Deep-learning models are being used in many fields, from health care diagnostics to financial forecasting. However, these models are so computationally intensive that they require the use of powerful cloud-based servers.
Dataland co-founder Refik Anadol, 38, is a media artist whose “crowd-pleasing – and controversial” works using artificial intelligence have been displayed around the world, including at the Museum of Modern Art in New York, the Serpentine and, most recently, the United Nations headquarters.
In the past two years, Anadol has found himself at the center of debates over the value of AI-generated art, as crowds have been reportedly “transfixed” by his massive interactive digital canvases, while some art critics have panned them as over-hyped and mediocre.
Now Anadol is looking to build artists like himself a permanent exhibition space among some of LA’s most prominent high-culture venues, and he is pledging that the AI art museum will promote “ethical AI” and use renewable energy sources.
Augmented reality (AR) takes digital images and superimposes them onto real-world views. But AR is more than a new way to play video games; it could transform surgery and self-driving cars. To make the technology easier to integrate into common personal devices, researchers report in ACS Photonics how to combine two optical technologies into a single, high-resolution AR display. In an eyeglasses prototype, the researchers enhanced image quality with a computer algorithm that removed distortions.
ChatGPT vulnerability patched by OpenAI after discovery of persistent spyware risk in memory feature, potentially exposing user data.
OpenAI pitched the White House on building data centers in the US as large as 5GW capacity — for ref, that’s enough to power 3 mil homes.
OAI’s analysis says it could add tens of thousands of jobs, boost GDP, and keep US ahead of China on AI.
Altman has spent much of this year trying to form a…
OpenAI has pitched the Biden administration on the need for massive data centers that could each use as much power as entire cities, framing the unprecedented expansion as necessary to develop more advanced artificial intelligence models and compete with China.
The large language models that have increasingly taken over the tech world are not “cheap” in many ways. The most prominent LLMs, such as GPT-4, took some $100 million to build in the form of legal costs of accessing training data, computational power costs for what could be billions or trillions of parameters, the energy and water needed to fuel computation, and the many coders developing the training algorithms that must run cycle after cycle so the machine will “learn.”
But, if a researcher needs to do a specialized task that a machine could do more efficiently and they don’t have access to a large institution that offers access to generative AI tools, what other options are available? Say, a parent wants to prep their child for a difficult test and needs to show many examples of how to solve complicated math problems.
Building their own LLM is an onerous prospect for costs mentioned above, and making direct use of the big models like GPT-4 and Llama 3.1 might not immediately be suited for the complex reasoning in logic and math their task requires.
“I estimate that 80% of 80% of all jobs, maybe more, can be done by an AI,” famed investor and entrepreneur Vinod Khosla has warned. “Be it primary care doctors, psychiatrists, sales people, oncologists, farm workers or assembly line workers, structural engineers, chip designers, you name it.”
Say hello to a universal income and a 3-day week.
Scientists have developed microscopic robots capable of treating brain aneurysms with unprecedented precision, offering a potential alternative to invasive brain surgeries. An international team, including researchers from the University of Edinburgh, engineered these nanorobots to safely and accurately deliver life-saving medications to the brain. This advancement comes in the context of a global health challenge, […].