Its much harder to produce a good fundamental list of biology problems because we are no where near as far along, so many basic things are not understood. There are still many unknown unknowns and these particular problems are limited to the realm of verifiable in a lab, which rules out much of what makes biology interesting and hard to study, and that is the organisms themselves and the interactions between their cells. The petri dish differs from the rat differs from the human and that is a part of what makes biology harder to progress.
None of these is likely the root to the wide array of chronic illnesses we can't treat and those seem like the next step to really put a lot of research into given how many people suffer from them and where we are today they seem achievable with the right investment.
> The petri dish differs from the rat differs from the human and that is a part of what makes biology harder to progress.
They all use DNA.
But I agree that nobody has shown in the lab how any of this leads to a genetic system that can self-reproduce reliably and assemble biomolecules/metabolites. This is a missing link. Just showing how RNA or amino acids arise, says nothing about any genetic system. They can not even answer whether RNA or DNA viruses existed first; and whether these existed before organisms/cells did.
> Just showing how RNA or amino acids arise, says nothing about any genetic system. They can not even answer whether RNA or DNA viruses existed first; and whether these existed before organisms/cells did.
Actually, we have quite a bit of evidence to evidence pointing at the order of development based on how strongly conserved some critical features of biochemistry.
The core component of ribosomes (which make proteins) is made from RNA called ribozymes. Other things like RNase P, self-splicing introns, the RNA cores of the spliceosome, and the fact that most central metabolic cofactors (ATP, NAD, FAD, coenzyme A) have ribonucleotide handles points to RNA as the initial building block, before viruses or archae or prokaryotes were even born.
It wasn’t until ribonucleotide reductase gets involved that RNA becomes DNA. DNA swaps uracil for thymine making the genome more error-resistant and a double helix to get stability over reactivity, as a clear evolutionary strategy because DNA doesn’t form like RNA does.
The core of the RNA world hypothesis is a ton of experiments that find that RNA and amino acids are stable in many different chemical conditions which cover a wide range of what the early earth would have looked like along with observed amino acids on outer space objects like comets and asteroids. What we don’t have is an experiment demonstrating how RNA becomes self replicating with the addition of amino acids, which would be one of the last steps to showing how life likely formed.
The goal of the suggested "origins of life" problem, as written, isn't to guess at history - it's to create some similar plausible self-emergent system in the lab.
Seems a bit of an ambitious goal for a language model though! There are presumably dozens of steps before you get to an RNA-based full-blown cell, and it's only been very recently that humans have managed to make an artificial self-replicating "cell" (container) of any type in the lab.
I really really recommend looking up Michael Levins bio work on intelligence at the cellular and organ level.
His most recent work is starting to touch on some pretty far out concepts. And I should note, that he does not state they are true or not, but they are attempting to make empirical methods on testing them.
One of the concepts they are looking at is "math as an actual thing" and that some simple algorithms have new deeper behaviors that we're just finding now. The hypothesis is that over the eons life has probed mathematics at scales humanity cannot even begin to imagine and is exploiting this deep algorithmic efficiency in accomplishing any number of tasks. These algorithms could help explain the missing links.
I'd suggest starting with some of his older work to see they are a credentialed research scientist and not making up 'woo' whole cloth.
I’m curious how you found Michael’s work? Like what led you to familiarize yourself with his research?
He seems to be essentially the only biologist that hackernews knows and he always (always!) comes up in biology discussion. I’m wondering how this particular situation arose.
It's been long enough that I'm not really sure. It's every time I see some of his work the way he looks at problems always intrigued me.
Dogma in science tends to blind people, and when a field starts slowing down and running into things we cannot address then we have to start looking at what we should be questioning.
Just searching it up in YouTube is a good starting place. He has visited a number of different podcasts. Then from there you can drill down into papers on the interesting things.
I’m a working research biologist, and I’m genuinely curious how he became so well known among the hackernews slice of the public. He seems to have hit on some very effective combination of research interests and public communication strategy.
I suspected it was the Lex Fridman podcast appearances, but I wasn’t sure if that was how most people became aware of him.
I think it helps Levin is saying something very different. He’s also much more readable for a computer science crowd since his organizing principles are computation adjacent at least, though he, thankfully, isn’t a computational functionalist in the traditional sense.
Part of the problem is that AI has been trained on all text, not just the internet but scientific papers and books of all varieties. AI style is almost certainly the average of that style approach but we use very different styles for different writing and getting it wrong grates, and AI doesn't seem to deal with these style differences well at all.
Thats the training data, but i dont think thats the biggest factor in the tone. I think its the RLHF. This thing has been guided by silicon valley techbros so it tlaks like them. Even claudes latest style of trying to cram as much information into as little space as possible by nouning verbs and just creating adhoc jargon, is how alot engineers (including me) actually talk. I think they just guided it towards that and overfit on it
I’d echo this. You can see it with other, perhaps lesser, models: GLM5.3 and Deepseek 4.1 have such a recognisably “Claude”-sounding patter I’d have (ill-informedly) SWORN I was using an Anthropic model.
If you’re distilling output from a frontier model, as we expect the open-weight leaders to be doing, it’s natural you’d pick up the language styles.
The problem is it will be detectable and detected and then the password demanded and a failure to provide it will result in charges. I think unfortunately the answer is the phone has to be plausibly empty when crossing the US border, they should focus their efforts on being able to store the full state of the phone remotely and encrypted and being able to restore it easily.
Would it be detectable to some goon at the border? Probably not. They'd put in the sanitized password, see nothing, and let the person go. If it gets seized and an FBI or CIA analyst gets ahold of it, then yeah the smart guys are going to see it but you'd be in that situation anyway, so why not have an out that may avoid it?
The trick around that is to use some form of oblivious block storage. That would completely remove those traces, though it is very performance intensive to anything obliviously.
However, that would clearly make your phone look suspicious from forensic analysis. To counteract that, you have two hidden volumes leaving you with three total systems: your insecure system (first password), the honeypot volume for “clever” actors to find, and then the truly secure volume.
I think one honeypot would be ideal. It needs to be convincing and have data that seems sensitive which would take a lot of effort. Put your nude photos there or something.
One thing that is I feel missed about uptime percentage when compared to on premise uptime is when the downtime occurs. Its far more impactful if its in the middle of the working day or during the busy period of shopping. A store that goes offline in the middle of black friday or in the run up to Christmas is harmed a lot more than some down time on a Sunday night/Monday morning at 3am.
One thing I have noted over time is a lot of these AWS, Azure et el downtimes is they occur in the middle of everyones day, millions of people are impacted by them. Same with github its getting in the way of work. Whereas when we hosted services on our own equipment the downtime was usually out of main hours. The percentages are in many ways the wrong measure of downtime because hours aren't equal in impact to businesses.
Surely there's a word for this, but I haven't learned it.
The problem with load balancing also shows up in employees mass quitting. It's the same queuing theory problem but I don't know the name of it.
Essentially, when you run a set of 'resources' near capacity, if one fails then the next most highly loaded one also goes past capacity and also fails. The work keeps getting foisted onto other units that also fail.
In retail, the beleaguered employee quits in frustration, and the three other people who can do the same onerous tasks the quitter did now find their jobs have gotten 33% worse with no extra remuneration for the insult, and one of them quits too. The last one or two simply refuse to do the task more than they used to, and the boss can't threaten them with being fired or reported for it because if they quit then the business ends. And still the whole thing goes off the rails.
That's why consistent hashing divides the work of one failed node and spreads it evenly over the remaining nodes, so that a spike is softened as much as possible instead of being concentrated on one or two fallbacks who also immediately fail. It's not that it's a great solution, it's that it's the least bad option amongst some pretty terrible ones.
The solution is to undersubscribe the hardware, which some beancounters hate. But most bean counters don't understand Queuing Theory.
I am much more interested in reigning in the industry itself with top level regulation to protect human rights like privacy. Once the excesses of the industry and its thirst for personal data result in crimes for the executives then we can talk about what happens if the developers decide to go along with the regulation breaking.
Governments and medicine tend to track deaths as the only bad outcome from events like 9/11 or Covid. But typically there are a lot more people injured who suffer for the rest of their lives with the consequences, damage and chronic conditions that these events have left them with. We do need to put a lot more research into understanding and improving the quality of life of those with chronic conditions, Historically they have been ignored and are currently highly stigmatised by governments, the press and the populace.
Diseases that lead to death have had substantially better funding over the past 100s of years and chronic conditions are often rarely diagnosed, properly recognised let alone treated. The disabled is a club almost everyone joins at some point in there life and everyone is one accident or infection away from joining it for the the rest of their life. At the moment societies recognition and treatment of those with these conditions is really bad. The 9/11 survivors will be suffering for the rest of their lives. Medicine is something we all want, but at the moment the amount invested by governments is quite low compared to the upside impact on humanity of finding real answers.
I totally agree with you, it is important for people to understand that a medical doctor does not really care if you can walk a mile without pain, but it is way too nuanced to track quality of life changes across a large population. We would need to change the insurance landscape and make it easier for other medical practitioners to get insurance money and let it naturally change.
If even a little bit of the insurance money could start funneling into things like physical therapy (actual physical therapy not the BS artists at big hospitals who print you out a sheet of generic exercises) people could see practitioners who actually care about you being functional.
I tore my achilles and saw a string of doctors, podiatrists, physical therapists, chiropractors, etc. before finally finding someone that doesn't take insurance but who had me running again within a few months. He was cheap compared to the amount my insurance was being billed for a chiropractor to try and sell me $500 custom insoles. The money is there it is just being funneled in all the wrong ways.
I miss all the programming articles. It feels like everyone has given up with the very idea of ever writing code now and the entire practice of making software has been handed over to AI.
Same. I miss the excitement around programming. New languages, new tricks, weird hacks, odd projects.
I have little to no interest in AI coding - I try it every couple months but always regret it, git reset, and go back to coding by hand.
It feels quite lonely these days. The general energy and enthusiasm from hn was a big source of motivation, or maybe community. Now using hn feels quite isolating.
I do see the occasional post about going back to hand coding though, and their frequency seems to be on the rise, so hopefully that correction continues
(I don’t need to see no AI, to each their own, just would be nice to see an equal amount of hand coding content one day)
Reddit's /r/programming is very well moderated, and they specifically don't allow articles about AI, unless it's programming AI. You should check it out.
There are already too many articles about programming and new things are constantly being invented even with AI. For example, I created a programming language called ACPUL by hand designed for humans and there are still articles about it that have yet to be written.
Programming will become like esports. Maybe out of the 30 million programmers who can program without AI, only 5 million will remain, but that is still a large number.
I also experience this as a great loss, but honestly yes, I can't get excited about perfecting the craft of writing computer code now that there are AI systems that have done so. I'll always be sad about this! But the flip side is that I'm way more excited about what I can do with software, now that it's so much easier to write.
I experience quite the opposite. I'm quite excited about the value my skills are gaining in relative terms. An entire generation of potential competition is getting addicted to the subsidized corporate tooling. Voluntarily!
What I fear is the future career path for manual programming is fixing AI generated systems. I suspect it will pay very well because you will be finding and fixing things the AI driven work can't. It is going to be soul destroying as reading AI code is deeply unpleasant in the same way reading the articles is.
I never go by pay. I won't fix bad systems whatever their provenance because trying to understand poorly coded software is very unpleasant.
I go by interesting problems and I like being able to chose from more options due to lessened expertise competition. Why people voluntarily renounce expertise is beyond me, but they are and I welcome the increase in choices of engagement I have been experiencing.
I would never engage in uninteresting work at any rate of pay, and working with LLM output directly or mediated is quite uninteresting to me.
The code is ultimately the codification (ha!) of domain knowledge in precise, non-ambiguous ways. It has extrinsic, non essential complexity yes.
But including ever more complexity in the process, by depending on complexity-slinger systems that you don't fully control or even understand, is not the solution, in my view.
If you lose control over the precise, detailed specification of the domain knowledge that the code is, ultimately you are just a glorified business analyst. Besides, the inherent complexity of the implementation is not without essential complexity that needs mastering for security and performance reasons. Deferring that mastery to some tool is self defeating. The complexity doesn't disappear. You're just shuffling it around and when it leaves your purview you are merely creating opportunity for someone else to capture that value.
Ultimately yeah the vision of being an LLM jockey who doesn't know code might be viable or even numerically dominant in the market in future. Why would you descend the value chain though, and voluntarily, that I don't understand. Competing for volume isn't historically in the interest of the autonomous worker. Maybe I'd feel differently about it if I owned capital and had some corporate strategy behind it. As an independent actor, I don't see it favoring me.
AI is a very useful tool for finding problems in codebases.
I'm very far from an "AI is going to take everyone's job" doomer, but I really do think "there will be programming jobs that don't involve using LLM based tooling" seems pretty unlikely.
The future is open models running on your device. No subsidized corporate tooling required. There will never be a reckoning for the people who are letting their coding skills atrophy.
Yeah I know it's not obvious. And very lucrative and very freeing, having this sort of knowledge and leveraging it.
Especially after clients have suffered the new found arrogance of non-experts riding on LLM output.
Look, let me be perfectly clear: if you're getting what you want out of your job and your personal projects, hobbies, whatever you do with your time, awesome! If you feel like the trade-offs of including LLMs in your workflows are good for you, great!
Just don't delude yourself into thinking this new technology, this new tool, is free of trade-offs. Net positive for you? Ok if you think so go for it. I haven't found the inclusion of LLMs in my activities beyond replacing the broken state of traditional search worth it. That's it. I'm not against it, I just don't find myself getting net positive value from deferring to code generated by these tools, is all I am saying. Nothing more, nothing less than that simple statement. Not for me.
Maybe! But probably not, IMO. There have been a number of generations now that have been "addicted" to using digital spreadsheets rather than doing bookkeeping by hand.
I don't think this is in any way a disagreement between us. In just the same way that spreadsheet software did not kill demand for accountants, I do not believe AI will kill the demand for other professionals.
It was quoting a word from this sentence in your comment:
> An entire generation of potential competition is getting addicted to the subsidized corporate tooling.
I think that using LLMs as tools for work is just like accountants using spreadsheets. If you want to describe both things with the word "addicted", then fair enough. But in my view, in both cases it is just people using a technology that is useful for their work.
And in both cases it leads to skill erosion in the workforce. We have a shortage of accountants and we will have a shortage of software developers when a few years down the line an entire new generation is addicted to corporate tooling and has been disincentivized to learn fundamental skills. So to the point: it is a real problem that has played out before. Ask anyone in manufacturing how much great welders are paid and if they are easy to find.
No, this is clearly not true of accountants! Using digital spreadsheets is not "skill erosion", it is the skill! That doesn't mean they don't still need to learn how to do the calculations that are encoded into the spreadsheets, of course that fundamental knowledge is still important. But running all those calculations by hand in the regular course of their work would be a giant waste of time.
It does seem that there is a shortage of accountants, but this doesn't seem to have anything to do with it... Like, "not enough people are entering CPA programs because it requires a big time commitment for not the best pay and horrible hours during tax season" seems like the main reasons and "the workforce got too addicted to Excel" seems like not one of the reasons at all?
Maybe all this time we were just in a ZIRP bubble and the people who claimed to be "interested in programming" were just grifting to the top all along.
I've always been interested in "building". Programming was always just the means to do so.
I got into it at a very young age, but the syntax and the languages were just the means to an end of building and creating. I'm academically interested in algorithms and data structures and distributed systems architectures, but I have no desire to actually code those things by hand.
You're probably not hand-writing your software in assembler.
Next to nobody will be writing code in 2050. It was always just a stepping stone.
They have throughout this period of AI products shown to reproduce works that they were trained on. They are getting sued all over the place for the theft of content right now and it seems courts and governments want to wave copyright protection (and ignore criminal acts because the "ai did it") to see where this leads.
Its why I stopped writing open source software, my code was stolen and put behind a paywall and the license under which it was published has not been adhered to. Doing work in the public domain at all now is just stupid, these companies are allowed to steal it and call it their own.
A lot of the problem with DMCA is how its been implemented by companies. There is a provision in the original law making it a crime to make false claims, but organisations like Youtube don't bother to make it even possible to counter claim in that way and trigger that side of the law. Everyone seems to have forgotten it was even part of it, I have never seen it enforced.
> don't bother to make it even possible to counter claim in that way and trigger that side of the law
It's not their responsibility. For that part of the law, you need to get your lawyer involved. And your lawyer will probably tell you not to waste your money, because the way the DMCA was written makes it practically impossible to find enough proof to actually win.
I don't think the "internet is a series of pipes" politicians could've foreseen Youtube or TikTok, but had I believed that the authors of early internet legislation had that foresight, I would've accused the law of being intentionally written to lead to these implementations.
Games are another big area where distance to copyright seems to be where the innovation is occurring. So many of the big genres of games and ultimately the "game" that started the genre begun as a mod of another game. Counterstrike from half life, the myriad of factory games from modded minecraft, Arma and DayZ spawned the survival genre and further Arma mods formed the idea of PubG as well. In sim racing mods to Assetto Corsa have influenced the successor title of Competizone which chose GT3 cars since they were the most popular online. Then the modders on AC made long journey driving modifications and this has now influenced the upcoming Evo. There are probably many more examples from Skyrim or other FPS games of ideas born first by modders.
A lot of these mods break copyright of original material but with it they create an entire genre of games far outweighing the value of the initial piece of copyright.
None of these is likely the root to the wide array of chronic illnesses we can't treat and those seem like the next step to really put a lot of research into given how many people suffer from them and where we are today they seem achievable with the right investment.
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