…reads MRIs and video to detect cancer

…analyze genomics for early target discovery

…assisting surgeons

…folding proteins

And the list goes on in other fields as well. Just hoping the recent AI counterculture doesn’t stigmatize other uses of AI.

Am I a fan of Claude code? Not particularly, but I have used it on occasion. And I’ll never understand someone using an LLM to write anything (especially a comment on a site like HN) intended for consumption by other people. Not because I think it’s subpar, but because the point - IMO - is to make human connections, learn, teach, and debate. That’s hard (impossible?) to do if you’re just typing a 30 second prompt and then copy/pasting the output.

I see it as a double edged sword. People that want the category of AI to succeed can claim a victory when someone uses it to approximate protien folding and invent new drugs. But that also means the entire field is constantly being dragged down by low quality vibe coded sites, slop videos on social media, whatever horrific thing Grok is doing this week, etc.

We need to remember what "Artificial Intelligence" actually means. It refers to the field of research starting in the 1950's developing algorithms related to combinatorial search, planning, and reasoning. Machine Learning isn't AI in the sci-fi movie sense, but it's among the topics you'll find in a textbook like Russell and Norvig.

A problem like protein folding isn't tangentially related to AI, it's at the heart of the kinds of problems the field has been trying to tackle for decades. Yet when there are legitimate breakthroughs, people deride it as "not real AI."

AI is the sum of all of these groups. Also, the "not real AI" thing is more about not real AGI. That's a very different target.

AGI isn't a well-defined concept. So when people say something isn't "real AI" because it's not AGI, I can't take them seriously because they're implying that everything the field has worked on for the past 70 years isn't real AI.

I’ve never found a setup with multiple desktops or similar with a way to quickly switch between apps I’m using more than “editor slightly more left, browser slightly more right, …” and just clicking on a border I know brings that app to the front. I’m sure many think I’m crazy. That’s ok. :)

That said, I generally hate the new OSX UI. Every UI element that is non usable just became larger and wastes space I should be able to utilize. Likewise, it made some operations insanely frustrating (here’s looking at you, corner drag resize!).

AI is definitely going to change things. It already has, but I don't think what it's done is the real change coming. Right now it's just a new tool in the toolbox. It does great at some things and terrible at others. Note: I'm speaking purely about LLMs/generative AI, because other forms of AI are -incredibly- useful and have been for a while (think DeepFold). I only mention it because it's important people remember there's different types of AI models used for all sorts of different things.

What's important to keep in mind are a few things:

* We all stand on the shoulders (abstractions) of giants. People of the past lamented about C, Java, ... every abstraction that came before. Did those abstractions cause the next batch of programmers to lose knowledge about what was really happening? Sure, but each also enabled an explosion of new ways of thinking and problem solving that brought us to where we are now. If you can recognize that, then that will help.

* You became a programmer/engineer for reasons (what I'll call "itches"). Only you know what those are. Buy, my guess is that - like most of us - there was something about the -problem solving- and logical analyses/thinking taking place, and seeing others gaining benefit from that work. First, if you look to another job, pick something that scratches those same itches, otherwise you'll be bored and depressed again very quickly. More importantly, the reason you're even asking the question is because something about AI feels like it's taken that "scratch" away from you. Keep in mind that your "itch" can be abstracted, too. Instead of solving a (for example) network byzantine problem, go one level higher, which has the same problem at the human-scale. Now AI becomes a tool to help you come up with and solve the problem instead of one that's replacing you. Same itch, different level, different tools.

* The comment mentioning "shadowing someone" is some solid advice. Right now you're succumbing to a "grass is greener" effect. That will disappear quickly if you do switch, and you'll still be in the same place if those itches are not being scratched. Again, identify the itch first.

Finally... and I can't stress this one enough... whenever I've been down due to the "itch" not being scratched at work (for any reason, not just AI), I've personally found the best solution to the problem is to volunteer and help others. This could be anything: food bank, big brother, translation services, helping to teach your native language to someone else, or even teaching something you consider important (i.e., programming) to kids at your local school via an after-school program. Every single time I do this I walk away feeling great. Inevitably there was a single point in the day in which I dramatically affected one person's life positively, and they - in turn - affected me similarly. In a class of 10 kids who want to learn to make games, there was 1 who had no way of being able to do this on their own due to at-home problems. At a food bank it was an elderly woman who couldn't speak English and I happened to be the one person who could speak her language (she was so excited to talk to someone). Or being in the children's ward at the hospital over x-mas, delivering toys. And sometimes I'd even walk away with a new set of ideas where my programming skills could solve a new set of problems I discovered existed and lead me to a whole new career.

I was a part time fitness instructor from 1999-2012 and was a (very bad) real estate investor from 2002-2008. I wouldn’t say fitness instructor is just for the young, my wife is now 50 and she has been teaching for 5 years. But it’s definitely not something you can do full time, the money isn’t there and trying to do it too much and is a wear and tear on your body. Even owning your studio isn’t that great as far as income.

But now at 51 and I have been working remotely between three companies since 2020, there is nothing I would rather do than wake up, wash up, and walk to my office in the other bedroom.

We have also done the digital nomad thing for a year and this year we will be away from home for a total of 3-4 months. There is nothing else that I would rather be doing.

My understanding though is that these steps are really the very beginning. Using a quantum computer with quantum algorithms to prove that it’s possible.

Once proven (which maybe article this is claiming?) the next step is actually creating a computer with enough qubits and entanglable pairs and low enough error rates that it can be used to solve larger problems at scale.

Because my current understanding with claims like these is that they are likely true, but in the tiny.

It’d be like saying “I have a new algorithm for factoring primes that is 10000x faster than the current best, but can only factor numbers up to 103.”

First, 100% agreed.

That said, I found myself pondering Star Trek: TNG episodes with the holodeck, and recreations of individuals (e.g. Einstein, Freud). In those episodes - as a viewer - it really never occurred to me (at 15 years old) that this was just a computer's random guess as to how those personages from history would act and what they would say.

But then there was the episode where Geordi had to the computer recreate someone real from their personal logs to help solve a problem (https://www.imdb.com/title/tt0708682/). In a later episode you find out just how very wrong the computer/AI's representation of that person really was, because it was playing off Geordi, just like an LLM's "you're absolutely right!" etc. (https://www.imdb.com/title/tt0708720/).

This is a long-winded way of saying...

1. It's crazy to me how prescient those episodes were.

2. At the same time, the representation of the historical figures never bothered me in those contexts. And I wonder if it should bother me in this (LLM) context either? Maybe it's because I knew - and I believed the characters knew - it was 100% fake? Maybe some other reason?

Anyway, your comment made me think of this. ;-)

It feels easier to portray famous characters how we'd think they'd act but seems harder how we'd expect them to critique something. I don't know of those are just points on a spectrum from easy to hard, or if one requires a level deeper than the other.

When watching a play the actor pretends to be a specific character, and crucially the audience pretends to believe them. If a LLM plays a character it's very tempting for the audience to actually believe them. That turns it from a play into a lie.

Was it, though?

They had Newton (died 1727) playing playing poker (invented at some point during the early 19th century), repeating the myth that the apple fell on his head and then reacting insulted when Data says "that story is generally considered to be apocryphal".

More generally:

In TNG, Holo-Moriarty claimed to be sentient and to have experienced time while switched off despite Barclay saying that wasn't possible, much like LLMs sometimes write of experiencing being bored and lonely between chat sessions despite that not being possible given how they work.

In DS9, there was a holo-village made out of grief, and when it got switched off to reveal the one real person who had made it, while the main cast treated all the holograms as people, that creator himself didn't. Vic Fontaine was ambiguous, being a hologram who knew he was a hologram but still preferring to keep his (fake) world to its own rules and eventually kicking Nog out of the fake world when it was becoming clear Nog was getting too swept up in the fantasy.

In Voyager, the Doctor was again ambiguously person and/or program, both fighting for his moral rights as an author in a lower-stakes echo of TNG's Measure of a Man, and also Janeway being unsure if he was stuck in a loop or making progress with grief about the death of Ensign Never-Before-Mentioned-In-This-Show.

Experienced Rust coders aren't going to find themselves in various borrow checker (and lifetime) pitfalls that newbies do, sure.

That said, the borrow checker and lifetime do cause problems for even experienced Rust programmers. Not because they don't understand memory management, lifetimes, etc. But because they don't - yet - fully understand the problem being solved.

All programs are an evolutionary process of developing a solution to a problem (or many problems). You think one thing, code it up, realize you missed something or didn't fully grok the issue, pivot, etc.

Rust does a great job in the compiler of letting the user know if they've borked something. But often times a refactor/fix in C/D/Zig due to learned (or new) requirements is just a tweak, while in Rust it becomes a major overhaul because now something needs to be `mut` or have a lifetime added to it. I - personally - consider that "fighting" the borrow checker, regardless of how helpful (or correct) it also is.

It absolutely is not. AI counts as a medical device: it’s used to help diagnose and inform medical treatments. However, this is a loophole, because (quoting fda.gov):

> FDA does have regulatory oversight over devices intended for animal use …. Pre-market Approval is Not Required: The FDA does not require submission of a 510(k), PMA, or any pre-market approval for devices intended for animal use.

The FDA will only step in after complaints or enough pets start dying.

- on the left tail are people who know little-to-nothing about (or have little experience with) the given topic and neeed a chunk of time

- then as knowledge and experience increases, less time is needed, eventually peaking out at what appears to be instance understanding + ability to communcate effectively about it

- but then something interesting happens when they get even more experience + knowledge: they now know about all the edge cases, things that go wrong, etc. and once again take more time to think through the topic

I've also found that most everyone is the same in this regard. Every once in a while (like any normal distribution) there's an outlier on one side of the spectrum or the other, but for the most part, everyone is the same.

Where people tend to differ is in their coping skills in such situations. Early in my career I had to learn to ask people to explain their thinking. Later it was me slowing down and realizing there's likely more to it than I think (and for those behind me).

Now it's me telling those at the peak of the curve to slow down, because while they may be right, and -maybe- they've thought it through, that's probably not the case.

TL;DR to anyone who thinks they are a slow thinker - you probably aren't (like imposter syndrome), and just need to learn to slow the room down. Doing so will help you, others behind you, and those in front of you.