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Fortune

Fortune reporter Trey Williams spotlights alumnus Alexandr Wang, co-founder of Scale AI, a “software company that tags text, images, and videos to help companies improve the data used to train AI algorithms.”

Marketplace

Prof. Zeynep Ton speaks with Marketplace host Meghan McCarty Carino about the impact of automation, such as self-service kiosks or chatbot customer service agents, on retail shopping. When thinking about self checkout stations and chatbots, Ton recommends companies evaluate whether the technologies can “improve value for the customer? And would this improve productivity for employees and make their jobs better so that they can serve the customers much better too.”

The Boston Globe

Boston Globe reporters Aaron Pressman and Jon Chesto spotlight Liquid AI, a new startup founded by MIT researchers that is developing an AI system that relies on neural-network models that are “much simpler and require significantly less computer power to train and operate” than generative AI systems. “You need a fraction of the cost of developing generative AI, and the carbon footprint is much lower,” explains Liquid AI CEO Ramin Hasani, a research affiliate at CSAIL. “You get the same capabilities with a much smaller representation.”

CNBC

Prof. Daron Acemoglu speaks with CNBC about the potential impact of AI in the workplace. “I think the incentive in the industry… especially with the idea that you have to dominate the market by becoming the largest players, I think those are not helping because those are making us rush down the easiest road, the lowest resistance path, which is often automation,” says Acemoglu. “I don’t think that is going to get us the kind of aspirations that are articulated where we can make blue collar workers, electricians, nurses, teachers much more capable because we have given them tools to be better workers and to make much higher quality services.”

TechCrunch

Prof. Daniela Rus, director of CSAIL, and research affiliates Ramin Hasani, Mathias Lechner, and Alexander Amini have co-founded Liquid AI, a startup building a general-purpose AI system powered by a liquid neural network, reports Kyle Wiggers for TechCrunch. “Accountability and safety of large AI models is of paramount importance,” says Hasani. “Liquid AI offers more capital efficient, reliable, explainable and capable machine learning models for both domain-specific and generative AI applications." 

Scientific American

Researchers from MIT and elsewhere have developed a new AI technique for teaching robots to pack items into a limited space while adhering to a range of constraints, reports Nick Hilden for Scientific American. “We want to have a learning-based method to solve constraints quickly because learning-based [AI] will solve faster, compared to traditional methods,” says graduate student Zhutian “Skye” Yang.

Politico

Writing for Politico, MIT Prof. Armando Solar-Lezama and University of Texas at Austin Prof. Swarat Chaudhuri examine the recent executive order on AI. “Especially as new ways to train models with limited resources emerge, and as the price of computing goes down,” they write, “such regulations could start hurting the outsiders — the researchers, small companies, and other independent organizations whose work will be necessary to keep a fast-moving technology in check.”

Curiosity Stream

Four faculty members from across MIT - Professors Song Han, Simon Johnson, Yoon Kim and Rosalind Picard - speak with Curiosity Stream about the opportunities and risks posed by the rapid advancements in the field of AI. “We do want to think about which human capabilities we treasure,” says Picard. She adds that during the Covid-19 pandemic, “we saw a lot of loss of people's ability to communicate with one another face-to-face when their world moved online. I think we need to be thoughtful and intentional about what we're building with the technology and whether it's diminishing who we are or enhancing it.”

TechCrunch

Prof. Russ Tedrake and Max Bajracharya '21 MEng '21 speak with TechCrunch reporter Brian Heater about the impact of generative AI on the future of robotics. “Generative AI has the potential to bring revolutionary new capabilities to robotics,” says Tedrake. “Not only are we able to communicate with robots in natural language, but connecting to internet-scale language and image data is giving robots a much more robust understanding and reasoning about the world.”

The Daily Beast

Researchers from MIT and elsewhere have developed a new 3D printing process that “allows users to create more elastic materials along with rigid ones using slow-curing polymers,” reports Tony Ho Tran for the Daily Beast. The researchers used the system to create a, “3D printed hand complete with bones, ligaments, and tendons. The new process also utilizes a laser sensor array developed by researchers at MIT that allows the printer to actually ‘see’ what it’s creating as it creates it.”

Fortune

Principal Research Scientist Andrew McAfee discussed the impact of artificial intelligence and technology on businesses at the Fortune CFO Collaborative, reports Sheryl Estrada for Fortune. Generative AI is “going to diffuse throughout the economy,” said McAfee. “It’s going to separate winners from losers, and it’s going to turbocharge the winners faster than you and I have been expecting.”  

The Economist

The Economist reporter Rachel Lloyd predicts a “distinct change” in topics for bestselling books in 2024. Lloyd predicts artificial intelligence will take a lead, spotlighting “The Heart and Chip: Our Bright Future with Robots,” by Prof. Daniela Rus, director of CSAIL, as a leading example of the shift.

The Wall Street Journal

Prof. David Rand speaks with Wall Street Journal reporter Christopher Mims about the impact of generative AI on the spread of misinformation. “When you show people deepfakes and generative AI, a lot of times they come out of the experiment saying, ‘I just don’t trust anything anymore,’” says Rand.