Our next iteration of the FSF sets out stronger security protocols on the path to AGI AI is a powerful tool that is helping to unlock new breakthroughs and make significant progress on some of the biggest challenges of our time, from climate change to drug discovery. But as its development progresses, advanced capabilities may

Podcast Transcript Bob – 0:00 Right Then today we’re taking a deep dive into something. You sent over a rather cheeky article from the AI blog asking, what is Elon Musk’s IQ? Oh, right, yeah, the chap, of course, Tesla, SpaceX, xAI all that. Now, yeah, we all have a sense that Musk is a

A simple but effective approach to improve long-context understanding Previous studies have mainly explored two major directions: input reduction and window extension. Input reduction reduces the length of the input context — for example, by directly truncating the input — before feeding to downstream LLMs. RAG extends this direction by breaking the input into chunks

Acknowledgements Special thanks to Michael Reneer for his critical contributions in setting up Parfait. Direct contributors to work on Parfait repositories include Galen Andrew, Isha Arkatkar, Sean Augenstein, Kallista Bonawitz, Amlan Chakraborty, Zachary Charles, Stanislav Chiknavaryan, DeWitt Clinton, Taylor Cramer, Katharine Daly, Stefan Dierauf, Randy Dodgen, Hubert Eichner, Nova Fallen, Ken Franko, Zachary Garrett, Emily

Humans possess a remarkable ability to localize sound sources and perceive the surrounding environment through auditory cues alone. This sensory ability, known as spatial hearing, plays a critical role in numerous everyday tasks, including identifying speakers in crowded conversations and navigating complex environments. Hence, emulating a coherent sense of space via listening devices like headphones

As artificial intelligence (AI) continues to advance, the landscape is becoming increasingly competitive and ethically fraught. Companies like Anthropic, which have missions centered on developing “safe AI,” face unique challenges in an ecosystem where speed, innovation, and unconstrained power are often prioritized over safety and ethical considerations. In this post, we explore whether such companies

Seeing as transformers and MPNNs are not the only ML approaches for the structural analysis of graphs, we also compared the analytical capabilities of a wide variety of other GNN- and transformer-based architectures. For GNNs, we compared both transformers and MPNNs to models like graph convolutional networks (GCNs) and graph isomorphism networks (GINs). Additionally, we

We made strong headway in ML foundations, with extensive work on algorithms, efficiency, data and privacy. We improved ML efficiency through pioneering techniques that reduce the inference times of LLMs, which were implemented across Google products and adopted throughout the industry. Our research on cascades presents a method for leveraging smaller models for “easy” outputs