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So smart! So talented! This week, I’m excited to introduce you to a new generation of brilliant minds working on some of the hardest problems in AI and beyond. You can read the full list of MIT Technology Review’s 35 Under 35 Innovators here.
We’ve already highlighted some of the most promising people in tech before they become household names. In 2002, the list included two young innovators named Larry Page and Sergey Brin from Google. Mark Zuckerberg, 23, was on the list in 2007. In 2008, we featured Andrew Ng, who wrote an excellent essay for us sharing his advice for aspiring innovators on testing, failure, and the future of technology. AI.
This year, we’ve seen tech companies rush to launch their newest, best-performing AI systems, often neglecting security and ethics.The AI scientists on this year’s list of innovators are more aware than ever of the damage the technology can pose and are determined to do something about it.They do this by developing new methods that help change the way the AI industry thinks about security.
Sharon Li,pictured above and our Innovator of the Year, is an assistant professor at the University of Wisconsin, Madison. She created a remarkable AI security feature called off-distribution detection. This feature helps AI models determine if they should refrain from acting on something they haven’t been trained on. This is crucial as AI systems are deployed from the laboratory and encounter new situations in the messy real world.
Irene Solaiman,global director of public policy at Hugging Face, developed an approach that calls for tech companies to release new models in stages, giving them more time to test their failures and build in guardrails.
Many of our innovators are working to combat climate change.I was thrilled to see so many people on the list using their AI skills to solve the biggest problem facing humanity, either by helping the AI community track and reduce their emissions or by using AI to mitigate emissions in high-polluting industries.
Sasha Luccioni,an AI researcher at startup Hugging Face, has developed a better way for tech companies to estimate and measure the carbon footprint of AI language models.
Catherine DeWolffrom ETH Zurich uses AI to help reduce emissions and material waste in the construction sector.
Alhussein Fawzifrom DeepMind has developed a gaming AI to accelerate fundamental calculations, thereby reducing costs and saving power on devices.
This year’s innovators are also working on practical applications of AI that illustrate how the technology could become increasingly useful.They’re coming up with exciting new ways to use it to drive scientific research and create useful tools in other fields.
Lerrel Pintofrom New York University uses AI to help robots learn from their mistakes. He hopes this will lead to home robots that do much more than vacuum and could become more integrated into our daily lives.
Connor Coleyfrom MIT has developed open source software that uses artificial intelligence to help discover and synthesize new molecules.
Pranav Rajpurkarfrom Harvard Medical School has developed a way for AI to teach itself to accurately interpret medical images without any human assistance.
Richard Zhang, a principal researcher at Adobe, invented the visual similarity algorithms that underpin image-generating AI models such as Stable Diffusion and StyleGAN. Without his work, we wouldn’t have the image-generating AI that has captivated the world.
That’s not all!This year’s list is full of inspiring people and ideas for the next big breakthrough in robotics, computing, biotechnology, and climate and energy. Read the full list of this year’s young innovators here.
And finally, if you work in the field of AI and think you have exciting and cutting-edge things to share, contact us! We’re always interested in hearing from people doing interesting work.
DeepMind Co-Founder: Generative AI is just a phase. The next step is interactive AI.
DeepMind co-founder Mustafa Suleyman wants to create a chatbot that does much more than chat. Here is Suleyman’s speech: In the future, we will have what he calls interactive AI, that is, robots capable of carrying out the tasks you assign to them by involving others software and others to get things done. He founded a new billion-dollar company, Inflection, to build it.
Say again?Suleyman, who left DeepMind in 2022, has some… interesting… thoughts on the success of online regulation that border on naivety. (“It’s pretty hard to find radicalization content or terrorist material online. It’s pretty hard to buy guns and drugs online.”) Despite this, he remains serious and evangelical in his beliefs, and he is able to make great progress in the field. industry. He sat down with Will Douglas Heaven, MIT Technology Review’s AI editor, to discuss his plans and the need for strict regulation of AI. Learn more here.
Bits and bytes
AI just beat a human test of creativity. What does it mean?
A new study found that AI chatbots achieved higher average scores than humans in a test commonly used to assess human creativity. The results do not necessarily indicate that AIs are developing an ability to do something uniquely human. However, they could give us a better understanding of how humans and machines approach creative tasks. (MIT Technology Review)
This driverless car company uses chatbots to make its vehicles smarter
Self-driving car startup Wayve can now interrogate its vehicles, ask them questions about their driving decisions and get answers. The idea is to use the same technology as ChatGPT to help train driverless cars. (MIT Technology Review)
How Silicon Valley pessimists are shaping Rishi Sunak’s AI plans
British Prime Minister Rishi Sunak wants to boost the AI industry in his country. But in a short space of time, something changed in the UK’s approach. The country appears to be becoming a strong supporter of the AI doomsday narrative, thanks to intense lobbying from the effective altruist movement. (Policy)
The religion of AI in Silicon Valley
A thought-provoking article about something I too have observed in the tech space: technologists are increasingly weaving a narrative around AI and artificial general intelligence that is not so different religious stories. This story connects the dots.
How Generative AI Works
A great and useful visual explainer that is essential reading for anyone curious about AI. (The Financial Times)