Deep neural networks, often criticized as “black boxes,” are helping neuroscientists understand the organization of living brains.
Category: robotics/AI – Page 1,952
Ex-US cyber command chief: Enemies using AI is ‘existential threat’
Certain cyber-artificial intelligence attacks could pose an existential threat to the US and the West, former US cyber command chief, Maj.-Gen. (ret.) Brett Williams said on Tuesday.
Speaking as part of Cybertech’s virtual conference, Williams said, “artificial intelligence is the real thing. It is already in use by attackers. When they learn how to do deepfakes, I would argue this is potentially an existential threat.”
DARPA Testing the Limits of Unmanned Ships in New NOMARS Program
As the Defense Advanced Research Projects Agency (DARPA) explores designs for a ship that could operate without humans aboard, the agency is keeping the Navy involved in the effort to ensure it progresses forward should the program’s work succeed.
While the Navy is creating unmanned surface vehicles based off designs meant for ships that could bring humans aboard, the No Manning Required Ship (NOMARS) program is the first to pursue a design that takes humans out of the calculation.
Gregory Avicola, the NOMARS program manager, told USNI News in a recent interview that DARPA has had conversations with Navy offices like PMS-406, the service’s program executive office for unmanned and small combatants, and the Surface Development Squadron, which has been tasked with developing the concept of operations for unmanned surface vehicles, since the agency started the NOMARS initiative.
Recreating Historical Streetscapes Using Deep Learning and Crowdsourcing
For many, gazing at an old photo of a city can evoke feelings of both nostalgia and wonder — what was it like to walk through Manhattan in the 1940s? How much has the street one grew up on changed? While Google Street View allows people to see what an area looks like in the present day, what if you want to explore how places looked in the past?
Microsoft unveils FREE app to create AI models without writing any code
Microsoft has released a public preview of a free app lets helps people train machine learning models without writing any code.
The Lobe desktop app for Windows and Mac currently only supports image classification, but Microsoft plans to expand it to other models and data types in the future.
“Just show it examples of what you want it to learn, and it automatically trains a custom machine learning model that can be shipped in your app,” the Lobe website explains.
If a robot is conscious, is it OK to turn it off? The moral implications of building true AIs
Philosophers say now is the time to mull over what qualities should grant an artificially intelligent machine moral standing.
Deci raises $9.1M to optimize AI models with AI
Deci, a Tel Aviv-based startup that is building a new platform that uses AI to optimized AI models and get them ready for production, today announced that it has raised a $9.1 million seed round led by Emerge and Square Peg.
The general idea here is to make it easier and faster for businesses to take AI workloads into production — and to optimize those production models for improved accuracy and performance. To enable this, the company built an end-to-end solution that allows engineers to bring in their pre-trained models and then have Deci manage, benchmark and optimize them before they package them up for deployment. Using its runtime container or Edge SDK, Deci users can also then serve those models on virtually any modern platform and cloud.
The Deck Is Not Rigged: Poker and the Limits of AI
Tuomas Sandholm, a computer scientist at Carnegie Mellon University, is not a poker player—or much of a poker fan, in fact—but he is fascinated by the game for much the same reason as the great game theorist John von Neumann before him. Von Neumann, who died in 1957, viewed poker as the perfect model for human decision making, for finding the balance between skill and chance that accompanies our every choice. He saw poker as the ultimate strategic challenge, combining as it does not just the mathematical elements of a game like chess but the uniquely human, psychological angles that are more difficult to model precisely—a view shared years later by Sandholm in his research with artificial intelligence.
“Poker is the main benchmark and challenge program for games of imperfect information,” Sandholm told me on a warm spring afternoon in 2018, when we met in his offices in Pittsburgh. The game, it turns out, has become the gold standard for developing artificial intelligence.
Tall and thin, with wire-frame glasses and neat brow hair framing a friendly face, Sandholm is behind the creation of three computer programs designed to test their mettle against human poker players: Claudico, Libratus, and most recently, Pluribus. (When we met, Libratus was still a toddler and Pluribus didn’t yet exist.) The goal isn’t to solve poker, as such, but to create algorithms whose decision making prowess in poker’s world of imperfect information and stochastic situations—situations that are randomly determined and unable to be predicted—can then be applied to other stochastic realms, like the military, business, government, cybersecurity, even health care.