Russ Tolsma

explorer, creator, swimming in the deep end of the pool 🇨🇦 — only trying to look back to move forward

[Russ Tolsma @russtolsma]

@yacineMTB Definitely sounds a little crazy

[Russ Tolsma @russtolsma]

This is the future.

[0xSero @0xSero]

I am most passionate about getting intelligence to run in constrained environments.

[0xSero @0xSero]

I am most passionate about getting intelligence to run in constrained environments.

[Séb Krier @sebkrier]

Three meta-observations on the state of AI:

1. AI will continue to improve, get better integrated, and produce lots of value. This is true even if you think there's a bubble-y dynamic or an imminent correction. Lots of people genuinely believe the transformative prospects, but also lots of people have strong incentives to believe so AND for others to believe so too. So a lot of bulls are *honestly* bullish, whilst at the same time self-selecting into, and being driven by, discourse that happens to align well with their own interests.

2. Not exactly a revolutionary insight, but the very same facts will lead some people to think the exact opposite of what another group believes. The shape of recent progress will make some people think we are close to some sort of 'recursive self-improvement' dynamic (sometimes with unstated accompanying beliefs about speed of societal transformation). But another group, looking at the same results but indexing on other variables, will conclude we're seeing diminishing returns, jaggedness, and real but incremental progress (sometimes with unstated accompanying beliefs about the criticality of temporary failures).

3. A lot of public discussions on AI feel like they rest on a scaffold of leaky and highly imperfect abstractions. Too much is being written about models with reference to parables, metaphors, analogies, and stylized stories. Ofc this is somewhat unavoidable, but many jump to easy pattern matching and reason probabilistically *within* a particular causal story without adequately representing uncertainty over the story itself. There's so much noise that the correlations seem more explanatory than they actually are. Because the underlying understanding is itself so murky and uncertainty is uncomfortable, people go for easy familiar abstractions and are too quick to trust the data generating process itself.

As a result of the above, the experts themselves are often more confused than one might expect, and so proper division of labour and deferral to authority is much harder in AI than in other established fields.

[Uncle Bob Martin @unclebobmartin]

People keep on telling me that my message about AI is undercutting my own books. Those people do not understand how agents work and who actually controls them. You can't tell an agent to be clean. You have to measure the cleanliness that they produce and have them correct failures of cleanliness.

Without such constraints agents are more than happy to build big balls of mud that they can't maintain.

[Russ Tolsma @russtolsma]

@hibakod They should just send it!

[Russ Tolsma @russtolsma]

@benhylak Especially since we have AGI already…

[Russ Tolsma @russtolsma]

@KaiNimma @natolambert @ollama Cursor is serving through other providers.

[Russ Tolsma @russtolsma]

@HedgieMarkets Revisionist history, written by the AI victors…

[Ahmad @TheAhmadOsman]

RTX 3090 owners trying to run Kimi_K3_3T_Q_0.0001_K GGUF

[Russ Tolsma @russtolsma]

Dead ☠️ 😂

[ThePrimeagen @ThePrimeagen]

If this is coding by hand, I agree we should stop

[dnap @dnapway]

David Sacks says Anthropic could stop Chinese distillation if they wanted to, but they won't because it slows growth

"The way that you know that this whole distillation thing is fake, is because if stopping distillation was their primary objective, Anthropic would push to ban Chinese access to American models, not American access to Chinese models."

"They’re the ones in the best position to block it. If industrial scale distillation is a national security threat, they’re the ones who need to stop it, because that is the place where distillation occurs. You have to stop it at the source."

"They know that if they KYC their customers, it’ll slow their growth. So instead, what they’re saying is, “Hey, ban our competitors.” If they really think it’s that big a threat, they should use a few points of their 90% gross margins to do that."

"It seems to me that this debate is all backwards. The question should be on Anthropic to explain why it’s doing such a bad job, not on the whole American open source ecosystem to be punished for Anthropic’s failure."

[Jensen Huang @JensenHuang]

For my first post, I’m sharing a letter @NVIDIA signed on why open models matter.

AI will transform every industry, power every company, and be built by every country.

Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty.

The world needs both frontier closed models and frontier open models.

https://t.co/AUKzoQ5Ikb

[Russ Tolsma @russtolsma]

@ibuildthecloud The compiler is in a recursive optimization loop.

[Russ Tolsma @russtolsma]

@DataChaz The AOL of AI

[Russ Tolsma @russtolsma]

@MacdevM Work of art…

[Russ Tolsma @russtolsma]

Composer isn’t equivalent to GPT-5.6 Sol or Fable, and for large code bases having a model with higher intelligence has significant advantages when planning out features. I move up and down the the intelligence and cost chain. Also, I’ve been measuring router and its results relative to the token cost and based on prior spend it’s actually pretty efficient.

[Russ Tolsma @russtolsma]

Everyone keeps on talking about loops and graphs, which is really just execution to build, but I rarely see any posts around what problems are being solved.

We need to start rethinking processes in business, not trying to jam AI into the process, but completely rethinking the business process.

I think the most successful companies in the future are going to be those who build products that address vertically defined business processes that the large labs can't solve because they're too busy trying to sell tokens.

[Russ Tolsma @russtolsma]

@drewproudx @unclebobmartin @theo @ori_pomerantz I target <7, anything higher 4 triggers warnings for review. It’s aggressive but I think it needs to be so that it forces higher coverage.

[Russ Tolsma @russtolsma]

@Tech_girl Would argue it’s purely about looking like they are still in the race. If you’re not shipping models then you become less relevant than the lab that is. Google is a great example of this.