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Powerful new artificial intelligence models sometimes, quite famously, get things wrong—whether hallucinating false information or memorizing others’ work and offering it up as their own. To address the latter, researchers led by a team at The University of Texas at Austin have developed a framework to train AI models on images corrupted beyond recognition.
The future might see AI becoming an integral part of emotional support networks, providing companionship that feels empathetic and informed.Read More
What should you play next on your PS5 or PS4? From Fallout 4 to Ghost of Tsushima, Sony’s subscription service has a ton of great video games.
Artificial intelligence built on mountains of potentially biased information has created a real risk of automating discrimination, but is there any way to re-educate the machines?
I’ve spent years struggling to find a chair that conforms to my back, rather than the other way around. My search might be over.
This is a 60 percent keyboard with most of the perks of larger, more spacious boards.
Large language model-based chatbots can’t effectively recognize users’ motivation when they are hesitant about making healthy behavior changes, but they can support those who are committed to take action, say researchers.
By now, the challenges posed by generative AI are no secret. Models like OpenAI’s ChatGPT, Anthropic’s Claude and Meta’s Llama have been known to “hallucinate,” inventing potentially misleading responses, as well as divulge sensitive information, like copyrighted materials.
Ebooks, paperbacks, and hardcover editions are deeply discounted through May 20.
Noise-canceling headphones are a godsend for living and working in loud environments. They automatically identify background sounds and cancel them out for much-needed peace and quiet. However, typical noise-canceling fails to distinguish between unwanted background sounds and crucial information, leaving headphone users unaware of their surroundings.