The State Space Model taking on Transformers Right now, AI is eating the world. And by AI, I mean Transformers. Practically all the big breakthroughs in AI over the last few years are due to Transformers. Mamba, however, is one of an alternative class of models called State Space Models (SSMs). Importantly, for the first […]
As computer vision researchers, we believe that every pixel can tell a story. However, there seems to be a writer’s block settling into the field when it comes to dealing with large images. Large images are no longer rare—the cameras we carry in our pockets and those orbiting our planet snap pictures so big and
Every year, the Berkeley Artificial Intelligence Research (BAIR) Lab graduates some of the most talented and innovative minds in artificial intelligence and machine learning. Our Ph.D. graduates have each expanded the frontiers of AI research and are now ready to embark on new adventures in academia, industry, and beyond. These fantastic individuals bring with them
In 1928, London was in the middle of a terrible health crisis, devastated by bacterial diseases like pneumonia, tuberculosis, and meningitis. Confined in sterile laboratories, scientists and doctors were stuck in a relentless cycle of trial and error, using traditional medical approaches to solve complex problems. This is when, in September 1928, an accidental event
The rise of the vector database As a result of the rapid advancement of generative AI in recent years, many companies are rushing to integrate AI into their businesses. One of the most common ways of doing this is to build AI systems that answer questions concerning information that can be found within a database
Have you ever trained a model you thought was good, but then it failed miserably when applied to real world data? If so, you’re in good company. Machine learning processes are complex, and it’s very easy to do things that will cause overfitting without it being obvious. In the 20 years or so that I’ve
The history of each living being is written in its genome, which is stored as DNA and present in nearly every cell of the body. No two cells are the same, even if they share the same DNA and cell type, as they still differ in the regulators that control how DNA is expressed by
One of the most fascinating problems that a computer scientist may be lucky enough to encounter is a complex sociotechnical problem in a field going through the process of digital transformation. For me, that was fish counting. Recently, I worked as a consultant in a subdomain of environmental science focused on counting fish that pass
In this article, we will talk about classical computation: the kind of computation typically found in an undergraduate Computer Science course on Algorithms and Data Structures [1]. Think shortest path-finding, sorting, clever ways to break problems down into simpler problems, incredible ways to organise data for efficient retrieval and updates. Of course, given The Gradient’s
This essay first appeared in Reboot. Credulous, breathless coverage of “AI existential risk” (abbreviated “x-risk”) has reached the mainstream. Who could have foreseen that the smallcaps onomatopoeia “ꜰᴏᴏᴍ” — both evocative of and directly derived from children’s cartoons — might show up uncritically in the New Yorker? More than ever, the public discourse about AI
