t_serpico

Well put. I ultimately view observational studies as hypothesis generators that can spur research into more targeted questions all the way down to the biochemical level.

On average yes, but I tend to agree that the 'jock' tech worker is an archetype that didn't exist 20 years ago. Tech is no longer counterculture and has become a more high status profession in the eyes of the public. This is probably good for short term productivity but bad for long term innovation. I'm a big believer in the idea that the biggest innovations generally begin as low status or 'unsexy' endeavors.

lol

cute story, welcome to the world of healthcare.

Unifying clinical and biological data is an incredibly challenging task for a variety of reasons. Private sector is much more well suited to tackle such problems because of the engineering and coordination required.

I think renaming was a massive strategic mistake. The metaverse, even if it succeeds from a technical standpoint, will need to be deemed 'cool' for people to adopt it. And generally, if you have something cool, you don't prematurely blurt it out to the rest of the world.

To avoid waiting for consensus, how about we decide to each send a random color and in the next turn announce the color that is first alphanumerically? We each know our own color and the color our partner sent.

The “protein folding problem” consists of three closely related puzzles: (a) What is the folding code? (b) What is the folding mechanism? (c) Can we predict the native structure of a protein from its amino acid sequence? (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2443096/).

It seems the purist definition of solving protein folding means specifying the sequence of actions to arrive at the native structure for a given input sequence. This implies your solution is grounded in a physical reality. Such approaches (i.e MD simulations) have not been very successful to my knowledge and are computationally intractable for most proteins. Even if you are able to do this, how do you verify that your folding mechanism is in fact correct? We don't have ground truth experimental data at the temporal resolution one would want to verify such a prediction.

For now, the only practical framing of the protein folding problem is to predict a native structure given an input sequence. This is simply because we have the requisite data...

You pick up relatively quickly fingerings that work. It's a matter of intuition and pattern matching.

Great point. They're primed for this.

"I feel like these kinds of papers only exist to be cited in support of cheap rhetoric."

Agreed. The authors already made up their mind regarding the conclusion before writing the paper. This is an analysis that should be done by a group not involved in aging research so it's 'unbiased'.

To me, the interesting thing is not the specific results but rather that you can accurately predict crystal structures from sequence alone. This begets the question: what other physical biological properties can we predict?

I wouldn't really consider this company a 'moonshot', unless you want to label all drug discovery company moonshots.

True, and the exact same thing can be said about classical music. The average person needs some sort of framework to learn the art form. And yes, this is more imitation than innovation, but nevertheless can serve as a framework for musical expression.

nice. glad to see this exists.

The question is why would you gossip on CH? My guess is that there is some excitement to 'getting caught' or just more generally doing it in public. It's like the equivalent of having a private conversation in a bar or coffee shop. Because of COVID, people turn to CH to replicate this experience. After COVID, I suspect this app will die out.

It would probably be safer for him to actually get covid than develop your own diy vaccine...

"The professional...must fight to preserve the naiveté that the layman already possesses" - a genius quote by Bill Evans that applies to more than just music.

Garbage is a strong word. I think there's definitely a moderate to strong correlation between h-index and quality of researcher. The downside with the h-index is that it also measures your ability to play the 'game' (i.e network, cite your peers, etc.), but I really see no way around that. You can also argue that this is an important skill to have. If you produce the most amazing research in the world and people don't cite you, that could point toward a number of red flags (e.g you're an asshole, your work isn't clear to understand, you don't appropriately cite your peers, etc.)

well said

ggplot >> matplotlib and dplyr >> pandas. its not even close imo.

Out of curiosity, why not?

Also, one important thing to realize is that AlphaFold was trained largely on proteins that we were able to crystallize. I'd be very curious to see how its performance fares as a function of 'ease of crystallization'.

Also, pharma does not really have a huge incentive to work on this problem. Solving the protein folding problem does not automatically translate to new drugs just in the same way CRISPR or DNA sequencing did not. It's another tool in the toolbox (which to be clear is a big deal).

You hit the nail on the head here.

This is true. If I wanted to have independent thoughts for things I believe basically because most people believe them, I would not have the time to do anything else. Some people have this drive and capacity but most don't.

That is fascinating. Could you point me towards some of his policies that benefit minorities? Genuinely interested. I'm also in agreement with you that most people who vote for Trump do so in spite of his character, not because of it.

Average revenue per user is about 3-4 times higher in the US than in Europe (slide 4). Any ideas why? Do we just have a proclivity to spend more or are we more influenced by advertising?

I generally agree with the author. I don't have hard evidence but basically feel that the culture, ethos, magic, whatever you want to call it is gone. Does this mean innovation is dead? Of course not! As the author pointed, it will just likely be more spread out.

Also, I think it's important to appreciate that the formation and growth of Silicon Valley was a remarkably special thing but was bound to eventually hit the diminishing returns phase of faster compute, faster internet, smarter software, etc. Silicon Valley started with a transformative and enabling technology (the transistor) and from there we built a remarkable hardware and software ecosystem over the span of a few decades around that technology. Those seem to be the two elements in order to 'replicate' SV: a transformative technology that spurs an ecosystem of technologies, all of which interconnect and benefit from each others innovation.

unrelated, but I browsed your company website and think the idea is brilliant (especially after reading this: https://onlinelibrary.wiley.com/doi/full/10.1111/acel.12737, which confirmed my initial speculation).