Business leaders and investors face a deepening paradox: Companies are pouring more money into artificial intelligence than ever, but they’re not seeing the productivity gains they expect.Business leaders and investors face a deepening paradox: Companies are pouring more money into artificial intelligence than ever, but they’re not seeing the productivity gains they expect.Business[#item_full_content]
Artificial intelligence is proving to be transformative in its ability to work with language and images. Now, with a growing push to apply AI to scientific discovery, Caltech’s Anima Anandkumar says there is a crucial ingredient missing from most AI models: the ability to understand the physical world. Take, for example, weather models, says Anandkumar, Caltech’s Bren Professor of Computing and Mathematical Sciences. If you want an AI model to predict weather, it must understand chaotic physical systems, like how the atmosphere changes around the planet and over time.Artificial intelligence is proving to be transformative in its ability to work with language and images. Now, with a growing push to apply AI to scientific discovery, Caltech’s Anima Anandkumar says there is a crucial ingredient missing from most AI models: the ability to understand the physical world. Take, for example, weather models, says Anandkumar, Caltech’s Bren Professor of Computing and Mathematical Sciences. If you want an AI model to predict weather, it must understand chaotic physical systems, like how the atmosphere changes around the planet and over time.[#item_full_content]
Artificial intelligence is proving to be transformative in its ability to work with language and images. Now, with a growing push to apply AI to scientific discovery, Caltech’s Anima Anandkumar says there is a crucial ingredient missing from most AI models: the ability to understand the physical world. Take, for example, weather models, says Anandkumar, Caltech’s Bren Professor of Computing and Mathematical Sciences. If you want an AI model to predict weather, it must understand chaotic physical systems, like how the atmosphere changes around the planet and over time.Artificial intelligence is proving to be transformative in its ability to work with language and images. Now, with a growing push to apply AI to scientific discovery, Caltech’s Anima Anandkumar says there is a crucial ingredient missing from most AI models: the ability to understand the physical world. Take, for example, weather models, says Anandkumar, Caltech’s Bren Professor of Computing and Mathematical Sciences. If you want an AI model to predict weather, it must understand chaotic physical systems, like how the atmosphere changes around the planet and over time.Computer Sciences[#item_full_content]
AI data centers get a bad rap, not least because of concerns that they drive climate change by consuming massive amounts of electricity. But one potentially larger impact of AI on global carbon emissions may be that it’s helping the fossil fuel industry become more productive. That’s the main finding of a paper published in the journal npj Climate Action that looked at how boosting productivity across both clean and dirty energy sources affects net CO2 emissions.AI data centers get a bad rap, not least because of concerns that they drive climate change by consuming massive amounts of electricity. But one potentially larger impact of AI on global carbon emissions may be that it’s helping the fossil fuel industry become more productive. That’s the main finding of a paper published in the journal npj Climate Action that looked at how boosting productivity across both clean and dirty energy sources affects net CO2 emissions.Energy & Green Tech[#item_full_content]
A new semiconductor integration platform developed at the Institute of Science Tokyo combines advanced chip packaging with high-density interconnects and improved thermal management. This combination of three complementary technologies helps overcome the key challenges in building high-performance artificial intelligence (AI) hardware.A new semiconductor integration platform developed at the Institute of Science Tokyo combines advanced chip packaging with high-density interconnects and improved thermal management. This combination of three complementary technologies helps overcome the key challenges in building high-performance artificial intelligence (AI) hardware.Hardware[#item_full_content]
For the first time, researchers have demonstrated that the “ability to forget” can serve as a new computational function for artificial intelligence.For the first time, researchers have demonstrated that the “ability to forget” can serve as a new computational function for artificial intelligence.Hardware[#item_full_content]
Researchers at the University of Stuttgart and the Max Planck Institute for Solid State Research have developed tiny rolls that can be unrolled and rolled up in a controlled manner using a magnet. The model for this was the proboscis of butterflies. These smart materials enable the development of more efficient drive technologies for micro- and soft robotics, a field of research of great economic importance. The results have been published in the journal Advanced Materials.Researchers at the University of Stuttgart and the Max Planck Institute for Solid State Research have developed tiny rolls that can be unrolled and rolled up in a controlled manner using a magnet. The model for this was the proboscis of butterflies. These smart materials enable the development of more efficient drive technologies for micro- and soft robotics, a field of research of great economic importance. The results have been published in the journal Advanced Materials.[#item_full_content]
The Multimedia Laboratory (MMLab) at The University of Hong Kong (HKU) has spearheaded the development of “RoboDojo,” a unified benchmarking platform designed to evaluate robotic manipulation across simulated and physical environments. Co-initiated by Professor Ping Luo, associate director (AI Research and Tech Transfer) of the HKU School of Computing and Data Science (CDS), and his Ph.D. student Tianxing Chen, the project was developed in collaboration with researchers from nearly 20 leading global universities, including the University of California, Berkeley, and Tsinghua University. The paper is posted to the arXiv preprint server.The Multimedia Laboratory (MMLab) at The University of Hong Kong (HKU) has spearheaded the development of “RoboDojo,” a unified benchmarking platform designed to evaluate robotic manipulation across simulated and physical environments. Co-initiated by Professor Ping Luo, associate director (AI Research and Tech Transfer) of the HKU School of Computing and Data Science (CDS), and his Ph.D. student Tianxing Chen, the project was developed in collaboration with researchers from nearly 20 leading global universities, including the University of California, Berkeley, and Tsinghua University. The paper is posted to the arXiv preprint server.Robotics[#item_full_content]
Who’s using AI at home and how do they use it? And is it making them more efficient?Who’s using AI at home and how do they use it? And is it making them more efficient?Machine learning & AI[#item_full_content]
Sending data centers into space. Building them at the bottom of the ocean. Converting California fairgrounds—and San Francisco’s Cow Palace—into massive buildings filled with servers.Sending data centers into space. Building them at the bottom of the ocean. Converting California fairgrounds—and San Francisco’s Cow Palace—into massive buildings filled with servers.Business[#item_full_content]
