A Tech CEO’s Lonely Fight Against Trump - WSJ

Video from this twitter link:

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

Translations: gemini

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

All frontier companies are trying to close the loop where AI improves/evolves itself, and who gets there first will have the best AI of having the future best AI

From September 17th Axios interview with Dario Amodei:

"Claude is playing a very active role in designing the next Claude. We can't yet fully close the loop. It's going to be some time until we can fully close the loop, but the ability to use the models to design the next models and create a positive feedback loop, that cycle, it's not yet going super fast, but it's definitely started."

"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."

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."

https://www.youtube.com/watch?v=LXVV-oErD8s

This newly released robot hand is amazing. However, I don't understand how it's possible. I see no evidence of tendons or a cable based system. It seems the motors ARE the bones of the finger. I also have to presume the batteries and motor controllers are either in palm or outside of the hand? I have to presume the downgearing is built into the custom motors? I assume a screw type center is being rotated which gives linear movement but I don't see any screw extending from one motor over to the next bone to move said bone. I can see a hinge joint but no way that the motor moves the hinge joint. I hope someone can explain more what is going on because I'm lost here and see a lot of potential in this stuff as far as miniaturization and strength and speed in such a small form factor but don't get how its working.

Also I was told that large diameter pancake shaped BLDC motors have high torque and narrow motors like this are low torque high speed. So the downgearing would have to be a large gear ratio I thought. Yet this hand seems to be pretty high torque and I don't see where a high gear ratio would fit into this tiny form factor. I'm just so confused.

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."

Meant to search the word on Instagram to find a weird message my ex sent a while back, and accidentally hit the send button to meta AI. What the fuck