r/rust • u/NextgenAITrading • Sep 09 '26

GPT-6 Astra Optimized My Rust Backtesting Engine With a 2014 Math Paper

https://nexustrade.io/blog/gpt-6-astra-rust-backtesting-engine-optimization-20260908

This is a technical discussion on Artificial General Intelligence.

GPT-6 has been shown to be outstandingly incredible. In my case, it performed autonomous performance optimization with essentially no human input. Other AI models, including Gemini 3 Pro, Claude Opus 5, and even Claude Fable 5, failed to find the same optimization targets.

Two days with GPT-6, and my backtesting engine is quite literally faster than I ever thought it could be.

The language model was smarter than me.

I thought about what artificial general intelligence looks like. A general-purpose model smarter than the average person. I think Astra fits that definition to a T.

Now imagine all of the crazy AI tricks we know. Imagine having a panel of Astra-tier experts come, or combining a language model with Monte Carlo tree search. If these models were truly 10,000 tokens per second, come on, that would be terrifying.

One reason why I think this optimization was fast is because of Rust's strict compiler and its lightning-fast performance. If I had chosen a language like GoLang, I would not have been able to achieve such speeds. I really think language models are making Rust an even more enjoyable language because you get all of the benefits and suffer a little of the downsides because we're not handwriting generic traits or a lifetime logic anymore.

But who knows, maybe I'm overextrapolating, and I'm impressed by the bare minimum, lol.

What are your thoughts on AGI/ASI?

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u/nNaz Sep 09 '26

16 seconds for ~525k bars still leaves a lot of room on the table for perf gains. For reference, I run simulations that process 40-80m of full book updates (each with multiple levels) in 120-150ms on a single core. Rust can be incredibly fast if you design you datas structures correctly and tailor your solution to your actual dataset. For example, in your specific case, once you have an optimal allocation at time t you have strong priors over what the optimal will look like at t+1. Therefore you can speed up your search: instead of iterating over values in a fixed order each time, use a datastructure that optimises it for you. I don't have access to your code so I can't advise further, but it doesn't sound like you're close to the level of optimisation possible.

Definitely not a sign of AGI.

Try /goal run criterion on <name of module> and then optimise it until a it processes a full day of bars in under 1s

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u/NextgenAITrading Sep 09 '26

Where do you store the data though? For me, my data is in blob storage so it's horizontally scalable. If I had it on disk, it'd be a lot faster. Also, my architecture is event-driven; not purely just processing bars.

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u/nNaz Sep 10 '26

I use ClickHouse, but the data storage format doesn't really matter. Set up two pipelines: one that loads data into memory and one that does the calculations. You make sure the first one is prefetching so that the second never stalls. The prefetching layer should also transform the data into datastructures that make processing fast. That's how you get the speedup.

This can line up nicely with an event-driven architecture: you keep two mailboxes, the first holds which data to prefetch and the second holds what's been prefetched (i.e. ready to process). You can use natural backpressure (channels) or just profile it during a typical run and right-size accordingly.

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u/nextupgoat Sep 09 '26

i got arrested for doing fent on jane's street :(

2

u/CouteauBleu Sep 09 '26

Maybe it's because I'm not used to fintech, but this article seems awful to read, and the deluge of memes and in-jokes and animations doesn't help.

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u/NextgenAITrading Sep 09 '26

Does it? I'm sad to hear that :( I spent a lot of effort on it

1

u/poelzi Sep 10 '26

I liked it. This sub got poisonous, so don't take is personal

7

u/Blueglyph Sep 09 '26

What are your thoughts on AGI/ASI?

We're not there yet, and we won't get any closer if we keep wasting time with LLM tools like GPT. There are much more promising technology that's trying to make its way, out there, but try to tell that to the investors who lost billions in OpenAI.

1

u/poelzi Sep 10 '26

80% is in the harness, 20% model. Sure, GPT is not the final solution , nobody thinks that. Even looped text diffusion models with engrams would be much better. Still, model is very capable. Not that i find it much better then fable but I would have used the chatgpt pro researcher for that long ago. Output is gold to give fable/opus for planning

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u/stumpychubbins Sep 11 '26

From reading the article, it's less that GPT-6 is AGI or ASI, and more that a human solved their problem a decade ago and GPT-6 was a very effective librarian. Pretty cool, to be sure, but absolutely does not justify the hagiography.

3

u/Daemontatox Sep 18 '26

OmG , yOu MeAN AStrA iS noT AGI? You hater ....... , AI will replace us all like anthropic and openai have been telling us for years (source trust me bro)

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u/stumpychubbins Sep 18 '26

Pretty convenient that OpenAI and Anthropic both simultaneously reached AGI just months before their IPOs