bglazer

Yes this is on the 777x, which is in pre-production and flight testing, seeking approvals from the FAA

If we go in and just check the DNA for Downs or Parkinson's

You should consider reading the wikipedia page about Parkinson’s disease.

Yes exactly, there are good and bad things to spend money on. This is a bad way to spend money for the reasons I explained above.

He's hubristic and selfish. None of his "research" is going to benefit anyone (himself included), making this essentially a huge waste of time and resources. Bryan will die just like all the rest of us, despite being very rich and self-obsessed. He could spend his enormous wealth on supporting real research and proper studies on real diseases that hurt lots of people. Instead he's acting like just another huckster promising a fountain of youth. He does this using bombastic terms and taboo methods (e.g. using his son as a blood boy), in a way that's calculated to direct enormous public attention towards himself. The science he advocates for is sketchy at best and the results of all his "experiments" will tell us nothing because we can't reproduce his methods (his program allegedly costs >$1M per year), nothing is blinded or controlled, and N=1. He's a bad person who uses bad methods to glorify himself and now he probably gave himself an autoimmune disease. He deserves to be mocked.

You’re probably thinking about non-small cell lung cancers. Small cell lung cancer (SCLC) is still absolutely devastating. The most progress made on SCLC has just been getting people to stop smoking, as its almost exclusively a smoker’s disease.

Anyways, I studied SCLC in grad school and saw lots of scans of people with tumors from their heads to their feet, and saw the enormous resources dedicated to caring for SCLC patients and to searching for a cure. It’s hard to overstate how profoundly evil the cigarette companies were and still are. They got people (children) addicted knowing what was coming for them, knowing they were killing them in horrific ways. Now we all get to pay for that in funerals and tax dollars.

Gene names aren't really acronyms in the traditional sense. Often they were originally conceived as acronyms at the time of the gene's discovery and naming, but the original acronym frequently reflects an incomplete or factually wrong understanding of the gene. For example, TP53 is a very very important gene in cancer. TP53 originally meant Tumor Protein 53, where the 53 signified its molecular weight of 53 kilodaltons. The problem is that the experiment used to measure TP53's molecular weight was incorrect and TP53 actually weighs about 44 kilodaltons. Oops, now we're stuck with TP53 for eternity. There are a ton more examples of this.

So, in biology a gene's name is sometimes an acronym but it's meaning is generally forgotten

The whole article is just that someone got a spam political text about the Texas Senate GOP primary.

This is demonstrably untrue. IQ has increased consistently for decades, far faster than genetic factors can explain. Environmental factors like education, nutrition, and medical care are the obvious explanation.

Yeah I have been reading a lot of posts like this lately. Technical blog post clearly written by an LLM summarizing something vibe-coded. They always start using project-specific jargon right away and they never give you enough context or backstory to understand why this thing exists. It's seems very clearly to be a symptom of someone pointing an LLM at a repo and telling it "write a github page for this project".

It really shines through in pieces like this that LLM's have a severely constrained worldview and underdeveloped theory of mind. They can't imagine that a line like "A 200-line POC that goes from 0/5 to 5/5 in four proposer steps" means nothing to me as a subtitle for the page. After all "proposer steps" and "5/5" are *right there* in it's context. Surely everyone has "proposer steps" in their context, right?

Ah causal data! It’s a shame none of the scientists or statisticians thought of getting causal data. How would we get that? Well maybe we could just inject amyloid into a person’s brain. Or simply remove all the amyloid from a person’s brain. That should do it, right?

I mean an amyloid injection is wildly unethical and it’s also not the natural progression of Alzheimer’s. Removing amyloid is a simple matter of investing billions of dollars into drug development. Also how do you tell whether that was actually “causal” if the patients improve after plaque removal.

I mean come on, you have to work the evidence and the experimental tools that we actually have. This kind of epistemic puritanism doesn’t help anyone.

This is insane, I love it.

I work in this field. It’s more or less correct but kind of lacking in detail. Cancer is a property of all multicellular life. I think it’s best understood as the behavior of a dynamical system that loses the feedback control that keeps cell growth under control.

Check out this paper from the Lander lab: https://elifesciences.org/articles/61026

It’s a bit jargon heavy but it’s a nice case study in how tumor growth is controlled through all the same mechanisms that normal tissue growth uses. Even cells with an outright cancerous gene mutation are basically still just doing normal growth and development.

This is quite similar to how eLife does publishing. You still have to submit to them but they basically just add reviewer comments and an “eLife Assessment” that serves as the quality/curation signal rather than a binary publish/reject

If you're an influential figure at a top-5 department in your field ... you all hate $journal.

That's the problem, they don't hate these journals, they love them. Generally speaking they're old people who became influential by publishing in these journals. Their reputation and influence was built on a pile of Science and Nature papers. Their presentations all include prominent text indicating which figures came from luxury journals. If Science and Nature lose their prestige so do they (or at least that's what they think)

This was very apparent when eLife changed their publishing model. Their was a big outpouring of rage from older scientists who had published in eLife when it was a more standard "high impact" journal. Lots of "you're ruining your reputation and therefore mine".

I think we could understand consciousness perfectly and still find it divine. In fact, I think however it arises is probably so beautiful that it would be wrong not to call it divine. Of course not in a literal, theological sense, but I think the true deep complexity of the human brain and consciousness is worth the title.

We absolutely do know about the molecular pathways that cause smoking induced lung cancer. It’s TP53 and RB1 mutations (among many others). There are probably more than a hundred thousand published papers about precisely this question

a certain age range your eyes determine they've grown to the correct size based on how well they focus

A certain age -> which one? Why?

your eyes determine -> How? What molecular growth signaling pathways are involved? How do they integrate with your brain's visual processing centers and how does that relate to "how well [your eyes] focus". Is there a biomechanical signal from muscle stress or eye curvature?

How would you test this? You'd have to change this process somehow to show that the effect is real, but you obviously can't do that with humans, so you'd probably have to use mice, but their eyes are different, but how so?

Without any of this information, it's a nice "just-so" story about cavemen looking at the horizon, but not much more than that.

That's a lovely theory, if quite imprecise in terms of the actual biology of eye development. The actually important part of science (the part that requires a lot of expertise and judgement) is figuring out how to make that an actually testable hypothesis and then whether or not its true.

Why does focusing on nearer things cause myopia? See if you're curious at even a basic level, you'd realize that there are important *details* about stuff like this where it actually helps to have some actual subject matter expertise and knowledge.

I occasionally say please and thank you to ChatGPT for my own sake, not for the LLM's. They're sufficiently similar to humans that allowing myself to be a jerk subtly degrades myself and makes it more likely that I'm a jerk to real people.

Where were you doing this? Were you ever successful? How did you do it, like what were your tactics? So many questions!

I’ve never heard about modern people doing serious persistence hunting, except for a stunt that I read about years ago. I think it was organized by like Outside or some running publication that got pro marathoners to try and they failed because they didn’t know anything about hunting

I genuinely did not expect to see a robot handling clothing like this within the next ten years at least. Insanely impressive

I do find it interesting that they state that each task is done with a fine tuned model. I wonder if that’s a limitation of the current data set their foundation model is trained on (which is what I think they’re suggesting in the post) or if it reflects something more fundamental about robotics tasks. It does remind me of a few years ago in LLMs when fine tuning was more prevalent. I don’t follow LLM training methodology closely but my impression was that the bulk of recent improvements have come from better RL post training and inference time reasoning.

Obviously they’re pursuing RL and I’m not sure spending more tokens at inference would even help for fine manipulation like this, notwithstanding the latency problems with that.

So, maybe the need for fine tuning goes away with a better foundation model like they’re suggesting? I hope this doesn’t point towards more fundamental limitations on robotics learning with the current VLA foundation model architectures

This is a very tiring criticism. Yes, this is true. But, it's an implementation detail (tokenization) that has very little bearing on the practical utility of these tools. How often are you relying on LLM's to count letters in words?

He Jiankui is better known for performing the first germ-line (i.e. inheritable by children) genome editing of humans.

evolution doesn't care about us beyond reproduction age

This isn’t totally true, group/kin selection are important.

What?

Please don’t post chatgpt output

AlphaGo showed that RL+search+self play works really well if you have an easy to verify reward and millions of iterations. Math partially falls into this category via automated proof checkers like Lean. So, that’s where I would put the highest likelihood of things getting weird really quickly. It’s worth noting that this hasn’t happened yet, and I’m not sure why. It seems like this recipe should already be yielding results in terms of new mathematics, but it isn’t yet.

That said, nearly every other task in the world is not easily verified, including things we really care about. How do you know if an AI is superhuman at designing fusion reactors? The most important step there is building a fusion reactor.

I think a better reference point than AlphaGo is AlphaFold. Deepmind found some really clever algorithmic improvements, but they didn’t know whether they actually worked until the CASP competition. CASP evaluated their model on new Xray crystal structures of proteins. Needless to say getting Xray protein structures is a difficult and complex process. Also, they trained AlphaFold on thousands of existing structures that were accumulated over decades and required millenia of graduate-student-hours hours to find. It’s worth noting that we have very good theories for all the basic physics underlying protein folding but none of the physics based methods work. We had to rely on painstakingly collected data to learn the emergent phenomena that govern folding. I suspect that this will be the case for many other tasks.

Yudkowsky seems to believe in fast take off, so much so that he suggested bombing data centers. To more directly address your point, I think it’s almost certain that increasing intelligence has diminishing returns and the recursive self improvement loop will be slow. The reason for this is that collecting data is absolutely necessary and many natural processes are both slow and chaotic, meaning that learning from observation and manipulation of them will take years at least. Also lots of resources.

Regarding LLM’s I think METR is a decent metric. However you have to consider the cost of achieving each additional hour or day of task horizon. I’m open to correction here, but I would bet that the cost curves are more exponential than the improvement curves. That would be fundamentally unsustainable and point to a limitation of LLM training/architecture for reasoning and world modeling.

Basically I think the focus on recursive self improvement is not really important in the real world. The actual question is how long and how expensive the learning process is. I think the answer is that it will be long and expensive, just like our current world. No doubt having many more intelligent agents will help speed up parts of the loop but there are physical constraints you can’t get past no matter how smart you are.

Here's one: Yudkowsky has been confidently asserting (for years) that AI will extinct humanity because it will learn how to make nanomachines using "strong" covalent bonds rather than the "weak" van der Waals forces used by biological systems like proteins. I'm certain that knowledgeable biologists/physicists have tried to explain to him why this belief is basically nonsense, but he just keeps repeating it. Heck there's even a LessWrong post that lays it out quite well [1]. This points to a general disregard for detailed knowledge of existing things and a preference for "first principles" beliefs, no matter how wrong they are.

[1] https://www.lesswrong.com/posts/8viKzSrYhb6EFk6wg/why-yudkow...