colincooke

My take is that the friction is the point, and I'd much rather have a colleague communicate poorly to me than have them give the LLM response. The reason being I view my relationships at work as investments, and working together (communicating) helps build that investment through learning and feedback.

If someone says "x broken" and that's a bad response it becomes a learning opportunitity, something I can invest in. When I communicate poorly, I hope my colleagues help me understand why and give me pointers to improve.

Perhaps I'm being overly optimistic, but I've had the best growth with co-workers when actually engaging at a meta level and trying to help (and be helped) communicate better.

Using AI shifts that burden and entirely demoralizes any investment motivation I have. It's a view that communication is transactional rather than collaborative (we're all on the same team).

I want my team to work better, and be better, and if people offload their comms to an external system to generate I've lost that opportunity for growth.

Oh man, this reminds me of my "party trick" back in the day of saying I could tell what OS a computer was running by listening to the HDD seeking. The good old days

It is worth noting that this study was tbh pretty poorly performed from a psychology/neuroscience perspective and the neuro community was kind of roasting their results as uninterpretable.

Their trial design and interpretation of results is not properly done (i.e. they are making unfair comparison of LLM users to non-LLM users), so they can't really make the kind of claims they are making.

This would not stand up to peer review in it's current form.

I'm also saying this as someone who generally does believe these declines exist, but this is not the evidence it claims to be.

Nice work! Would totally have used this when I was freelancing. Honestly love the serif'd fonts, would love to see everything serif'd tbh.

Also back when I had to do these (I used Wave) having a notes section was very useful to include a few things (i.e. I used to include conversion rates). Would probably be pretty easy.

Again please read my post carefully. There is a valid critique of overhead rates, but simply doing it suddenly in this manner has little added economic benefit in the long run, while ruining lives and creating waste/chaos in the short run.

You can make a strong argument these institutions require reform, but such reform should be done not overnight, and not through such broad strokes.

The entire academic industry is in turmoil, the uncertainty on how bad things could get is probably the worst of it as Universities are having to plan for some pretty extreme outcomes even if unlikely.

For those who are questioning the validity of a 59% (or higher for some other institutions) overhead rate, your concerns are worth hearing and a review could be necessary, but oh my please not like this. This was an overnight (likely illegal!) change made with no warning and no consultation.

If the government decided that a cap was necessary it should be phased in to allow for insitutions to adjust the operational budgets gradually rather than this shock therapy that destroys lives and WASTES research money (as labs are potentially unable to staff their ongoing projects). A phased in approach would have nearly the same long-term budget implications.

Are there too many admin staff? Likely? Is this the right way to address that? Absolutely not.

For those who are unfamiliar with how career progress works in Academia, it is so competitive that even a year or two "break" in your career likely means you are forever unable to get a job. If you're on year 12 of an academic career, attempting to get your first job after your second (probably underpaid) postdoc and suddenly there are no jobs, you can't just wait it out. You are probably just done, and out of the market forever as you will lose your connections and have a gap in your CV which in this market is enough to disqualify you.

Quite a fun paper, but very difficult to draw conclusions from. Their headline finding is that they created a map between resting state and "watching a movie".

This is, for better or worse, the kind of research you can only do at institutions which have free fMRI scanning (MIT, Princeton, Harvard, etc.). No behavioural links, only very detailed activation maps that we can't really draw conclusions from. A missed opportunity IMO to spend these kinds of scanning resource on some kind of more narrowly focussed task with some behavioural outcome they can link to brain data.

To me the issue with AI generated code, and what is different than prior innovations in software development, is that it is the the wrong abstraction (or one could argue not even an abstraction anymore).

Most of SWE (and much of engineering in general) is built on abstractions -- I use a Numpy to do math for me, React to build a UI, or Moment to do date operations. All of these libraries offer abstractions that give me high leverage on a problem in a reliable way.

The issue with the current state of AI tools for code generation is that they don't offer a reliable abstraction, instead the abstraction is the prompt/context, and the reliability can vary quite a bit.

I would feel like one hand it tied behind my back without LLM tools (I use both co-pilot and Gemini daily), however the amount of code I allow these tools to write _for_ me is quite limited. I use these tools to automate small snippets (co-pilot) or help me ideate (Gemini). I wouldn't trust them to write more than a contained function as I don't trust that it'll do what I intend.

So while I think these tools are amazing for increasing productivity, I'm still skeptical of using them at scale to write reliable software, and I'm not sure if the path we are on with them is the right one to get there.

Seeing as you're here, the reason the price is too high for us is that "SCALE" plan is too much for us and the "PRODUCTION" plan is too little. I'd happily pay $200/month for two servers, but can't justify $400/month for two (we only have two right now).