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UC Berkeley College of Engineering: Emerging speech neuroprostheses may offer a way to communicate for people who are unable to speak due to paralysis or disease, but fast, high-performance decoding has not yet been demonstrated. Now, transformative new work by researchers at UCSF and UC Berkeley shows that more natural speech decoding is possible using the latest advances in artificial intelligence. Led by UCSF neurosurgeon Edward Chang, the researchers have developed an implantable AI- powered device that, for the first time, translates brain signals into modulated speech and facial expressions. As a result, a woman who lost the ability to speak due to a stroke was able to speak and convey emotion using a talking digital avatar. The researchers describe their work in a study published today (Wednesday, Aug. 23) in the journal Nature. Study co-author Gopala Anumanchipalli, assistant professor, and Ph.D. student and co-lead author Kaylo Littlejohn, both from UC Berkeley's Department of Electrical Engineering and Computer Sciences, discussed this breakthrough study with Berkeley Engineering.

In 2016, political pundits were stunned by the presidential election results. Donald J. Trump would be the next president of the United States, defying most political pundits’ predictions. This prompted the media, politicians and others to reflect on the accuracy and usefulness of election forecasting. Heading into the 2024 presidential election cycle, we spoke with Lakshya Jain, an election forecaster and UC Berkeley computer science and engineering alum. Jain shared how computing has changed political prediction efforts and why he started Split Ticket, a political analysis website. He also discussed how the August 23 Republican presidential primary debate fits into forecasts.

UC Berkeley experts taught ChatGPT how to quickly create datasets on difficult-to-aggregate research about certain materials that can be used to fight climate change, according to a new paper published in the Journal of the American Chemical Society. These datasets on the synergy of the highly-porous materials known as metal-organic frameworks (MOFs) will inform predictive models. The models will accelerate chemists’ ability to create or optimize MOFs, including ones that alleviate water scarcity and capture air pollution. All chemists – not just coders – can build these databases due to the use of AI-fueled chatbots.This breakthrough by experts at the College of Computing, Data Science, and Society’s Bakar Institute of Digital Materials for the Planet (BIDMaP) will lead to efficient and cost-effective MOFs more quickly, an urgent need as the planet warms. It can also be applied to other areas of chemistry. It is one example of how AI can augment and democratize scientific research. 

Stuart Russell, a computer science professor at UC Berkeley, recently testified at the U.S. Senate hearing titled “Oversight of A.I.: Principles for Regulation.” The Senate Committee on the Judiciary’s Subcommittee on Privacy, Technology, and the Law hosted the July 25 hearing. Russell said artificial general intelligence – a significant milestone where AI could independently learn and complete tasks like human beings – could offer significant benefits to the public. It could be used to spur economic growth and improve healthcare and education, for example. However, it also presents significant risks “up to and including human extinction,” he said. Russell offered suggestions on how to regulate these kinds of technologies, ranging from creating a regulatory agency to enforcing rigorous safety requirements for AI systems. Watch Russell testify starting at 50:55 to hear his full testimony.

Just a few years ago, Berkeley engineers showed us how they could easily turn images into a 3D navigable scene using a technology called Neural Radiance Fields, or NeRF. Now, another team of Berkeley researchers has created a development framework to help speed up NeRF projects and make this technology more accessible to others. Led by Angjoo Kanazawa, assistant professor of electrical engineering and computer sciences, the researchers have developed Nerfstudio, a Python framework that provides plug-and-play components for implementing NeRF-based methods, making it easier to collaborate and incorporate NeRF into projects. Kanazawa and her team will present their paper on Nerfstudio at SIGGRAPH 2023. “Advancements in NeRF have contributed to its growing popularity and use in applications such as computer vision, robotics, visual effects and gaming. But support for development has been lagging,” said Kanazawa. “The Nerfstudio framework is intended to simplify the development of custom NeRF methods, the processing of real-world data and interacting with reconstructions.”

UC Berkeley researchers have designed an extreme-weather proven, hand-held device that can extract and convert water molecules from the air into drinkable water using only ambient sunlight as its energy source, a study published in Nature Water today shows. This atmospheric water harvester used an ultra-porous material known as a metal-organic framework (MOF) to extract water repeatedly in the hottest and driest place in North America, Death Valley National Park. These tests showed the device could provide clean water anywhere, addressing an urgent problem, as climate change exacerbates drought conditions. “Almost one-third of the world’s population lives in water-stressed regions. The UN projects in the year 2050 that almost 5 billion people on our planet will experience some kind of water stress for a significant part of the year,” said Omar Yaghi, the Berkeley chemistry professor who invented MOFs and is leading this study. “This is quite relevant to harnessing a new source for water.”

California allocated $6.87 million in its 2023-24 budget to UC Berkeley to develop the Police Records Access Project, a first-of-its-kind, state-wide database of police misconduct and use-of-force records. Berkeley’s Institute for Data Science, Graduate School of Journalism and partners will collect, curate and make accessible records that a 2019 state law unlocked for the public. It will help communities, journalists, public defenders, prosecutors, and police departments develop a deeper understanding of California policing. “There is an information gap getting in the way of protecting people,” said Saul Perlmutter, the faculty director of the Berkeley Institute for Data Science (BIDS) who initiated this project at Berkeley. “Using data science and artificial intelligence to make that connection offers a classic example of the promises of modern information technologies.”

Through project-based programs, students learn how data science can help solve real-world problems, said Ashley Atkins, West Big Data Innovation Hub executive director. They gain skills like how to communicate about data to people with non-technical backgrounds, and they see in practice how to consider ethics and the impact of their choices on society, she said. DataJam, the University of Washington’s Data Science for Social Good program and UC Berkeley’s Data Science Discovery program – all affiliated with West Big Data Innovation Hub – are creating Data Science Experiential Pathways to connect these three programs. The effort will build and expand project-based learning opportunities, participation and workforce pipelines. Launching this fall with a focus on transportation projects, the pathways initiative will serve students in middle and high school, community and four-year colleges and graduate schools.

Berkeley News: Over 1,200 computer hackers from around the world packed UC Berkeley’s Martin Luther King Jr. Student Union last weekend during a 36-hour artificial intelligence (AI) learning language model (LLM) hackathon that Berkeley leaders say was the largest event of its kind. Dubbed “the Woodstock of Hackathons,” the event was hosted by Berkeley’s premiere startup accelerator, Berkeley SkyDeck, and Cal Hacks, a nonprofit that runs collegiate hackathons. Hackers traveled to campus from as far away as New Zealand and Singapore to bring their AI-inspired projects to life by building applications on top of LLMs similar to ChatGPT.

People participating in augmented and virtual realities are sharing significantly more information than previously understood through their motion data, two new UC Berkeley-led studies show. Users can be reliably identified using just minutes of their head and hand movements, researchers found. Movement data, which is collected and shared with companies and other players to fuel these worlds, can be used to infer dozens of details from age to disability status. These privacy and security risks are currently most relevant to gamers, the most common consumers of immersive physical and virtual computer-generated environments. People bought almost 10 million virtual reality headsets in 2022, and these risks could become even more pervasive soon. Last week Apple announced its own mixed reality headset, which will compete with Meta to make virtual reality tools interesting and accessible to a mainstream audience.