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Timaeus in 2024

The AI Alignment Forum

Published on February 20, 2025 11:54 PM GMT TLDR: We made substantial progress in 2024: We published a series of papers that verify key predictions of Singular Learning Theory (SLT) [ 1 , 2 , 3 , 4 , 5 , 6 ]. We scaled key SLT-derived techniques to models with billions of parameters, eliminating our main concerns around tractability.

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QuickBooks Keeps Kantorei Singing

Tech Soup

The participants learn the foundations of choir singing, such as posture and breathing, vocal technique, and tone. They also learn theory, ear training, foreign language skills, and the study of music within a social context. It was founded in 1964 and has served hundreds of members over the years.

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Learning and Development Trends We Will Keep an Eye on in 2024

Gyrus

How will these trends influence learning efficiencies? Personalized learning experiences Personalized and adaptive learning is gaining traction in the L&D space, which is a welcome change from the traditional ‘one-size-fits-all’ approach. Learn how to leverage virtual reality to engage millennia’s.

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Learning and Development Trends We Will Keep an Eye on in 2024

Gyrus

How will these trends influence learning efficiencies? Personalized learning experiences Personalized and adaptive learning is gaining traction in the L&D space, which is a welcome change from the traditional ‘one-size-fits-all’ approach. Learn how to leverage virtual reality to engage millennia’s.

Trend 52
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Learning and Development Trends We Will Keep an Eye on in 2024

Gyrus

How will these trends influence learning efficiencies? Personalized learning experiences Personalized and adaptive learning is gaining traction in the L&D space, which is a welcome change from the traditional ‘one-size-fits-all’ approach. Learn how to leverage virtual reality to engage millennia’s.

Trend 52
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Research directions Open Phil wants to fund in technical AI safety

The AI Alignment Forum

Through these research directions, we aim to develop robust safety techniques that mitigate risks from AIs before those risks emerge in real-world deployments. Jailbreaks and unintentional misalignment : New techniques for finding inputs that elicit competent, goal-directed behavior in LLM agents that the developers clearly tried to prevent.

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AXRP Episode 40 - Jason Gross on Compact Proofs and Interpretability

The AI Alignment Forum

And for that, I think you need something like derandomization techniques, where the simplest example of this is that if you have a collection of random vectors in high dimensions, theyre almost always almost orthogonal. Which, I dont quite know what the upshot of that is, but its hopefully vaguely interesting.

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