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mgrund

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mgrund
·เดือนที่แล้ว·discuss
The big question is if they manage to keep on their enterprise consumers. Vowing changes nothing, they will be looking at the actual numbers.

Dissatisfaction is kind of expected (my cost goes up 2 orders of magnitude and I already cancelled since there are better options at market rate). Complaining without change won’t matter.
mgrund
·2 เดือนที่ผ่านมา·discuss
Read-only access to all non-sensitive code is how things should be. Huge engineering culture and productivity booster. It’s also very useful to keep each other honest (I’ve found so many “interesting” things hidden away in organizations with tight read access restrictions).
mgrund
·2 เดือนที่ผ่านมา·discuss
swe-bench is a standardized evaluation suite so that's why I'm asking - hopefully there are well-defined criteria on whether this is an open/closed book benchmark.

As I understand it, it is designed to evaluate the LM itself and not agentic systems with online access (very high likelihood of unintentional cheating/solution leaking). The paper and docs are not super clear on the concrete requirements (although reproducibility is emphasized which goes against online access). So I was hoping for someone with more familiarity to chip in.

Obviously not a problem for internal evaluations, but for fair scoreboard submissions it matters. It's not a matter of whether internet searches are useful, but rather what the benchmark is intended to benchmark.
mgrund
·2 เดือนที่ผ่านมา·discuss
I was under the impression that swe-bench (and I guess most other benchmarks) were supposed to be run offline?

I get that you may accidentally include something in local git history, but it feels off to me to run these kinds of benchmarks online.
mgrund
·2 เดือนที่ผ่านมา·discuss
I really really want to like local AI, but I highly doubt it will see wide adoption for a long time.

The additional up-front cost for hardware designed to run an LLM in addition to normal workload is unlikely to be accepted by most consumers.

The scale will be very constrained (like Apples on-device models which are small, heavily quantized, and have a small 4K token context window). It’s also terrible for battery life.

AI as it is implemented today is simply just computationally expensive and unless you put in dedicated hardware (like the ANE) for only this purpose - a large cost driver - I don’t really see it getting large scale adoption.

Companies will probably need a server-backed solution as fallback if they want reasonable user experience, so why even invest in diverse hardware support.
mgrund
·2 เดือนที่ผ่านมา·discuss
My thought exactly! First the usage limits + model limitations and now fundamental change to the billing. Hope some consumer watchdogs are looking into this!
mgrund
·3 เดือนที่ผ่านมา·discuss
There is but I don’t think this is it.

I’ve worked most of my career in US tech satellite offices and I have not experienced EU team members to be less productive than US team members, nor spend less time on work (if anything, more really since they also need to be available for US time zone overlap).

It’s true there are chill jobs here, as there are in the US.

But ambitious people tend to work as much as ambitious US people (and it’s really more like 40 hours work weeks - 39,5 where I live since lunch is not work time). But again, many are not really counting, it’s just a full time job.

Vacations (typically 3 weeks summer holiday and additional weeks to distribute over the year) does create longer time on skeleton crew. Skilled tech labour is also cheaper so you can just hire more to make up for it.