What we’re about
ATTENTION: Please join the PWL Discord and hop into the #nyc channel -> https://https://discord.gg/B7aHhwBb8r
We are organizing the next steps for PWL NYC there!
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What was the last paper within the realm of computing you read and loved? What did it inspire you to build or tinker with? Come share the ideas in an awesome academic/research paper with fellow engineers, programmers, and paper-readers. Lead a session and show off code that you wrote that implements these ideas or just give us the lowdown about the paper (because of HARD MATH!). Otherwise, just come, listen, and discuss.
We're curating a repository for papers and places-to-find papers. You can contribute by adding PR's for papers, code, and/or links to other repositories.
We're posting videos of all our presentations, from all our chapters.
If you need to reach out to us or have ideas for papers, just ask us via our twitter account.
Papers We Love has a Code of Conduct. Please contact one of the Meetup's organizers if anyone is not following it. Be good to each other and to the PWL community!
Upcoming events (1)
See all- Rylan Talerico on Zep: A Temporal Knowledge Graph Architecture for Agent MemoryDatadog, New York, NY
We're please to present Rylan Talerico on Zep: A Temporal Knowledge Graph Architecture for Agent Memory (read the paper)
Today's large language models (LLMs) are stateless: at test time, the scope of their accessible information extends only to their internally encoded knowledge and the tokens in their context window. AI memory has emerged to address this, enabling long-horizon continuity and user personalization in LLM applications by intelligently hydrating the context window before inference. Zep is a low-latency, temporally aware, graph-based AI memory architecture. Zep reports strong performance on the Deep Memory Retrieval (DMR) and LongMemEval (LME) benchmarks, and is among the most well-known architectures in the space today. Zep retrieves and reconstructs relevant information across histories exceeding 115,000 tokens, as demonstrated in LME.
Rylan Talerico is co-founder and CPO of Retriever, where he works on AI memory and personalization. A self-taught engineer who dropped out of high school to self-direct, Rylan founded Crate.fm, a cloud storage and collaboration platform for musicians, before starting Retriever. Outside of work, he loves reading, music, and running.
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⚠️ Required: You must have your real name on your account and provide a photo ID at the entrance to attend, per the venue rules. If you are not on the list, you will not be admitted.
🚔 Reminder: Papers We Love has a code of conduct. Breaching the CoC is grounds to be ejected from the meetup at the organizers' discretion.
📹 The event will be recorded and made available 1-2 weeks afterwards.
💬 Join us on the Papers We Love Discord - https://discord.gg/6gupsBg4qp
