MurphyA/hacker-news huggingface dataset:
by bruce511 | 2025-05-31 06:33:25+00:00
Practice.

You've done some interviews. You know what questions the ask. Write them on some flashcards. Pick a random card from time to time, and answer it.

This helps in 2 ways. Firstly you'll be better prepared for common questions. Secondly the process of figuring out how best to answer that question will help you figure out other questions faster.

Try not to sound rehersed. The goal is not to write a script. The goal is to listen, consider, respond. Remember you don't have to respond immediately. You can take a beat to consider your answer. (Take a sip of water, comment that the question is interesting, or that it's not been asked before etc.)

Sometimes deliberating and answer is just as interesting as the answer. Remember the question is just there to prompt you to talk about yourself.

Avoid "bullshit" answers. Like 'my biggest flaw is I work too hard.' Asking for flaws is a test of self-awareness. A better answer is '"I struggle with time management. I often used to work late because I couldn't leave the task unfinished. Now I understand that I was correcting that work the next day anyway, so I now end the day at a fixed time. Maybe a couple times a year I break that rule, because of a special time-sensitive thing, like a conference, but its a couple times a year, not every week."

It's a better answer because it tells them about you, tells them you're self-aware, and also sets a boundary. And it's not just a platitude you think they want to hear.

But practice. Get so you can answer and still be relaxed. Yes, you're nervous in thd interview, but being relaxed, and prepared, always improves your chances.

And remember, there are a lot of folk on the market right now, so don't be too hard on yourself. You're gonna get some rejections even after good interviews.

Good luck.
by eddythompson80 | 2025-05-31 06:33:27+00:00
That doesn't really make sense. You either make the LLM provider liable for the output of the model, or you have the current model. The friction already exists. All these AI companies and cloud providers are running "censored models" and more censorship is added at every layer. What would more friction be here? more pop-ups?

Doing the former basically means killing the model-hosting business. Companies could develop models, use them internally and give them to their employees, but no public APIs exists. Companies strike legally binding contracts to use/license each other models, but the general public doesn't have access to those without something that would mitigate the legal risk.

Maybe years down the line, as attitudes soften, some companies would begin to push the boundaries. Automating the legal approval process, opening signups, etc.
by jimmySixDOF | 2025-05-31 06:36:09+00:00
Error control as in LLM-as-a-Judge needs to be integrated into every pipeline there are use at home (sub 7B) sized models and nano's (fit into browser) [1] so push out to the edge if its a Google sized scale/cost problem. Should actually be like VirusTotal where you get a consensus score of x/72 different lookups.

[1] see haize labs : https://www.haizelabs.com/product/judges
by californical | 2025-05-31 06:36:25+00:00
It’s really interesting to hear your points.

I do think I may struggle a bit to find something comparable to my current company, but we’re also hiring right now. And it’s a very small company in the grand scheme of things, even though we have customers much bigger.

I guess having that experience makes me think that there must be a lot of other small companies working in their own interesting niche, providing a valuable product for a subset of major companies. You just don’t usually know they exist unless you need their specific niche.

But I recognize your points too. It seems like the B-to-C space is really tricky right now, and likely fits closer with what you’re describing.

I think that the flip side is that a company doesn’t need to make it big to be successful. If you can hire 5 developers and bring in $2m/yr, there’s nothing at all wrong with that as a business. Maybe we will get lucky and the market will trend towards more of those to fill in the void that you mentioned. I think it could lead to a lot of innovation and a really healthy tech world! But maybe it’s just being overly optimistic to think that might be the path forward :)
by ivape | 2025-05-31 06:37:19+00:00
You are not understanding what I am saying. I am saying its the calm before the storm before everyone realizes they are paying a bunch of startups for literally no comparative value given AI. First the agile people are going to get fired, then the devs are just going to go "oh yeah I just manage everything in my LLM".

I'll be here in a year, we can have this exact discussion again.
by kergonath | 2025-05-31 06:38:43+00:00
> Think 3D-printing that was supposed to take over manufacturing.

3D printing is making huge progress in heavy industries. It’s not sexy and does not make headlines but it absolutely is happening. It won’t replace traditional manufacturing at huge scales (either large pieces or very high throughput). But it’s bringing costs way down for fiddly parts or replacements. It is also affecting designs, which can be made simpler by using complex pieces that cannot be produced otherwise. It is not taking over, because it is not a silver bullet, but it is now indispensable in several industries.
by Llamamoe | 2025-05-31 06:38:45+00:00
I already went through a realization a while ago that you just can't mention something to people anymore and expect them to be able to learn about it by searching the web, like it used to be possible, because everything is just unreliable misleading SEO spam slop.

I shudder to think how much worse this is going to be with "AI Overview". Are we entering an era of people googling "how does a printer work" and (possibly) being told that it's built by a system of pulleys and ropes and just trusting it blindly?

Because that's the kind of magnitude of errors I've seen in dozens of searches I've made in the domains I'm interested in, and I think everyone has seen the screenshots of even more outlandish - or outright dangerous - answers.
by godelski | 2025-05-31 06:40:02+00:00
No, of course not. That would be laughably absurd. So do you think I'm trolling or you're misunderstanding? Because who isn't familiar with triage?

Do you think every bug's monetary value is perfectly aligned with user impact? Certainly that isn't true. If it were we'd be much better at security and would be more concerned with data privacy. There's no perfect metric for anything, and it would similarly be naïve to think you could place a dollar value on everything, let alone accurately. That's what I'm talking about.

My main concern as an engineer is making the best product I can.

The main concern of the manager is to make the best business.

Don't get confused and think those are the same things. Hopefully they align, but they don't always.
by wiseowise | 2025-05-31 06:40:43+00:00
I will never understand this argument. If you have a super tool, that can magically double your output, why would you suddenly double your output publicly? So that you now work twice essentially for the same money? You use it to work less, your output stays static or marginally improves - that’s smart play.

Note: I’m talking about your run of the mill SE waggie work, not startups where your food is based on your output.
by lotsofpulp | 2025-05-31 06:41:32+00:00
Google maps says Salem is 40min+ from Cambridge, and Nashua is 50min+ from Cambridge, and add another 10min to 20min from other parts of Boston.

Each minute of driving costs at least $0.67 (from IRS), excluding increased morbidity and mortality risks (injury from car collisions is the top health risk for most Americans).

So even using $0.50 per minute of driving, if you are only going to NH to evade sales tax, that is 80min*$0.50cents = $40. $40/0.0625 =$640.

So the first $640 of the purchase doesn't even save you any money (even more for most Bostonians further than Cambridge), and it costs you 1 to 2 hours of your life driving back and forth. If you value your leisure time at at least $100 per hour, then you're looking at spending at least $2,200 for the tax evasion to start paying off.

I'm just positing why Microcenter will not open a NH location anytime soon, because most of its customers (who are in Boston metro) won't find that it pays off to travel to NH.
by euroderf | 2025-05-31 06:42:00+00:00
Writing it down by hand is better - that's all fine and dandy. But to sell me on it, include two more "features" (i.e. requirements):

- Give me an app to scan my (mostly neatly-written) notes into text, maybe with hooks so I can train it on my own quirks of notation. Then I can review my notes more easily - even on the go - during the semester, and rearrange & reformat & refactor them.

- As long as you have that training data, also generate for me a custom font that re-creates my handwriting style.
by throwaway2037 | 2025-05-31 06:42:30+00:00
I don't want to shill for LLMs-for-devs, but I think this is excellent corporate strategy by Microsoft. They are dog-fooding LLMs-for-devs. In a sense, this is R&D using real world tests. It is a product manager's dream.

The Google web-based office productivity suite is similar. I heard a rumor that at some point Google senior mgmt said that nearly all employees (excluding accounting) must use Google Docs. I am sure that they fixed a huge number of bugs plus added missing/blocking feature, which made the product much more competitive vs MSFT Office. Fifteen years ago, Google Docs was a curiosity -- an experiment for just how complex web apps could become. Today, Google Docs is the premiere choice for new small businesses. It is cheaper than MSFT Office, and "good enough".
by neilv | 2025-05-31 06:42:45+00:00
On the Google search Web site, the "AI responses may include mistakes." weak disclaimer small print is also hidden behind the "Show more" button.

When OpenAI launched ChatGPT, I had to explain to a non-CS professor that it wasn't AI like they're thinking of, but currently more like a computational parlor trick that looks a lot like AI.

But turns out this parlor trick is awesome for cheating on homework.

Also good at cheating at many other kinds of work, if you don't care much about quality, nor about copyrights.
by tialaramex | 2025-05-31 06:43:08+00:00
All you're getting to is that we're not obliged in Rust to ever decide we didn't need the Goat - but I didn't argue that we are.

The "finalizer problem" in the Garbage Collected languages isn't about a Goat which never becomes unused, it's about a situation where the Goat is unused but the clean-up never happens.
by eddythompson80 | 2025-05-31 06:43:25+00:00
I think Google is in a particularly bad situation here.

For over a decade now, that spot in the search page had the "excerpt from a page" UI, which made a lot of sense. It cut down an extra click, and if you trusted the source site, and presumably Google's "Excerpt Extraction Technology" (whatever that was) what was left not to trust? It was very trust worthy information location.

Like if I search for a quick medical question, and there is an except from the mayoclinic, I trust the mayoclinic, so good enough for me. Sometimes I'd copy the excerpt from google, and go to the page and ctrl-f it.

Google used to do a decent job at picking reputable sources, the excerpts were always indeed found in the page in a non-altering context, so it was good enough to build trust. Now that system has degraded over the years in terms of how good it was at picking those reputable sources. Most likely because it was SEO gamed.

However, it has been replaced with a the AI Overview. I'm not against AI, but AI is fundamental different than "a relevant excerpt from a source you trust with a verifiable source in milliseconds".
by delusional | 2025-05-31 06:44:02+00:00
"Run the global economy" doesn't necessarily mean abundance. The current age of relative abundance and decent equality is actually pretty rare in human history. "Running the economy" could instead mean that nothing can happen without the central planning computer, which of course means it gets to set whatever prices it wants, take whatever cut it wants, distribute that surplus however it wants, including to its owners.

It is possible to increase productivity while also centralizing that profit. That's what communists would call "exploitation of labor"
by neepi | 2025-05-31 06:44:13+00:00
To be fair people are pretty damn unintelligent when it comes to verifying information. Despite my academic background I catch myself doing it all the time as well.

However LLMs amplify this damage by sounding authoritative on everything and even worse being promoted as authoritative problem solvers for all domains with a small disclaimer. This double think is unacceptable.

But if they made the disclaimer bigger then the AI market would collapse in about an hour much like people’s usage does when they don’t verify something and get shot by someone actually authoritative. This has happened at work a couple of times and caused some fairly high profile problems. Many people refuse to use it now.

What we have is bullshit generator propped up by avoiding speaking the truth because the truth compromises the promoted utility. Classic bubble.
by rhdunn | 2025-05-31 06:44:28+00:00
And like those technologies it will find its own niches (like XML and no-SQL being used heavily in the publishing, standards, and other similar industries using document formats such as JATS) or fade away to be replaced with something else that fills the void (like CORBA and WSDL being replaced by other technologies).

I think LLMs will find their uses, it just takes time to distil what they are really useful for vs what the AI companies are generating hype for.

For example, I think they can be used to create better auto-complete by giving them the context information (matching functions, etc.) and letting them generate the completion text from that.
by firesteelrain | 2025-05-31 06:45:01+00:00
We know how to calculate the necessary sample size because the Central Limit Theorem tells us that the sampling distribution of the mean (or proportion) becomes approximately normal as the sample size grows. This justifies using Z-scores from the normal distribution to derive confidence intervals - and from there, solve for the sample size needed to achieve a desired margin of error and confidence level.

Article used a Python library without really understanding the reason or science behind the result. Knowing this can help when you read an article or watch a news report where they quote a study that says “a study of 300 people…” well why 300 people? You can reasonably assume that the researchers used the CLT.
by audunw | 2025-05-31 06:45:04+00:00
I don’t think it’s hard to know. We’re already seeing several signs of being near the plateau in terms of capabilities. Most big breakthrough these days seems to be in areas where we haven’t spent the effort in training and model engineering. Like recent improvements in video generation. So of course we could get improvements in areas where we haven’t tried to use ML yet.

For text generation, it seems like the fast progress was mainly due to feeding the models exponentially more data and exponentially more compute power. But we know that the growth in data is over. The growth in compute has a shifted from a steep curve (just buy more chips) to a slow curve (have to make exponentially more factories if we want exponentially more chips)

Im sure we will have big improvements in efficiency. Im sure nearly everyone will use good LLMs to support them in their work, and they may even be able to do all they need to do on-device. But that doesn’t make the models significantly smarter.
by bruce511 | 2025-05-31 06:45:21+00:00
Certainly there are lots of fads that went mainstream then flittered away. 3D TV to name but one. VR seems to be another. Generally categorized as "solutions looking for problems".

Crypto falls into that camp (it solves some problems for a small subset, notably criminals, but relies on 'bigger fool' ideas to appeal to the man in the street.)

On the other hand some fads are society changing. Phones being one. PCs in general being another. (I'm old enough to remember a time when all records etc were on paper.) Inagjbe z life without Visicalc (or Excel.)

AI is here to stay. But remember how the internet was hyped in the 90s? Sure it'll change the world, but it's too early to predict how or when. But clearly we've entered a new era and if will be interesting to see how it plays out.

It has very obvious limits - but the nature of every hype cycle is to ignore those limits and predict grandiose futures. (The phone was supposed to kill the PC, then the tablet was etc.) But it's only by trying it everything that we can find out for sure, what those limits are.
by pjerem | 2025-05-31 06:46:11+00:00
F# is an hidden gem, iteration 5 278.

I think it stays niche because it’s targeted at people knowing the dotnet ecosystem but most of those people reason a lot in OOP/imperative because well, they work with C#.

But it’s amazing to me that F# is still evolving and cutting edge after more than two decades of being extremely niche. You’d think Microsoft would abandon it or let it rot but no. Though I think F# is in fact the laboratory for new language features for C#.
by yuvalpinter | 2025-05-31 06:46:28+00:00
We've been working on this problem for quite some time in my lab. We released a benchmark piling together several "intrinsic evaluations" that don't require model training. We're currently investigating correlations between performance on this benchmark and on downstream tasks. Here it is - https://github.com/MeLeLBGU/tokenizers_intrinsic_benchmark - where there's a link to the paper we introduced it in, used for checking how inference schemes work together with various token vocabs. It's for English, but cited work and citing work have some of these for other languages as well.
by ImPostingOnHN | 2025-05-31 06:47:55+00:00
gemini is the worst LLM I've used, whether directly or through search. As in your experience, it regularly makes stuff up, like language/application features, or command flags (including regarding google products), and provides helpful references to sources which do not say what is cited from them.

in my case, it does so roughly half the time, which is the worst proportion, because that means I can't even slightly rely upon the truth being the opposite of the output.
by godelski | 2025-05-31 06:48:54+00:00
I never thought to extend the analogy like that, but I like it. It's showing. I mean look how people think my comments imply I don't know what triage is. Not knowing that would be counter to everything I'm saying, which is that a lot of these value numbers are poor guestimates at best. Happens every time I bring this up. It's absurd to think we could measure everything in terms of money. Even economists will tell you that's silly
by johan914 | 2025-05-31 06:49:23+00:00
Qwerty is top-row heavy. In my experience, a natural fast typer will naturally lean away from home row "touch typing" to a top-middle row hover style of typing. You have to use an alternate layout to really grasp what home row typing should be. Also, Z (and similar for the whole left bottom row) should be pressed with the ring finger. I'm really curious why anyone would use the pinky there, unless your hand is angled to the left.
by antisol | 2025-05-31 06:49:30+00:00
It seems someone hasn't been very thorough in their investigation.

Actually, this user has been posting in this thread for months - the earliest post I saw was in January. The user posted several times asking for updates as to whether this feature was planned or not, fairly politely it seems to me, and was totally ignored as far as I can see.

After repeatedly asking for updates and having no response whatsoever, it seems they became disillusioned. Which I think isn't unreasonable - it's my opinion that it's pretty rude for a maintainer to ignore reasonable questions put to them, and that it's quite reasonable to be offended when you are ignored in this way. You talk about "aggression", I say ignoring people is an act of aggression, and it seems to me that this user has simply responded in kind.

We could get into a discussion on whether a maintainer has any responsibility to respond to users asking questions, and then use that as a basis for deciding whether specific posts by this user were justified or not, but my point is that the picture you paint with your post is inaccurate and incomplete. At best.
by badsectoracula | 2025-05-31 06:50:17+00:00
> Take something like JIRA, it's entirely laughable because a simple LLM can handle entire project management with freaking voice with zero programming

When I used a not-so-simple LLM to make it act as a text adventure game it could barely keep track of the items in my inventory, so TBH i am a little bit skeptical that an LLM can handle entire project management - even without voice.

Perhaps it might be able to use tools/MCP/RPC to call out to real project management software and pretend to be your accountant/manager/whoever, but i wouldn't call that the LLM itself doing the project management task - and someone would need to write that project management software.
by gsundeep | 2025-05-31 06:50:35+00:00
We'll be adding the ability to run MCP Defender through a local LLM soon, so using that approach no data will leave your computer to perform a scan.

Yes, there is a delay for MCP exchange, but I imagine that most MCP calls in the future will be done in "YOLO" mode where the user prompts a large task and an agent makes 1000's of MCP calls over hours to accomplish it. This would add some time to the overall task but IMO this is a small price to pay for added security. Also, the delay will decrease over time.
by yuvalpinter | 2025-05-31 06:50:53+00:00
A few years ago we released SaGe, which is a contextual tokenizer, meaning that it builds a vocab that's fit for an LM use case because tokens are selected to appear within as clear a context set as possible in a corpus. https://github.com/MeLeLBGU/SaGe It does better than both BPE and UnigramLM in several benchmarks. https://aclanthology.org/2024.acl-short.73/
by wonnage | 2025-05-31 06:50:57+00:00
I think this is one of those things that's way easier if you start early. Not sure if schools still have typing classes now. I vaguely remember mine in the 90s, but I didn't really get fast until I started playing MUDs and typing was a matter of life and death!

Now that I think of it, they were also really helpful for learning how to scan a wall of console text and look for the useful bits, and also realizing the value of configuring shortcuts and syntax highlighting. I see someone already had the idea of using a text adventure to learn Bash: https://gitlab.com/slackermedia/bashcrawl
by jaggederest | 2025-05-31 06:51:10+00:00
The wonderful thing about a sigmoid is that, just as it seems like it's going exponential, it goes back to linear. So I'd guess we're not going to see 1000x from here - I could be wrong, but I think the low hanging fruit has been picked. I would be surprised in 10 years if AI were 100x better than it is now (per watt, maybe, since energy devoted to computing is essentially the limiting factor)

The thing about the latter 1/3rd of a sigmoid curve is, you're still making good progress, it's just not easy any more. The returns have begun to diminish, and I do think you could argue that's already happening for LLMs.