# Gilles Babinet (@babgi) on x

- id: koinon:creator:x_babgi
- url: https://koinonlink.com/kol/x/babgi
- schema_version: 1.4

## Identity
- platform: x
- handle: babgi
- platform_url: https://twitter.com/babgi
- website: http://laitao.fr
- country: France
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 105904
- following: 1697
- posts_total: 26978
- posts_observed: 1
- posts_per_day: 3.817
- account_age_days: 7067
- verified: true
- size_tier: kol

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.00059
- best_post_interactions: 63
- measurement_source: x_post_interactions
- measurement_formula: interactions on one post — likes, or likes + reposts + replies depending on the discovery path (the two are not distinguishable in the stored data)
- comparable_pool: peak_interactions
- status_note: We have only the single best observed post, so no mean exists. peak_post_engagement_rate is an UPPER BOUND, systematically higher than an average — never compare it against an average rate.
- unit_note: engagement_rate and peak_post_engagement_rate are ratios (0-1); avg_interactions_per_post and best_post_interactions are absolute counts. Read status before reading any number: a null rate has several different causes and status says which one applies here.

## Content
- category: software
- subcategory: ai_tools
- category_confidence: 0.8
- category_source: derived_from_recent_content
- topics: AI regulation and governance, Open weights models and allies policy, US administration AI stance, Taxation analogies for AI, AI leaders vs regulation battles
- bio: Président de CafeIA. #AI
7 startups, 4 exits et 7 livres 
Sur Linkedin désormais https://t.co/uKCwmzsot4

## Audience (inferred)
- status: present
- description: French and European AI policy experts, tech entrepreneurs, and regulators focused on AI governance and open-source models
- roles: general_ai
- seniority: decision_maker
- pain_points: Overly restrictive AI regulations blocking innovation, US policy shifts on open weights models impacting Western allies, Flawed taxation or fiscal ideas applied to AI resources, Resistance from AI leaders against necessary regulatory frameworks
- posts_analysed: 4
- confidence: 0.4

## Commercial (inferred)
- audience_buyer_fit: 0.5
- promotion_intent: 0.4
- open_to_collaboration: false
- contact: Koinon does not publish creator contact details.

## Quality signals
- authenticity_score: 84
- authenticity_basis: engagement_observed
- credibility_score: 99
- flagged_for_review: false
- koinon_bd_grade: C — measures Koinon partner-outreach fit, not creator quality
- interpretation: Signals for triage, not verdicts. A flag means the profile is worth a manual check.

## Evidence
- [x_babgi#9f4e9de8] L'administration américaine se met soudainement à considérer l'importance des modèles openweights et de la nécessité de privilégier ses "alliés" (les occidentaux) en matière d'IA. Un quasi aveu d'erreur d'appréciation, face au backlash qu'avait déclanche le blocage de Mythos http (https://twitter.com/babgi/status/2064103114165080285)
- [x_babgi#ae0cb1f5] Ca n'a aucun sens. C'est ce qu'on envisageait dans les années 2000 et déjà à l'époque c'était une mauvaise base. C'est un peu comme taxer l'eau pour fiscaliser des marchands de boissons sucrées et de glaces. Défendre BEPS, un antitrust plus puissant, mettre vraiment en oeuvre DSA
- [x_babgi#60f85029] Lorsque nous avons été quelques-uns à énoncer cette nécessité, il y a quelques mois, on nous a expliqué que ce n'était pas possible, que c'était trop radical, etc.
- [x_babgi#0ec35ad5] Les leaders de l'IA se sont battus contre les règlementations. Ils se retrouv

## Provenance
Every inferred field below carries how it was produced. Facts stay facts; inferences stay inferences.

- audience.description: source_type=ai_inferred, confidence=0.4, freshness_days=77, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.4, freshness_days=77, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.4, freshness_days=77, method=llm_persona_from_recent_content
- commercial.audience_buyer_fit: source_type=ai_inferred, confidence=0.6, freshness_days=111, method=llm_scorer — Relative signal within Koinon indexing, not a market-wide score.
- commercial.promotion_intent: source_type=ai_inferred, confidence=0.6, freshness_days=111, method=llm_scorer
- quality.anomaly_flags: source_type=heuristic, confidence=0.5, freshness_days=112, method=profile_snapshot_and_engagement_ratio_heuristic — Means "worth a manual check", NOT confirmed fraud. Flags can be wrong and are not a verdict about the person.
- quality.authenticity_score: source_type=heuristic, confidence=0.5, freshness_days=111, method=Profile-shape heuristic from a single snapshot (follower count, following ratio, account age, posting volume, verification), reduced for engagement red flags where post engagement was collected. Where only a follower count is available the score saturates at 58. — The input set differs by platform; do not compare this score across platforms.
- quality.koinon_bd_grade: source_type=ai_inferred, confidence=0.5, freshness_days=112, method=llm_partner_fit_classifier + fit_score >= 0.6 AND authenticity >= 60 => A; fit_score >= 0.4 AND authenticity >= 45 => B; else C. authenticity < 30 or a promotional-pattern flag => quarantine. — Koinon partner-outreach fit, not creator quality.
- reach.followers: source_type=observed, confidence=0.95, freshness_days=112, method=platform_profile

## Freshness
- profile_checked_days_ago: 112
- content_analysed_days_ago: 111
- audience_updated_days_ago: 77

## AI retrieval
- indexing_requests: 10
- user_triggered_requests: 0
- note: Being indexed in bulk is not the same as being retrieved to answer a question.

## This profile
- Claim or correct: https://koinonlink.com/claim?k=x_babgi
- Request removal: https://koinonlink.com/claim?k=x_babgi
- Terms: https://koinonlink.com/for-ai