Lifeboat Foundation

Google is consolidating its generative AI teams under the leadership of DeepMind to accelerate the development of more advanced models, building on previous consolidation efforts such as the merger of DeepMind and Brain last year.

A diss track featuring the apparent vocals of rapper Kendrick Lamar made its rounds on social media earlier this week, escalating the beef between him and Aubrey “Drake” Graham.

Now a 23-year-old musician who goes by the moniker Sly the Rapper has come forward, alleging he’s behind the viral track, which was titled simply “Freestyle.” And guess what? He says it was AI-generated.

Continue reading “Internet Fooled by AI-Generated Kendrick Lamar Diss Track” »

A new technique can be used to predict the actions of human or AI agents who behave suboptimally while working toward unknown goals.

MIT and other researchers developed a framework that models irrational or suboptimal behavior of a human or AI agent, based on their computational constraints. Their technique can help predict an agent’s future actions, for instance, in chess matches.

To build AI systems that can collaborate effectively with humans, it helps to have a good model of human behavior to start with. But humans tend to behave suboptimally when making decisions.

Intel says its new brain-like computer is significantly fast, energy-efficient and it has the potential to revolutionize future AI tools.

The world’s first fully AI-generated movie has been announced with the trailer for Next Stop Paris predictably containing one too many fingers.

TCLtv+ Studios is a brand new production team and its first release will be a short AI-generated romcom featuring professional voice actors and an original script but the imagery will be generated with AI tools.

Continue reading “The Trailer for the World’s First Fully AI-Generated Film is Here” »

Causal machine learning methods could be used to predict treatment outcomes for subgroups and even individual patients; this Perspective outlines the potential benefits and limitations of the approach, offering practical guidance for appropriate clinical use.

Here’s what the recent measurements suggest — and why it’s too soon to update models of the Universe’s distant future.

CWI senior researcher Sander Bohté started working on neuromorphic computing already in 1998 as a PhD-student, when the subject was barely on the map. In recent years, Bohté and his CWI-colleagues have realized a number of algorithmic breakthroughs in spiking neural networks (SNNs) that make neuromorphic computing finally practical: in theory many AI-applications can become a factor of a hundred to a thousand more energy-efficient. This means that it will be possible to put much more AI into chips, allowing applications to run on a smartwatch or a smartphone. Examples are speech recognition, gesture recognition and the classification of electrocardiograms (ECG).

“I am really grateful that CWI, and former group leader Han La Poutré in particular, gave me the opportunity to follow my interest, even though at the end of the 1990s neural networks and neuromorphic computing were quite unpopular”, says Bohté. “It was high-risk work for the long haul that is now bearing fruit.”

Spiking neural networks (SNNs) more closely resemble the biology of the brain. They process pulses instead of the continuous signals in classical neural networks. Unfortunately, that also makes them mathematically much more difficult to handle. For many years SNNs were therefore very limited in the number of neurons they could handle. But thanks to clever algorithmic solutions Bohté and his colleagues have managed to scale up the number of trainable spiking neurons first to thousands in 2021, and then to tens of millions in 2023.

Robin Hanson comments on Nick Bostrom’s new tome … has a great cover with a number of interesting questions and a subtitle that hints that it might address the meaning of life in a future where AI and robots can do everything. But alas, after much build up and anticipation, he leaves that question unanswered, with an abrupt oops, out of time on page 427. … He tries to address meaty topics like, what keeps life interesting? What is our purpose and meaning when the struggle is gone? Can fulfillment get full? But in each case, the pedagogy is more of a survey of all possible answers versus the much more difficult task of making specific predictions. (More)