Recent submissions

Comment · 4 days ago
Would you address other concerns voiced above? They are pretty serious points or allegations. Also, a PCB sourcing should not require a custom NDA when the selling point is convenience, legal protection, and speed vis-a-vis overseas sourcing.
Comment · 1 month ago
I hesitate to recast the discussion in a negative tone, but this doesn't sound right on technical terms.

Is World Labs' Atlas genuinely novel? Their demos do not seem to be better than the existing state of the art.

Fei Fei Li has been criticized even in the ImageNet days as a shower than a doer. Her roadshow past two years extolling "world model" in vague terms didn't show much insight, and her company's demo seems to merely rehash what has been available in the field for years. If you haven't seen the current SoTA in Gaussian splats, then World Labs' demos may seem cool, but they are mostly standard in the field now. If someone is more familiar with the inner workings of World Labs, I am happy to be corrected (but inner details wouldn't change the fact that demos are no better than SoTA).

I really had high hopes for World Labs, but I am quite saddened to realize that perhaps all this was just a financial maneuver and the detractors were right from the beginning.

source: I used to be in the downstream field: Gaussian spats for robotics. The exact field that World Labs' is supposed to help.

Comment · 1 month ago
This was an interesting overview. Thank you.

A minor correction: both the original Cheetah and Mini Cheetah motor designs were QDDs and were using BLDCs. The innovation was from using a off-the-shelf BLDC model as much as possible instead of a custom-design/modify one. Moreover the placement of electronics and gearbox was much more compact, leading to the modern day design. If any thing, the original Cheetah motors were actually simpler than those in Mini Cheetah.

Comment · 2 months ago
A human victory by sheer willpower. I find the story oddly uplifting.
Comment · 3 months ago
Better yet, the Viets became communist in name only and actually quite capitalist. Moreover, they don't like the Chinese in the north, their former ally in the war.

Wouldn't it be great if Iran becomes our friend and trade partner in two decades?

Comment · 3 months ago
Could you share the specs of your laptop?
Comment · 3 months ago
Is your Qwen3.6 locally run on your laptop? What kind of tokens/s are you getting from your laptop GPU?
Comment · 3 months ago
Your answer shows why flat surfaces were acceptable for a bomber (with an asterisk) given the constraints.

Then, the question becomes why is the B-2 bomber (and latest stealth fighter jets) not angular like F 117.

Scientific computing has come a long way since the days of F-117. We do not need flat surfaces to scatter the beams away. Finding optimal curved surfaces that scatter the beams away is just a harder math problem.

Comment · 3 months ago
The whole mirror analogy for angular facets breaks down when you realize airplane is a moving object and at some point in its trajectory, one of the facets is likely to be facing the radar (maximum cross section).

If I remember from my numerical analysis days, it was the ease of numerical computing that necessitated the facets. Think 3D graphics from the 90s. All polygons.

Comment · 4 months ago
> The numbers seem to agree. According to its SEC filing, “in part helped by progress in AI, revenue per full-time equivalent Spooner increased from $1.12 million in 2023 to $2.57 million in 2025, and was $0.97 million in Q1 2026.”

Is there a typo somewhere?

Comment · 4 months ago
There are so many derisive comments here.

David Ha, CEO and co-founder, was one of the youngest managing director at Goldman Sachs before doing ML at Google. His ML publications were considered top-notch almost a decade ago. I had high hopes for him when he raised money and founded Sakana.

I do agree with some comments here that perhaps this particular product is not well thought out. I also agree with the criticism that David calls Sakana a frontier AI lab while making money just selling AI B2B applications to Japanese businesses. I also agree with the assessment that Sakana has abrasive and antagonistic, sometimes openly hostile, recruiting tactics. I also agree that his then-impressive publications may have lost their luster in the age of LLMs.

However, the man is clearly driven; and he and his team may have more to offer in future. I admire the man for not taking the conventional AI-research career path.

Comment · 6 months ago
There could be geometrically tiny optimizations that lead to an outsized impact in noise and flow by turbulence reduction. While optimizing an impeller with computational FSI (fluid structure interaction) is not as hard as before, it still is not trivial. And it's these (perhaps small) optimizations that justify Noctua being 5x more expensive than generic black fan.
Comment · 6 months ago
Interesting. This observation only reinforces the hypothesis that my colleague had. Well optimized components procured with exclusivity.
Comment · 6 months ago
No, not Rentech. While Rentech is truly marvelous, it has been around for a while. There is a new kid in town, and this kid is very very good. To the point that it drove out other veteran shops out of the same market it traded.
Comment · 6 months ago
I have an interesting discussion with a senior colleague: why ASML? why are they by far the best? Their competitors are a few generations behind.

The colleague claimed that there is no special magic. It's not that ASML is using some otherwise unknown laws of physics nor is any single step or component particularly special or novel. It's just that they meticulously optimized each step, and the sum of such steps is the winning solution.

In fact, this is probably why it's so hard to copy ASML. If there was a single magic component, a single or few engineers could be poached away to a competitor to copy it. However, copying a well-optimized company with many simultaneous optima is a much harder task.

Our discussion was in the context of why our quant hedgefund competitor was performing so well, far above the market norm. By nature and design, quant finance is an incredibly efficient field (and most techniques are more or less known by veterans), and we had thought unlikely that one fund could do so much better. Our conclusion was that this fund must be the well-optimized ASML of our field. My colleague happened to know the founder and indeed that was his personal impression as well.

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