Lifeboat Foundation

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.

Military hierarchies are, by necessity, rigid structures. DARPA’s ‘Mosaic Warfare’ project aims for something much more fluid and adaptable, with AI doing the logistical grunt work so human commanders can get creative.

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 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.

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Philosophers say now is the time to mull over what qualities should grant an artificially intelligent machine moral standing.

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.

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.

The future Russian soldier is going to be able to control drone swarms, have landmine proof boots and an exoskeleton/suit to enhance their physical abilities and situational awareness.

Russia will integrate the ability to control small size attack drone swarms, robots, and exoskeletons into its next-generation soldier gear, in a development that feels more like a videogame update than reality.

I wish I could ride a robot. 😃

Weighing 15 tons and standing 17 foot tall, Megabots are a cross between Robot Wars on steroids and the ultimate demolition derby.

We piloted one for the first time.

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