The Paris prosecutor's cybercrime unit descended on the X's French offices, marking a dramatic escalation in a legal battle that's been simmering since early 2025. At the heart of it: how X handles illegal content, from child sexual abuse material to nonconsensual deepfakes, and content tied to denial of crimes against humanity (a criminal offense under French law).

But investigators weren't just hunting for documents. They wanted to peer inside the machine itself, the algorithms that decide what spreads and what gets buried. The question French officials are pressing: Has X's recommendation engine been warping automated enforcement? And perhaps more provocatively, has it been tilting the domestic political playing field?

The probe traces back to a complaint from French MP Eric Bothorel alleging biased algorithms reduced voice diversity on the platform. Prosecutors are examining whether these systems were manipulated, including whether major decisions were influenced at the highest levels of the company. The investigation also expanded to include complicity in the dissemination of harmful content after reports that the Grok chatbot produced problematic outputs tied to historical atrocities.

X France director Laurent Buanec previously said the company maintained strict user protection rules. Still, the prosecutor’s office has taken the unusual step of announcing it is leaving the platform entirely, shifting official communications to LinkedIn and Instagram.

French authorities issued summons for voluntary interviews on April 20, 2026, in Paris. The summons went to Elon Musk and former CEO Linda Yaccarino, who prosecutors describe as de facto and de jure managers. Officials say the goal is eventual compliance with French law through a constructive legal process.

The raid also fits a broader EU crackdown on major platforms. X has faced a €120 million EU fine tied to Digital Services Act transparency obligations. Whatever X’s view of the motives, police showing up in person signals a tougher phase of enforcement in Europe.

Google DeepMind just launched AlphaGenome, an AI model that predicts how genetic variants function across the human genome. AlphaFold handled protein structure (the 2% of DNA coding for proteins), but this tool goes further. AlphaGenome targets the harder problem of non-coding DNA, which makes up the remaining 98% and often contains disease-relevant mutations.

Published in Nature, the model can analyze DNA sequences up to 1 million base pairs long and forecast outcomes like RNA production and splicing. By modeling how non coding regions regulate gene expression, researchers aim to better understand rare diseases, neurodegeneration, and cancer.

AlphaGenome’s value is triage. It helps prioritize which variants are likely functional rather than noise, narrowing the search space in genomics. Researchers at Memorial Sloan Kettering Cancer Center have described it as having state-of-the-art performance across a whole spectrum of genomic tasks. DeepMind also reports strong performance across many sequence prediction benchmarks, trained on large public datasets including ENCODE and GTEx.

DeepMind positions the model as infrastructure for biology, speeding target discovery by predicting where genes start and end and how regulatory elements shape expression. It is not validated for clinical decision making and it does not solve complex trait interpretation, but it can accelerate research workflows that feed into those areas.

DeepMind says the tool has seen broad research uptake, with thousands of researchers across many countries using it. The company has provided a free non commercial API and released source code for custom research applications, echoing the open science approach used for AlphaFold.

It has also acknowledged biosecurity concerns while arguing the health benefits dominate. If the model keeps improving, it could become a core layer for synthetic biology and more personalized approaches to treatment, not a general chatbot, but a specialized engine for biological discovery.

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Here’s what to do:

🧠 1) Map the story Use ChatGPT or Gemini to write 10 numbered scenes with 3 choice moments. Each choice must point to a scene number.

🎭 2) Lock the main character Have ChatGPT or Gemini create a tiny character sheet (look, outfit, vibe). Reuse it in every prompt so the character stays consistent.

🎬 3) Generate your scenes as videos Use Veo 3.1 to make 6 short video clips: start, twist, 2 choice scenes, and 2 endings. Keep each clip 5 to 10 seconds. Every prompt includes character sheet, setting, mood, one clue object.

📦 4) Package the clips + script Save videos as simple files (Scene1, Scene2, etc.) and keep your story map in a clean list that says Scene X → Choice A goes to Scene Y.

🧩 5) Turn it into a playable app Paste this into Replit:

“Build me a simple web app that plays short video scenes in a Choose Your Own Adventure format. I have 10 scenes and 3 choice points. Each scene has a video file named Scene1.mp4, Scene2.mp4, etc. The app should:

Keep it dead simple and make it run in the Replit preview.”

🏁 6) Test twice Do one “worst choices” run and one “best choices” run. Fix dead ends and any confusing jumps.

✅ Win You have a live link to a tiny video adventure that reaches two different endings.

Will the legal pressure on X in France set a new global standard for how AI algorithms are policed? Or is this just the beginning of a fragmented internet where rules vary by border? See you next time! 🚀

Stay informed, stay curious, and stay ahead with Jumble!

Zoe from Jumble