In 2017, having just received his PhD in theoretical chemistry, John Jumper heard rumors that Google DeepMind had moved from gaming AI to a secret protein structure prediction project. He applied for a job.
Just three years later, Jumper and CEO Demis Hassabis led the development of an artificial intelligence system called AlphaFold 2, which was capable of predicting the structure of proteins down to the width of an atom, delivering lab-level precision and doing so many times faster, returning results in hours rather than months.
Jumper and Hassabis received the Nobel Prize in Chemistry last year. Now that the hype has died down, what impact has AlphaFold really made? How do scientists use it? So what next? To find out, I talked to Jumper (as well as several other scientists). Read the whole story.
—Will Douglas Heaven
The State of Artificial Intelligence: Chatbot Companions and the Future of Our Privacy
—Eileen Goh and Melissa Heikkilä
Even if you don't have an AI friend, you probably know someone who does. Recent research has shown that one of the main applications of generative artificial intelligence is communication: on platforms such as Character.AI, Replika or Meta AI, people can create personalized chatbots that will pose as ideal friends, romantic partners, parents, therapists or any other persona they can think of.
Some state governments are taking notice and are beginning to regulate related AI. But tellingly, one area that the laws don't address is user privacy. Read the whole story.
This is the fourth edition of The State of Artificial Intelligence, our collaboration between Financial Times And MIT Technology Review. Register here to get future episodes every Monday.
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