Cover Image for NEAR AI Paper Club - DeepSeek V3 & R1
Cover Image for NEAR AI Paper Club - DeepSeek V3 & R1
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NEAR AI

NEAR AI Paper Club - DeepSeek V3 & R1

Registration
Welcome! To join the event, please register below.
About Event

Welcome to NEAR AI's third IRL paper club where we'll dive into DeepSeek V3, a groundbreaking advancement in large language models that pushes the boundaries of AI capabilities. In this session, we'll explore the model's innovative Mixture-of-Experts (MoE) architecture with 671B parameters, its remarkable efficiency improvements through FP8 training, and its impressive performance across benchmarks. Join us to discuss the technical breakthroughs, training methodology, and implications for the future of AI development.

You should attend if you're an AI researcher, ML practitioner, or anyone interested in understanding the latest developments in large language models!

Not going to be there in-person? Follow and turn on notifications on NEAR AI's Twitter to get notified for when we go live: https://x.com/near_ai

Event Details

  • Date: Monday, January 27th

  • Time: 6:30pm - 8:00pm PT

  • Format: Discussion based lead by a moderator (Alexander Skidanov, Co-Founder of NEAR AI)

  • Audience: Researchers and practitioners interested in machine learning, distributed systems, and large-scale computing

  • Active participation is encouraged!!

Before Joining the Paper Club

  • Please familiarize yourself with the paper: DeepSeek-V3 Technical Report (https://arxiv.org/abs/2412.19437)

  • Come prepared to engage in a discussion, sharing your thoughts, questions, and insights about the paper

  • Be respectful and open-minded, listening to diverse perspectives and opinions

  • Avoid presenting your own research or promoting your own work during the discussion

  • Keep the discussion focused on the paper and its implications, avoiding off-topic conversations

About the Organizers

NEAR AI: A research organization dedicated to teaching machines to code, enabling them to conduct research that advances open-source AGI.

EDGE: A research & development foundation advancing edge intelligence. Established in early 2023, Edge was founded in response to the rapidly evolving AI and next-gen web landscape, emphasizing open, autonomous, and user-centric intelligence. It currently operates one of the largest Open Source Campus in San Francisco. Follow them at @EdgeAGI.

Location
717 Market St #3rd
San Francisco, CA 94103, USA
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Presented by
NEAR AI