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Category: robotics/AI – Page 1266

Circa 2015

New software being developed at MIT is proving able to autonomously repair software bugs by borrowing from other programs and across different programming languages, without requiring access to the source code. This could save developers thousands of hours of programming time and lead to much more stable software.

Bugs are the bane of the software developer’s life. The changes that must be made to fix them are often trivial, typically involving changing only a few lines of code, but the process of identifying exactly which lines need to be fixed can be a very time-consuming and often very frustrating process, particularly in larger projects.

But now, new software from MIT could take care of this, and more. The system, dubbed CodePhage, can fix bugs which have to do with variable checks, and could soon be expanded to fix many more types of mistakes. Remarkably, according to MIT researcher Stelios Sidiroglou-Douskos, the software can do this kind of dynamic code translation and transplant (dubbed “horizontal code transplant,” from the analogous process in genetics) without needing access to the source code and across different programming languages, by analyzing the executable file directly.

Continue reading “MIT system can fix your software bugs on its own (by borrowing from other software)” | >

What does the future of AI look like? Let’s try out some AI software that’s readily available for consumers and see how it holds up against the human brain.

🦾 AI can outperform humans. But at what cost? 👉 👉 https://cybernews.com/editorial/ai-can-outperform-humans-but-at-what-cost/

Whether you welcome our new AI overlords with open arms, or you’re a little terrified about what an AI future may look like, many say it’s not really a question of ‘if,’ but more of a question of ‘when.’

Okay, you’ve got AI technologies on a small scale to a grand scale. From Siri — self-driving cars, text generators — humanoid robots, but what really is the real threat? As far back as 2013, Oxford University (ironically) used a machine-learning algorithm to determine whether 702 different jobs throughout America could turn automated, this found that a whopping 47% could in fact be replaced by machines.

Continue reading “Watch: 🤖 🤖 Will AI become an “existential threat?”” | >

https://youtu.be/QEy2tZu25UM

The Swiss company called K-Team invented a new kind of robot! The engineering team took as a basis the swarm intelligence of ants and created the kilobot swarm. Each of the devices follows a small set of rules, but when placed together, they mold into some sort of a universal mind clever enough to solve complex tasks. In the future, this system will be able to unify not only kilobots but other robots too, the ones we can see only at exhibitions for now.

What will happen if they start swarming around cities of the future all at once? Which robots would come to our aid during the worst disasters? Why is this piece of magnetic slime learning how to sneak into your intestines? And how will robots change our lives in a real city of the future?

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Staff Scientist Daniele Filippetto working on the High Repetition-Rate Electron Scattering Apparatus. (Credit: Thor Swift/Berkeley Lab)

– By Will Ferguson

Scientists have developed a new machine-learning platform that makes the algorithms that control particle beams and lasers smarter than ever before. Their work could help lead to the development of new and improved particle accelerators that will help scientists unlock the secrets of the subatomic world.

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With our brand new documentary premiering at #SIGGRAPH 2022, you’ll get to take a look behind the scenes of the 2022 Spring GTC and discover how NVIDIA’s creative, engineering, and research teams pushed the limits of NVIDIA GPUs, AI, USD, and @NVIDIA Omniverse to deliver our most watched GTC ever.

Global Documentary Premiere: Wednesday, August 10, at 10:00 a.m. PT

Add the event to your calendar: https://nvda.ws/3z9kltq

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Energy, mass, velocity. These three variables make up Einstein’s iconic equation E=MC2. But how did Einstein know about these concepts in the first place? A precursor step to understanding physics is identifying relevant variables. Without the concept of energy, mass, and velocity, not even Einstein could discover relativity. But can such variables be discovered automatically? Doing so could greatly accelerate scientific discovery.

This is the question that researchers at Columbia Engineering posed to a new AI program. The program was designed to observe through a , then try to search for the minimal set of fundamental variables that fully describe the observed dynamics. The study was published on July 25 in Nature Computational Science.

The researchers began by feeding the system raw video footage of phenomena for which they already knew the answer. For example, they fed a video of a swinging double pendulum known to have exactly four “state variables”—the angle and of each of the two arms. After a few hours of analysis, the AI produced the answer: 4.7.

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A chess-playing robot fractured the finger of its 7-year-old opponent during a tournament in Moscow last week.

The incident happened after the boy hurried the artificial intelligence-powered robot, the president of the Moscow Chess Federation told the Russian state news agency Tass. “The robot broke the child’s finger — this, of course, is bad,” Sergey Lazarev said.

Video of the incident, which occurred at the Moscow Chess Open competition Tuesday, went viral on social media after a post by the local outlet Baza News.

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