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The Berkeley Artificial Intelligence Research (BAIR) Lab brings together UC...
It takes ten times more electricity for ChatGPT to respond to a prompt than for Google to carry out a standard search. Still, researchers are struggling to get a grasp on the energy implications of generative artificial intelligence both now and going forward.
6 minutes read
In this episode, we explore how a generative AI tool is marking a major milestone in biology and accelerating advancements in healthcare, genetics, and drug development.
11 minutes read
Trained on a dataset that includes all known living species—and a few extinct ones, Evo2 can predict the form and function of proteins in the DNA of all domains of life, identify molecules useful for bioengineering and medicine
5 minutes read
Yevgeniy Vorobeychik, Ning Zhang and William Yeoh receive $1.5 million DoD grant to enhance multiple facets of generative AI
2 minutes read
NPUs are integrated units that excel in real-time AI tasks on edge devices like smartphones and IoT systems with low power consumption. TPUs are standalone processors designed for large-scale AI workloads in data centers, delivering exceptional performance in deep learning tasks.
Missed out latest webinar? Watch it on demand now to stay up to date with all the latest from Generative AI at the Edge.
The use of generative artificial intelligence in protein design stands to revolutionize new drug development. EPFL ambitions putting together a consortium to further explore this avenue.
5 minutes read
Generative AI has evolved to become an advanced, general-purpose technology that has reached the level of practical use, and the usage scenarios have become more familiar applications. Nowadays, the application of AI including generative AI has even expanded into the field of sports.
6 minutes read
In the final chapter of the Edge AI Technology Report: Generative AI Edition explores the technical hurdles organizations face as they attempt to leverage edge-based generative AI. It also examines strategic opportunities for innovation in hardware, deployment configurations, and security measures.
Join us for The Rise of Generative AI at the Edge: From Data Centers to Devices webinar on Wednesday, January 15th
Creating realistic 3D models for applications like virtual reality, filmmaking, and engineering design can be a cumbersome process requiring lots of manual trial and error.
Edge AI Technology Report: Generative AI Edition Chapter 3. Advances in model optimization techniques like pruning, quantization, and knowledge distillation pave the way for more efficient deployment of generative AI at the edge.
Stanford engineers are testing foods using an approach that combines a three-dimensional mechanical technique and AI to mimic our sensory experience.
4 minutes read
This article examines gen AI’s impact on data center design and operations and explores the changes necessary to support its continued development.
Fine-tuning large language models adapts pre-trained models to specific tasks or domains using tailored datasets, while Retrieval-Augmented Generation (RAG) combines retrieval systems with generative models to dynamically incorporate external, up-to-date knowledge into outputs.
