Better Performance
Using a high-capacity architecture allows our ads system to more broadly & deeply understand new concepts and relationships in data and benefits advertisers through joint optimization of a large number of goals. 2/5
@aiatmeta
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High-Capacity Ads System for Better Performance and Optimization
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Meta Lattice improves AI compute efficiency and innovation agility
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Improved AI efficiency
We expect that transitioning to Meta Lattice will enable our fleet to improve compute efficiency. Maintaining & advancing fewer, but more powerful models also allows us to be more nimble with future innovations. 3/5 -
Meta Lattice: Faster Market Adaptation Through Generalized Learning
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Faster adaptability to the shifting market landscape
Meta Lattice is capable of generalizing its learnings across domains and objectives. Fewer models also means we can proactively and efficiently update models and adapt to the fast-evolving market landscape. 4/5 -
Meta Lattice: New Model Architecture Improves Ads System Performance
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Today we’re sharing details on Meta Lattice, a new model architecture that improves Meta’s ads systems performance and efficiency.
— AI at Meta (@AIatMeta) 12 mai 2023
More on this new work ➡️ https://t.co/0KXgAbk248
Three ways that this new work is enhancing our ads system 🧵 pic.twitter.com/Jt7t1ZkDyLToday we’re sharing details on Meta Lattice, a new model architecture that improves Meta’s ads systems performance and efficiency. More on this new work https://
bit.ly/3W07lkO Three ways that this new work is enhancing our ads system -
ImageBind: Meta AI’s Multimodal Model Binding Six Data Types
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Introducing ImageBind by Meta AI: the first AI model capable of binding data from six modalities at once. This breakthrough brings machines one step closer to the human ability to bind together information from many different senses.
— AI at Meta (@AIatMeta) 9 mai 2023
More on this new open source work ⬇️Introducing ImageBind by Meta AI: the first AI model capable of binding data from six modalities at once. This breakthrough brings machines one step closer to the human ability to bind together information from many different senses. More on this new open source work
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Santosh’s Team Building Next Generation AI Innovation Backbone
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Santosh and his team are building the backbone for the next generation of AI innovation. https://
x.com/techatfacebook
/techatfacebook/status/1655625976691273753
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SSL Cookbook: Practical Guide for Self-Supervised Learning Research
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Self-supervised learning is a key ingredient in recent AI breakthroughs. To lower barriers + help democratize access to this research, we compiled The SSL Cookbook: a practical guide for researchers navigating the intricacies of this research space.
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Meta AI At Scale Virtual Event May 18th Infrastructure Innovations
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#AtScaleMetaAI is a one-day virtual event featuring a range of speakers from Meta who will unveil the latest AI infrastructure investments and innovations powering Meta's products and services. RSVP to join us and get a reminder before we go live on May 18th @ 9am PT
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SSL Models Privacy Risks from Unintended Image Memorization
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Do SSL models have Déjà Vu? Meta AI researchers uncovered previously unknown privacy risks resulting from unintended memorization of image-specific information in SSL models + suggest practical mitigation strategies for new models. Paper https://
bit.ly/413zhoZ -
Meta AI showcases recent work at ICLR 2023 conference
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Want to see more on our recent work and how you can connect with Meta AI? You can see more on our ICLR 2023 page https://
ai.facebook.com/events/iclr-20
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