> code itself has an exact value of $0. That's because AI can generate it
That's only true for problems that has been solved and well documented before.
AI can't solve novel problems. I have ton of examples I use from time to time when new models come out. I've tried to ride the hype train, and I've been frustrated working with people before, but I've never been so frustrated as trying to make AI follow simple set of rules and getting:
"Oh yes, my bad, I get that now. Black is white and white is black. Let me rewrite the code..."
My favorite example is tasked AI with a rudimentary task and it gave me a working answer but it was fishy, so I googled the answer and lo and behold I landed on stackoverflow page with exact same answer being top voted answer to question very similar to my task. But that answer also had a ton of comments explaining why you never should do it that way.
I've been told many times that "you know, kubernetes is so complicated, but I tell AI what I want and it gives me a command I simply paste in my terminal".
Fuck no.
AI is great for scaffolding projects, working with typical web apps where you have repeatable, well documented scenarios, etc.
Natural language is too ambiguous for this, which makes it impossible to automatically verify
What you need is indeed spec-driven development, but specs need to be written in some kind of language that allows for more formal verification. Something like https://en.wikipedia.org/wiki/Design_by_contract, basically.
It is extremely ironic that, instead, the two languages that LLMs are the most proficient in - and thus the ones most heavily used for AI coding - are JavaScript and Python...
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It's worth noting that the meme of "it was DNS", including the haiku[0], is from the old school sysadmin world, which has a lot more terrible DNS implementations than modern stuff (especially including Active Directory which has DNS attached to a massive complex system that does dozens of other things as well and because of which has its reliability suffer), so the meme is really a reflection of a harsher time.
I like the idea but the example doesn't make much sense.
In what application would you load all users into memory from database and then filter them with TypeScript functions? And that is the problem with the otherwise sound idea "Functional core, imperative shell". The shell penetrates the core.
Maybe some filters don't match the way database is laid out, what if you have a lot of users users, how do you deal with email batching and error handing?
So you have to write the functional core with the side effect context in mind, for example using query builder or DSL that matches the database conventions. Then weave it with the intricacies of your email sender logic, maybe you want iterator over the right size batches of emails to send at once, can it send multiple batches in parallel?
Yes. The same Internet that was going to connect the gay teenager in gay-hostile territory like rural Alabama or Iran and save them from suicide, it unfortunately turns out can also connect actual neo-Nazis and KKK members across the globe.
> Increased diversity in communities usually comes from active outreach work. PyCon's talk selection process starts blinded.
There is no world in which 40% of programmers are women. 1% in 2011 is also probably evidence of discrimination. But too few people are willing to admit that if 40% of the speakers are women that represents a drop in the quality of the talks. There just aren't that many women programmers.
If DEI is all about promoting women in the hopes that they'll succeed later, I could get behind that. But often DEI goes to absurd lengths like lowering standards for female firemen or combat soldiers.
Big changes have always been a little rocky. Over time I expect they will refine it and work out the bugs. We’ve been through this before, and every OS goes through things like this from time to time.
But again, that’s the Mossad scenario - NSA in this case. You’re essentially reinforcing the OP point. There are three threat models given in Figure 1 of the OP doc, and what you’re saying really only applies to the third.
You had better luck than me. The San Jose PD only begrudgingly gave me a police report weeks after reporting it (needed it for insurance purposes), and told me a could get a copy of it a month later. I'd have to go to the records dept in person between the hours of 10AM - 2PM (email a copy? Are you crazy?).
So I did that, showed up. No other people there. Person behind the counter told me they were too busy, and I'd have to show up some other (unspecified) day.
> the Curtis Yarvin / dark enlightenment nexus is big enough and really weird, but also not a topic for HN (not because it's political but because it's stupidly gross and dark).
It has high overlap with the rad trad Catholic wing, believe me. I am a fairly traditional Catholic. I had heard of Yarvin via the Haskell world, and was floored when a parishioner at my parish brought him up. Such a strange crossing of worlds.
I imagine by LGBTQ colleagues must have the same feelings at whatever it is they do on Sundays
Honestly I sometimes think I'm the most normal person in the field, but we all probably think that. I think if my colleagues found out that I only go to a traditional Novus Ordo on Sundays where we use a lot of Latin and not a full-fledged Tridentine Mass, all of them would be angry at me. The LGBTQ crowd for being Catholic and the rad-trad crowd fro not being the right kind lol.
But anyway, I guess what I meant with my last point is: where are the diversity initiatives to get 'normal' people into this field? Everyone agrees it attracts the neuro-diverse? Then doesn't it stand to reason that we ought to encourage the neuro typical? Imagine how great PLs would be if they were actually eloquent haha.
If you do a site search you'll find 700+ comments linking to it. I wouldn't be surprised if it was the number one most frequently linked page in HN history.
If you’ve tried OpenAI’s Deep Research or similar tools, you’ll know they pull far more info than Wikipedia. But if you’re an expert, you’ll quickly spot errors since the breadth is huge but the depth and accuracy are only so-so.
For non-experts just exploring new topics, it’s still perfectly useful. Grokipedia probably uses a similar search, verify, summarize workflow, so it naturally inherits mistakes from the internet, which isn’t really an LLM problem.
Grok is just the first to make it public, and other AI companies could easily build their own synthetic data Wikipedias, and some probably already have.
On the same page here, read it multiple times to see if I can convince my mind, this is bit off in terms of reading the code as its being executed. There are high chances of people making mistakes over the time with such patterns. As usual there is always a trade off involved, readability is the one taking hit here.
This is not suprising at all. Having gone through therapy a few years back, I would have had a chat with LLMs if I was in a poor mental health situation. There is no other system that is available at scale, 24x7 on my phone.
A chat like this is not a solution though, it is an indicator that our societies have issues is large parts of our population that we are unable to deal with. We are not helping enough people. Topics like mental health are still difficult to discuss in many places. Getting help is much harder.
I do not know what OpenAI and other companies will do about it and I do not expect them to jump in to solve such a complex social issue. But perhaps this inspires other founders who may want to build a company to tackle this at scale. Focusing on help, not profits. This is not easy, but some folks will take such challenges. I choose to believe that.
Good God! My wife got cancer last year and I managed to stay on a very stressful contract gig until the end of the year, but after that I realized how burnt out I was and how much I needed to just focus on her recovery, which was going to take way longer than the FMLA-allotted 12 weeks and so I had to swallow a lot my pride and just quit and focus no caregiving. It's now almost a year since the stem cell transplant and there have been a lot of ups and downs, including 2-3 hospitalizations, but right now she's doing fairly decent. It's just that my career is wrecked. Part of me doesn't even care because I've been doing tech stuff for about 30 years, it's just hard to give it all up suddenly.
My advice to this gentleman is to just stop doing all that stuff, enjoy the family, keep jogging, and let the world turn. It's what I have have had to learn to do. I even went to a few therapy sessions recently, but it didn't help me that much even though I'm trying to give it a chance. It's because I was always all about the mission--the next project, the next all night troubleshooting session, whatever the challenge was, and sitting still doesn't suit me, but I'm learning.
That's only true for problems that has been solved and well documented before. AI can't solve novel problems. I have ton of examples I use from time to time when new models come out. I've tried to ride the hype train, and I've been frustrated working with people before, but I've never been so frustrated as trying to make AI follow simple set of rules and getting:
My favorite example is tasked AI with a rudimentary task and it gave me a working answer but it was fishy, so I googled the answer and lo and behold I landed on stackoverflow page with exact same answer being top voted answer to question very similar to my task. But that answer also had a ton of comments explaining why you never should do it that way.I've been told many times that "you know, kubernetes is so complicated, but I tell AI what I want and it gives me a command I simply paste in my terminal". Fuck no.
AI is great for scaffolding projects, working with typical web apps where you have repeatable, well documented scenarios, etc.
But it's not a silver bullet.