Ross Perot Jr. described the STEM education event as a “first-of-its-kind” across the country. The event comes days before Pres. Bush, Gov. Abbott, several Republican presidential candidates and executives from Amazon, Microsoft, Walmart and more gather at mobility summit.
We know less about the strength of the strong force than of any of the other fundamental forces of nature, but researchers at CERN have now made the most precise measurement of it ever.
By Leah Crane
To better understand how neural networks learn to simulate writing, researchers trained simpler versions on synthetic children’s stories.
As creative industries grapple with AI’s explosion into every artistic medium at once, separate calls from artists warning the world to take action before it’s too late are starting to converge. From fake Drake songs to stylized Instagram profile pictures, art conjured with newly sophisticated AI tools is suddenly ubiquitous — and so are conversations about how to rein in the technology before it does irrevocable harm to creative communities.
This week, digital rights organization Fight for the Future partnered with music industry labor group United Musicians and Allied Workers to launch #AIdayofaction, a campaign that calls on Congress to block corporations from obtaining copyrights on music and other art made with AI.
The idea is that by preventing industry behemoths like major record labels, for example, from copyrighting music made with the assistance of AI, those companies will be forced to keep looping humans into the creative process. But those same concerns — and the same potential strategies for pushing back against the onslaught of AI — exist across creative industries.
Generative AI, dominated by proprietary models locked inside big tech companies, is being disrupted by a new wave of open-source models.
Advocates argue open sourcing has vital benefits like enabling wider access, fostering innovation, and promoting transparency. Many people argue that open source will win in the marketplace.
But that conclusion is not obvious.
Continue reading “Generative AI Throwdown: Open Source Vs. Proprietary Models” »
“As I was racking my brains for a way to make keyboards more portable and fashionable, I had an aha moment. Carrying around a keyboard was a closed-minded idea.”
In yet another episode of “Cool stuff the Japanese come up with”, Google Japan has once again taken a playful detour from the mundane with its latest creation: the Gboard CAPS.
While this head-mounted keyboard integrated into a baseball hat may sound like the stuff of sci-fi or the whimsical fantasies of keyboard enthusiasts, the Gboard CAPS project is real, and designed with a delightful touch of humor.
It turns out there is a correlation between odors and colors that is quite commonplace.
An example of synesthesia, a perceptual phenomena when activation of one sensory or cognitive pathway results in involuntary experiences in another, is the idea of “smell color” or connecting odors with colors. In this situation, those who experience “smell-color synesthesia,” a particular form of synesthesia, may think that odors have corresponding colors.
Design Cells/iStock.
In order for robots to effectively partake in search and rescue operations, they need to effectively navigate obstacles in their way. One area that is particularly common and difficult to venture into is vegetation.
Robots typically use a combination of sensors to perceive their surroundings such as ultrasonic sensors, Lidar (Light Detection and Ranging), infrared sensors and camera systems. However, these are not often enough to allow robots to actually bypass the vegetation so commonly found in real outdoor environments.
That’s why engineers at Carnegie Mellon University are working on solving this particular dilemma.
These systems are based on nuclear fusion.
How do we get beyond our solar system? Current technologies simply can’t support this type of travel. However, speaking to Universe Today.
Shigemi Numazawa/ Project Daedalus.
Continue reading “How magnetic fusion plasma engines can take us to outer space” »
Instead of looking at individual neurons, they look at combinations of neurons that form patterns or features.
Artificial neural networks are like digital versions of our brains. They learn from data, not rules, and they can perform extraordinary tasks, from translating languages to playing chess. But how do they do it? What is the logic behind their calculations? And how can we trust them to be safe and reliable?
XH4D/iStock.
Continue reading “What makes AI brains tick? A study shows how to find out” »
