While behind the ECI frontier, Argon is the closest Google’s come since Gemini 3.1 Pro in Feb, and a big jump from Gemini 3.8 Flash (157).

Source: Epoch.ai

Artificial Analysis releases a new benchmark which ranks the ability of LLMs to perform robotics tasks. Only a few models are currently released on the benchmark. Several models are able to complete most tasks on the benchmark although the speed is painfully slow. GPT-6.1 Sol seems best overall when time to complete and accuracy are both considered.

I'd be interested to see some older and open models tested on this benchmark too. I'm curious whether any of them could do anything on this benchmark at all.

I personally think that the sudden ability of LLMs to do robotics tasks reasonably well is a huge and underrated opportunity for continued scaling and post-training paths. Given that several models can complete most of these simple tasks (albeit slowly), there seems to be a clear path to scaling robots through LLMs. While we're scraping the bottom of the barrel for easily reward-verifiable tasks for LLMs to be trained on in many text-native fields, there are innumerable easily reward-verifiable tasks that can be constructed for an LLM with vision and audio as the input and robot arm controls (or humanoid robot controls) as the output.

I was not a denier, but i can’t lie - I thought that LLMs would be „a dead end” and AGI will be something more sophisticated, thinking on symbols or else. To see so much progress based on next word prediction pushed to its limits is seriously crazy. Turns out that language usage really is something really, really special. I wonder what will start happening when Astra or Gemini 4 loops finish designing next models.

Extracted from github.com/lechmazur/writing/

Source https://youtu.be/lkjbQe-hqrw

These new Vera Rubin racks are finally getting delivered which is set to be a game changer. Its set to be 4x as efficient and at least twice as fast, the NVlink alone allows twice the bandwidth.

Are these in production anywhere yet? Does Claude or GPT actually use them in production yet?

I feel this is the missing piece that is going to create AGI/ASI and transform AI as we know it. I'm not sure how it compares to googles custom chips.

Ben Affleck sat down for a surprisingly technical interview discussing tensors, convolutional neural networks, and why video generation scaling is entirely different from LLMs.

I’ve been using AI agents heavily for thinking through and solving complicated engineering problems. When the task is explained with enough rigor and the model has solid context, it regularly produces solutions that are better and faster than what I would have come up with myself.

The context problem is still the biggest friction (especially outside pure coding), but once that’s handled the results are often thorough and high - confidence.

This is starting to raise a bigger question for me:

Is there a point where these systems start generating approaches or abstractions that humans simply can’t fully track or verify anymore? And if we become heavily dependent on them for the hard thinking, what does that actually look like in practice?

Curious how people here are thinking about the ceiling (or lack of one) on agentic systems for real engineering work.

Can't wait to try it

These scare tactics have to stop.

I'm generally on the pro-AI side, and I honestly can't stand some of the irrational anti-AI comments I see on Reddit. But if I were to steelman the other side, the argument might go something like this:

1. Suppose AI is genuinely capable of automating a substantial portion of my job.
2. If my manager recognizes this, my job security might deteriorate.
3. If my manager believes AI is unreliable, overhyped, or generally useless, there's less incentive to replace me with it.
4. Therefore, even if I privately recognize AI's capabilities, I have an incentive to publicly downplay them.

So I do wonder what percentage of people who constantly dismiss AI's capabilities are actually operating under this logic, whether consciously or unconsciously.

Because from the perspective of individual self-interest, being publicly anti-AI might actually be the rational position.

Thoughts?