becquerel

Location: Alameda, CA

Remote: Yes

Willing to relocate: No

Technologies: GenAI, C#, .NET, SQL Server, Azure, Blazor (serverside and WASM), React.

Résumé/CV: https://jkendall327.github.io/jkendall327/cv

Email: jkendall 3096 at gmail dot com

A lot of experiencing working with and modernizing legacy systems, think WinForms and MSMQ.

I wonder when people will finally feel comfortable not putting vibe coding in scare quotes. Maybe when it accounts for 50% of all new software, instead of only 10%.

Try using a model from a year ago.

I know it's old hat now, because it happened over a week ago, but it's amusing that Millennium Problems are now just benchmarks we use for discussing models.

They could just actually believe what they're saying. People are known to sometimes actually believe things.

Thesis, antithesis, synthesis?

I don't really care, personally. What I care about is that something now exists which didn't exist before. A Ouija board would be equally as good.

AI is becoming a more and more powerful lever that lets you move greater loads per application; it is in a real sense giving you more leverage. But the lever is difficult to use effectively, and the methods for using the level change every week or so.

Don't you remember how awful they were at using versions? When o1 and 4o were both products available at the same time, or how they skipped from o1 to o3?

Try using astra as an orchestrator for deepseek 4.1 flash, it seems to work out quite well.

Text is in a sense way harder to do than images because of radical nonlocality. A word at the start of one paragraph can directly influence the meaning of a word five paragraphs away. Whereas images typically represent the real world, or at least a spatial domain, which gives you a lot of structure 'for free'. If you are drawing a human, you can make a reasonable guess where their hands go in relation to their face. If someone hands you the first half of an essay, finishing it is not trivial.

It would be nice if I could live my life without concern for producing capitalist exchange value. However, I live under the regime of capital and need to pay rent. So my goal is to pay rent with the least amount of suffering on my part.

More compute is coming online at all times.

Perhaps raw statistics, or estimates based on measuring traces in wastewater. I know that in the U.S. during covid they traced some new viral strains using that method.

I think the play now is to just try out whatever the best new model is every time you see a headline that fundamentally reorganizes your conception of what's possible.

If the post drops long before the IPO, it's vain boosterism. If it's near the IPO, it's fattening the pig. If it's after the IPO, it's pumping the stock price.

Build monumental architecture and increase the size of your harem.

Spectacular use of free will.

And you couldn't make Blazing Saddles today.

Around 9T parameters, depending on quantization.

He's been vibecoding some stuff himself personally, on one of his scuba projects. You could take people as actually believing in the things they do and say.

Are you aware of how productivity has increased over the past century in general? That didn't lead to 100x wage increases or more free time. Labour is a market commodity and follows market rules. Increased productivity means more gets done in less time. It doesn't mean you spend less time working

People like checking items off of lists.

You get AIs to prove their code is correct in precisely the same ways you get humans to prove their code is correct. You make them demonstrate it through tests or evidence (screenshots, logs of successful runs).

Tao's broad project, which he has spoken about a few times, is for mathematics to move beyond the current game of solving individual theorems to being able to make statements about broad categories of problems. So not 'X property is true for this specific magma' but 'X property is true for all possible magmas', as an example I just came up with. He has experimented with this via crowdsourcing problems in a given domain on GitHub before, and I think the implications of how to use AI here are obvious.

Does a system being deterministic really matter if it's complex enough you can't predict it? How many stories are there about 'you need to do it in this specific way, and not this other specific way, to get 500x better codegen'?

If you haven't tried it yet, OpenCode is quite good.

It's an extension of how I've noticed that AIs will generally write very buttoned-down, cross-the-ts-and-dot-the-is code. Everything gets commented, every method has a try-catch with a log statement, every return type is checked, etc. I think it's a consequence of them not feeling fatigue. These things (accessibility included) are all things humans generally know they 'should' do, but there never seems to be enough time in the day; we'll get to it later when we're less tired. But the ghost in the machine doesn't care. It operates at the same level all the time

You can recognise that the technology has a poor user interface and is wrought with subtleties without denying its underlying capabilities. People misuse good technology all the time. It's kind of what users do. I would not expect a radically new form of computing which is under five years old to be intuitive to most people.

The industry is still seeing how far they can take transformers. We've yet to reach a dollar value where it stops being worth pumping money into them.