What Is Emergence In Complex Systems ? And How Physics Can Explain It
Forbes | July 28, 2024
Column by bioengineering professor Gabriel Silva. Full Story
This Mighty Brain Chip Is So Efficient It Could Bring Advanced AI to Your Phone
SingularityHub | August 30, 2022
This month, a study in Nature upgraded CIM from the ground up. Rather than focusing solely on the chip?s design, the international team?led by neuromorphic hardware experts Dr. H.S. Philip Wong at Stanford and Dr. Gert Cauwenberghs at UC San Diego?optimized the entire setup, from technology to architecture to algorithms that calibrate the hardware. Full Story
New AI Chip Twice as Energy Efficient as Alternatives
IEEE Spectrum | August 29, 2022
A team of researchers have developed a prototype of a new compute-in-memory (CIM) chip that eliminates the need for this separation. Their prototype, they claim in their paper published in Nature on 17 August, demonstrates twice the efficiency of existing AI platforms. Full Story
AI chip adds artificial neurons to resistive RAM for use in wearables, drones
The Register | August 18, 2022
A newly published research paper describes a compute-in-memory (CIM) chip that combines artificial neurons with resistive RAM (RRAM) so that the AI model weights can be stored and processed on the same chip. Full Story
48 core neuromorphic AI chip uses resistive memory
eeNews | August 17, 2022
A team of researchers in the US and China has designed and built a neuromorphic AI chip using resistive RAM, also known as memristors. The 48 core NeuRRAM chip developed at the University of California San Diego is twice as energy efficient as other compute-in-memory chips and provides results that are just as accurate as conventional digital chips. Full Story
?Unprecedented? artificial intelligence breakthrough could make complex machines a reality
The Sun | August 17, 2022
A CHIP designed to run calculations without cloud computing has the potential to rapidly advance the artificial intelligence revolution. The chip runs artificial intelligence programs using memory stored locally. Full Story
Neuroscience and artificial intelligence can help improve each other
Chicago Tribune | July 9, 2019
Despite their names, AI technologies and their component systems, such as artificial neural networks, don't have much to do with real brain science. I'm a professor of bioengineering and neurosciences interested in understanding how the brain works as a system - and how we can use that knowledge to design and engineer new machine learning models. In recent decades, brain researchers have learned a huge amount about the physical connections in the brain and about how the nervous system routes information and processes it. (Gabriel A. Silva, University of California San Diego) Full Story
Neuroscience and artificial intelligence can help improve each other
CT Post | July 9, 2019
(Gabriel A. Silva, University of California San Diego) Despite their names, artificial intelligence technologies and their component systems, such as artificial neural networks, don't have much to do with real brain science. I'm a professor of bioengineering and neurosciences interested in understanding how the brain works as a system - and how we can use that knowledge to design and engineer new machine learning models. Full Story
Neuroscience and artificial intelligence can help improve each other
Seattle PI | July 9, 2019
Gabriel A. Silva, University of California San Diego (THE CONVERSATION) Despite their names, artificial intelligence technologies and their component systems, such as artificial neural networks, don't have much to do with real brain science. I'm a professor of bioengineering and neurosciences interested in understanding how the brain works as a system - and how we can use that knowledge to design and engineer new machine learning models. In recent decades, brain researchers have learned a huge amount about the physical connections in the brain and about how the nervous system routes Full Story
Neuroscience and artificial intelligence can help improve each other
Times Union | July 9, 2019
Gabriel A. Silva, University of California San Diego (THE CONVERSATION) Despite their names, artificial intelligence technologies and their component systems, such as artificial neural networks, don?t have much to do with real brain science. I?m a professor of bioengineering and neurosciences interested in understanding how the brain works as a system ? and how we can use that knowledge to design and engineer new machine learning models. In recent decades, brain researchers have learned a huge amount about the physical connections in the brain and about how the nervous system routes Full Story