MIT announced its 35 under 35 for this year. The list is published by the MIT Technology Review. "Progress in AI has been breathtaking in the past year. "These innovators are employing it to redefine entire fields and to make sure it's safe to use", stated the report.

Sharon Li, an assistant professor at the University of Wisconsin, Madison; Connor Coley, assistant professor of chemical engineering and computer science at MIT; Catherine De Wolf, assistant professor in architecture at ETH Zurich; Alhussein Fawzi, Google DeepMind; Sasha Luccioni, researcher at the AI startup Hugging Face; Pranav Rajpurkar, assistant professor of biomedical informatics at Harvard Medical School; Irene Solaiman, Hugging Face; and Richard Zhang senior research scientist at Adobe are grouped by MIT for their contributions in the field of AI among many others.

The research focus of these AI evangelists ranges from sustainable development to the field of medicine. 

Sharon Li pioneered an AI safety feature called out-of-distribution (OOD) detection. This feature, she says, helps AI models determine when they should abstain from action if faced with something they weren't trained on. Connor Coley developed open-source software that uses artificial intelligence to help discover and synthesize new molecules. The suite of tools, called ASKCOS, is used in production by over a dozen pharmaceutical companies and tens of thousands of chemists to create new medicines, materials, and more efficient industrial processes.

Catherine De Wolf is using AI to help reduce emissions and waste of materials in the construction industry. Her goal is to aid the transition away from a one-time-use building philosophy, where materials used in construction are discarded when a building is torn down. Alhussein Fawzi is pioneering game-playing AI to speed up fundamental computations. Sasha Luccioni, a researcher at the AI startup Hugging Face, has developed a better way for tech companies to estimate and measure the carbon footprint of AI language models.

Sasha Luccioni has developed a better way for tech companies to estimate and measure the carbon footprint of AI language models. Pranav Rajpurkar has developed a way for AI to teach itself to accurately interpret medical images without any help from humans.

Irene Solaiman continues her work to build clear, standardized processes for how future AI models are released. Richard Zhang, a senior research scientist at Adobe, invented the visual similarity algorithms underlying image-generating AI models like Stable Diffusion and Stylegan. 

The major categories under which the innovators are grouped include AI, climate and energy, computing, biotechnology and robotics.