A new algorithm takes pixelated images of faces and creates realistic-looking versions with up to 64 times the resolution.
Category: robotics/AI – Page 1728
OpenAI API
Posted in robotics/AI
We’re releasing an API for accessing new AI models developed by OpenAI. Unlike most AI systems which are designed for one use-case, the API today provides a general-purpose “text in, text out” interface, allowing users to try it on virtually any English language task. You can now request access in order to integrate the API into your product, develop an entirely new application, or help us explore the strengths and limits of this technology.
What does this have to do with AI self-driving cars?
AI Self-Driving Cars Will Need to Make Life-or-Death Judgements
At the Cybernetic AI Self-Driving Car Institute, we are developing AI software for self-driving cars. One crucial aspect to the AI of self-driving cars is the need for the AI to make “judgments” about driving situations, ones that involve life-and-death matters.
Autonomous weapons present some unique challenges to regulation. They can’t be observed and quantified in quite the same way as, say, a 1.5-megaton nuclear warhead. Just what constitutes autonomy, and how much of it should be allowed? How do you distinguish an adversary’s remotely piloted drone from one equipped with Terminator software? Unless security analysts can find satisfactory answers to these questions and China, Russia, and the US can decide on mutually agreeable limits, the march of automation will continue. And whichever way the major powers lead, the rest of the world will inevitably follow.
Military scholars warn of a “battlefield singularity,” a point at which humans can no longer keep up with the pace of conflict.
The human brain operates on roughly 20 watts of power (a third of a 60-watt light bulb) in a space the size of, well, a human head. The biggest machine learning algorithms use closer to a nuclear power plant’s worth of electricity and racks of chips to learn.
That’s not to slander machine learning, but nature may have a tip or two to improve the situation. Luckily, there’s a branch of computer chip design heeding that call. By mimicking the brain, super-efficient neuromorphic chips aim to take AI off the cloud and put it in your pocket.
The latest such chip is smaller than a piece of confetti and has tens of thousands of artificial synapses made out of memristors—chip components that can mimic their natural counterparts in the brain.
Deepfakes have struck a nerve with the public and researchers alike. There is something uniquely disturbing about these AI-generated images of people appearing to say or do something they didn’t.
With tools for making deepfakes now widely available and relatively easy to use, many also worry that they will be used to spread dangerous misinformation. Politicians can have other people’s words put into their mouths or made to participate in situations they did not take part in, for example.
That’s the fear, at least. To a human eye, the truth is that deepfakes are still relatively easy to spot. And according to a report from cybersecurity firm DeepTrace Labs in October 2019, still the most comprehensive to date, they have not been used in any disinformation campaign. Yet the same report also found that the number of deepfakes posted online was growing quickly, with around 15,000 appearing in the previous seven months. That number will be far larger now.
Driverless cars are coming, and they’re likely to make life on the road easier and more convenient — for some of us. But will they create new ethical problems?
AI Is The Brain’s Exoskeleton
Posted in cyborgs, robotics/AI
Humans have always looked for ways to work smarter. With a boost from AI, we can achieve more than ever before.
Duke University researchers have developed an AI tool that can turn blurry, unrecognizable pictures of people’s faces into eerily convincing computer-generated portraits, in finer detail than ever before.
Previous methods can scale an image of a face up to eight times its original resolution. But the Duke team has come up with a way to take a handful of pixels and create realistic-looking faces with up to 64 times the resolution, ‘imagining’ features such as fine lines, eyelashes and stubble that weren’t there in the first place.
“Never have super-resolution images been created at this resolution before with this much detail,” said Duke computer scientist Cynthia Rudin, who led the team.