But you probably need >$10M to not HAVE to work and live a low-risk comfortable life in even modestly expensive parts of the US.
The funny thing about money is, it's really hard to save $1M and $10M, but once you get there, it's pretty easy to grow that substantially.
The fundamental problem in the West, IMO, is that we make it so hard to save even small amounts of money, and so easy to compound huge amounts of money (and no the EU is not much better on this front than the US).
$10M is also perhaps asking for too much to live a modest life even without working, but I hear you with rising costs and healthcare. In any case, $10M is 100x smaller than $1B.
Good point. I currently choose to give money to Anthrophic rather than OpenAI because they align a tiny bit more with my values and the product is good. Perhaps releasing an open source model every year could be a differentiator from competitors, where enterprise and individuals choses the lab not because is the best model out there but because gives autonomy in case something happens to the organization providing the models.
For now. Progress in hardware/model efficiency is one of the threats the big AI labs face, because if LLMs become commoditized they can’t make back the billions they spent.
Every serious engineer I've seen try to use it ran away screaming, because of limitations in the sandbox.
I've also seen people set their coding agents up entirely within containers -- that may be the better way going forward, but it's an extra stop and a lot of extra plumbing to maintain.
Doing so would be an effective admission that LLM guardrails are inherently probabilistic, unpredictable, and insecure. Plus the only truly robust sandbox approach would be clunky setup of a local VM.
> I have the feeling that the introduction of automatic QA may raise the bar of quality for new releases of software, and maybe partially compensate for the lower quality of the code produced at high speed with the use of automatic programming.
I've been building a compiler with LLMs for a memory safe language like Rust with near zero cost abstractions (no GC), but with WAY less cognitive overhead.
I can tell you right now:
1) It's 100x more than I could have achieved with zero compiler design experience.
2) I'm HIGHLY skeptical that LLMs can build something of this complexity (in some ways it's more difficult than implementing a Rust compiler) - so the testing is quite robust - 3 different systems (unit, integration, fuzz tests) each with mutant testing, each with between ~65-90% line coverage and ~50-80% branch coverage, combined with ~99% line coverage and ~86% branch coverage.
There is ZERO chance I could get something even close to this level of "working" by myself ever - let alone with minimal effort.
The test is kind of simple - if LLM's can do this... They should be able to do just about anything... Compilers are notoriously difficult to verify they actually work, rather than just kind of work sometimes...
People can say I'm wasting my time all they want.
But, one, it's been enlightening. I'm literally in awe of what they can do and have done.
Two, I've developed a bunch of tooling / metrics necessary to get them to be able to do something at this level of complexity without falling over themselves. And I think it can work at scale pretty easily.
Nearly all of the research comes from the 80s or farther back for the complexity metrics.
Hate to be a pedant, but that's really not what "zero cost abstractions" means. The idea behind those is that you get a cleaner interface to some gross machine functionality/OS API/etc. layer, but don't pay a performance cost vs. using the gross lower-level layer. E.g. Rust's Option, unlike C++'s std::optional.
What you're thinking of is "no runtime" or "lightweight runtime", which does often mean "no garbage collector".
Rust's zero cost abstractions mainly stem from its affine ownership model managing memory lifetimes safely and correctly with zero cost - as that is the killer feature... That's what I do.
When people think of "zero cost" they don't think about std::optional. They think about not having to manage memory lifetimes AND NOT having to pay for a Garbage Collector to do it for you. That was always the trade you made until Rust.
I add on some cost to locks to prevent deadlock, and some cost to loops to insert co-operative yields in concurrent contexts unless you turn it off.
Affine as in substructural linear types. They correspond to linear logic [0], and affine logic is named such because the way it's defined corresponds to affine functions. You don't literally need to scale your pointers though.
You're not wasting your time; LLMs have written plenty of compilers. Compilers are easy for LLMs to work on, because their level of verifiability is very high. That is, an LLM can easily determine whether what a compiler is doing is correct or incorrect.
Automated verifiability goes down once a software project incorporates things like:
> while simultaneously making themselves look good to investors by showing they're embracing the hip new technologies to become a more streamlined and cost-efficient operation than ever.
This is not anything new... It just has a new name...
Contrary to popular belief, solar panels don't generate zero power on cloudy days.
They typically generate 10-25% of their maximum output on the cloudiest of days. Most cloudy days are not maximally cloudy.
We don't need solar panels everywhere to get even close to ~100% renewables (with nuclear, wind, new geothermal, and hydro). The areas where you put them are distributed enough that it would be exceptionally rare to ever encounter a meaningful need to ration.
So, storage is an issue, but not as big of an issue as most people think, and we do not generate anywhere near enough solar energy for it to be a reasonable concern yet...
There's also more solutions than just conventional batteries. There's pumped hydro, etc...
> They typically generate 10-25% of their maximum output on the cloudiest of days. Most cloudy days are not maximally cloudy.
If you're at higher latitudes, this is notably less of a drop-off than you see between high/low season.
My friends with residential solar see <10% overall output in January vs July. (~60% drop from fewer sunshine hours, ~80% drop from decreased solar irradiance.)
This gets complex quickly, because temperature matters too: cells are more efficient when they are cold. These effects interact and the results are sometimes surprising.
Many pure-numbers theoretical comparisons also make the assumption that you can consume all the power that the cells generate, which is not always the case. In an off-grid installation with a battery, for example, you might not be able to consume everything, depending on the month of the year. Practical example: my installation gets some of peak usage numbers in March/April, because that's when it's still cold and I use the power for heating. The cells are cold, I need the power, and there is some sunshine, all this combines. It's not obvious.
Yeah, I mean these aren't entirely theoretical, like observationally, people I know locally are getting <10% January vs July generation - I'm working backwards to get the relative proportion of the drops due to solar hours vs irradiance.
They all have a relatively generous (I think - I'm not especially familiar with policies anywhere else) grid policy where they sell back any over-production in the summer. (They switch between summer/winter rates, so in the summer they buy/sell at ~35c/kWh and in the winter they buy/sell at ~8c/kWh. These rates are only effective as long as you don't have a net-surplus of generation in the year, so it doesn't make sense economically to oversize the system for more winter generation, as then you'll be generating more in the summer than you can use or sell back.)
Curtailment and dump loads are pretty straightforward, though, so using all the power isn't as critical as people might imagine either.
It's better to overbuild the dc-to-ac ratio moderately and just accept that on a summer noon you'll be dumping or curtailing, and still get useful percentages in the winter. I'm in the fortunate position of having an essentially infinite dump load (water pumping and heating) that would effectively turn most of my solar into real usage, but even most people can preheat a hot water tank and things like that. With electric cars it's even better.
One of Standard Thermal's use cases is excess DC power from existing solar farms that would otherwise be curtailed because of inverter/interconnect limits.
There's also the angle of the sun to consider, it changes quite a bit in higher latitudes between summer and winter so if you want maximum efficiency you need to tilt the cells accordingly. But I don't think most residential solar does that.
The way the math works for grid-connected residential here, if you're not adjusting the angle, between seasons, you'd be best off leaving it at the optimal winter angle all year, which would minimize the difference between peak/trough generation.
And people use less energy at night. Yes, they do need heating/cooling and a few other things at night, but the peak is during the day and in the evening.
This argument is almost closed at this point, with PV + batteries being quite price competitive. We're no longer in 2018.
I've worked in many places on many teams and never met anyone that essentially does nothing besides write code...
I question the obsession engineers have with their "code writing" being replaced by a machine.
Do you really think that's the value you bring to the table?
Non-engineers don't want to sit down and think about anything, they don't want to sit down and test that thinks actually work, they don't want to think about all the failure cases that could go wrong besides a few shallow tests, and they definitely don't want to have to pick up the mess if something does go wrong...
This is what you get paid to do. Coding is a small part of that.
You are on point: The developers of the future need to hold much more of the domain that is being developed for. It is not a job to write JSX and tailwind classes anymore, so you need to move up in abstraction - and complexity.
But you probably need >$10M to not HAVE to work and live a low-risk comfortable life in even modestly expensive parts of the US.
The funny thing about money is, it's really hard to save $1M and $10M, but once you get there, it's pretty easy to grow that substantially.
The fundamental problem in the West, IMO, is that we make it so hard to save even small amounts of money, and so easy to compound huge amounts of money (and no the EU is not much better on this front than the US).
It should be the opposite.
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