Lifeboat Foundation

The study, authored by five MIT researchers and titled Beyond AI Exposure, delves deep into the practicalities of replacing human labor with AI in the US, focusing on tasks that lend themselves to computer vision, such as those performed by teachers, property appraisers, and bakers.

Like many of us, you might find yourself nodding to a familiar digital doomsday chorus that vibrates through offices and coffee shops alike: AI will take my job!

Continue reading “Rethinking AI’s impact: Study reveals economic limits to job automation” »

A team of MIT researchers has found that in many instances, replacing human workers with AI is still more expensive than sticking with the people, a conclusion that flies in the face of current fears over the technology taking our jobs.

As detailed in a new paper, the team examined the cost-effectiveness of 1,000 “visual inspection” tasks across 800 occupations, such as inspecting food to see whether it’s gone bad. They discovered that just 23 percent of workers’ total wages “would be attractive to automate,” mainly because of the “large upfront costs of AI systems” — and that’s if the automatable tasks could even “be separated from other parts” of the jobs.

That said, they admit, those economics may well change over time.

Will AI automate human jobs, and — if so — which jobs and when?

That’s the trio of questions a new research study from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), out this morning, tries to answer.

There’s been many attempts to extrapolate out and project how the AI technologies of today, like large language models, might impact people’s’ livelihoods — and whole economies — in the future.

Artificial intelligence models can now replicate independently new AI systems without any human intervention, according to scientists of the project.

A scientific collaboration between Aizip Inc., the Massachusetts Institute of Technology, and several University of California campuses has made a breakthrough in using larger AI models that can create smaller AI models.

OATH OF OFFICE: DID BIDEN FULFILL HIS PROMISE TO RESTORE THE ECONOMY?

On Thursday, Meta CEO Mark Zuckerberg described the company’s efforts at achieving artificial general intelligence.

WASHINGTON — The U.S. needs to flex its space muscles in the face of China’s lunar ambitions, argues a new report from the Mitchell Institute for Aerospace Studies released Jan. 17.

More specifically, the U.S. military should step up collaboration with NASA and support the development of infrastructure for scientific and economic activities in cislunar space, “as well as the means to secure those activities from potential threats such as territorial claims and irresponsible or hostile behavior,” writes Charles Galbreath, senior fellow for space studies at the Mitchell Institute.

Cislunar space — the region of space between Earth and the orbit of the moon — is becoming increasingly important strategically and economically due to potential lunar exploration, space mining and other commercial efforts poised to ramp up in the coming years.

For example, the New York Times states: “The AI industry this year is set to be defined by one main characteristic: A remarkably rapid improvement of the technology as advancements build upon one another, enabling AI to generate new kinds of media, mimic human reasoning in new ways and seep into the physical world through a new breed of robot.”

Ethan Mollick, writing in his One Useful Thing blog, takes a similar view: “Most likely, AI development is actually going to accelerate for a while yet before it eventually slows down due to technical or economic or legal limits.”

The year ahead in AI will undoubtedly bring dramatic changes. Hopefully, these will include advances that improve our quality of life, such as the discovery of life saving new drugs. Likely, the most optimistic promises will not be realized in 2024, leading to some amount of pullback in market expectations. This is the nature of hype cycles. Hopefully, any such disappointments will not bring about another AI winter.

(Bloomberg) — Google DeepMind, Alphabet Inc.’s research division, said it has taken a “crucial step” towards making artificial intelligence as capable as humans. It involves solving high-school math problems. Most Read from BloombergWall Street Dials Back Fed Wagers After Solid Data: Markets WrapMusk Pressures Tesla’s Board for Another Massive Stock AwardChina’s Economic Growth Disappoints, Fueling Stimulus CallsChina Population Extends Record Drop on Covid Deaths, Low BirthsApple to Allow Outsi.

New advancements in technology frequently necessitate the development of novel materials – and thanks to supercomputers and advanced simulations, researchers can bypass the time-consuming and often inefficient process of trial-and-error.

The Materials Project, an open-access database founded at the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) in 2011, computes the properties of both known and predicted materials. Researchers can focus on promising materials for future technologies – think lighter alloys that improve fuel economy in cars, more efficient solar cells to boost renewable energy, or faster transistors for the next generation of computers.