oldmanhorton

“Not with that attitude!”

Standing by morals and ethical responsibilities is hard, it takes mental and physical energy and there are plenty of ethical fights we all have to concede every day as a result. But at the “society” level, I think this sort of rhetoric just leads us further down the hole. We can continue to fight the battles that we have the willpower and means to fight, and that’s a very individual decision. Principled people with high tolerance for bullshit (seemingly like the guy in TFA) can make a lot of difference, IMO.

Nah man, no you don’t. There are very few absolutes in the world and that certainly isn’t one of them.

It’s mostly from people using their personal accounts to run LLM services that serve a larger team or organization. At least at Microsoft, it’s still impressively hard to get access to an LLM for service usage with high enough rate limits to be useful, making running services on dev boxes much more appealing (despite the countless drawbacks that few people seem to care about around security, compliance, reliability, etc).

It’s interesting that models seem, to a distant outsider of biology and drug discovery like me, to be good at coming to new conclusions from existing data. I feel like in coding, it’s the opposite - I have to drag the models kicking and screaming towards anything resembling a novel or nuanced approach to some problems. If anything, this behavior in coding is why we say senior+ engineers will continue to be high value employees, because we can steer the models away from boilerplate and overly generic solutions towards ones that fit aspects of the domain we understand more intrinsically.

This could easily just be how it looks from the outside of biology, but it does seem to produce more novel conclusions in biology than it does in coding and art. Curious if others have counter examples…

The dotnet team provides some agent plugins which solve some of these issues. I expect unions in dotnet 11 will need some skill updates too.

The change with this justification absolutely exists and has existed for a long time, but this justification only works for small changes (in the past and still today). Don’t come to me with a huge refactor or new feature and this explanation, which is happening more and more recently (it’s an easy strawman to make and hard to prove, but I certainly see it in practice).

Some of us don’t use an adblocker because we are aware that ads are how most websites get paid for on the internet. I pay for sites I care to support, but for something like LinkedIn, I’d rather have their monetization scheme push me away from any usage than block the ads and make the site slightly more palatable.

I think this is a pretty unfair takeaway when AI generated text is often so wordy, flowery, and full of jargon and abstract nouns. People are never going to read East of Eden or academic dissertations as quickly as direct, simple language either

You’re not a novice, there are a lot of us who know exactly what we are doing and see this as a huge downside. We are just being told to go faster, faster, faster lest we miss out on… something?

Both ahead of time compilers and JIT compilers often perform autovectorization of tight loops. The problem is that lots of hot loops are not necessarily simple loops, and in particular a lot of source code is written in a way which uses sequential dependencies that can’t be modeled in SIMD code. Aside from undefined behavior in C/C++, most compilers will fail to autovectorize because doing so would very slightly change the behavior of your code in a very hard to understand way.

A year and a half later? Does that really count?

I feel like this can be explained in part by “I like using it for myself, but I hate when others use it.”

When you use ChatGPT for yourself, you may have a sense that what you see is made up; when someone else that you trust uses it and pronounces the output in a way that suggests it is their own, you are left doing much more complex social math to figure out if your trust in this person or entity can hold. It gets exhausting, personally.

“Think of the children!”

When AI produces those meaningful advances in those fields, great, we can start having meaningful discussions about them. The greatest medical advancement of the 21st century is likely mRNA, or maybe GLP-1 for some. Neither were LLM assisted in any meaningful way as far as I know (they predate ChatGPT, perhaps more primitive models were involved in ways I’m not familiar with). Until those advances come, this argument is fanfic.

Plus, in the most morbid way possible: who gives a shit about living longer if they are stripped of their career, are inundated with slop at every angle, and can’t trust any information. These are real problems that AI has already created, unlike the fanfic of ridding cancer.

I have no advice to offer, I only wish you good luck. I am still lucky enough to be employed, but when this whole parade ends, I have no idea what comes next - my only skill is programming and related knowledge work. I think the only path forward is to try to jump ship to another white or blue collar industry…

Have you considered just… writing code? Like we used to in the good old days? If the tool drives you to that point of frustration, maybe it’s time to give the tool a break.