ghc

I've been using Haskell for 20 years. I've been running a company built on Haskell for 10. I have a very large legacy Haskell codebase. I've invested in several companies built on Haskell. Your anecdote is about your own lack of familiarity, nothing more.

Yes, companies can get into trouble with Haskell compile times, memory use, etc., but enforcing disciplined coding rules and advances in tooling solved the majority of the problems by 2016.

We use LLMs to assist in writing Haskell and have for several years. We keep track of compile times to catch regressions and on our largest code base an agent-driven change takes an average of 96 seconds (as of this month) to compile. Agents looking to do quick compile checks during code writing can run with flags that make the compilation run in less than 5 seconds. In all cases, running out test suites takes a lot longer than compile times.

The only time this isn't true is when you compile from cold start, as you would when using multiple work trees...which is the expected behavior when vibe coding features. So yes, I believe the issues they're running into have a lot to do with vibe coding. Check out all their integrations...Haskell's probably a poor match for what they do, but vibe coding integrations is probably what they need to do to get new customers.

I was puzzled by this article at first, but when you put it that way it makes more sense. The author also had a presentation awhile back about why Haskell is a terrible language for startups to adopt. I imagine that in the current venture environment vibe coding is being pushed heavily by investors since companies are effectively in an arms race where feature development cost is moving towards zero and investors don't care about individual companies because they have a portfolio of bets.

It's people over 65. Cell phone ownership is pretty much universal, but only 78% of people 65+ own a smartphone. I don't think that's really surprising at all. I wouldn't expect an 80 year old to adopt a smartphone when their cognition, fine motor control, and/or vision is going. And who needs one in a nursing home? I bet if they broke it down further you'd find that the non-ownership skews towards people who were already elderly ~15 years ago.

Tragic. Most of the crew onboard were almost certainly aerospace engineers tasked with collecting sensor data.

Perhaps unsurprisingly, in New England jam seems more popular than jelly. The FDA regulates the labels...jelly is made from fruit juice, while jam is made from fruit chunks. The only jelly I routinely see is concord grape jelly. Jams are usually apricot, raspberry, or strawberry.

Given the number of small batch jams available at various farmers markets, my guess would be that for smaller farms, making jam is more practical than jelly.

Reviewing code is important, but it's only 50% of the learning process, at best

I don't know about everyone else, but the code I reviewed as a Junior was high quality code I was expected to learn from. That's entirely different from doing code review on whatever CC outputs.

BitTorrent also enabled search engines to be built easily, which created discoverability. Unfortunately it's a much harder problem for git repos, especially when competing with GitHub search.

Oh, that's pretty cool! Now I can't decide whether that approach or one based on AT is better...

Is there really nothing like BitTorrent for git, or have we just not heard about it because of GitHub's network effects? It feels like this problem was solved long ago for binaries.

Things Fall Apart

Turning and turning in the widening gyre

The falcon cannot hear the falconer;

Things fall apart; the centre cannot hold;

Mere anarchy is loosed upon the world,

The blood-dimmed tide is loosed, and everywhere

The ceremony of innocence is drowned

Except ASML licensed the technology from the US Government, after the government labs built the first EUV fab in 2001. Not to take anything away from ASML...all the US companies that also licensed the tech failed to commercialize it, but the US Government blocked Canon and other Japanese companies from acquiring the technology. The entire reason ASML has the technology and nobody in Japan does is geopolitical.

Optics and photoresist materials too. The partnership developed the first EUV lithography in 2001: https://www.llnl.gov/article/27641/euvl-partnership-makes-it...

Let's not forget the really big gamble (inventing EUV) was made in the 1990s by US national labs: Sandia, Lawrence Livermore, and Lawrence Berkeley.

I mean, your brain has an order of magnitude more neurons than there are people on the planet. I think humans are just incapable of wrapping our heads around the sheer number of tiny things that fit in small macroscopic spaces.

Why would a machine need to make anything? Is a robot arm not a machine? How about a trash compactor? Are the 6 types of simple machines not machines?

the relational model can subsume "graph" queries, but for all the reasons Codd laid out back in the 60s... network (aka connected graph) databases cannot do the latter.

Except network databases have little in common with graph databases...they're much more closely related to hierarchical databases.

I would say that Graph databases are now a strict superset of relational databases, not the other way around. In a graph database a node's named edge can naturally point to a node of any type or having any property schema. Doing this in a relational model requires one of several approaches that could only be classified as fighting against the model (or torturing it, as my PI liked to say).

Oh you're right! I was looking at the last documentation update timestamp, but the original release was 2006. That makes a lot more sense than Itanium support in 2021.

how does this compare to gpt-oss-120b? It seems weird to leave it out.

Oracle® Database Platform Guide 10g Release 2 (10.2) for Microsoft Windows Itanium (64-Bit)

Well, I guess that at least confirms Oracle on Itanium (!?) still supported RAW 5 years ago.

I'm guessing everyone's on ASM by now though, if they're still upgrading. I ran into a company not long ago with a huge oracle cluster that still employed physical database admins and logical database admins as separate roles...I would bet they're still paying millions for an out of date version of Oracle and using RAW.

It seems like Claude has taken Github's place in terms of developer reaction to it being unavailable. It's like everyone forgot how they did things 18 months ago.

I'm so old I remember working on databases that were designed to use RAW, not files. I'm betting some databases still do, but probably only for mainframe systems nowadays.

It took me way too long to get that.

Here's my take on what he was getting at:

Build vs. buy is an eternal question in enterprises. I remember many in-house data teams trying to build tools for "digital transformation" and cloud migration about 10 years ago. The challenge was, building those tools was more expensive than those enterprises could budget for (IT as cost center), so a startup like Snowflake would easily outcompete in-house solutions with their custom, cloud-based tech stack that was necessarily complex because it needed to serve the needs of thousands of customers.

If he's right, the build vs. buy equation has shifted more towards build, at least as far as enterprise software is concerned. IT is still a cost center, but in theory an internal team can now handle more requests for custom tools without looking to outside vendors. Essentially the cost of building in-house might be collapsing and therefore enterprise software startups will be serving fewer customers (who would all pay you more because if solving the problem was cheap they'd do it).

If you had to build a stack for dozens of customers paying huge amounts of money, how would that stack differ from the stack you'd build to serve thousands of customers? Certainly it wouldn't need to be as scalable! And that's probably what he's getting at. I think what you'd do instead, to capture those higher price point customers, is solve their problems more specifically, in a higher value manner.

Many companies already do this, investing far more in field engineers than they do in their tech stack, since customization is essential.

Oh, that actually tracks. I should have checked his bio.

So you're basically telling me to get off HN (and the internet), where lazy writing co-authored by LLMs is increasingly becoming the norm. Great.

The writing style seems a little unnatural, but the odd grammatical error convinced me that it wasn't the result of someone asking an LLM to review the libraries and write the reviews in the voice of an intellectual who went to Harvard.

What a world we live in, that suspecting an LLM guided by a specific prompt would be my first instinct.

As straw men go, this is an attractive one, but...

When I was fresh out of undergrad, joining a new lab, I followed a similar arc. I made mistakes, I took the wrong lessons from grad student code that came before mine, I used the wrong plotting libraries, I hijacked python's module import logic to embed a new language in its bytecode. These were all avoidable mistakes and I didn't learn anything except that I should have asked for help. Others in my lab, who were less self-reliant, asked for and got help avoiding the kinds of mistakes I confidently made.

With 15 more years of experience, I can see in hindsight that I should have asked for help more frequently because I spent more time learning what not to do than learning the right things.

If I had Claude Code, would I have made the same mistakes? Absolutely not! Would I have asked it to summarize research papers for me and to essentially think for me? Absolutely not!

My mother, an English professor, levies similar accusations about the students of today, and how they let models think for them. It's genuinely concerning, of course, but I can't help but think that this phenomenon occurs because learning institutions have not adjusted to the new technology.

If the goal is to produce scientists, PIs are going to need to stop complaining and figure out how to produce scientists who learn the skills that I did even when LLMs are available. Frankly I don't see how LLMs are different from asking other lab members for help, except that LLMs have infinite patience and don't have their own research that needs doing.

The Apollo program cost about as much as 22 Gerald Ford class nuclear carriers.

Amortized over the whole program, each launch cost the same as building 2 Gerald Ford class nuclear carriers, or $26 billion USD.

Here I was thinking this article would tell me how to turn my unmanaged switches into routers, but no, "anything" actually means "any fully featured general purpose computer with networking".

Something many may not know is that beyond his own novels, Tracy was also deeply involved in Jonathan Harr's book, "A Civil Action." He and Harr were friends, and he told Harr about the courtroom case. Later, when Harr would get stuck, he worked with Harr to edit and give feedback on his drafts.