skysight-inc/HackerNews huggingface dataset:
I feel like sometimes software could benefit from a better conceptual differentiation between failures and errors.

Failures happen, and robust software should deal with them in a predictable manner. Not all software needs to be able to recover from failures automatically, but they should remain in a consistent state so that an operator can fix the situation, allowing the system to recover. A database system unexpectedly going down is a failure, and a system that expects it will never happen can't be considered correct.

Errors are the result of a mistake: Either there's an invalid input from the user, or a bug has caused data corruption. Errors can be detected with defensive coding (eg. by validating input), but often systems can't recover from errors, so they to be communicated to the user. You'll want systems to abort their current task if they encounter errors, as the state will be undefined, and continuing may make the situation worse.
Given the DNA code for one of the "machines" that run cells, we can generate an atomic model of that machine. This means we can "compile" (one part of) the DNA code. It was already possible, but so slow that entire datacenters would spend months calculating this for a single protein and even then we can't use them on the really complex ones at all, necessitating things like neutron spectroscopy which are totally insane, and only work on like 1% of proteins.

This is useful because for example chemical simulation tools don't run on DNA code, but on atomic models. And also to produce "images" of the molecules (images between quotes because most proteins are too small to interact with reasonable photons, and no interaction with photons means you can't see them in any way)

DNA has other parts that are really important but we don't understand at all yet, where this doesn't help at all. This applies to sections of DNA sent to ribosomes, to produce actual molecules. Besides that, there are pieces of DNA that "index" the DNA, pointers (from one gene to another), triggers (that for instance start production of an enzyme based on some external influence, like detection of a marker molecule) and export markers (that tell you what to do once the protein is produced, for example, mark a protein to be removed from the cell, incorporated into the cell membrane, or for instance used inside the cell nucleus, and there's also one that essentially says "at this point stop producing a protein and instead couple the rest of the DNA code to the end of the protein you just made").
You're right that they focused on income (not quite the same as cashflow but it's a good point).

What was interesting is that above a certain income, life satisfaction actually began to decrease. I wonder if there is a similar corollary to wealth.
"A few" does appear quite dismissive of the enormous amounts of effort in structural biology so far. There are more than 170,000 structures in the PDB right now.

To determine potential targets for drugs we have to understand what the proteins do. Having the structure is not really enough for that, it doesn't tell you the purpose of the protein (though it certainly can give you some hints).

In most cases the proteins were determined to be interesting by other experiments, and then people decided to try and solve their structure. So the structures we already solved are also biased towards the more biologically relevant proteins.
I'm an atheist more or less and I agree with this sentiment. I'm not fond of transhumanism. But I don't think the mRNA vaccine process fits this description.
CASP (Critical Assessment of protein Structure Prediction) is calling it a solution. To quote from the article:

"We have been stuck on this one problem – how do proteins fold up – for nearly 50 years. To see DeepMind produce a solution for this, having worked personally on this problem for so long and after so many stops and starts, wondering if we’d ever get there, is a very special moment."

--Professor John Moult
Co-founder and chair of CASP
This does indeed sound like a game changer then, if true
Yes - this was a $2.2 trillion dollar relief bill and the total amount in question is well under $34 million (that number included Americans living abroad). That’s smaller than the amounts individual businesses claimed inappropriately and delaying sending the checks to check all of the recipients would probably have cost more since a lot of that money went straight into the economy paying taxes and keeping people employed.
Manual mode with onbody interface solves a lot of transitional problems.

See https://www.xprize.org/prizes/avatar
Moderna didn't just have the vaccine in march. They had it mid-January 2020.
It is not a hyperbole.
Tactics are more essential for initial improvement than strategy for the simple reason that you cannot execute sound strategic plans if your execution contains tactical flaws.
I agree. "AlphaFold achieves a median score of 87.0 GDT". While this is a major advance, to me 100 GDT would be 'solved', not 87.
Additional commentary in Science: https://www.sciencemag.org/news/2020/11/game-has-changed-ai-...

(submitted by furcyd : https://news.ycombinator.com/item?id=25254888 ).
Webvan vs. Instacart. So many dead startups that are brought back because they were just too soon.
How did he manage installing applications such as banking apps from the place store?
Unless you’re going to be sideloading the app how do you know that you’re getting official banking app and not just downloading some file online.
> Software used to design and manage synthetic DNA projects may also be susceptible to man in-the-browser attacks

First time I heard that phrase 'man in the browser'. What does it even mean? Browsers now run in their own sandboxes and it's quite hard to run arbitrary untrusted code in a browser (but still possible). Do bad actors burn browser-0days just to inject junk DNA creating sort of mutant pathogens? It would be a great opportunity to create a honeypot and capture those exploits in the wild.
What's the actual news, here? AlphaFold is amazing, but it's been around for a while.
I think this is the interesting part because there aren't going to be the same regulatory hurdles for using ribosomes to manufacture technology as there are for medicines. Synthetic organelles that weave fibers, build metamaterials, etc could lead to pretty magical advances in our capability.
I love SciFi so here are my top 5 around 10,000 words or less.

1) The Machine Stops - Nothing beats it

2) The Futurological Congress - Best short SciFi novel

3) The Unpleasant Profession of Jonathan Hoag - Freaking hilarious

4) Perfect Day for Bananafish - Not sci fi but amazing!

5) Blue Screen: How Peter Gustafson Defragmented the World - I wrote a short SciFi novel and my mom tells me its great :)

[1] https://www.amazon.com/Machine-Stops-M-Forster/dp/1609420667

[2] https://www.amazon.com/Futurological-Congress-Memoirs-Ijon-T...

[3] https://www.amazon.com/Unpleasant-Profession-Jonathan-Hoag-e...

[4] https://www.amazon.com/Nine-Stories-J-D-Salinger/dp/03167695...

[5] https://www.amazon.com/Blue-Screen-Peter-Gustafson-Defragmen...
Cloud Data Sync Methods and Benchmark: DVC vs. Rclone
There is an additional question that opens the door to all sorts of hidden exclusions: Were study participants given medical advice prior to participation?

If I ask my doctor whether it is a "good idea" for me to participate in an investigational study like this, there are all number of reasons he may advise against. Those reasons form a defacto hidden list of exclusions. Would a doctor advise a patient with diabetes, high blood pressure, or any other chronic illness, to participate in such a study?
I'll admit I'm not super well informed on covid, so my opinion on this is weakly held, but isnt that an insanely small percentage of people?

I was under the impression that vaccine + immunity will just lead to herd immunity and the disease to go away on its own.
I forgot that part.

That's the reason why also young healthy people need to take the vaccine in order to stop the spread. It's a solidarity gesture.
It was obviously Obama's fault. (This is a joke and sarcastic).
Salesforce Deal for Slack Expected to Be Announced Tuesday: Report
They're teaching the most widely understood accent for pragmatic reasons.
>So if you want to be "as good as PGP", there is no need to learn those concepts.

Sure, but we really have to aspire to be better than PGP. We are obviously missing the point if we are wasting time on new features when no one can use the old features.

>The "safety numbers" concept does need to be learned, but I think it is way easier to explain than PGP key management.

If the question is "why do I have to care when the safety number changes" then the answer still involves the basic concept of cryptography identity in both cases.
> What are the immediate real-world applications of this?

A protein is actually a linear sequence of amino acids, but in a cell this sequence has a three-dimensional arrangement like a clew of thread. The arrangement is not random, but dependent on the specific composition of the sequence (i.e. selection and order of amino acids) and some other factors. To understand the function of a protein, we need to know this three-dimensional arrangement (i.e. structure). Up to now the structure determination process was mostly manual, complex, time-consuming (several months up to more than a year) and error prone. If structure determination by DNN is reliable, this is a big win for life science. There are still a lot of problems open: e.g. the structure is not constant over time but there are "moving parts" in the structure which are important for its function.
It’s less important with desk lamps, but I occasionally wonder how green old appliances really are. Sure, they last a long time, which reduces the emissions from production and transit. But on average they also consume a boat load of energy compared to their energy star equivalents, and they do it for decades.

The reason it matters lies with a desk lamp is because you probably aren’t still running incandescent bulbs in it.
Most of the people catching it atm is from private social gatherings, AKA dumb behaviour.
I'm definitely down that rabbit hole now. Online chess has cut into the time I used to spend reading and playing music, but I'm an amateur at all those things. Plus, I've started playing more with my kids in the evening. I'm sure I'll get back over to music and the "long novels I need to read" project eventually, and no real harm.

Brief infatuations can have a lasting tail, and I hope that's what happens here, for chess, which really is a phenomenal game. Kind of like archery and "the hunger games", the initial bump isn't sustainable, but there may very well be a lasting increase in interest.
> What I'm getting at is that I'm a fan of the way Rust does error handling, but I don't get _why_ it feels different to the way Java does it.

It's because of the way the exception information gets annotated. In Rust, exception information is part of the return type, so you can handle potentially-exceptional functions using mechanisms that are generic over any return type. For example, Iterator::map lets you call every function that might fail, and gather the results as failures, even if you don't fail-fast. But in Java, the exception information is passed in a separate part of the type signature, so generic functions have to be written differently to also handle functions that might fail.
For what it's worth, you could have walked into an Apple store and bought the M1 Mini the same day. No need to wait 3 weeks.
If you're in line for bariatric surgery and your doctor doesn't inform you of the risks and possible adverse outcomes then she hasn't received informed consent from you yet.
I think the chess puzzles are what could shine in this book:

http://www.chessproblems.org/ (it is the Chess Quizzer from the OP)

I have tried a few, and I enjoy the explanation of the solutions in plain English. Short and clear.
> the outstanding question as far as to whether or not this is useful for evaluating novel proteins

That is not an outstanding question. The test on which DeepMind scored high marks is a test of how well the algorithm folds novel proteins -- proteins whose ground-truth structure has not yet been published.
We watched 100% of Dr. Campbell's videos for the first few months of the pandemic, and my wife still watches all of his stuff. Highly recommended.

He's strongly evidence and data based and steers clear of most anything that can reasonably be considered 'political'.
It would do everyone in this conversation some good if you just directly linked to the data you’re talking about.
Wow. Other companies would kill for half that combination of enthusiasm and skill.

Good job SW. Your paint covers like trash anyway.
Changing Unfamiliar Code? First, Seek to Understand
I think this is good advice if your goal is side income along with your high-paying tech job, or perhaps a lifestyle business where you earn enough passively to sit on a beach or ski more often than not. Personally that's where I am (the former) and most programmers who want to "make money online" probably are, too.

It's certainly not where the people who want to found a "startup" in the PG sense of the word, or be the CEO of a massive company, are. And (also paradoxically) I think most of them are probably in the same place the author is. Even if they have hobbies and passions, their #1 passion is probably "making more money."
Some years ago a different “MacDonalds french fries” recipe was posted, I think it did the rounds on HN, and it was much more like the recipe you describe: fried twice and cooled between, no sugar, add salt.

There are some other variations, like blanching the potatoes with vinegar, or freezing the potatoes overnight between frying. The idea is to make them crispy on the outside and soft on the inside.
Yeah, I certainly didn't intend for it to be a faith/atheism battle. I'm simply stating that so far, all I've seen has been that one perspective. I'm interested in the potential fallout others are predicting.
It seems unlikely there will be any large changes in life from solving protein folding. Knowing the structure of a protein (or really, its dynamics) is useful for identifying drugs that bind, but the real bottlenecks n drug discovery and biotech are elsewhere.
I think that this is a heuristic "near optimal" method rather than an exact analytic method (I have little to no idea of what that would be in protein folding). A domain I do understand a bit which is np-hard is the travelling sales man. Computing an exact solution is unrealistic, but doing heuristic searches that get you to 99% of the optimal 99% of the time is relatively doable.

But - you don't know that you are 1% from the solution... even if you are pretty confident that you are. It's quite possible (unlikely) that you are way off the optimal, but if you have a decent solution that's ok.
Considering that this system "uses approximately 128 TPUv3 cores (roughly equivalent to ~100-200 GPUs) run over a few weeks" to determine a single protein structure, making predictions for all proteins encoded in a human genome seems impractical at this stage. With luck, this advance will help lead to discovery and definition of new folding rules and optimizations that will make protein folding predictions for the whole human genome more tractable.
Why a global community is discussing creativity and the power of storytelling
What is your reason for assuming P < 0.05% for long-term harm due to COVID-19? You quite clearly assumed 0.05% for death only, therefore attributing even less to long-term health effects. But so far, there appear to be many indications that COVID-19 does have significant medium (and possibly long) term consequences even in asymptomatic cases.

I fully admit that I am not up to speed in proven COVID-19 medium- or long-term effects beyond having seen headlines, but to essentially assume none when there have been very obvious and multi-faceted indications of them implies you must have a very good basis of research to base your estimate on. Care to share?
That is interesting. I haven't worried about setuptools since like 2009 and haven't cared about my pip version since like 2012.

I have had FAR more issues with performing Bundler/Ruby upgrades than I've ever had with Python.
I can also vouch for lichess.org

It's free software (https://github.com/lichess-org), and you only need web browser to play [1]. Even Magnus Carlsen and many other top Grandmasters play there.

As for cheating, all games are checked for computer play, so even if you can occasionally lose a game or two from a cheater, he will be caught, and you will get back your rating points (if you care).

[1] Dunno what they are using for latency adjustments on lichess, but it seems to work fine. No external software necessary, unlike chess servers of yore: https://www.freechess.org/Help/HelpFiles/timeseal.html
The vaccine doesn't "hack or mix our DNA".

Heck, it's trying to get the body to get rid of viruses. One particular type of virus (retroviruses) do "hack or mix our DNA".
This is awesome. As the CEO of a startup, holy crap, the legal and financial garbage I have to sit through is godawful. And lawyers are expensive. And it's something you want to "get right".

Bookmarking this.
For-profit corporations that value protein engineering will beat a path to DeepMind's door ASAP, like pharmas.

Protein conformation prediction is essential when engineering new small-molecule drug compounds that must 'dock' with the specific proteins that regulate disease. Knowing how to create a protein with the precise shape to become biologically active has soaked up a lot of R&D funding toward pie-in-the-sky techniques that promise to advance that agenda (like quantum or DNA computing).

If this method works as DeepMind says, it will immediately be adopted by every pharma to assess and tweak the shape of candidate proteins.
You're asking if there are vaccines that do not lead to sterilizing immunity?
Yes.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7296151/
"Become a world-class leader in just 2 minutes a day".

Do you honestly believe that?
Why compare yourself to Elon Musk though? If you could run like Usain Bolt, you'd be an olympic medalist ;)
Pasting this from another comment:

Poetry is still rough around the edges but I think the core experience is great and it's well on its way to be a very popular tool.

Before using it at work, we are waiting on waiting on https://github.com/python-poetry/poetry/issues/2610 (alternate repository not getting used for transitive dependencies) and ideally this https://github.com/python-poetry/poetry/issues/1556 (disable SSL verify for alternate repositories)

If you don't use your own PyPi for a bunch of internal packages, it works great imo. One more wish item would be having absolute path dependencies instead of only relative path.
I think I might be the exception on HN based on the current comments, as I am not in a hurry to get the vaccine. I know it has been in trials and appears to be safe but I personally don't think enough time has passed to properly make that determination.

I feel is that it has been less than a year since the pandemic was declared and the fact that a vaccine using new synthetic RNA technology that has never been used before is being promoted before studying the long term effects is scary as hell.

How many years did we use Antibiotics before it became apperant that over-use results in super bugs?

There have been many other novel medications that have turned out to be less than good after they were studied over a longer duration of time. I am worried in 5 or 10 years from now, a whole bunch of people are going to get some new type of autoimmune disease, or liver cancer, or their yet to be concieved kids will get it, or something I can't even imagine right now.

I hope I am wrong and that everything works out but I feel this whole situation could use some sober second thought before jumping in head first and dose-ing a large percentage of the human species so quickly with a novel technology.

* Edit: I would also like to see antibody tests being done prior to vaccination as already having antibodies might result in negative reactions that were not studied in the current trials, not to mention the effect it would have on the statistics that will be used as a metric to encourage more people to get jabbed.
retroviruses, mostly. Crispr, obviously.
Agreed that the sooner your caffeine cutoff is, the better. I used to do 7pm with poor results. I find 5pm and going to bed at around 11pm to be fine. I normally finish drinking caffeine at around noon. Just 5 is my hard cutoff no matter what.

I dont know about the jogging prior to bed. Jogging amps me up and gets my mind fired up. But it may help some folks, so it's worth a try for others.
So who will have access to this? DeepMind never publishes their models.
Private Chat and DMs are Good, Actually (with a couple careful caveats)
I occasionally ask our principle / sr. Python engineers about this, and their response is always, "These things come and go, virtualenv/wrappers + pip + requirements.txt works fine - no need to look at anything else."

We've got about 15 repos, with the largest repo containing about 1575 files and 34MBytes of .py source, 14 current developers (with about 40 over the last 10 years) - and they really are quite proficient, but haven't demonstrated any interest at looking at anything outside pip/virtualenv.

Is there a reason to look at poetry if you've got the pip/virtualenv combination working fine?

People who use poetry seem to love it - so I'm interested in whether it provides any new abilities / flexibility that pip doesn't.
Anandtech's article indicates they have an out-of-order buffer of around 630 entries (Zen 3 is only 256 entries). The M1 has 7 integer math ports and 4 FP/SIMD math ports plus several bunch of load/store/branch ports . It seems like they could completely saturate those decoders given the right code.
The number of architectural registers are still relevant for register allocation because of course overlapping and independent code sequences cannot share the same architectural register name. This is not very important for integer loads, but still relevant for FP where optimal scheduling requires having multiple computations in flight at the same time. In some cases 16 FP registers are not enough and Intel had to add 16 more FP registers with AVX512.
This is about proteins, not DNA.
I run magicsandbox.com. Right now moving to all remote, still weighing options but might settle back in my home country (Croatia)
SymPy is pretty niche, but it saved my butt many years ago in my years of collegiate robotics. We spent months unsuccessfully trying to compute kinematics and sensor coordinate transformations on vectors of quarternions by “hand” with numpy. I wouldn’t wish it on my worst enemy. There are so many opportunities for mistakes, and the intermediate numbers can rarely be checked against your intuition.

With SymPy however (and some optional Newtonian physics package), one can simply define their free-bodies and coordinate systems, and SymPy will spit out simplified, compiled tensors of whatever expressions they want! It was truly magical at the time.
For sure, I don't mean to suggest it's cheap research. But whether you charge a lot or nothing for the first few doses out of the lab, it seems like this won't really make a dent in the research cost. (I don't know if this $375,000 number is in that category, or not.)
Did you socialize face-to-face in the week before falling ill?
What is to be made of “e” ending so many Middle English words?
AlphaFold 2. The article specifically mentions it.
Art's a smart guy and I have a lot of respect for his biological intuition, but his understanding of computational biology is very limited.
Imagine protein computers or protein metamaterials