Timen

Author of Compounding Trust

[Timen @TimenBaart]

@SlootLau Het gaat te veel over belasten, en te weinig over besparen

[Timen @TimenBaart]

De discussie gaat teveel over belasten, en te weinig over besparen.

[Timen @TimenBaart]

@OnsOranje Ex psv, huidig psv, toekomstig psv

[Timen @TimenBaart]

Most annoying Claude Co-work issue

[Timen @TimenBaart]

@DavidSacks Never thought I’d support a David Sacks argument. Well said

[Timen @TimenBaart]

@RikElfrink Ik vind em niveautje Saibari

[Timen @TimenBaart]

@JeroenKapteijns Haha nooit! Wereldnieuws

[Timen @TimenBaart]

@RikElfrink Ok, geen Lammers nodig. Wen Tillman Rik?

[Timen @TimenBaart]

@De_belegger Want Nvidia bezit 122M class-A shares van SpaceX, tegen ongeveer 17.8 miljard usd.

[Timen @TimenBaart]

@Dic3t @KrisXiaoming @aleabitoreddit And they miss the margins LEO brings

[Timen @TimenBaart]

@JeroenKapteijns Ha, maakt daar even een wereldgoal

[Siddhartha Saxena @siddsax]

Anthropic onboarding day: Michael Scott introducing Karpathy like he just signed Wemby in free agency.

[Timen @TimenBaart]

@Lee_Trades No exposure to SSIT?

[Aviv Shaham @avivs]

@kevinrose The idea of maxing out a Claude plan is flawed. You just need to buy another one and use two now. It’s like saying you maxed out employee #1. Great - time to hire another one.

[Timen @TimenBaart]

@levie I believe a successful transition into the ‘new optimal’ requires an intensity beyond what most orgs can sustain

[Rohan Paul @rohanpaul_ai]

Wharton’s latest AI study points to a hard truth: “AI writes, humans review” model is breaking down

Why "just review the AI output" doesn't work anymore, our brains literally give up.

We have started doing "Cognitive Surrender" to AI - Wharton’s latest AI study points to a hard truth: reviewing AI output is not a reliable safeguard when cognition itself starts to defer to the machine.when you stop verifying what the AI tells you, and you don't even realize you stopped. It's different from offloading, like using a calculator.

With offloading you know the tool did the work. With surrender, your brain recodes the AI's answer as YOUR judgment. You genuinely believe you thought it through yourself.

Says AI is becoming a 3rd thinking system, and people often trust it too easily.

You know Kahneman's System 1 (fast intuition) and System 2 (slow analysis)? They're saying AI is now System 3, an external cognitive system that operates outside your brain. And when you use it enough, something happens that they call Cognitive Surrender.

Cognitive surrender is trickier: AI gives an answer, you stop really questioning it, and your brain starts treating that output as your own conclusion. It does not feel outsourced. It feels self-generated.

The data makes it hard to brush off. Across 3 preregistered studies with 1,372 participants and 9,593 trials, people turned to AI on over 50% of questions.

In Study 1, when AI was correct, people followed it 92.7% of the time. When it was wrong, they still followed it 79.8% of the time.

Without AI, baseline accuracy was 45.8%. With correct AI, it jumped to 71.0%. With incorrect AI, it dropped to 31.5%, worse than having no AI. Access to AI also boosted confidence by 11.7 percentage points, even when the answers were wrong.

Human review is supposed to be the safety net. But this research suggests the safety net has a hole in it: people do not just miss bad AI output; they become more confident in it.

Time pressure did not eliminate the effect. Incentives and feedback reduced it but did not remove it. And the people most resistant tended to score higher on fluid intelligence and need for cognition. That makes this feel less like a laziness problem and more like a cognitive architecture problem.

[Qadi @Bigqadi]

Absolutely outrageous from Gout Gout.

10.04 at the age of 16. Speechless.

[Aakash Gupta @aakashgupta]

Cursor is raising at a $50 billion valuation on the claim that its “in-house models generate more code than almost any other LLMs in the world.” Less than 24 hours after launching Composer 2, a developer found the model ID in the API response: kimi-k2p5-rl-0317-s515-fast.

That’s Moonshot AI’s Kimi K2.5 with reinforcement learning appended. A developer named Fynn was testing Cursor’s OpenAI-compatible base URL when the identifier leaked through the response headers. Moonshot’s head of pretraining, Yulun Du, confirmed on X that the tokenizer is identical to Kimi’s and questioned Cursor’s license compliance. Two other Moonshot employees posted confirmations. All three posts have since been deleted.

This is the second time. When Cursor launched Composer 1 in October 2025, users across multiple countries reported the model spontaneously switching its inner monologue to Chinese mid-session. Kenneth Auchenberg, a partner at Alley Corp, posted a screenshot calling it a smoking gun. KR-Asia and 36Kr confirmed both Cursor and Windsurf were running fine-tuned Chinese open-weight models underneath. Cursor never disclosed what Composer 1 was built on. They shipped Composer 1.5 in February and moved on.

The pattern: take a Chinese open-weight model, run RL on coding tasks, ship it as a proprietary breakthrough, publish a cost-performance chart comparing yourself against Opus 4.6 and GPT-5.4 without disclosing that your base model was free, then raise another round.

That chart from the Composer 2 announcement deserves its own paragraph. Cursor plotted Composer 2 against frontier models on a price-vs-quality axis to argue they’d hit a superior tradeoff. What the chart doesn’t show is that Anthropic and OpenAI trained their models from scratch. Cursor took an open-weight model that Moonshot spent hundreds of millions developing, ran RL on top, and presented the output as evidence of in-house research. That’s margin arbitrage on someone else’s R&D dressed up as a benchmark slide.

The license makes this more than an attribution oversight. Kimi K2.5 ships under a Modified MIT License with one clause designed for exactly this scenario: if your product exceeds $20 million in monthly revenue, you must prominently display “Kimi K2.5” on the user interface. Cursor’s ARR crossed $2 billion in February. That’s roughly $167 million per month, 8x the threshold. The clause covers derivative works explicitly.

Cursor is valued at $29.3 billion and raising at $50 billion. Moonshot’s last reported valuation was $4.3 billion. The company worth 12x more took the smaller company’s model and shipped it as proprietary technology to justify a valuation built on the frontier lab narrative.

Three Composer releases in five months. Composer 1 caught speaking Chinese. Composer 2 caught with a Kimi model ID in the API. A P0 incident this year. And a benchmark chart that compares an RL fine-tune against models requiring billions in training compute without disclosing the base was free.

The question for investors in the $50 billion round: what exactly are you buying? A VS Code fork with strong distribution, or a frontier research lab? The model ID in the API answers that.

If Moonshot doesn’t enforce this license against a company generating $2 billion annually from a derivative of their model, the attribution clause becomes decoration for every future open-weight release. Every AI lab watching this is running the same math: why open-source your model if companies with better distribution can strip attribution, call it proprietary, and raise at 12x your valuation?

kimi-k2p5-rl-0317-s515-fast is the most expensive model ID leak in the history of AI licensing.

[Timen @TimenBaart]

@TimurNegru 50km to Volterra, meaning you’re in Siena? Or South? Very appealing listing

[Timen @TimenBaart]

@BieriePSV “Ik ben de broer van Geert den Ouden”