A recent study of the car loans sector showed that a machine learning algorithm could make decisions that were 34% more profitable than salespeople in dealerships.
However exciting the technological developments may be, the task of reading and analyzing the Greek and Latin texts recovered from the papyri will fall to human beings.
The toll on wildlife from illegal fishing, bycatch and entanglement in fishing gear is likely underestimated, because it doesn’t account for ‘dark’ fishing vessels, a new study finds.
Danielle Williams, Arts & Sciences at Washington University in St. Louis
Enthusiasm for the capabilities of artificial intelligence – and claims for the approach of humanlike prowess –has followed a boom-and-bust cycle since the middle of the 20th century.
Traditionally dominated by the use of centralised, resource-intensive servers, machine learning is being democratised with the growth of “TinyML”, distinguished by its small size and low cost.
Artificial intelligence is everywhere, and the tech industry is racing along to develop ever more powerful AIs. Three scholars look ahead to the next chapter in this technological revolution.
Research suggests AI could diagnose depression from health records or even social media posts. And it could overcome GP bias when it comes to prescribing medications.
It’s the fourth most popular website in the world, but our new study shows toxic commentary can still thrive on Wikipedia. There’s a lot at stake if too many editors are driven away.
Researchers fed an advanced AI algorithm with satellite photographs to see if it could identify areas of poverty and it interpreted the data through abstract images.
The explosion of generative AI tools like ChatGPT and fears about where the technology might be headed distract from the many ways AI affects people every day – for better and worse.