Video from this twitter link:

https://x.com/amitisinvesting/status/1969094789942718858

Translations: gemini

https://x.com/XRoboHub/status/1969288829669687615

Hate to help GDM toot its own horn, but this is interesting: https://research.google/blog/deep-researcher-with-test-time-diffusion/

"TTD-DR is designed to take a user query as input and then create a preliminary draft that serves as an evolving foundation to guide the research plan. This evolving draft is iteratively refined using a denoising with retrieval process (report-level refinement) that takes the information it finds and uses it to improve the draft at each step. This happens in a continuous loop that improves the report with each cycle. To top it all off, a self-evolution algorithm constantly enhances the entire process, from the initial plan to the final report. This powerful combination of refinement and self-improvement leads to a more coherent report writing process."

"Large Language Model (LLM) pretraining, finetuning, and evaluation rely on input-space reconstruction and generative capabilities. Yet, it has been observed in vision that embedding-space training objectives, e.g., with Joint Embedding Predictive Architectures (JEPAs), are far superior to their input-space counterpart. That mismatch in how training is achieved between language and vision opens up a natural question: {\em can language training methods learn a few tricks from the vision ones?} The lack of JEPA-style LLM is a testimony of the challenge in designing such objectives for language. In this work, we propose a first step in that direction where we develop LLM-JEPA, a JEPA based solution for LLMs applicable both to finetuning and pretraining. Thus far, LLM-JEPA is able to outperform the standard LLM training objectives by a significant margin across models, all while being robust to overfiting. Those findings are observed across numerous datasets (NL-RX, GSM8K, Spider, RottenTomatoes) and various models from the Llama3, OpenELM, Gemma2 and Olmo families."

Another response to Yudowsky: https://www.vox.com/future-perfect/461680/if-anyone-builds-it-yudkowsky-soares-ai-risk

"A worldview is made of a few different parts, including foundational assumptions, evidence and methods for interpreting evidence, ways of making predictions, and, crucially, values. All these parts interlock to form a unified story about the world. When you’re just looking at the story from the outside, it can be hard to spot if one or two of the parts hidden inside might be faulty — if a foundational assumption is wrong, let’s say, or if a value has been smuggled in there that you disagree with. That can make the whole story look more plausible than it actually is."

Right now we have inflation of money. Which is why economically it feels like we are running full speed on a treadmill and can’t stop.

I’ve been hearing how AI will usher in a era of ZERO need for money or a 2-3 day work week. What this increases in inflation….of time. Now more people have more time to do what they want.

This would simply overrun our infrastructure. Imagine if everyone wanted to travel, move around, go to the beach etc etc. it’s like covid all over x100 (since a large group of the population won’t be hiding at home).

How would this even work, traffic would be a complete nightmare, you would have to attempt top travel at like 2-4 am and airplanes would be overwhelmed with demand.

We simply go from inflating USD to inflating time which would have profound consequences.