NVIDIA Nemotron 3 Ultra is now live!
Frontier accuracy, 5X greater speed, 30% lower cost.
Deploy however you need - on-premise, on the cloud, or at the edge.
Model is live on HuggingFace under the OpenMDW 1.1 license.
https://t.co/IOfAwv3jB6
Nemotron 3 Super is here โ 120B total / 12B active, Hybrid SSM Latent MoE, designed for Blackwell.
Truly open: permissive license, open data, open training infra. See analysis on @ArtificialAnlys
Details in thread ๐งตbelow:
Crafting listening experiences for users through reinforcement learning. ๐ง ๐ก๐ง
Explore how @Spotify leveraged the TensorFlow ecosystem to solve recommendation problems, design an extendable offline simulator, and train RL Agents to generate playlists. โ https://t.co/IdbWzDzdH5
In #recsys you might want to predict different types of user events (click, like, share, purchase).
In this post we introduce multi-task learning (MTL) for ranking models and how to easily build and train such models using #Merlin and #tensorflow.
https://t.co/pMMNRt3Ig6
I've been playing around with NVIDIA's Merlin Models library for the last couple days for the H&M Kaggle competition and here are my thoughts on the library! ๐งต
I had fun time talking to @anders_arpteg on the AIAW podcast. We spoke about a wide variety of different topics, spanning from @nvidia, @Spotify, @join_ef, Recsys, ML-ops & Web-3. It can be found as video (https://t.co/87bIfZ6nxZ) + podcast platforms like https://t.co/kV6ivVhFvg
@eugeneyan@nvidia Nice, that makes it easier since our TF examples are a bit behind our PyTorch ones. Just lemme know if you get stuck somewhere in our tutorials
@gspmoreira@eggie5 It would be interesting to see if this happens more often on larger recsys datasets as well. We made it very easy in Transformers4Rec to combine various masking-schemes with transformer-architectures from Huggingface. Docs: https://t.co/SOdZQiEyAO
ASML is the most important company you've never heard of.
The $300B+ Dutch firm makes the machines that make semiconductors. Each one costs $150m and access to them are a huge geopolitical flashpoint.
Here's a breakdown ๐งต
Incredibly excited to share that our @NVIDIAAI paper "Transformers4Rec: Bridging the Gap between NLP and Sequential/Session-Based Recommendation" which wraps @huggingface transformers for use in RecSys has been accepted to @ACMRecSys. See you in Amsterdam #RecSys2021!
1/ Personal update: after 4 amazing years at @spotify, I am very excited to start a new chapter today at @nvidia. I will be working on https://t.co/VamhiLXIZy, an open source end-to-end GPU-accelerated recsys platform.
3/ Building large-scale recommender systems is notoriously hard, and open-source tooling is arguably behind compared to more mature ML-fields like Computer Vision & NLP.