, SigOpt |
luOceBSzcBc |
| Oct. 2020 |
Connecting Reinforcement Learning to Simulation Software - Max Pumperla, Pathmind |
U9deXfKYDSs |
| Oct. 2020 |
Data Scientists are More Valuable than Hardware: The Design of Modin - Devin Petersohn, Intel |
9XsQuJiZeoA |
| Oct. 2020 |
Distributed Deep Learning with Horovod on Ray - Travis Addair, Uber |
rEB3NPUoxMM |
| Oct. 2020 |
Cloudstate—Towards Stateful Serverless - Jonas Bonér & James Roper, Lightbend |
fFein01olEA |
| Oct. 2020 |
ML Engineering Kubeflow - Pavel Dournov, Google Cloud |
TXoUn9oLvlU |
| Oct. 2020 |
Distributed Black-Box Model Explanation with Ray - Alexandru Coca, Seldon |
Y7UoIQqFxE0 |
| Oct. 2020 |
Utilizing Reinforcement Learning Techniques for Supply Chain with Amazon SageMaker - Anna Luo, AWS |
i53rl7u_NhI |
| Nov. 2020 |
Anyscale Connect: Population Based Training with Ray Tune |
iBVveUT72jU |
| Dec. 2020 |
Anyscale Connect: Encrypting and Tabulating Big Elections (Dan Wallach, Rice University/VotingWorks) |
m7r33EuN6Zw |
| Jan. 2021 |
AI use cases in Industrial Operations and Supply Chain by Chris Nicholson (Pathmind) |
n4erTp67b_0 |
| Jan. 2021 |
A Glimpse into the Ray Autoscaler by Ameer Haj Ali |
BJ06eJasdu4 |
| Feb. 2021 |
Transforming Medicine - Machine Learning Takeover by Dr. Roger Ng (Care Protocol) |
Kd6262ymAkM |
| Mar. 2021 |
Seamlessly Scaling your ML Pipelines with Ray Serve - Archit Kulkarni |
DqgwRAKhIUs |
| Jul. 2021 |
[Opening Keynote] Anyscale Demo: Machine Learning Application from Dev to Prod |
ZYaumfW_ofw |
| Jul. 2021 |
[Opening Keynote] State of Ray |
OSdFnBfDwT0 |
| Jul. 2021 |
[Opening Keynote] Making Distributed Computing Easy |
dn8hu2sgRWU |
| Aug. 2021 |
Achieving Scalability and Interactivity with Ray Serve |
RLyt8RKF7II |
| Aug. 2021 |
Fusion Computing at Ant Group |
9suhqGZCYP8 |
| Sep. 2021 |
Ray Serve: Patterns of ML Models in Production |
mM4hJLelzSw |
| Nov. 2021 |
Human-in-the-Loop Reinforcement Learning |
LEzdi-eJR8k |
| Nov. 2021 |
DeepCoMP: Multi-agent Reinforcement Learning for Multi-cell Selection in 5G and Beyond |
Qy4SzJKXlGE |
| Nov. 2021 |
How Ray and Anyscale Make it Easy to do Massive-scale ML on Aerial Imagery |
3fMY1yj05dc |
| Nov. 2021 |
Distributed XGBoost on Ray |
N49_mRCm4_4 |
| Nov. 2021 |
Data Processing on Ray |
G8Di0d1_XDg |
| Nov. 2021 |
Offline RL with RLlib |
lhcCotAsgHg |
| Nov. 2021 |
W&B Tables and Ray |
N-yHXpD6y88 |
| Nov. 2021 |
End-to-End AutoML with Ludwig on Ray |
nV3uWgmGjvY |
| Nov. 2021 |
Ray Internals: Object Management with the Ownership Model |
1oSBxTayfJc |
| Nov. 2021 |
Panel: ML Platform on Ray |
_L0lsShbKaY |
| Nov. 2021 |
Ray and Anyscale: An Optimization Journey |
3AjdwwMwAF8 |
| Nov. 2021 |
Building High Availability and Scalability Online Computing Applications on Ray |
47RTYT_6HAY |
| Nov. 2021 |
Scaling Interactive Data Science with Modin and Ray |
ycSf1IbBGWk |
| Nov. 2021 |
Application of Online Resource Allocation Based on Ray |
IxTyDuabd_s |
| Nov. 2021 |
Petabyte Scale Datalake Table Management with Ray, Arrow, Parquet, and S3 |
h7svj_oAY14 |
| Nov. 2021 |
Improving Ray for Large-scale Applications |
ft2LACVr9Ao |
| Nov. 2021 |
Detection of Sensitive Personal Data in Large Data Sets Using Ray with Deep Learning |
wiFV6MJ5LTw |
| Nov. 2021 |
Mobile Order Click-Through Rate (CTR) Recommendation with Ray on Apache Spark at Burger King |
S9D21Sngwpk |
| Nov. 2021 |
Lessons from the Kubernetes Adventure |
y3EraJvSl0g |
| Nov. 2021 |
The Quick Journey to Using Ray: How We Implement Ray and Anyscale to Speed up our ML Processes |
e_tWFyym69w |
| Nov. 2021 |
Neural MMO: Building a Massively Multiagent Research Platform with Ray and RLlib |
9V6EvSEMREg |
| Nov. 2021 |
Per-epoch Shuffling Data Loader: Mix It Up As You Train! |
jbYAfehBg64 |
| Nov. 2021 |
A 24x Speedup for Reinforcement Learning with RLlib + Ray |
ezCJQscPuGE |
| Nov. 2021 |
Using Reinforcement Learning to Optimize IAP Offer Recommendations in Mobile Games |
cGQk8rIoc1Y |
| Nov. 2021 |
Simplify Big Data & AI on Spark and Ray with MLSQL |
SJ9CaFbfpM0 |
| Nov. 2021 |
Data Science at Scale: From Notebook to Production with Airflow and Ray |
MM3vzZnEP8g |
| Nov. 2021 |
Using RLLib in an Enterprise Scale Reinforcement Learning Solution |
0uLsAUupp0w |
| Nov. 2021 |
Large Scale Data Loading and Data Preprocessing with Ray |
5XCUJEtv50M |
| Nov. 2021 |
Mars-on-Ray: Accelerating Large-scale Tensor and DataFrame Workloads |
DnwZqjrn2EQ |
| Nov. 2021 |
A Deep Dive into Ray’s Scheduling Policy |
EJUYKXWGzfI |
| Nov. 2021 |
Introducing Amazon SageMaker Kubeflow Reinforcement Learning Pipelines for Robotics |
stnR_zCzjdU |
| Nov. 2021 |
NumS: Scalable Array Programming for the Cloud |
S6Wl0lOnhso |
| Nov. 2021 |
The Journey from AI to Bedside: Translating Academic Research to Serving Patients Using Ray |
xnInmBAKOa8 |
| Nov. 2021 |
Powering Open Data Hub with Ray |
0SRk5lfaYYE |
| Nov. 2021 |
Scaling and Unifying SciKit Learn and Spark Pipelines using Ray |
L7ZmnFV8fzc |
| Nov. 2021 |
Machine Learning and Microbiology in the Cloud Through Ray |
alr9LWPOa64 |
| Nov. 2021 |
Cloud Computing Made Better: An AWS View on Serverless Computing |
dkQ8eat_IlY |
| Nov. 2021 |
JAX: Accelerated Machine Learning Research via Composable Function Transformations in Python |
hyQ-tgD5sgc |
| Nov. 2021 |
Software 2.0 Needs Data 2.0: A New Way of Storing and Managing Data for Efficient Deep Learning |
etMEAlCztC8 |
| Nov. 2021 |
Anomaly Detection on Remote Sensing with Ray + Horovod |
nox9R0dK0E8 |
| Nov. 2021 |
Towards Building a Responsible Data Economy |
_BrPQB4GqmI |
| Nov. 2021 |
How Smart is the ECG? Lessons from Advanced ECG Analytics |
_giUXD3L724 |
| Nov. 2021 |
A Growing Ecosystem of Scalable ML Libraries on Ray |
23FpEPyv8FQ |
| Nov. 2021 |
Applying Ray and RLlib to Real-life Industrial Use Cases |
VihUmxaiDhU |
| Nov. 2021 |
Elements of Learning Systems |
u1xHAeqpeIQ |
| Nov. 2021 |
Collective-on-Ray: High-performance Collective Communication for Distributed Machine Learning on Ray |
zhpipOFhr-U |
| Nov. 2021 |
Deeper Dive on Making Boats Fly with AI on Ray |
cLCK13ryTpw |
| Dec. 2021 |
Instantly scale your AI with Ray and Anyscale |
Iu_F_EzQb5o |
| Dec. 2021 |
Anyscale Product Demo |
Q1t9qeDJquI |
| Jan. 2022 |
Ray Meetup is Back in the New Year 2022 |
M3pZDp1zock |
| Mar. 2022 |
[Ray Meetup] Ray Train, PyTorch, TorchX, and distributed deep learning |
e-A93QftCfc |
| Apr. 2022 |
AlphaDow: Leveraging Ray’s ecosystem to train & deploy an RL industrial production scheduling agent |
_TJ3qhW2plQ |
| Apr. 2022 |
Reinforcement learning-based simulation of markets |
Om9A-k29GyE |
| Apr. 2022 |
Keynote - Offline reinforcement learning |
o76FwLvsb3U |
| Apr. 2022 |
Reinforcement learning in the physical world |
jJK2p0RPCdQ |
| Apr. 2022 |
Productionizing ML at scale with Ray Serve |
UtH-CMpmxvI |
| May. 2022 |
RLlib office hours: May 10 |
bj6cIOSWXwQ |
| May. 2022 |
RLlib office hours: May 24 |
49-b8gv6OZk |
| Jun. 2022 |
RLlib Office Hours June 7 |
5Dmvof1_jzU |
| Jun. 2022 |
RLlib office hours: June 21 |
IkAMq6osL4Y |
| Jul. 2022 |
RLlib office hours: July 5 |
vEg7WOkMZRc |
| Jul. 2022 |
RLlib office hours: July 19 |
eB3AcMiZtTQ |
| Aug. 2022 |
RLlib office hours: August 2 |
wCEQAUw3_jU |
| Aug. 2022 |
RLlib office hours: August 16 |
ZcrzzdD09mk |
| Nov. 2022 |
Ray Observability - Present and future |
v_JzurOkdVQ |
| Nov. 2022 |
Scaling Instacart fulfillment ML on Ray |
3t26ucTy0Rs |
| Nov. 2022 |
Scalable training of language models using Ray, JAX, and TPUv4 at Cohere |
For8yLkZP5w |
| Nov. 2022 |
Predibase - A low-code deep learning platform built for scale |
B5v9B5VSI7Q |
| Nov. 2022 |
The Magic of Merlin - Shopify's new machine learning platform |
kbvzvdKH7bc |
| Nov. 2022 |
Ray Summit 2022 - Day 1 Keynote - Fireside Chat: Greg Brockman + Robert Nishihara |
CqiL5QQnN64 |
| Nov. 2022 |
Ray Summit 2022 - Day 2 Keynote - Fireside Chat: Smitha Shyam + Jaikumar Ganesh |
GUxIzOpHfuk |
| Nov. 2022 |
Ray Summit 2022 - Day 1 Keynote - Robert Demo |
IfjGP9jIaQ0 |
| Nov. 2022 |
Ray Summit 2022 - Day 1 Keynote - Ion Stoica |
GzByaMCY-uc |
| Nov. 2022 |
Ray Summit 2022 - Day 1 Keynote - Robert Open |
VY7H8iXqSM8 |
| Nov. 2022 |
How Meta scales distributed training of AI workloads on Ray |
-fV43Bvzrso |
| Nov. 2022 |
How Netflix scales ML workloads and speeds AI innovation on Ray |
GtQjTWGQUHI |
| Nov. 2022 |
How KocDigital scales AI and simplifies AI development and Ops on Ray |
mt-zM9tliYo |
| Nov. 2022 |
How Amazon cuts costs and improves scalability by an order of magnitude with Ray - Patrick Ames |
RNrE7B8WTCU |
| Dec. 2022 |
November '22 Ray Meetup |
N_4pg2iKgBE |
| Jan. 2023 |
January '23 Ray Meetup |
kYfupnqGd-0 |
| Feb. 2023 |
BigDL 2.0- Seamlessly scaling end-to-end AI pipelines at Intel |
ebidMHNmO8E |
| Feb. 2023 |
A cross-platform, cross-tool Ray on Kubernetes deployment |
eQswQMBYnDc |
| Feb. 2023 |
Graphs at scale with Ray, for AI in Manufacturing |
VT5xnsmx0CU |
| Feb. 2023 |
BigDL 2.0- Seamlessly scaling end-to-end AI pipelines |
xdNIsi19GMs |
| Feb. 2023 |
Ray + Weights & Biases: Build and deploy real-world ML models |
SzTCNKUVgIw |
| Feb. 2023 |
Evaluating large language models with Ray in hybrid cloud |
2dQ9hFXgz4U |
| Feb. 2023 |
SkyML: Infra-less machine learning on any cloud |
cN2SX6jPS9A |
| Feb. 2023 |
Operationalizing Ray Serve on Kubernetes |
NekkpRrcAWg |
| Feb. 2023 |
Scaling Training and Batch Inference- A Deep Dive into AIR's Data Processing Engine |
zmoF3lKy520 |
| Feb. 2023 |
Large-scale deep learning to augment production RL workloads at Riot Games |
8EsQkFxWYhU |
| Feb. 2023 |
Cruise.data - A new dataset processing pipeline for Cruise ML |
gj0BqvfX_wI |
| Feb. 2023 |
Production RL and decision-making with RLlib |
WWSr-Xu7Dp4 |
| Feb. 2023 |
Large-scale distributed training with TorchX and Ray |
f-Bwru7TJSc |
| Feb. 2023 |
Large-scale data shuffle in Ray with Exoshuffle |
Fj-nC44HQ2g |
| Feb. 2023 |
How Spotify sped up ML research and prototyping with Ray |
WgWInt6wZts |
| Feb. 2023 |
Gearing up for FIFA 2022 using RLlib-powered traffic control |
e2fmk_aO01k |
| Feb. 2023 |
Ray Summit 2022 - Day 2 Keynote - Anca Dragan |
zX-QTRpSf8w |
| Feb. 2023 |
Ray Summit 2022 - Day 2 Keynote - Dario Gil |
68pYS-x4SHk |
| Feb. 2023 |
Ray Workflow - Durable Ray tasks for efficient, flexible data pipelines |
WAnudkHm9_c |
| Feb. 2023 |
State of Ray Serve in 2.0 |
gBS9fo4YQOE |
| Feb. 2023 |
Alpa - Simple large model training and inference on Ray |
HRo90WL4Znc |
| Feb. 2023 |
Highly available architectures for online serving in Ray |
zjRPu-ykHHI |
| Feb. 2023 |
Ray for distributed mixed integer optimization at Dow |
jAWKkFA6MWo |
| Feb. 2023 |
KubeRay - A Kubernetes Ray clustering solution |
tMEwSAeC1jo |
| Feb. 2023 |
FastCFE- A counterfactual explainer using reinforcement learning |
dqFzpDt5PFY |
| Feb. 2023 |
Wind farm optimization using RL and large-scale simulation |
0RQiuIss-SY |
| Feb. 2023 |
A serverless resilient graph analysis platform built on Ray at ByteDance |
7tMntN9kQbA |
| Feb. 2023 |
Multi-model composition with Ray Serve deployment graphs |
lO335UWNGWY |
| Feb. 2023 |
Scalable feature engineering with Hamilton on Ray at StitchFix |
7KB3AyUbeEY |
| Feb. 2023 |
What's new in RLlib |
DZUiD9SIYUk |
| Feb. 2023 |
Distributed training with Ray on Kubernetes at Lyft |
rowxoxMsJH0 |
| Feb. 2023 |
Zero-copy model loading with Ray and PyTorch |
yIHGKhVXNIs |
| Feb. 2023 |
Hugging Face + Ray AIR |
GhY-krGu7uI |
| Feb. 2023 |
Reducing cost, latency, and manual efforts in hyperparameter tuning at Redicell |
i2t8HwIHejo |
| Feb. 2023 |
Introducing Ray AI Runtime |
73Cui_sGA_A |
| Feb. 2023 |
Running a question-answering system on Ray Serve at Deepset |
tKt5kEDYWYc |
| Feb. 2023 |
Ray Summit 2022 - Day 1 Keynote - Kim Hazelwood |
DYjLcge9z1M |
| Feb. 2023 |
Ray Summit 2022 - Day 1 Keynote - Soumith Chintala |
ImooSx7xHko |
| Feb. 2023 |
Large-scale deep learning training and tuning with Ray at Uber |
gMT_ONmI9RM |
| Feb. 2023 |
Ray Community European Meetup Talks |
tdGvtMv8IiE |
| Mar. 2023 |
Ray Dashboard Walkthrough |
VPksEcjACOM |
| Mar. 2023 |
Ray NYC March 2023 with NYC ML/AI Meetup |
1MpEYlIlu7w |
| Apr. 2023 |
Open Source LLM Search Engine with LangChain on Ray |
v7a8SR-sZpI |
| May. 2023 |
LangChain + Ray Tutorial: How to Generate Embeddings For 33,000 Pages in Under 4 Minutes |
hGnZajytlac |
| May. 2023 |
Reducing Hallucinations in LLMs | Retrieval QA w/ LangChain + Ray + Weights & Biases |
Sy-Xp-sdlh0 |
| May. 2023 |
The Big Problem with LLMs... and how to fix it |
mXD5fq7YiNM |
| May. 2023 |
Ray Dashboard Series: Part Seven | Logs |
8V187F2DsN0 |
| May. 2023 |
Ray Dashboard Series: Part Six | Metrics |
yn5Q65iHAR8 |
| May. 2023 |
Ray Dashboard Series: Part Five | Actors |
MChn6O1ecEQ |
| May. 2023 |
Ray Dashboard Series: Part Four | Cluster |
K2jLoIhlsnY |
| May. 2023 |
Ray Dashboard Series: Part Three | Serve |
eqXfwM641a4 |
| May. 2023 |
Ray Dashboard Series: Part Two | Jobs |
CrpXSSs0uaw |
| May. 2023 |
Ray Dashboard Series: Part One | Overview |
i33b1DYjYRQ |
| May. 2023 |
Introducing Ray Aviary | 🦜🔍 Open Source Multi-LLM Serving |
WmqPfQOXJ-4 |
| Jun. 2023 |
Bay Area Ray June Meetup Community Talks |
RY02VBJBIm0 |
| Jun. 2023 |
How to Build an LLM Query Engine in 10 Minutes | LlamaIndex x Ray Crossover |
Vd_8lS1iDBg |
| Sep. 2023 |
Ray Summit 2023: Day 1 Keynote |
r-NYSeAXCko |
| Sep. 2023 |
Ray Summit 2023: Day 2 Keynote |
WbZ6tuAan5M |
| Oct. 2023 |
Redesigning Scheduling in Ray to Improve Cost-Efficiency at Scale |
zA2bOT7GYew |
| Oct. 2023 |
Developing Ray Applications on Google Cloud TPUs |
1aaFaMvJhq8 |
| Oct. 2023 |
Ray Scalability Deep Dive: The Journey to Support 4,000 Nodes |
1lYTmch4AbY |
| Oct. 2023 |
Scaling time-series forecasting models to cope with the multi-verse with Ray |
9Iw-a1CCBBo |
| Oct. 2023 |
Developing and Serving RAG-Based LLM Applications in Production |
YO9jYy-HIRY |
| Oct. 2023 |
Tend and Tune Your MARL Experiments with Ray and Weights & Biases |
UrO2ttqMuwM |
| Oct. 2023 |
AI Factory Accelerating Solutions with Ray |
ZELH3S93igw |
| Oct. 2023 |
How to simplify execution of cloud-native model training & validation with CodeFlare: A HandsOn Demo |
fQangtWW6Sc |
| Oct. 2023 |
Deploying Many Models Efficiently with Ray Serve |
QUYucglQzBw |
| Oct. 2023 |
Running ML Workloads with AWS Purpose Build ML Accelerators and Ray |
17g107UXfDQ |
| Oct. 2023 |
From Spark to Ray: An Exabyte-Scale Production Migration Case Study |
u1XqELIRabI |
| Oct. 2023 |
On-Demand Ray Clusters in ML Workflows via KubeRay & Sematic |
6xuTqBLbFlE |
| Oct. 2023 |
Modernizing DoorDash Model Serving Platform with Ray Serve |
SZUwN_1UjjI |
| Oct. 2023 |
Scaling up Terascale Deep Learning on Commodity CPUs with ThirdAI and Ray |
2y7MrWjYKLc |
| Oct. 2023 |
Making it easy to provision Ray clusters to support enterprise AI/ML efforts |
O81rAHdieNk |
| Oct. 2023 |
Bridging MLOps and LLMOps: Integrating Governed Generative AI into your Enterprise |
c6ZnHrjEWJ8 |
| Oct. 2023 |
Lessons From Fine-Tuning Llama-2 |
_OIq-9dKkbI |
| Oct. 2023 |
Efficient Expert Witness Profiling with Ray: Automated Key Phrase Extraction from Legal Documents |
TR3zzKNq834 |
| Oct. 2023 |
Building a Distributed Query Engine with Ray |
h6onw7ufRok |
| Oct. 2023 |
Ray Serve for IOT at Samsara |
GgzwT2cx3Bk |
| Oct. 2023 |
Parallel inferencing with KServe Ray integration |
8bynanD6VP4 |
| Oct. 2023 |
50x Faster Fine-Tuning in 10 Lines of YAML with Ludwig and Ray |
5P3GTHIup9A |
| Oct. 2023 |
Ray Observability 2.0: How to Debug Your Ray Applications with New Observability Tooling |
6cjyRCSxfGg |
| Oct. 2023 |
GenAI for Enterprises—Practical Considerations From Pilot to Scale |
g6gfbPYw4fc |
| Oct. 2023 |
How Spotify Built a Robust Ray Platform with a Frictionless Developer Experience |
wi2Ae4mB0SY |
| Oct. 2023 |
Scaling AI Health Assistants: Challenges and Solutions |
NCVOhn8LI8Y |
| Oct. 2023 |
TimeGPT: A Foundation Large Time Series Model |
tH3Vig7YYwg |
| Oct. 2023 |
Standing Up Ray Clusters in the Blink of an AI to Drive Private AI |
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| Oct. 2023 |
Forecasting Covid Infections for the UK's National Health Service using Ray and Kubernetes |
GAqzh6k0Dlc |
| Oct. 2023 |
Real-Time Vectorization for Transactional Workloads with MongoDB Atlas + Anyscale |
UUJHcONFM7Y |
| Oct. 2023 |
BentoML or RayServe, You Can Choose Both with BentoRay |
NI8z-a1N8nY |
| Oct. 2023 |
Decentralized Ray - Scaling Ray for Global Inference |
ie-EAlGfTHA |
| Oct. 2023 |
NLP And The Future of Search With You.com |
wmPdiIkjR4U |
| Oct. 2023 |
Python-centric AI Application Building in Minutes with Lepton and Ray |
rgjkmmSg6I8 |
| Oct. 2023 |
Building an Instant-On Serverless Platform for Large-Scale Data Processing Using Ray |
zwFZTl_murw |
| Oct. 2023 |
How Ray Empowered Ant Group to Deliver a Large-Scale Online Serverless Platform |
_yu0Rtuetuc |
| Oct. 2023 |
Building an Instant-On Serverless Platform for Large-Scale Data Processing Using Ray |
zQKScuKy58Q |
| Oct. 2023 |
How to Build an AI Copilot for Your Application |
n0zZX2bVcro |
| Oct. 2023 |
Gismo for Ray: A Multi-Node Shared Memory Object Store That Accelerates Ray Workloads |
sJmM47ce48I |
| Oct. 2023 |
Supercharging self-driving algor dev w/ Ray: scaling sim workloads and democratizing autotuning@Zoox |
m5MEc7WcUGg |
| Oct. 2023 |
KubeRay: A Ray cluster management solution on Kubernetes |
1vGb0nn5n0o |
| Oct. 2023 |
Last Mile Data Processing for ML Training using Ray |
I1eTzQs9QkU |
| Oct. 2023 |
A Ray-based ML Platform for Early Cancer Detection |
X-UVR-0Zfw8 |
| Oct. 2023 |
Best Practices for Productionizing Distributed Training with Ray Train |
gpAgn2pC95E |
| Oct. 2023 |
The Different Shades of using KubeRay with Kubernetes |
mGk5P_6VCVM |
| Oct. 2023 |
Faster and Cheaper Offline Batch Inference with Ray |
qzgphfXMNUU |
| Oct. 2023 |
Enabling End-to-End LLMOps on Michelangelo with Ray |
NsQF67YokcM |
| Oct. 2023 |
From Good to Great: Elevating DoorDash Model Training with Ray |
pzemMnpctVY |
| Oct. 2023 |
OneDigital ML Platform: Unleashing the Power of Machine Learning at Scale |
QGTTgJaCnKk |
| Oct. 2023 |
Hyperparameter Tuning with Ray[Tune] for Next-Gen Training Platform at LinkedIn |
V-MrQPMGJko |
| Oct. 2023 |
The Ray Dataplane: History and the Cloudsort World Record |
PCU34t1NgqE |
| Oct. 2023 |
Intellectual Property with GenAI: What LLM Developers Need to Know |
YGRXU46N6A8 |
| Oct. 2023 |
Anyscale Workspaces: A Scalable Interactive ML Development Environment with Zero Setup |
oLMARKfkXB4 |
| Oct. 2023 |
Semiconductor Fab Production Scheduling Using Deep Reinforcement Learning |
jL30JowDKH8 |
| Oct. 2023 |
Deploying Ray Cluster on an Air-Gapped Kubernetes Cluster with Tight Security Control: Challenges an |
-J8-xONW3oo |
| Oct. 2023 |
FlightAware and Ray: Scaling Distributed XGBoost and Parallel Data Ingestion |
f6DTzwX6yEk |
| Oct. 2023 |
Large Scale Pathways Recommender Systems (PaRS) at Verizon |
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| Oct. 2023 |
Simplified Training, Tuning and Deployment of Foundational Models as a Service with Red Hat OpenShif |
TogUKeGdjhk |
| Oct. 2023 |
How Snorkel Builds Interactive Enterprise ML Products Using Ray |
Ea9AWuu03V0 |
| Oct. 2023 |
Ray for Large-Scale, Time-Series Energy Forecasting to Plan a More Resilient Power Grid |
tg2-F2Gf19I |
| Oct. 2023 |
Heterogeneous Training Cluster with Ray at Netflix |
QVQo6wG0jyY |
| Oct. 2023 |
Building Samsara's Machine Learning Platform with Ray |
5eKBUKKWijQ |
| Oct. 2023 |
Understanding the Landscape of the Latest Large Models |
QoHqR3TBztE |
| Oct. 2023 |
Fast, Flexible, and Scalable Data Loading for ML Training with Ray Data |
Qhyxx3Q7Fik |
| Oct. 2023 |
Build Augmented Reality Maps With Ray |
cTJ2i4sIBO0 |
| Oct. 2023 |
Embeddings and Vectors are the Key to Production AI |
HfMI1VE-vDQ |
| Oct. 2023 |
Ray, Knative, and Running Serverless Workloads in the Cloud |
zYzyR36g108 |
| Oct. 2023 |
Easily Scale to Production-Ready Generative AI with NVIDIA and Anyscale |
Y3mqEM05SS8 |
| Oct. 2023 |
Enabling Cost-Efficient LLM Serving with Ray Serve |
TJ5K1CO9Wbs |
| Oct. 2023 |
Inference Graphs at LinkedIn Using Ray-Serve |
JqpefcQS1a4 |
| Oct. 2023 |
Open Source LLMs: Viable for Production or a Low-Quality Toy? |
Ri_LJ_qOTPM |
| Oct. 2023 |
Scaling Computer Vision Models with Ray:A Cost-Effective and Efficient Distributed Training Framewor |
dzH0kqvNmNY |
| Oct. 2023 |
Building Production AI Applications with Ray Serve |
bEp_bBrAxak |
| Oct. 2023 |
SkyPilot: Run AI on Any Cloud |
rgQxO54hN8Q |
| Oct. 2023 |
Ray Data Streaming for Large-Scale ML Training and Inference |
wiFbNbNzXNI |
| Oct. 2023 |
Perplexity AI: How We Built the World's Best LLM-Powered Search Engine in 6 Months, w/ Less Than $4M |
-mQPOrRhRws |
| Oct. 2023 |
Build Instacart Training Platform on Ray |
VTqM16UGs44 |
| Oct. 2023 |
Gorilla: Large Language Models Connected with Massive APIs |
wQl9C3I936Q |
| Oct. 2023 |
Large Language-Style Universal Models for Short Video Recommendations |
2Gj5XWnbPtw |
| Oct. 2023 |
Fast LLM Serving with vLLM and PagedAttention |
5ZlavKF_98U |
| Oct. 2023 |
Managed Cloud Infrastructure for LLMs |
Wk7S7MTwqj4 |
| Oct. 2023 |
Serving Large Language Models with KubeRay on TPUs |
RK_u6cfPnnw |
| Oct. 2023 |
Automatically scaling the execution of Foundation Models workflows: Ray with CodeFlare and Red Hat |
EFi0NhgS-gI |
| Oct. 2023 |
Optimizing LLM Training with Airbnb's Next-Gen ML Platform |
-sZvzW40NrM |
| Oct. 2023 |
Building Context-Aware Reasoning Applications with LangChain and LangSmith |
Hy08dbsfJGg |
| Oct. 2023 |
Llama, Scaling Up LLMs in an Open Ecosystem |
W_INHoKBVFc |
| Oct. 2023 |
Enterprise Vector-based Information Retrieval & Prompt Engineering at Scale using Open Source on AWS |
eg-tW7mdtqc |
| Oct. 2023 |
Making your Enterprise GenAI Ready and GenAI Enterprise Ready |
M7cPv4kOC-g |
| Oct. 2023 |
Practical Data Considerations for Building Production-Ready LLM Applications |
WLKRAzORtOI |
| Oct. 2023 |
Integrating Ray.io into the Google Cloud Ecosystem for the Enterprise |
Nj_YOz0MX10 |
| Oct. 2023 |
Ray/RLLib-Empowered Reinforcement Learning Based Recommender Systems in NetEase Game |
Kla1iqANltE |
| Nov. 2023 |
Ray Train: A Production-Ready Library for Distributed Deep Learning |
GmtyTb0eARo |
| Nov. 2023 |
Elevate Your AI Applications with Anyscale and Ray: Simple, Scalable, Secure |
AABc_eTlZbM |
| Dec. 2023 |
Build a chat assistant fast using Canopy from Pinecone and Anyscale Endpoints |
3vZ6EhhvpWo |
| Feb. 2024 |
Meetup: Evaluating LLMs: Needle in a Haystack |
aswbFKE_0Dg |
| Jun. 2024 |
End-to-End LLM Workflows with Anyscale |
xw-F6Nk-KdE |
| Jun. 2024 |
Fast and Scalable Model Training with PyTorch and Ray |
ZxaMq-i6HC0 |
| Jul. 2024 |
Anyscale Replica Compaction |
dHEZit6tl8E |
| Jul. 2024 |
The Anyscale Unified Log Viewer |
ru7l2LdFovk |
| Jul. 2024 |
Anyscale Job Queues |
J-NQcFCD9OQ |
| Aug. 2024 |
Scalable and Cost Efficient AI Workloads with AWS and Anyscale |
pRiKZPk_-98 |
| Sep. 2024 |
Optimizing LLM Inference with AWS Trainium, Ray, vLLM, and Anyscale |
tzzduslVzos |
| Oct. 2024 |
Ray Summit 2024 |
nlbFV1j36bA |
| Oct. 2024 |
Optimized AI Workloads on Anyscale with RayTurbo |
01X7cMSbbzw |