Sachdeva’s breakthrough challenges one of the most studied problems in computer science, known as maximum flow, which ...

Existing algorithms can partially reconstruct the shape of a single tree from a clean point-cloud dataset acquired by ...

The future of work will demand fluency in both science and technology. From addressing climate change to designing ethical AI systems, tomorrow’s challenges will require interdisciplinary thinkers who ...

Understand and implement the RMSProp optimization algorithm in Python. Essential for training deep neural networks ...

As a self-driving car cruises down a street, it uses cameras and sensors to perceive its environment, taking in information ...

“Imagine a computation that produces a new bit of information in every step, based on the bits that it has computed so far. Over t steps of time, it may generate up to t new bits of information in ...

As AI evolves, its potential to support older adults remains strong, offering new opportunities for safety, connection and ...

Artificial Intelligence (AI) models are only as good as the data on which they are trained. Yet gathering enough high-quality ...

Today, a new technological revolution is emerging: quantum computing. With its unprecedented computational power, quantum computing is expected to transform everything from risk analysis and portfolio ...

For 21 years, between 1999 and 2020, millions of people worldwide loaned UC Berkeley scientists their computers to search for ...

Initiative aims to publish a formally verified implementation of Shor’s quantum factoring algorithm with relevance to cryptography and other high-value domains ...

Recent survey delivers the first systematic benchmark of TSP solvers spanning end-to-end deep learners, hybrid methods and brand-new LLM-based ...