261–270 of 343 posts
Looks like science is out, black box prediction is in. It's like the era of epicycles all over again. Oh well. Fellow realists, see you all 1500 years from now!
There are things so complex in science that a human mind can never understand them, but a large neural network can.
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It also proved that deep learning models are a valid approach to bioinformatics - for all its flaws and shortcomings, AlphaFold solves arbitrary protein structure in minutes on commodity hardware, whereas previous approaches were, well, this: https://en.wikipedia.org/wiki/Folding@home A gap between biological research and biological engineering is that, for bioengineering, the size of the potential solution space and…
AlphaFold doesn’t work for engineering though. Getting a shitty answer ends up being worse than useless. It seems to really accelerate productivity of researchers investigating bio molecules or molecules very similar to existing bio molecules. But not de novo stuff.
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It’s fascinating how the affluent backgrounds of many famous scientists and entrepreneurs are downplayed. Eg Warren Buffet, Jeff Bezos, etc
Because having some degree of runway is almost always necessary but never sufficient. Thousands of Americans receive similar amounts of money from their parents in the form of inheritance of the family home and other major assets. Only one took windfall of that size and created Amazon.
I wonder if they are actually more likely to come from upper middle class (where parents are highly paid professionals) than the proper idle rich or even CEOs and company founders...
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It also proved that deep learning models are a valid approach to bioinformatics - for all its flaws and shortcomings, AlphaFold solves arbitrary protein structure in minutes on commodity hardware, whereas previous approaches were, well, this: https://en.wikipedia.org/wiki/Folding@home A gap between biological research and biological engineering is that, for bioengineering, the size of the potential solution space and…
AlphaFold and Folding@home attempt to solve related, but essentially different, problems. As I already mentioned here, protein structure prediction is not fully equivalent to protein folding.
I agree with you, though - they're two different answers. I've done a bunch of work in the metagenomics space, and you very quickly get outside areas where Alphafold can really help, because nothing you're dealing with is similar enough to already-characterized proteins for the algorithm to really have enough to draw on. At that point, an actual solution for protein folding that doesn't require a supercomputer would make a difference.
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> You also seem very certain that Amazon's scale is a good thing, overall, which I remain unconvinced of. What do you find unconvincing about roughly 30 billion in net income and free cashflow in 2023?
That's one metric, that only reflects Amazon's function as an income generator. I view businesses through other metrics as well, including their impact on society in a variety of different ways. From some of those perspectives, it is not clear to me that Amazon (where I was the 2nd employee) is a net benefit.
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It’s fascinating how the affluent backgrounds of many famous scientists and entrepreneurs are downplayed. Eg Warren Buffet, Jeff Bezos, etc
Bill Gates, but (according to the Isaacson book) not Elon Musk
I suspect Bezos, then Gates, then Musk, but it could be any order.
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The Nobel prize is aimed at the general public. It has a kind of late 19th century progressive humanistic ethos. It's science outreach. This way, at least once a year, the everyday layperson hears about scientific discoveries. The Nobel isn't a vehicle to recognize hundreds of thousands of deeply technical scientific researchers. How could it be? They have to pick a symbolic figurehead to represent a breakthrough. Th…
> The Nobel prize is aimed at the general public... Which is okay. The Nobel prize is okay. > This way, at least once a year, the everyday layperson hears about scientific discoveries. Spot on. The problem we have is that the everyday layperson hears very little about scientific discoveries. The scientists themselves, one in a million of them, can get a Nobel prize. The rest, if they are lucky, get a somewhat okay sa…
I think I disagree with most of the comments here stating it’s premature to give the Nobel to AlphaFold. I’m in biotech academia and it has changed things already. Yes the protein folding problem isn’t “solved” but no problem in biology ever is. Comparing to previous bio/chem Nobel winners like Crispr, touch receptors, quantum dots, click chemistry, I do think AlphaFold already has reached sufficient level of impact.
It also proved that deep learning models are a valid approach to bioinformatics - for all its flaws and shortcomings, AlphaFold solves arbitrary protein structure in minutes on commodity hardware, whereas previous approaches were, well, this: https://en.wikipedia.org/wiki/Folding@home A gap between biological research and biological engineering is that, for bioengineering, the size of the potential solution space and…
A lot of bioinformatics tools using deep learning appeared around 2017-2018. But rather than being big breakthroughs like AlphaFold, most of them were just incremental improvements to various technical tasks in the middle of a pipeline.
Demis Hasabis has a really interesting and unusual CV for a nobel laureate [1], he started his career in AI game programming (he worked e.g. on Popoulous II, Syndicate, Theme Park for Bullfrog, and later for Lionhead Studios on Black & White) before doing a PhD in neuroscience, becoming an entrepreneur and starting DeepMind. I would say this is a refreshing and highly uncommon pick for a nobel prize, really cool to s…
I'm always interested in hearing about these people who go and get a PhD in an unrelated field to their original studies, often years after leaving university and working in an industry. Here it says Hasabis did an undergraduate degree in a computer science program, and them spent a decade working on computer games at studios, and then somehow just rocked up to a university and asked to do a PhD in neuroscience. I fe…
In more chill fields where the waters are relatively calm, this may be less of an issue.
But let's also consider the fact that Hassabis did his undergrad at the University of Cambridge, likely with excellent results. He wasn't just some random programmer.