The panel on the challenges and opportunities of the future of ML compute has started with @ce__zhang (@togethercompute) , @tusharkrishna29 (@GeorgiaTech_ECE ), Ada Gavrilovska (@gatech_scs), @DAlistarh (@MIT_CSAIL and @ISTAustria), @stevelaskaridis and @alsched.

We are now starting the third keynote of the day, with @aurelien_bellet presenting his work on Privacy Guarantees for Decentralised Federated Learning

Second keynote speaker of the day is @tusharkrishna29, talking about hardware-software co-design in distributed systems.

Great start of the day with @ce__zhang's insightful keynote on the current tensions of training and deploying LLMs.

Announcing our speaker lineup for this year's @DistributedML, including @ce__zhang (@togethercompute) , @tusharkrishna29 (@GeorgiaTech_ECE ), @aurelien_bellet (@inria), Ada Gavrilovska (@gatech_scs) and @DAlistarh (@MIT_CSAIL and @ISTAustria). Looking forward to a great program!

We are very excited to release the list of accepted papers for this year's @DistributedML workshop, along with a tentative schedule here: distributedml.org/program/ Looking forward to seeing you in Paris, @ACMSIGCOMM #CoNEXT23.

Pencils down in 11 days. Submission deadline for distributedml.org has now been extended for a week. New deadline is set for Sep 22nd AoE.

Reminder: Almost one week left until the submission deadline of distributedml.org (Sep 15th). We are looking forward to receiving some great papers this year! In the meantime, we have been organising an exciting program for this year's workshop. Stay tuned for more!

distributedml.org is to be held along #CONEXT2023 this year in Paris. We welcome novel, previously unpublished, work in the area of Distributed #MachineLearning, with special focus on training and deploying large foundational models. Submission deadline on September 15!

How can we make ML training and deployment at scale more efficient? @anaklimovic' research sheds light on the data ingestion bottlenecks in ML processes.

How do you scale training as models gets increasingly large and accurate? Great insights on programmable networks for performant distributed deep learning by @elfmar in the first session of @DistributedML.

Counting hours to our 3rd iteration of the DistributedML workshop co-located with @ACMSIGCOMM #CoNEXT. Program starts at 10am CEST in Sapienza Uni Di Roma🇮🇹. Attendance is hybrid. Tune in for some great talks and fruitful discussions in the area of #distributedml.

The list of accepted papers of this year's @DistributedML is out, along with the speakers and provisional program. We are really excited to welcome @anaklimovic (ETHz), @elfmar (KAUST), Dimitrios Dimitriadis (MSR) and Christos Louizos (Qualcomm AI). Registrations are now open.

DistributedML'22 is around the corner: Sep 16th. It is co-located with @ACMSIGCOMM #CoNEXT and this year it is happening hybrid in Rome on Dec 9th. Accepted papers will be included in the conference proceedings. Looking forward to your submissions. distributedml.org

If you haven't heard the news, DistributedML'22 is going to Rome with @ACMSIGCOMM #conext2022. We look forward to your submissions and seeing you hopefully in person this year. Submissions deadline: 16.09 More details here: distributedML.org #distributedml #research