Lifeboat Foundation

News, analysis and opinion from the Financial Times on the latest in markets, economics and politics.

Elon Musk’s latest rocket—the most powerful ever built—would offer better economics than conventional craft.

In an era where artificial intelligence (AI) is reshaping the contours of technology, a groundbreaking initiative has emerged: the AI Alliance. The alliance is a consortium of leading organizations spanning various sectors — industry, academia, research, startups, and government–united in their commitment to fostering open innovation and open science in AI.

Created by IBM and Meta, the AI Alliance is a testament to the belief that open and transparent innovation is crucial for harnessing AI advancements in a way that prioritizes safety, diversity, and widespread economic opportunity.

At the heart of the AI Alliance’s mission is creating an open community that accelerates responsible AI innovation while ensuring scientific rigor and trust. The effort is action-oriented and distinctly international, reflecting the global nature of AI’s impact.

Nolej’s cofounder, Bodo Hoenen, used AI to help design an exoskeleton for his paralysed daughter, Lorelei.

The people who were most afraid of the risks of artificial intelligence decided they should be the ones to build it. Then distrust fueled a spiraling competition.

The potential impact of generative AI on the economy, society, and work is polarizing, swinging from the positive benefits of a technological revolution to doomsday scenarios. The authors have come to think about this issue as points on a spectrum and have created a sports analogy to help think about it: AI tools can range from steroids, to sneakers, to a coach, each representing a different relationship between human users and the technology. Steroids elevate short-term performance, but leave you worse off in the long term. AI-powered tools can instead be used to augment people’s skills and make them more productive — much like a good running sneaker. On the most desirable end of the spectrum, AI-powered tools can be used like a coach that improves people’s own capabilities. This framework can be used to help conceptualize how we might craft AI-based tools that enhance rather than diminish human capabilities.

Page-utils class= article-utils—vertical hide-for-print data-js-target= page-utils data-id= tag: blogs.harvardbusiness.org, 2007/03/31:999.368607 data-title= A Sports Analogy for Understanding Different Ways to Use AI data-url=/2023/12/a-sports-analogy-for-understanding-different-ways-to-use-ai data-topic= AI and machine learning data-authors= Jake M. Hofman; Daniel G. Goldstein; David M. Rothschild data-content-type= Digital Article data-content-image=/resources/images/article_assets/2023/11/Nov23_22_200404124-001-383x215.jpg data-summary=

Will next-gen tools be used as a steroid, sneaker, or coach?

“We’re looking at a race, a race between China, between IBM, Google, Microsoft, Honeywell,” Kaku said. “All the big boys are in this race to create a workable, operationally efficient quantum computer. Because the nation or company that does this will rule the world economy.”

It’s not just the economy quantum computing could impact. A quantum computer is set up at Cleveland Clinic, where Chief Research Officer Dr. Serpil Erzurum believes the technology could revolutionize the world of health care.

Quantum computers can potentially model the behavior of proteins, the molecules that regulate all life, Erzurum said. Proteins change their shape to change their function in ways that are too complex to follow, but quantum computing could change that understanding.

https://www.youtube.com/watch?si=bnXHwQIbHdyoSNV9&v=Ofv3…e=youtu.be

Computers, cars, mobile phones, toasters: countless everyday objects contain microchips. They’re tiny, unremarkable and cheap, but since the outbreak of the coronavirus pandemic, they’ve been at the center of a political and industrial tug of war.

Against the backdrop of the trade war between China and the US, “The Microchip War” spotlights all the aspects of this conflict. In the film, the world’s most influential actors in this industrial sector weigh in.

Continue reading “The global battle over microchips | DW Documentary” »

One of the big questions GiveDirectly is trying to answer is how to direct cash to low-income households. “Just give cash” is a fun thing to say, but it elides some important operational details. It matters whether someone gets $20 a month for two years or $480 all at once. Those add up to the same amount of money; this isn’t a Side Hustle King situation. But how you get the money still matters. A certain $20 every month can help you budget and take care of regular expenses, while $480 all at once can give you enough capital to start a business or another big project.

The latest research on the GiveDirectly pilot, done by MIT economists Tavneet Suri and Nobel Prize winner Abhijit Banerjee, compares three groups: short-term basic income recipients (who got the $20 payments for two years), long-term basic income recipients (who get the money for the full 12 years), and lump sum recipients, who got $500 all at once, or roughly the same amount as the short-term basic income group. The paper is still being finalized, but Suri and Banerjee shared some results on a call with reporters this week.

By almost every financial metric, the lump sum group did better than the monthly payment group. Suri and Banerjee found that the lump sum group earned more, started more businesses, and spent more on education than the monthly group. “You end up seeing a doubling of net revenues” — or profits from small businesses — in the lump sum group, Suri said. The effects were about half that for the short-term $20-a-month group.