kidel001

Amen. (or erm maybe that is not the right response ;-D)

"days" -- laughs maniacally in biologist

I like that we are amazed by this. And yet all of my books from 34 years ago open up just fine (without cheating, no book opening emulator required!). I can even open a book on my shelf from 1896 without emulation. Not trying to troll too hard but I do think it is shocking how accustomed we've gotten to zero backwards compatibility in the world of software.

I am surprised they end on a gene mutation already known to be involved in a rare disease and a vague hypothesis about the mechanism. Among the many things DCTN1 does... it also directs autophagosomes toward lysosomes for waste degradation. Hm, disruptions in waste degradation.. build up of unwanted proteins and waste in cells... yeah that seems like it would cause neurodegeneration as well! Point being, there are dozens of things, maybe hundreds. Is cholesterol particularly compelling here? Not really. PhD students come up with similar hypotheses every hour. Hypotheses are cheap. I'm sure it can and will do better, but for now... I feel they might be underprepared for curing all disease in 10 years.

Well, when people say "organ on a chip" it sounds completely synthetic, but some organ-on-a-chip designs (and many organoid platforms) actually require the killing of untold numbers of mice to generate the matrix compounds. So that would just be an industrial obfuscation of who is doing the killing: now it is not the scientist doing all the killing but the Matrigel manufacturer. But to be fair, this will likely change over time as more synthetic approaches are developed. And the lung-on-a-chip described in this article does not use Matrigel. So I think it is actually a pretty good example of moving away from animal use in biomedical research.

The house called 12 of your 116 scored numbers: 10%.

Blind guessing would average about 12.9 of them (11%).

Only 2 of the 206 people in a psychology study were more random than you. The house found you extremely hard to read.

At first this was my take as well. That plus, well, maybe they are just on a serious PR kick with maths. But I am starting wonder if they have determined, or strongly suspect, that the road to exponential model improvement must first be paved with extraordinary improvements in math. Like in some sense this seems like a test case for where their true intensions might go: vast improvements in the efficiency / size / speed of models and their training. Hard to imagine trusting the models in all those spaces without first trusting them / training them to address new or unsolved math.

I too maintain an older thinkpad! i want to say T430 so probably not as old, maybe got in 2012 or so? In any case, I have replaced: the screen, the battery, the power button (3D printed), the hard drive, the RAM, and the entire internal fan /cooling structure, and probably some more things I've forgotten. Why? Well it's all been over the years. But 1) because you can! like this post describes. Also: it's been nice to have a windows system around that I can remote into for certain tasks that are difficult or impossible on linux, like using the adobe suite. The last time something broke (the fan) I looked up how much a used T430 costs on ebay (~$40-$50) and buying a new fan was still cheaper. So I fixed it. It's been like that every time and it's still here.

To add onto this... some amount of what they are calling edge detection here seems to overlap with what has already been implemented in microscopy using phase contrast... which has been around since 1932.

Technically... they are outlining edges at the speed of light. Detection is a separate process entirely.

Ah yes, the bird-inspired ... nose propeller.

These types of articles are so fundamentally flawed... it beggars belief. Why not ask the opposite question: if bandwidth works the way they describe, why can't H100 GPUs (3TB/s bandwidth) perform sensorimotor tasks 24 trillion times faster than a human? (Spoiler alert: they can not).

<s> Could it be... there is a bit of a straw man argument here? About how much information it actually takes to input and output a complete sensorimotor task? I dare say! </s

bioinformatician here. nobody has intuition or domain knowledge on all ~20,000 protein coding genes in the human body. That's just not a thing. Routinely comparing what a treatment does we do actually get 20,000 p-values. Feed that into FDR correction, filter for p < 0.01. Now I have maybe 200 genes.Then we can start applying domain knowledge. If you start trying to apply domain knowledge at the beginning, you're actually going to artificially constrict what is biologically possible. Your domain knowledge might say well there's no reason an olfactory gene should be involved in cancer, so I will exclude these (etc etc). You would be instantly wrong. People discovered that macrophages (which play a large role in cancer) can express olfactory receptors. So when I had olfactory receptors coming up in a recent analysis... the p values were onto something and I had to expand my domain knowledge to understand. This is very common. I ask for validation of targets in tissue --> then you see proof borne out that the p-value thresholding business WORKS.

People need tools to filter results. Using a somewhat arbitrary cutoff for what to work with is actually fine because people need to make decisions. Further, papers that report false positives do not tend to lead to huge branches of successful science because over time the findings do not replicate.

But I am curious about something else. I am not a statistical mechanics person, but my understanding of information theory is that something actually refined emerges with a threshold (assuming it operates on SOME real signal) and the energy required to provide that threshold is important to allow "lower entropy" systems to emerge. Isn't this the whole principle behind Maxwell's Demon? That if you could open a little door between two equal temperature gas canisters you could perfectly separate the faster and slower gas molecules and paradoxically increase the temperature difference? But to only open the door for fast molecules (thresholding them) the little door would require energy (so it is no free lunch)? And that effectively acts as a threshold on the continuous distributions? I guess what I am asking is that isn't there a fundamental importance to thresholds in generating information? Isn't that how neurons work? Isn't that how AI models work?