But they will be wingmen, not squadron leaders
CLASSIC DOGFIGHTS, in which two pilots match wits and machines to shoot down their opponent with well-aimed gunfire, are a thing of the past. Guided missiles have seen to that, and the last recorded instance of such combat was 32 years ago, near the end of the Iran-Iraq war, when an Iranian F-4 Phantom took out an Iraqi Su-22 with its 20mm cannon.
But memory lingers, and dogfighting, even of the simulated sort in which the laws of physics are substituted by equations running inside a computer, is reckoned a good test of the aptitude of a pilot in training. And that is also true when the pilot in question is, itself, a computer program. So, when America’s Defence Advanced Research Projects Agency (DARPA), an adventurous arm of the Pentagon, considered the future of air-to-air combat and the role of artificial intelligence (AI) within that future, it began with basics that Manfred von Richthofen himself might have approved of. Read More
Daily Archives: November 16, 2020
AI is wrestling with a replication crisis
Tech giants dominate research but the line between real breakthrough and product showcase can be fuzzy. Some scientists have had enough.
Last month Nature published a damning response written by 31 scientists to a study from Google Health that had appeared in the journal earlier this year. Google was describing successful trials of an AI that looked for signs of breast cancer in medical images. But according to its critics, the Google team provided so little information about its code and how it was tested that the study amounted to nothing more than a promotion of proprietary tech.
“We couldn’t take it anymore,” says Benjamin Haibe-Kains, the lead author of the response, who studies computational genomics at the University of Toronto. “It’s not about this study in particular—it’s a trend we’ve been witnessing for multiple years now that has started to really bother us.” Read More
System brings deep learning to “internet of things” devices
Advance could enable artificial intelligence on household appliances while enhancing data security and energy efficiency.
Deep learning is everywhere. This branch of artificial intelligence curates your social media and serves your Google search results. Soon, deep learning could also check your vitals or set your thermostat. MIT researchers have developed a system that could bring deep learning neural networks to new — and much smaller — places, like the tiny computer chips in wearable medical devices, household appliances, and the 250 billion other objects that constitute the “internet of things” (IoT).
The system, called MCUNet, designs compact neural networks that deliver unprecedented speed and accuracy for deep learning on IoT devices, despite limited memory and processing power. The technology could facilitate the expansion of the IoT universe while saving energy and improving data security. Read More
When it Comes to Data Transfer, 5G is Just the Beginning
f ever there was a technology tailor made for the world we currently live in, it’s 5G. Everything we do seems based on the need for speed and connectivity. High bandwidth and low latency enables hospital employees working in remote ICUs to communicate with, and quickly send information back to, their main campuses. 5G will also be invaluable in smart cities with densely packed networks of devices that need to communicate and share information in real-time. Then, there are the more everyday tasks that power our lives– a video conference here, a media streaming break there.
But while 5G has the potential to be the engine that moves all of the various bits and bytes around in these examples, what really happens with those bits and bytes? How do we take advantage of that 5G infrastructure? Read More
Defending against the cryptographic risk posed by quantum computing
The nation must address a significant future threat in the potential adversarial development and deployment of a quantum computer—a machine that extends the usual rules of computation via quantum physics. Such a deployment would potentially have grave impacts on the security of the United States and its citizens if the proper technical mitigations are not put in place. Now is the time to prepare—in four ways highlighted below—for the complex transition to post-quantum algorithms well before the advent of a quantum computer. Read More
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