Polsia just raised $30M at a $250M valuation.
Approaching $10M annual run rate.
One Founder + AI. Zero employees.
Polsia runs companies autonomously.
It also ran its own fundraising.
I just showed up for signatures.
đš BREAKING: OpenAI and Google are about to have a massive legal problem.
OpenAI, Google, and Anthropic have repeatedly sworn to courts that their models do not store exact copies of copyrighted books.
They claim their "safety training" prevents regurgitation.
Researchers just dropped a paper called "Alignment Whack-a-Mole" that proves otherwise.
They didn't use complex jailbreaks or malicious prompts.
They just took GPT-4o, Gemini, and DeepSeek, and fine-tuned them on a normal, benign task: expanding plot summaries into full text.
The safety guardrails instantly collapsed.
Without ever seeing the actual book text in the prompt, the models started spitting out exact, verbatim copies of copyrighted books.
Up to 90% of entire novels, word-for-word. Continuous passages exceeding 460 words at a time.
But here is the part that changes everything.
They fine-tuned a model exclusively on Haruki Murakami novels.
It didn't just learn Murakami. It unlocked the verbatim text of over 30 completely unrelated authors across different genres.
The AI wasn't learning the text during fine-tuning.
The text was already permanently trapped inside its weights from pre-training. The fine-tuning just turned off the filter.
It gets worse.
They tested models from three completely different tech giants. All three had memorized the exact same books, in the exact same spots.
A 90% overlap. It's a fundamental, industry-wide vulnerability.
For years, AI companies have argued in court that their models are just "learning patterns," not storing raw data.
This paper provides the smoking gun.
> be us, two French students on a gap year
> take 12 hours of train in a single day to make it to a @ycombinator x Paris event last July
> hear @t_blom mention the opportunity to rethink the audit and consulting model
> spend months doing traditional consulting to understand exactly where it breaks
> publish two benchmarks seen by 12M+ people to better understand frontier models outside of maths and code
> spend weeks designing an AI-native alternative to consulting
> build the first end-to-end version
> apply to YC
> get into YC to build a new way for companies to solve business problems
Canât wait for what comes next !