GPT-3 is the third generation Generative Pre-trained Transformer machine learning model that was developed by OpenAI and released in November 2021. It is a deep learning neural network with well over 175 billion machine learning parameters. Wait… but what does this all mean? GPT-3 is a major game changer in the way that artificial intelligence produces written text. It's the closest AI has ever been to mimicking a human being.

Synthetic voices have become ubiquitous. They feed us directions in the morning, shepherd us through phone calls by day, and broadcast the news on smart speakers at night. And as the technology used to make them improves, these voices are becoming more and more human-sounding. This is the final frontier in synthetic speech: replicating not just what we say, but how we say it. Rupal Patel heads a research group at Northeastern University that studies speech prosody--the changes in pitch, loudness and duration that we use to convey intent and emotion through voice.

And a tool like this has many new uses, both good (from powering better chatbots to helping people code) and bad (from powering better misinformation bots to helping kids cheat on their homework). But when a new AI milestone comes along it too often gets buried in hype. Even Sam Altman, who co-founded OpenAI with Elon Musk, tried to tone things down: "The GPT-3 hype is way too much. It's impressive (thanks for the nice compliments!) but it still has serious weaknesses and sometimes makes very silly mistakes. AI is going to change the world, but GPT-3 is just a very early glimpse. We have a lot still to figure out."

No human, or team of humans, could possibly keep up with the avalanche of information produced by many of today's physics and astronomy experiments. Some of them record terabytes of data every day--and the torrent is only increasing. The Square Kilometer Array, a radio telescope slated to switch on in the mid-2020s, will generate about as much data traffic each year as the entire internet. Original story reprinted with permission from Quanta Magazine, an editorially independent publication of the Simons Foundation whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences. The deluge has many scientists turning to artificial intelligence for help. With minimal human input, AI systems such as artificial neural networks--computer-simulated networks of neurons that mimic the function of brains--can plow through mountains of data, highlighting anomalies and detecting patterns that humans could never have spotted.

Right now, I can open up Google Photos, type "beach," and see my photos from various beaches I've visited over the last decade. I never went through my photos and labeled them; instead, Google identifies beaches based on the contents of the photos themselves. This seemingly mundane feature is based on a technology called deep convolutional neural networks, which allows software to understand images in a sophisticated way that wasn't possible with prior techniques. In recent years, researchers have found that the accuracy of the software gets better and better as they build deeper networks and amass larger data sets to train them. That has created an almost insatiable appetite for computing power, boosting the fortunes of GPU makers like Nvidia and AMD.

There's already plenty of angst out there about the prospect of jobs lost to artificial intelligence, but this week, artists got a fresh reason to be concerned. A new "Rembrandt" painting unveiled in Amsterdam is not the work of the Dutch master Rembrandt van Rijn at all, but rather the creation of a combination of technologies including facial recognition, AI, and 3D printing. Essentially, a deep-learning algorithm was trained on Rembrandt's 346 known paintings and then asked to produce a brand-new one replicating the artist's subject matter and style. Dubbed "The Next Rembrandt," the result is a portrait of a caucasian male, and it looks uncannily like the real thing. One particularly interesting detail about The Next Rembrandt project, which was a collaboration among several organizations including Dutch bank ING and Microsoft, is how the algorithm chose the subject for its painting, since it had to be entirely new.

There's already plenty of angst out there about the prospect of jobs lost to artificial intelligence, but this week, artists got a fresh reason to be concerned. A new "Rembrandt" painting unveiled in Amsterdam is not the work of the Dutch master Rembrandt van Rijn at all, but rather the creation of a combination of technologies including facial recognition, AI, and 3D printing. Essentially, a deep-learning algorithm was trained on Rembrandt's 346 known paintings and then asked to produce a brand-new one replicating the artist's subject matter and style. Dubbed "The Next Rembrandt," the result is a portrait of a caucasian male, and it looks uncannily like the real thing. One particularly interesting detail about The Next Rembrandt project, which was a collaboration among several organizations including Dutch bank ING and Microsoft, is how the algorithm chose the subject for its painting, since it had to be entirely new.