kevinqi

it's a good default because you really do get prompted incessantly without it. and since plenty of people are going to be using auto mode anyway, might as well make it as widely-used as possible so that you can focus on making auto mode safe.

does anyone have a data-backed reason as to why US market share has capped out around 10%? is it economics + lack of access to chinese EVs? range anxiety?

my assertion isn't that china isn't able to surpass western AI. I think it may well happen. I've been to china many times and am well aware of how ahead they are in many technological/societal areas.

at the same time, I don't buy the idea that distillation is unimportant in assessing what Chinese labs are capable of. If it wasn't, why did Kimi's release timing coincide so well with Fable's launch?

and if Anthropic hadn't released Fable, would we have Kimi today? If the answer is no, then I think that's still a very important point to consider.

I agree distillation isn't illegal; I also think Moonshot/Kimi is very impressive. But the more interesting question is whether labs like Moonshot can be a real competitor to OpenAI/Anthropic. If you can only play catchup (however quickly you do that), then you're never going to be at the frontier - I think that's why distillation matters.

don't think it's a societal problem; it's just a direct result of capitalism. and while capitalism causes all sorts of huge problems, it might also be the best of the options we've got

Gridmatic | Product engineer + data engineer | 175-235k + equity | Cupertino, CA (hybrid)

Hi HN! We’re an energy + AI startup that applies modern deep learning and optimization to improve the use of renewables and grid-scale batteries to deliver cheap, clean energy to commercial/industrial customers. We also do energy trading and battery optimization.

Roles:

- Data engineer: we're hiring our first data eng! Looking for a startup-minded SWE to work on both ingest and transformation of datasets that power our best-in-class ML models for energy forecasting.

- Product engineer: our energy sales have been growing rapidly and we want to 10x it from here, which involves building a lot of tooling to make sales more automated. This tends to be backend/data heavy, but will also have some frontend (NextJS/React/Typescript).

If you're interested in making a real-world impact on climate/energy, or if you know someone that might, please email me and include a one sentence description of the most impressive thing you've built: kevin@gridmatic.com

yeah not redeploying on credential changes seems like a design flaw. Render redeploys on env var changes, for instance.

it is disappointing, but is it shocking that people most driven by gaining money/power are the ones the most successful at achieving it?

I don't know if it's guaranteed to work, but the strategy is real. I know Notion won vs. competitors in the space because they focused on consumer first, and consumers then brought Notion into their workplaces.

I think Prisma does type-safe ORM really well on the typescript side, and was sad it doesn't seem to be super supported in python. This feels sort of similar and makes a lot of sense!

seems nice. I imagine the strategy here is going for expanding user base so Apple can sell more software services?

just one q: have you been to china before?

I think there are profitability requirements, right?

+1, very polite way of saying it. of course there's a difference between the two posts. open source is interesting but not enough with a financial app, since it's all about trust + usefulness.

landing page needs to look good and communicate the value prop super effectively. If it doesn't look good you'll lose people's interest in about 2 seconds.

probably the "slapping steamOS" part of that

my only minor critique is using lorem ipsum examples. It tends to make me want to gloss over instead of reading; I prefer seeing realistic data. other than that, it's a really cool post

right, it is just syntactic sugar, but if that wasn't helpful then why have it in dev either? I find it more confusing to have asserts be stripped, which creates an implicit dev/prod discrepancy

really? it's pretty but I find it unreadable/unusable

I didn't think much of it until I canceled Cursor to try out copilot, which is slower and yet also worse quality. I reluctantly resubscribed to Cursor.

interesting, I didn't know that corollary. sounds about right though.

duplicate code is not that bad. reduce duplication over time as you find the common patterns/abstractions, instead of trying to build abstractions too early

very cool. btw, I also love that "sorry" is the "any" equivalent in Lean

as someone who hasn't seen Lean before but was curious from alphaproof, love the intro! curious if you can mention what you're working on in Lean?

I mean, why do systems go down at all? a lot of big outages are simple misconfiguration or cascading failure from what seemed like small changes. It's rarely due to the physical constraints of the world

I made a web microtonal keyboard a while ago which does support this! different format though

https://www.microharmonic.com

yeah, the benchmarks are just a proxy. o3 was a step change where I started to really be able to build stuff I couldn't before

super cool

just based on how long it takes to produce these images, and how much text responses cost, I wouldn't be surprised at all if it was close to cost

Gridmatic | Senior fullstack software engineer, Senior backend software engineer (ML infra) | Full-time | Hybrid (Cupertino, CA)

Gridmatic uses ML and weather data to forecast energy prices in the US, which can get really volatile as extreme weather becomes more common with climate change. We’ve been using those price forecasts to e.g. optimize very large batteries, which help make the grid more stable.

On the fullstack side, we're building tools to apply our forecasts to automated battery storage optimization and energy volatility risk mitigation. On the ML infra side, we're working on infra to be able to scale to larger and more complex models, and to apply better (but more computationally intensive) weather models in our forecasting.

Our stack: python, react/nextjs, kubernetes, GCP, postgres, bigquery

Our goal is to help accelerate the adoption of renewable energy on the grid. It's super interesting, the team is incredibly smart, and we're profitable.

If you're interested, DM me or email me at kevin@gridmatic.com, and please answer the following question: what's the most impressive thing you've built? (include a link to code if possible)

I don't disagree, but since the quality of AI is largely a function of the quality of human content, there's always going to be value in well-written human content. If humans stop producing content, I think the value of AI/LLMs drop significantly as well.