1 - I worked abroad and wasn't really familiar with the systems there. Gemini made me aware of a kind of pension account that I could withdraw from when I left the country netting me a few thousand dollars.
2 - Working as a tech contractor, charging by deliverable, Codex/Claude Code speed me up and it doesn't seem to have significantly dropped rates in the market.
3 - Also contractor related: I had Claude do a quick legal sanity check of my contracts, and it warned me of some clauses that I'd be better off removing/changing/refining. I was not aware of these nuances and would not have paid a lawyer for this as the contract was too small, but the changes were accepted by the client and reduced my risk exposure meaningfully.
4 - Learning a foreign language, I use it to check my draft emails and messages. It corrects them but also serves a tutoring role providing feedback, improving both the accuracy of my communication and my rate of language acquisition.
5 - Gemini Deep Research helped me narrow down tent models that met my fairly specific set of requirements. Very happy with the tent I ended up buying, from a brand that was not on my radar before.
Yes I was very surprised after the whole "scandal" around ChatGPT becoming too sycophantic that there was this massive change in tone from the last preview model (05-06) to the 06-05/GA model. The tone is really off-putting, I really liked how the preview versions felt like intelligent conversation partners and recognize what you're saying about useful pushback - it was my favorite set of models (the few preview iterations before this one) and I'm sad to see them disappearing.
Many people on the Google AI Developer forums have also noted either bugs or just performance regression in the final model.
https://ppc.cs.aalto.fi/ covers some of this (overlapping with the topics the person you responded to mentioned, but not covering all, and including some others)
If the only moat really will be the scale of computation resources, that's great news for users, because it will be an extremely competitive market where prices will be driven down very effectively.
I suspect that model quality/vibes and integrations will play a role as well though.
I can't tell if you're insinuating that Singapore is a pass-through for H100's heading towards China or whether there is some significant development taking place in Singapore that I'm unaware of?
What's happening definitely makes me nervous, but "at best a WW3-event and at worst an extinction-event" seems a bit much. Mainly because there are a _lot_ of unknowns. Better try to get comfortable with just riding this out.
I'm trying to parse the idea of "a collective agreement" but can't fully wrap my head around how that would work.
It seems to me more like the lack of a "Walmart Law" is a result of e.g. lack of economies of scale and other economic structure, rather than some collective agreement. (If it was profitable to break out of that agreement and start a "Walmart Law", it seems we'd see that happen pretty quickly?)
But if you know more about this and I'm off the mark I'd love to learn
For me the excitement is that around the o3 announcement I had a feeling like we were heading to an OpenAI / Sam Altman controlled dystopia. This resets that - you can run the model yourself, you can modify it yourself, it's essentially on par with the best public models, and it gives hope that the smaller players have a fighting chance going forward. They also published their innovations bringing back some of the feeling of open science that used to be in ML research but which mostly went away.
Given what we just saw in terms of the DeepSeek team squeezing a lot of extra performance out of more efficient implementation on GPU, and the model still being optimized for GPU rather than CPU - is it unreasonable to think that in the $6k setup described, some performance might still be left on the table that could be squeezed out with some better optimization for these particular CPUs?
I don't think the part about the market reaction is too surprising, for COVID it took a while for the market to react as well.
Seeing that DeepSeek-R1 has benchmark scores like o1 is not the same as seeing that people actually like it, that it's being adopted, and that stated training costs are getting accepted as credible.
(But I agree that there is a lot of irrationality in these markets.)
My interpretation is that yes in the long haul, lower energy/hardware requirements might increase demand rather than decrease it. But right now, DeepSeek has demonstrated that the current bottleneck to progress is _not_ compute, which decreases the near term pressure on buying GPUs at any cost, which decreases NVIDIA's stock price.
A bit like humanoid robotics - not the most efficient, cheapest, easiest etc, but highly compatible with existing environments designed for humans and hence can be integrated very generically
I followed the drama. The point I was (somewhat unsuccessfully) trying to make was that while, sure, there were groups who wanted him back (mainly the groups with vested financial interests and associated leverage), my sense was that the way it played out was not necessarily in line with wider humanity's best interest, i.e. as would have been hoped based on OpenAI's publicly stated goals.
The first few years out of university I consistently had < $10k on my bank account and was traveling as much as I could, with just occasional part time work to "fill up" a few k$. I loved it and couldn't imagine living any other way, neither retirement nor risks were just really on my mind at all (it wasn't really a zen thing).
Now I have a child and feel completely different. The moment she arrived I immediately felt way behind on retirement savings and stability and since then my #1 priority has been to catch up. I'm hoping that not long from now I'll be able to translate being more secure on paper to also mentally getting back the care free feeling I had before.
1 - I worked abroad and wasn't really familiar with the systems there. Gemini made me aware of a kind of pension account that I could withdraw from when I left the country netting me a few thousand dollars.
2 - Working as a tech contractor, charging by deliverable, Codex/Claude Code speed me up and it doesn't seem to have significantly dropped rates in the market.
3 - Also contractor related: I had Claude do a quick legal sanity check of my contracts, and it warned me of some clauses that I'd be better off removing/changing/refining. I was not aware of these nuances and would not have paid a lawyer for this as the contract was too small, but the changes were accepted by the client and reduced my risk exposure meaningfully.
4 - Learning a foreign language, I use it to check my draft emails and messages. It corrects them but also serves a tutoring role providing feedback, improving both the accuracy of my communication and my rate of language acquisition.
5 - Gemini Deep Research helped me narrow down tent models that met my fairly specific set of requirements. Very happy with the tent I ended up buying, from a brand that was not on my radar before.