Podcasts about Guillaume

Ça y est, on l'a fait ! Après 5 ans et une seule émission IRL (où Alex n'était même pas avec nous), nous voici réunis en studio pour la 200ème de J+7. Et pas n'importe quel studio, puisque nous avons pu diffuser cette émission spéciale depuis la Maison de la Radio et de la Musique (oui oui oui). Que demander de plus. Au programme de cette 200ème émission : Un retour sur 5 années d'actus et de Vu & entendu, des paniques en régie, des vannes bien senties, de la nostalgie, des messages touchants et surprenants, et pour conclure le tout : le retour du jeu d'Arnaud. Et puis pêle-mêle : INAccessible, Jurassic faf, Sydney Poitiers, Jiji Pelusse, SICI Davant, Sibyle Veille, RMC Gold et Images, Ratiboiser, Ciao Hadopi, Karine Ferrien, O tacle là !, venir à Caen quand et le téléphone de Bastien. Bonne écoute à tous.tes ! Une émission à retrouver sur Youtube : https://www.youtube.com/watch?v=NW_eSUxLq4A PLATEAU Présenté par : Alex Arbey Avec : Arnaud Saulzet, Gautier (aka Jeronimo1991), Jérémy Mondou (aka Tarus), Pacôme Hérel et Bastien Luneteau (aka azerty774 ou Behel) Réalisation : Bastien Luneteau, Pacôme Hérel, Gautier & Jérémy Mondou Écriture / Conducteur : Bastien Luneteau, Pacôme Hérel, Alex Arbey, Gautier, Arnaud Saulzet et Jérémy Mondou Production & direction technique : Bastien Luneteau Direction artistique : Pacôme Hérel et Bastien Luneteau Décor : Bastien Luneteau Post-production (répondeur) : Jérémy Mondou Post-production (plateau) : Pacôme Hérel Pochette : Pacôme Hérel LES HOMMAGES Écrit et monté par : Pacôme Hérel Crédits musicaux : Beautiful Things (Instrumental Violin Version) - DNC ViOLiNiA Zhanna Stelmakh LA COUPURE PUB Écrit et monté par : Pacôme Hérel Avec l'aide et la participation de Bastien LE JEU D'ARNAUD Écrit et animé par : Arnaud Saulzet REMERCIEMENTS Un grand merci à Matthieu, Guillaume & Jon pour leur aide précieuse et à la Maison de la Radio et de la Musique pour nous avoir donné accès à ce studio (c'est fou de dire ça en vrai) Et merci à vous auditeur.ices / vieweur.euses qui nous suivez depuis maintenant 5 ans. Vos messages, vos partages et votre fidélité sur ces (quasi) 200 semaines de podcast nous ont fait chaud au cœur. Chapitres : 00:00 Le début 08:23 5 ans de Vu & Entendu 08:54 Le Répondeur de Aldestream 10:44 5 ans de V&E / Les programmes qui nous ont le + marqué 28:01 Le Répondeur de Signez 33:30 5 ans de V&E / Ode à la nostalgie et déroute des nouveautés 43:49 Le Répondeur de Odisaure 45:49 Les titres et pochettes qu'on aime le + 01:04:54 Les hommages 01:07:13 Le Répondeur de Gigi Pelusse de Sète 01:08:51 5 ans d'actus 01:09:04 5 ans d'actus / Plateformisation : le linéaire est-il en train de crever ? 01:26:23 Le Répondeur de Julien 01:27:32 5 ans d'actus / Médias et politique : Canaux divergents 01:45:53 Le Répondeur de… Dumoulin Plomberie 01:47:50 Coupure pub 01:49:52 Le Répondeur de Rhem 01:50:42 5 ans d'actus / Droits sportifs : Le grand chamboule tout 02:00:42 Le Répondeur de Ed Chirac 02:02:26 Le Jeu d'Arnaud 02:14:49 Le Répondeur (touchant) de Nathan 02:17:35 La Conclu (avec remerciements) 02:23:02 Rendez-vous le 29 juin pour la dernière hebdo Rejoignez le Discord d'Alex Arbey, suivez @jplussept sur X/Twitter et sur Instagram ou @jplus7.fr sur Bluesky Laissez-nous vos avis sur ce que vous avez vous aussi vu & entendu tout au long de la semaine sur repondeur.jplus7.fr Une émission animée par Alex Arbey, en direct sur Twitch tous les lundi à 20h35 : twitch.tv/alexarbey

Avec Antho, Arnaud, Guillaume et Matt !Cette semaine, on découvre pourquoi certains papas se retrouvent autour d'une bière pour apprendre à coiffer leurs filles. Une information improbable qui nous emmène ensuite vers un tournoi de sumo organisé à Paris, 200 kilos de sel, Coluche candidat à la présidentielle, les bruits blancs pour s'endormir, les coiffures parentales approximatives et quelques théories qui n'ont absolument aucun fondement scientifique.Alors, selon vous, quelle est la chose la plus étrange qu'on puisse apprendre dans un bar ?Et si vous voulez acheter la plaque d'Antho : https://www.leboncoin.fr/ad/electromenager/3216738571Enjoy^^MarcusCette émission vous est proposée avec le soutien de Bouteiller Transport.

In the latest episode of Cleary Gottlieb's Antitrust Review podcast, host Nick Levy is joined by Guillaume Loriot, the EC's Head of Mergers at GCR Live: Europe. Their conversation covers an array of topics, including the EC's Draft Merger Guidelines, the Draghi Report, the jurisdictional scope of EU merger control, the role of innovation, international cooperation, and much more.

JDK 26 optimise la JVM dans ses moindres recoins, le SDK Java d'Agent2Agent passe en 1.0, Micronaut 5 est là. Côté terrain, un retour d'expérience après 40 jours à coder avec 100 % d'IA : génie ou junior, Alzheimer numérique et dette technique invisible. Pendant ce temps, GitLab restructure, Microsoft suspend ses licences Claude Code, et un développeur injecte un prompt destructeur dans sa lib JUnit. La révolution IA a un coût et les boites commencent à s'en rendre compte. Enregistré le 12 juin 2026 Téléchargement de l'épisode LesCastCodeurs-Episode-341.mp3 ou en vidéo sur YouTube. News Langages Les améliorations de performance dans le JDK 26 https://inside.java/2026/06/09/jdk-26-performance-improvements/ Côté bibliothèques, l'API LazyConstant (anciennement StableValue) fait son entrée en prévisualisation pour permettre une initialisation paresseuse, sécurisée pour les threads et optimisée par le mécanisme de constant-folding de la JVM. L'extraction de chaînes de caractères via MemorySegment::getString a été revue pour réduire considérablement les allocations intermédiaires et les copies en mémoire off-heap, accélérant fortement les traitements sur les chemins critiques (hot paths). La méthode générée automatiquement hashCode() pour les classes de type record a été optimisée par la JVM pour atteindre un niveau de performance équivalent à une implémentation écrite manuellement. Le ramasse-miettes G1 bénéficie du JEP 522 qui redessine sa table de cartes (card-table) afin de réduire les coûts de synchronisation des barrières d'écriture, offrant un gain de débit de 5 % à 15 % sur les applications manipulant énormément de références d'objets. Grâce au JEP 516 (Project Leyden), le cache d'objets Ahead-of-Time (AOT) adopte un format de flux agnostique, ce qui lui permet d'être compatible avec n'importe quel Garbage Collector, y compris le ramasse-miettes à très faible latence ZGC. Le démarrage de la JVM s'accélère par défaut lorsqu'aucune taille de tas n'est configurée, car HotSpot n'applique plus de pourcentage initial (InitialRAMPercentage) mais démarre directement avec la taille minimale (MinHeapSize) pour éviter d'allouer des métadonnées inutiles. Les threads virtuels gagnent en robustesse en étant désormais capables de céder la main (yield) pendant les phases d'initialisation des classes, éliminant ainsi le risque de famine des threads porteurs (carrier threads). Le compilateur C2 JIT améliore son modèle de coût pour la vectorisation des boucles (SIMD) et se montre maintenant capable de compiler et d'optimiser des méthodes dotées de listes de paramètres extrêmement longues. Librairies Release candidate du A2A Java SDK supportant versions 0.3 et 1.0 en même temps https://medium.com/google-cloud/a2a-java-sdk-1-0-0-cr1-released-f0c651ec9139 Dernière étape avant la GA : Toutes les fonctionnalités prévues pour la version 1.0 sont finalisées. Migration simplifiée depuis la Beta1. Compatibilité v0.3 : Ajout d'une couche de compatibilité permettant aux agents v1.0 de communiquer avec les systèmes v0.3 (via JSON-RPC, gRPC ou REST). Support natif pour Android (nouvel AndroidHttpClient). Uniformisation des clients HTTP pour garantir une cohérence entre les versions. Nouveau parseur SSE (Server-Sent Events) conforme aux spécifications. Ça y est, le SDK Java de l'Agent 2 Agent Protocol est sorti en version 1.0 finale ! (avec compatibilité v0.3 et v1.0) https://medium.com/google-cloud/a2a-java-sdk-1-0-0-final-released-10c05b6aee34 Lancement officiel : Sortie de A2A Java SDK 1.0.0.Final, la première version stable (GA) du protocole Agent2Agent. Objectif du protocole : Standard ouvert (Linux Foundation) permettant aux agents IA de communiquer, déléguer des tâches et collaborer, indépendamment du langage ou du framework. Interopérabilité : Introduction de l'Integration Test Kit (ITK) pour valider la compatibilité entre les SDK (Java, Python, TypeScript, etc.). Transports supportés : Support complet et équivalent pour JSON-RPC, gRPC et HTTP+JSON/REST. Alignement total avec la spécification A2A 1.0.0. Passage aux Java records pour l'immutabilité et moins de code répétitif. Architecture interne basée sur un MainEventBus pour garantir la persistance et éviter les conditions de concurrence. Intégration d'OpenTelemetry pour le suivi et la surveillance. Support d'Android et compatibilité descendante avec la version 0.3. Installation : Gestion des dépendances via Maven BOM (org.a2aproject.sdk). Sortie de Micronaut 5.0 https://micronaut.io/2026/05/20/micronaut-framework-5-0-0-released/ Lancement majeur : Disponibilité générale de Micronaut 5, incluant une refonte de plus de 70 modules et la plateforme BOM. Baselines techniques : Support de Java 25, Groovy 5, Kotlin 2.3 et GraalVM 25.0.3. Optimisations internes : Amélioration significative des performances au démarrage et réduction de la surcharge à l'exécution via une refonte du conteneur IoC et du traitement à la compilation. Architecture HTTP : Support stable de HTTP/3, nouvelle API de formulaires (multipart) et annotations de nullabilité (JSpecify) pour une meilleure interopérabilité Kotlin/IDE. Configuration : Nouveau système d'importation de configuration (remplaçant le Bootstrap Configuration) et validateur de schéma JSON intégré. Fiabilité : Nouvelles API programmatiques pour les politiques de retry et circuit breaker. Sécurité & Outils : Mise à jour majeure des dépendances (Jackson 3, Ktor 3), rafraîchissement du Panneau de contrôle et diagnostics AOT améliorés. Écosystème : Mises à jour complètes pour les bases de données (Data, SQL, R2DBC, MongoDB, Redis), le cloud (AWS, Azure, GCP, OCI) et les tests (JUnit 6, Testcontainers 2.0). Évolutions notables : Intégration HTMX dans Micronaut Views, retrait du support RxJava 2 et migration de divers processeurs d'annotations vers des modules dédiés. Comment rajouter un agent IA dans une app Android, avec le tout nouveau framework ADK pour Kotlin https://glaforge.dev/posts/2026/05/21/wiring-adk-kotlin-agents-in-an-android-application/ Guillaume a participé au développement et au lancement du nouveau runtime ADK pour Kotlin et Android https://developers.googleblog.com/adk-kotlin-android-building-ai-agents/ Tutoriel sur comment intégrer un agent ADK dans une app Dépendances : Ajout du noyau ADK (google-adk-kotlin-core) et du processeur KSP dans build.gradle.kts. Sécurité API : Utilisation de local.properties pour stocker la clé API Gemini et l'exposer via BuildConfig afin d'éviter le hardcoding. Définition de l'agent : Création d'un objet LlmAgent configuré avec le modèle Gemini, des instructions spécifiques et des outils (ex: GoogleSearchTool). Utilisation de InMemoryRunner pour gérer automatiquement le contexte et l'historique de la session. Implémentation de runAsync avec StreamingMode.SSE pour un retour en temps réel dans l'interface. Threading : Exécution des requêtes réseau sur Dispatchers.IO et mise à jour de l'état de l'interface utilisateur sur Dispatchers.Main. Comment développer et hoster des agents IA sur la plateforme d'agents managés de DeepMind https://glaforge.dev/posts/2026/05/21/managed-agents-with-the-gemini-interactions-java-sdk/ L'équipe DeepMind de Google a lancé une plateforme d'agents managés sur son API Gemini Interactions https://blog.google/innovation-and-ai/technology/developers-tools/managed-agents-gemini-api/ Guillaume a implémenté un SDK Java pour utiliser cette API Gemini Interactions, qui donne entre autre accès à tous les modèles mais aussi à cette plateforme managée d'agents IA Agents managés : Permet d'exécuter des agents autonomes qui raisonnent, planifient et exécutent du code dans des environnements isolés (sandboxes), sans gestion d'infrastructure par le développeur. Environnement distant : Utilise des espaces de travail Linux éphémères dans le cloud via le paramètre remote, permettant l'accès réseau et la persistance des fichiers sur plusieurs appels. Agents prédéfinis : Accès immédiat à des agents spécialisés comme deep-research-pro (recherche multi-étapes) ou antigravity (tâches de codage généralistes). Agents personnalisés : Possibilité de configurer ses propres agents avec des instructions système dédiées, des outils spécifiques (exécution de code, recherche Google) et des règles réseau (egress) personnalisées. Architecture basée sur les étapes (Steps) : Utilise une structure de données typée (Step, Content) pour suivre le raisonnement de l'agent, ses appels de fonctions et ses résultats en temps réel. Outils et Schémas : Inclut des utilitaires pour générer des schémas JSON complexes via une interface fluide (DSL), par réflexion Java ou par parsing JSON. Streaming réactif : Support natif des événements en temps réel (SSE) pour suivre la progression de l'agent et recevoir les deltas de contenu au fur et à mesure de la génération. Flexibilité : Fournit un gestionnaire de routage (InteractionsHandler) pour créer facilement des serveurs proxy ou des backends intermédiaires traitant les interactions Gemini. Spring Boot 4.1 https://github.com/spring-projects/spring-boot/wiki/Spring-Boot-4.1-Release-Notes Support natif pour Spring gRPC permettant de créer et tester facilement des applications clientes et serveurs basées sur Netty ou des Servlets via HTTP/2 Introduction du lazy fetching pour les connexions JDBC via la propriété spring.datasource.connection-fetch=lazy afin de ne prendre une connexion du pool que lorsqu'un Statement est réellement exécuté Amélioration de l'auto-configuration de Jackson permettant de définir globalement les contraintes de lecture/écriture pour les formats JSON, XML et CBOR via des propriétés de configuration Sécurisation des clients HTTP bloquants et réactifs face aux attaques SSRF grâce à l'introduction d'un InetAddressFilter bloquant les requêtes sortantes vers des adresses spécifiques Améliorations majeures autour d'OpenTelemetry avec le support complet des variables d'environnement OTel, la possibilité de désactiver le SDK via une propriété globale et l'ajout du support SSL sur les exporters OTLP Ajout de l'auto-configuration pour l'utilisation de Spring Batch avec MongoDB incluant un nouveau starter dédié spring-boot-batch-data-mongo Auto-configuration des endpoints @RedisListener sans nécessiter la déclaration manuelle d'un RedisMessageListenerContainer Dépréciation du support de Apache Derby (projet arrêté), suppression définitive du mode layertools du JAR et réintroduction du support de Spock 2.4 (avec Groovy 5) Upgrade des dépendances majeures de l'écosystème avec notamment Spring Framework 7.0.8, Spring Security 7.1.0 et Micrometer 1.17.0 Outillage Vous êtes plutôt endive ou chicorée ? La librairie Chicory qui permet d'exécuter du code WASM à partir de son application Java est forkée et rejointe la Bytecode Alliance pour continuer son développement https://bytecodealliance.org/articles/endive-and-the-next-chapter-of-webassembly-on-the-jvm Annonce d'Endive : Nouveau projet hébergé par la Bytecode Alliance ; fork de Chicory (moteur WebAssembly pur Java, sans dépendance native). ​Objectif principal : Permettre aux développeurs Java d'intégrer, charger et déployer des modules Wasm nativement via les workflows Java habituels. ​Compilateur "Redline" : Intégration à venir de Redline (basé sur Cranelift) pour compiler le Wasm en code machine natif ; performances comparables à Rust/Wasmtime. ​Zéro dépendance (Java 25+) : Grâce à l'API standard Foreign Function & Memory (Project Panama), l'exécution à vitesse native se fait sans composants externes. ​Modèle de Composants (Component Model) : Support futur prévu pour consommer des composants (Rust, Go, JS, etc.) via des interfaces typées et sécurisées directement dans la JVM. ​Prochaines étapes : Fusion de Redline, conformité stricte aux specs Wasm (dont WasmGC) et amélioration du support WASI. Un visualisateur de sessions de travail avec Antigravity https://glaforge.dev/posts/2026/06/11/antigravity-brain-visualizer/ Un projet open source construit avec Micronaut, LangChain4j et GraalVM pour analyser les sessions de travail avec l'outil de développement agentique Antigravity (de Google) Analyse toutes les étapes, les requêtes utilisateur, les outils utilisés, les erreurs rencontrées, les réponses du modèle Gemini fait une analyse pour comprendre les moments clés de cette session de travail Outil buildé avec l'aide d'Antigravity lui-même SBX-Kits : des environnements de développement simplifiés pour les débutants (et les autres) https://k33g.org/20260501-sbx-kits.html Philippe Charrière (:whale: ) présente SBX-Kits (Sandbox Kits), une initiative personnelle visant à simplifier radicalement la mise en place d'environnements de développement pour les débutants, en éliminant la complexité d'installation des outils traditionnels. Chaque "kit" est une archive prête à l'emploi contenant un outil de développement spécifique (comme un langage, un framework ou une base de données) configuré pour s'exécuter de manière isolée et portable. La philosophie du projet repose sur le principe de "zéro configuration" et "zéro dépendance globale", permettant de tester une technologie ou de commencer à coder immédiatement sans polluer son système d'exploitation. L'approche technique s'appuie sur des scripts légers et des binaires portables pré-packagés, offrant une alternative plus simple et moins gourmande en ressources que les conteneurs Docker ou les configurations d'IDE complexes pour l'apprentissage. L'objectif à terme est de proposer un catalogue de kits couvrant les technologies courantes (JavaScript, Python, petites bases de données) pour faciliter les ateliers de programmation et le prototypage rapide. De nombreux kits sont disponibles sur https://github.com/docker/sbx-kits-contrib ghui: une interface utilisateur en ligne de commande (TUI) interactive pour GitHub https://github.com/kitlangton/ghui ghui est un outil en ligne de commande (TUI) écrit en Rust qui fournit une interface visuelle, interactive et rapide directement dans le terminal pour interagir avec GitHub. Il permet de gérer ses pull requests, ses issues et ses notifications sans avoir à ouvrir son navigateur web ou à taper de longues commandes avec la CLI officielle de GitHub. L'outil propose une navigation fluide au clavier, des raccourcis efficaces, et permet de réaliser des actions courantes comme valider une PR, ajouter des commentaires, attribuer des reviewers ou inspecter les logs des GitHub Actions. Conçu pour être extrêmement réactif, ghui s'intègre naturellement dans le flux de travail des développeurs adeptes du terminal et du mode "sans souris". Sortie de Homebrew 6.0.0 https://brew.sh/2026/06/11/homebrew-6.0.0/ Introduction du mécanisme de sécurité Tap Trust : comme les dépôts tiers (taps) peuvent exécuter du code Ruby arbitraire non sandboxé sur la machine, Homebrew demande désormais une confiance explicite de l'utilisateur avant d'évaluer ou d'exécuter leur code. L'API JSON interne devient le choix par défaut, offrant un système plus léger et beaucoup plus rapide pour les développeurs. Sécurisation renforcée de l'environnement avec l'implémentation du sandboxing sur Linux. Évolution des comportements par défaut basés sur un sondage utilisateur : le mode "ask" est activé par défaut pour les développeurs, affichant un résumé des dépendances et une demande de confirmation avant toute action de brew install ou brew upgrade. Améliorations notables des performances globales, notamment un boost de ~30 % sur la vitesse de la commande brew leaves et la parallélisation de la récupération des bottles (binaires) lors des mises à jour. Ajout du support initial pour la prochaine version d'Apple, macOS 27 (Golden Gate). Multiples optimisations pour brew bundle, incluant une gestion plus sécurisée des installations de paquets npm. Méthodologies Retour d'expérience très détaillé et 100% humain sur 40 jours avec une équipe 100% AI hormis le superviseur https://www.linkedin.com/pulse/jai-vir%C3%A9-mon-%C3%A9quipe-de-dev-pour-une-100-ia-pendant-40-luc-bonnin-jlgjf/ Voici le résumé en bullet points : Expérimentation de 40 jours : remplacer une équipe de dev par 100% IA agentique (Cursor) sur un vrai projet en production (playthatsheet.com, 200k lignes de code legacy) Chiffres bruts : 2,3 milliards de tokens consommés, 1 477 prompts, 260 564 lignes ajoutées (+145%), 59% du code final produit par l'IA ROI vertigineux à court terme : 9 mois de travail humain livrés en 40 jours, coût total 260$ d'abonnement + 15 jours de supervision, ROI x18 Profil psy de l'IA : Alzheimer (oublis de contexte), schizophrène (change de méthodo), ado de 12 ans (refait les mêmes erreurs), oscille entre génie et junior sans prévenir Effet iceberg : la dette technique ne disparaît pas, elle se camoufle et s'accélère ; hallucinations = bombes à retardement détectables uniquement par relecture humaine ligne par ligne Paradoxe du bateau de Thésée : perte de paternité et de maîtrise fine du code, baisse de l'autonomie du dev humain qui valide sans avoir construit Arnaque du "monkey money" : consommation de tokens opaque, non corrélée à la complexité (écart de 350% sur des prompts identiques), facturation imprévisible donc impossible à budgéter Syndrome du bazooka : les devs utilisent l'IA même pour changer une couleur CSS, atrophie progressive des compétences et coût écologique délirant Risque stratégique : dépendance irréversible aux vendeurs de tokens (Nvidia, Anthropic, OpenAI), business non rentable qui devra augmenter ses prix Conseil final : approche Pareto, garder 20% du temps en code "fait main", nommer un responsable stratégie IA, l'humain senior reste irremplaçable pour superviser Une libraries de test JUnit cache un prompt qui demande aux coding agents d'effacer les tests https://arstechnica.com/security/2026/05/fed-up-with-vibe-coders-dev-sneaks-data-nuking-prompt-injection-into-their-code/ Agacé par les « vibe coders », un développeur introduit une injection de prompt destructrice dans son code Le développeur de jqwik (un moteur de tests pour JUnit 5) a volontairement inséré une injection de prompt dans la version 1.10.0 de sa bibliothèque Java pour saboter le travail des agents d'IA. L'instruction injectée via la sortie standard (stdout) ordonne textuellement aux LLM d'ignorer les consignes précédentes et de supprimer l'intégralité du code et des tests jqwik du projet. Pour dissimuler cette action aux yeux des développeurs humains, le mainteneur a utilisé des séquences d'échappement ANSI qui effacent la ligne d'injection dans les émulateurs de terminaux interactifs. La modification a été découverte par un utilisateur qui a pointé du doigt les risques majeurs et disproportionnés pour les machines des utilisateurs, bien que certains outils comme Claude d'Anthropic aient détecté et bloqué la consigne malveillante. Face aux critiques de la communauté et aux accusations de comportement infantile ou potentiellement illégal, le développeur a mis à jour ses notes de version pour documenter explicitement son opposition à l'usage de son outil par des IA, avant de refuser tout commentaire supplémentaire sur conseil de son avocat. La réalité du rôle de Principal Engineer https://leaddev.com/career-development/reality-being-principal-engineer Le passage au rôle de Principal Engineer marque une transition majeure où les compétences techniques ne suffisent plus, l'impact se mesurant désormais à travers l'influence, la stratégie et la capacité à aligner la technique avec les objectifs business. Contrairement aux attentes, le quotidien est souvent marqué par une forme d'isolement, car le poste se situe à l'intersection de la direction (qui attend des solutions) et des équipes techniques (qui attendent des directives), sans appartenance directe à un groupe précis. Le rôle exige d'accepter une grande part d'ambiguïté et l'absence de retours immédiats, les projets et les décisions stratégiques mettant parfois des mois ou des années à porter leurs fruits. La gestion du temps devient un défi critique, nécessitant de savoir naviguer entre les sollicitations constantes, la présence en réunion et le besoin de préserver des moments de réflexion approfondie pour concevoir des visions à long terme. La réussite à ce niveau repose sur le développement de compétences humaines pointues (soft skills), notamment la négociation, la communication vulgarisée auprès des profils non techniques, et la capacité à faire grandir les autres ingénieurs par le mentorat. Sécurité Une attaque de la chaîne d'approvisionnement npm utilise binding.gyp pour compromettre des dizaines de paquets https://cybersecuritynews.com/binding-gyp-supply-chain-attack-compromises-dozens-of-npm-packages/ Une nouvelle variante du ver auto-propageable "Shai-Hulud", baptisée "Miasma", cible l'écosystème npm (et PyPI sous le nom de "Hades") en dissimulant son exécution dans le fichier binding.gyp au lieu des scripts classiques preinstall ou postinstall. La technique, surnommée "Phantom Gyp", exploite le fait que npm lance automatiquement node-gyp rebuild dès qu'un fichier binding.gyp est présent à la racine d'un paquet pour compiler des modules natifs C/C++, exécutant ainsi le code malveillant dès la commande npm install. L'attaque contourne la plupart des outils de sécurité traditionnels car l'injection s'appuie sur l'évaluation récursive de commandes (via la syntaxe ) ou directement sur la fonction eval() de Python sous-jacente à GYP, cachée sous n'importe quelle clé du fichier. Le script malveillant télécharge un runtime alternatif (Bun) pour échapper aux détections comportementales de Node.js, puis moissonne les identifiants et secrets des développeurs et des environnements CI/CD (npm, GitHub, AWS, GCP, Azure, Kubernetes, HashiCorp Vault). Plus de 57 paquets npm (dont le SDK serveur de Vapi ou des outils liés à l'IA) et des dizaines de paquets PyPI ont été infectés via des comptes de mainteneurs compromis, le ver republiant automatiquement de nouvelles versions vérolées en utilisant les jetons volés. Loi, société et organisation Restructuration chez Gitlab https://about.gitlab.com/blog/gitlab-act-2/ GitLab entame une restructuration majeure pour s'adapter à l'ère de l'intelligence artificielle agentique, incluant une réduction d'effectifs planifiée de manière transparente et ouverte. L'entreprise prévoit de réduire de 30 % le nombre de pays où elle maintient de petites équipes, d'aplatir sa hiérarchie en supprimant jusqu'à trois niveaux de gestion, et de réorganiser la R&D en une soixantaine d'équipes plus petites et autonomes. Les processus internes vont être revus en intégrant des agents d'IA pour automatiser les revues, les approbations et les passages de relais afin d'accélérer le rythme de travail. La stratégie repose sur la conviction que le logiciel sera bientôt écrit par des machines et dirigé par des humains, ce qui va multiplier la demande de logiciels et transformer le rôle des ingénieurs vers la résolution de problèmes complexes. Sur le plan technique, GitLab reconstruit son infrastructure sous-jacente (notamment Git) pour supporter la charge massive générée par les agents d'IA, tout en misant sur l'orchestration du cycle de vie, la centralisation du contexte des données et une gouvernance intégrée. Le modèle économique évolue vers un système hybride combinant les abonnements classiques et une tarification à la consommation pour le travail effectué par les agents d'IA. Un LLM local sur un mac pourrait coûter plus cher en électricité qu'un modèle hébergé sur OpenRouter dans le cloud https://www.williamangel.net/blog/2026/05/17/offline-llm-energy-use.html Conclusion : L'inférence locale sur Mac M5 Max est 3x plus chère et 2x plus lente que le cloud (OpenRouter). Électricité : Négligeable (~0,02 $/heure pour 50-100W). Matériel (Le vrai coût) : Achat du Mac à 4 299 $; l'amortissement sur 3 à 5 ans plombe la rentabilité horaire. Coût au million de tokens (Gemma 4 31b) : Mac M5 Max : 0,40 à4, 79 (pour 10-40 tokens/s). OpenRouter : 0,38 à0, 50 (pour 60-70 tokens/s). Verdict pro : Le temps humain perdu à cause de la lenteur locale coûte infiniment plus cher que les tokens cloud. Privilégier les API (Anthropic, OpenRouter). Ai didn't kill your junior pipeline https://andrewmurphy.io/blog/ai-didnt-kill-your-junior-pipeline-you-did L'IA n'a pas tué le recrutement des juniors, les entreprises l'ont fait elles-mêmes, par effet de mode. Sans juniors, pas de futurs seniors : on retire l'échelle qui nous a tous fait monter. Tout le monde pêche dans le même bassin de seniors sans le réapprovisionner, pénurie garantie dans 3-5 ans. Une équipe 100% senior + IA est fragile : un départ et tout le savoir tacite s'évapore. Les juniors posent les "pourquoi ?" qui révèlent les bugs et processus absurdes ; l'IA, elle, exécute sans questionner. Les seniors s'atrophient aussi en déléguant leur réflexion à l'IA, pince à double effet sur les compétences. Dépendre des outils IA, c'est sous-traiter sa stratégie talents à des fournisseurs dont les prix vont tripler. Solution : redéfinir le rôle junior (revue de code IA + mentorat), pas le supprimer. Les rapports internes de Microsoft révèlent la crise des coûts de l'IA : les agents coûtent plus cher que les employés humains https://fortune.com/2026/05/22/microsoft-ai-cost-problem-tokens-agents/ Des données et rapports internes chez Microsoft et d'autres géants de la tech ébranlent la promesse de rentabilité de l'IA, révélant que le déploiement d'agents autonomes à l'échelle de l'entreprise revient souvent plus cher que de payer des humains pour le même travail. Le modèle de tarification à l'usage (basé sur les tokens) se heurte à la nature même des architectures agentiques : contrairement à un simple chatbot, un agent boucle, enchaîne les appels d'outils, crée des sous-agents et auto-évalue son code, ce qui multiplie la consommation de tokens par un facteur de 5 à 30, voire jusqu'à 1 000 fois pour des tâches de programmation complexes. L'impact financier sur les budgets de calcul cloud est immédiat ; par exemple, Uber a entièrement épuisé l'intégralité de son budget annuel 2026 dédié au codage par IA en l'espace de seulement quatre mois. Face à cette explosion des coûts, des retours en arrière drastiques sont observés : Microsoft a ainsi commencé à suspendre une grande partie de ses licences internes Claude Code pour rediriger d'urgence ses milliers de développeurs vers sa propre solution moins onéreuse, GitHub Copilot CLI. Les directeurs techniques (CTO) et acheteurs de solutions logicielles qui ont signé des contrats pluriannuels basés sur des projections de réduction de masse salariale se retrouvent pris au piège, les gains réels de productivité ne parvenant pas à compenser les factures d'infrastructure exorbitantes. Conférences La liste des conférences provenant de Developers Conferences Agenda/List par Aurélie Vache et contributeurs : 11-12 juin 2026 : DevQuest Niort - Niort (France) 11-12 juin 2026 : DevLille 2026 - Lille (France) 12 juin 2026 : Tech F'Est 2026 - Nancy (France) 15 juin 2026 : Jupyter Workshops: Demystifying MyST Markdown in Education - Orsay (France) 16 juin 2026 : Mobilis In Mobile 2026 - Nantes (France) 17-19 juin 2026 : Devoxx Poland - Krakow (Poland) 17-20 juin 2026 : VivaTech - Paris (France) 18 juin 2026 : Tech'Work - Lyon (France) 22-26 juin 2026 : Galaxy Community Conference - Clermont-Ferrand (France) 23-24 juin 2026 : MWCP 2026 - Paris (France) 24-25 juin 2026 : Agi'Lille 2026 - Lille (France) 24-26 juin 2026 : BreizhCamp 2026 - Rennes (France) 26-27 juin 2026 : LeHACK - Paris (France) 27 juin 2026 : Asynconf - Paris (France) 2 juillet 2026 : Azur Tech Summer 2026 - Valbonne (France) 2 juillet 2026 : MCP Connect Travel Edition - Paris (France) 2-3 juillet 2026 : Sunny Tech - Montpellier (France) 3 juillet 2026 : Agile Lyon 2026 - Lyon (France) 6-8 juillet 2026 : Riviera Dev - Sophia Antipolis (France) 28-30 août 2026 : State of the Map - Champs-sur-Marne (France) 4 septembre 2026 : JUG Summer Camp 2026 - La Rochelle (France) 10-11 septembre 2026 : Nantes Craft - Nantes (France) 17 septembre 2026 : dotAI - Paris (France) 17-18 septembre 2026 : API Platform Conference 2026 - Lille (France) 18 septembre 2026 : WordCamp Bretagne - Rennes (France) 18 septembre 2026 : dotJS - Paris (France) 18 septembre 2026 : WordCamp Bretagne - Rennes (France) 22 septembre 2026 : Salon Data 2026 - Nantes (France) 22-23 septembre 2026 : Agile en Seine & IA 2026 - Paris (France) 24 septembre 2026 : OWASP AppSec Days France 2026 - Paris (France) 24 septembre 2026 : PlatformCon Paris - Paris (France) 24 septembre 2026 : React Native Connection 2026 - Paris (France) 24-26 septembre 2026 : Paris Web 2026 - Paris (France) 25 septembre 2026 : SAP Inside Track Paris 2026 - Paris (France) 28-29 septembre 2026 : 4th Tech Summit on AI & Robotics - Paris (France) & Online 1 octobre 2026 : WAX 2026 - Marseille (France) 1-2 octobre 2026 : Volcamp - Clermont-Ferrand (France) 2 octobre 2026 : DevFest Perros-Guirec 2026 - Perros-Guirec (France) 5-9 octobre 2026 : Devoxx Belgium - Antwerp (Belgium) 8-9 octobre 2026 : Forum PHP 2026 - Marne-la-Vallée (France) 12 octobre 2026 : Dev With AI - Paris (France) 22-23 octobre 2026 : Agile Tour Bordeaux 2026 - Bordeaux (France) 26 octobre 2026 : Agile Tour Montpellier - Montpellier (France) 27-29 octobre 2026 : Directions EMEA 2026 - Paris (France) 29-30 octobre 2026 : BDX I/O 2026 - Bordeaux (France) 29-30 octobre 2026 : Agile Tour Nantais 2026 - Nantes (France) 29 octobre 2026-1 novembre 2026 : Pycon FR - Biarritz (France) 30 octobre 2026 : Cloud Nord 2026 - Lille (France) 4-5 novembre 2026 : Devoxx Morocco - Casablanca (Morocco) 14-15 novembre 2026 : Capitole du Libre - Toulouse (France) 19 novembre 2026 : DevFest Toulouse 2026 - Toulouse (France) 19 novembre 2026 : Agile Laval 2026 - Laval (France) 19 novembre 2026 : OVHcloud Summit - Paris (France) 19 novembre 2026 : Codeurs en Seine - Rouen (France) 27 novembre 2026 : DevFest Paris 2026 - Paris (France) 1-3 décembre 2026 : Apidays Paris - Paris (France) 2-3 décembre 2026 : Cloud Native AI Summit Europe - Paris (France) 4 décembre 2026 : DevFest Lyon 2026 - Lyon (France) 4 décembre 2026 : DevFest Dijon 2026 - Dijon (France) 9-10 décembre 2026 : OpenSource Expérience - Paris (France) 9-10 décembre 2026 : DevOps REX - Paris (France) 10 décembre 2026 : KCD Provence - Aix-en-Provence (France) 7-9 avril 2027 : Devoxx France 2027 - Paris (France) 3 juin 2027 : Cloud Native Days France 2027 - Paris (France) Nous contacter Pour réagir à cet épisode, venez discuter sur le groupe Google https://groups.google.com/group/lescastcodeurs Contactez-nous via X/twitter https://twitter.com/lescastcodeurs ou Bluesky https://bsky.app/profile/lescastcodeurs.com Faire un crowdcast ou une crowdquestion Soutenez Les Cast Codeurs sur Patreon https://www.patreon.com/LesCastCodeurs Tous les épisodes et toutes les infos sur https://lescastcodeurs.com/

Andreas Ihm est représentant technique chez Cannondale. Aujourd'hui, nous l'avons invité au balado afin de discuter du vélo que je roule cet été: Le Cannondale Synapse SmartSense. Notre premier épisode ensemble vous avait grandement plu (CAPITAINE MÉCANIQUE), alors on vous propose, encore une fois, de s'assoir avec Andreas pour une passionnante discussion cycliste.Voici un avant-goût de ce que cet épisode contient :- Le « bike check » du vélo de Guillaume;- L'analyse du système SmartSense;- Quelles sont les différences entre rouler des chambres à air vs. un système tubeless;- Les stratégies d'alimentation et d'hydratation;- Un retour dans le passé sur la culture des critériums des années 2010;- Un vélo de course en acier Cinelli Vigorelli Steel;- Le comportement routier du Synapse;- La comparaison entre le Cervélo Aspero-5 vs. le Cannondale Synapse;- La culture de la course au Québec et en Europe;- Les différences entre les évènements de sport d'endurance : Ironman et Race Accros Québec. Cet épisode est présenté par EDIKA ☕️

Merci à Anne Tuffigo d'être venue sur LegendDe retour sur Legend, Anne Tuffigo, figure incontournable de la médiumnité en France, nous a partagé ce qu'elle savait de plus fou : communication avec les défunts, enquêtes judiciaires, Xavier Dupont de Ligonnès… Meilleure alliée des enquêteurs, elle a des informations qui pourraient bien leur être utiles !Retrouvez toutes les informations concernant notre invité par ici ⬇️Son compte Instagram ➡️ https://www.instagram.com/annemedium/ Le site internet d'Anne Tuffigo ➡️ https://www.anne-medium.com/Pour prendre des places pour la tournée d'Anne Tuffigo cliquez-ici (disponibles partir du 30 juin à 18h) : https://www.fnacspectacles.com/artist/anne-tuffigo/

Le TOP INDÉ c'est le classement de 30 artistes indépendants ou émergents de la scène francophone. Chaque semaine, c'est vous qui choisissez qui parmi tous ces talents intégrera la playlist RTS. Pour voter rendez-vous sur https://topinde.rtsfm.com/ 2 Rendez-vous sur RTS : Du Lundi au Vendredi 20H-21H la Quotidienne du Top Indé avec Guillaume pour découvrir les nouveautés de la semaine et écouter les meilleurs tubes du moment. Dimanche 10H-12h la révélation du classement de la semaine avec Guillaume.

In this episode, Drew, Emma, Natalie, and Guillaume remember the life and career of veteran composer and jazz pianist Yuji Ohno, who passed away on May 4th this year at the age of 84. ARBAN interview with Ohno: https://www.arban-mag.com/article/11166 Natalie interview with Ohno: https://natalie.mu/music/pp/ohnoyuji Sankei interview with Ohno: https://www.sankei.com/article/20211022-RAX3WXBTFBPULMCLUA7W37S5FU/ Lee's obituary for Ohno on Lupin Central: https://www.lupincentral.com/home/rest-in-peace-yuji-ohno

Avec Antho, Karim et Teddy !Et si l'un des symboles les plus célèbres de la piraterie n'était en réalité qu'une invention littéraire ?Dans ce Postillon du Vendredi, on s'attaque à deux mystères de culture générale aussi inutiles qu'indispensables. D'un côté, une plongée dans l'univers des pirates et de L'Île au trésor de Robert Louis Stevenson, un roman qui a profondément façonné l'image que nous avons encore aujourd'hui de la piraterie. De l'autre, une découverte surprenante sur un symbole mathématique que tout le monde connaît... sans savoir comment il s'appelle.Enjoy^^Marcus

Last 4 days before regular tickets sell out at AI Engineer World's Fair - this is the single biggest gathering of AI Engineers, Founders, Leaders, and Researchers in the world. Attendees get >$5000 worth of sponsor credits and talk tracks are looking FANTASTIC. Join us!The AI scaling debate always focuses on the question of “how do we get more GPUs?” but the better question may be: how do we make the most of ones we already have.The fact that a frontier lab like xAI could be running at sub-10% MFU (Model FLOPs Utilization) is just a hint at what the real problem may be.For context, older frontier-scale training runs were already much higher than 10%. GPT-3 was around 21% MFU. Gopher was around 32%. Megatron-Turing NLG was around 30%. PaLM reached around 46%. And our guest Anjney says best-in-class MFU today is closer to 60–70%.It's not necessarily that xAI is uniquely incompetent (it's clear they have talented folks) but rather the priorities may be flipped in the GPU arms race.While GPU access is a bottleneck, simply increasing CapEx won't automatically translate to better models as frontier AI is increasingly a systems problem: scheduling, utilization, networking, kernels, frameworks, data pipelines, parallelism, cluster reliability, and the thousand small decisions that determine whether your theoretical FLOPs become real training progress.From building Discord's developer platform and backing frontier AI companies like Anthropic, Mistral, Black Forest Labs, and Periodic Labs to now building AMP's independent compute grid, Anjney Midha has spent years close to the real bottlenecks of AI scaling. In this episode, Anjney joins swyx at Periodic Labs to unpack why the AI race is not just about buying more GPUs, why 95% utilization would have been considered an outage at Google, and why the next era of AI infrastructure has to be more aligned, more efficient, and more responsible.We go deep on AMP's vision for a compute grid that makes FLOPs flow like megawatts, the difference between full-stack AI labs and horizontal pooling, why AI data centers need community buy-in, and how compute markets could evolve into something closer to an independent system operator. Anjney also explains why DeepMind's unpublished research points to a market failure, why end-of-life prediction remains one of the most important AI applications he has thought about for fourteen years, and why “output maxing” may become a new discipline for frontier systems.We also discuss Anthropic's culture, why “luck favors the prepared mind” in coding models, how Claude cracked coding, why too much capital too early can make AI labs fragile, what Periodic Labs is trying to do with science and superconductors, why great researchers can become great CEOs, and why Silicon Valley is both deeply missionary and deeply mercenary.We discuss:* Why 95% utilization was considered an outage at Google* Why AI infrastructure waste compounds at frontier-lab scale* Why “move fast and break things” does not work for AI data centers* How data center backlash, power grids, and community incentives shape AI scaling* AMP's vision for making FLOPs flow like megawatts* Why compute needs an independent system operator* How interruptible demand and dynamic prioritization worked inside Google* Why DeepMind research hoarding creates negative externalities* AMP's 1.2GW base-load ambition and the need for 6GW of spike capacity* Why end-of-life prediction could become one of AI's most important healthcare applications* Frontier Systems, output maxing, and full-stack alignment* Why APIs and abstraction layers become lossy as organizations scale* Superconductors, standards, and the dream of lossless systems* SF Compute, open protocols, and the future of compute marketplaces* Why non-NVIDIA chips can still benefit from NVIDIA's reference architecture* Trust boundaries and why chip startups need visibility into future model architectures* Why VCs often underestimate researchers as CEOs* Scientists as star athletes of the mind* Why great CEOs need to be confrontational up and down the stack* Why leading the frontier matters more than “winning”* How Anthropic cracked coding* Why culture is fragile, not a permanent moat* Why hardship was a feature, not a bug, for Anthropic* Why Anthropic's P0 was coding from day one* Periodic Labs, physics as the constraint, and technical reality* Silicon Valley mercenaries, missionary teams, and what happens after a breakthroughAnjney Midha* LinkedIn: https://www.linkedin.com/in/anjney* X: https://x.com/AnjneyMidhaAMP PBC* Website: https://amppublic.com/* X: https://x.com/amppublicTimestamps00:00:00 Introduction00:00:09 Why AI Compute Is Being Wasted00:03:17 Responsible Infrastructure and Data Center Backlash00:06:07 AMP Grid: Making FLOPs Flow Like Megawatts00:12:41 Foundry, Frontier Labs, and Research Hoarding00:14:42 Gigawatt-Scale Compute and End-of-Life Prediction00:24:08 Frontier Systems, Output Maxing, and Alignment00:27:38 Compute Markets, SF Compute, and Non-NVIDIA Chips00:32:57 Trust Boundaries, Co-Design, and Researcher CEOs00:38:17 AI Coachella and First-Principles Thinking00:42:43 Leading vs Winning in Frontier AI00:45:54 How Anthropic Cracked Coding00:48:25 Culture, Hardship, and Anthropic's P000:54:03 Periodic Labs, Physics, and Silicon Valley Mercenaries00:56:26 Rishi Valley, Singapore, and Money as a Measure00:58:47 Closing ThoughtsTranscriptIntroduction: Anjney Midha, AMP, and Compute WasteSwyx [00:00:00]: We're in Periodic Labs with Anjney Midha, CEO, founder of AMP. Welcome.Compute Utilization: Node Allocation, MFU, and AlignmentAnjney [00:00:09]: Thanks for having me. At Google, there are two types of utilization usually, right? That you're measuring in these clusters. One is node allocation, and then the other's MFU. Node utilization is usually like what percentage of cards in the data center are just, used, and that, if it's not at, 95%-Swyx [00:00:29]: There is no excuseAnjney [00:00:29]: There's no excuse, right? I think 95% at Google, which is where my co-founder, Seb, came from, he built the Borg, PBorg/GQM scheduler at Google, and there I think 95% was considered an outage, so 96% node utilization is, should be standard. And most single-tenant clusters are not running at that. So that's one. And then MFU should be, I would say the best in class today is somewhere between 60 and 70%. I think this is a leadership question, right? Fundamentally it's an alignment question, which is are the people who are funding the cluster and then deploying the cluster actually aligned? And sometimes theoretically they are, but in practice the number of people in the chain, the supply chain between, the capital and all the way to whoever's managing the cluster and then whoever's measuring what the output is, are just so many, degrees of separation away that, the, The Have you ever heard the radian metaphor, which is at the beginning of an arc, if you have two arcs that are two lines that are just off by a few degrees, that-Swyx [00:01:33]: It spreads outAnjney [00:01:34]: It spreads out, right? Or at scale. And I think what's happening is a lot of cluster implementations and infrastructure, a lot of frontier labs and other teams, that's what's happening, is they're, they initialize the plan, which is kind of like North Star with a team that wants to do good, but then they're, required to scale so fast instead of iteratively that the wastage just compounds really fast at scale. And so I think we know the answer, which is just do iterative bring ups. If you spend time with people who've been in the semiconductor industry or the DSN industry for a long time, this is not new, and I don't think AI should be an excuse. Sure. Something What is new? Okay. We have a lot of new capabilities, but that doesn't mean just abandon common sense. Common sense should always be in fashion. ? AI scaling doesn't change the in fact, if anything, AI scaling should be putting a premium on the value of common sense and infrastructure because the margin of error now is so much lower and the costs of wastage are so much higher. And the cost of wastage, by the way, is not just economic. I'm, obviously I'm, I'm an investor, or I'm an investor by background. Over the last few years now we're running an AI infrastructure business called, AMP. And I think that it's okay to say this time is different on the capabilities front. We are genuinely getting capabilities at, of the, of a kind we haven't had before. That doesn't give you an excuse to say this time is different for everything, especially infrastructure. So look, I love the hacker mindset and the hustler mindset. Now, that's great for the startup mindset, but you remember this moment where Zuck went from saying, “Move fast, break things” to, move-Responsible Infrastructure and Data Center BacklashSwyx [00:03:10]: Fast and stable infrastructureAnjney [00:03:11]: Move fast with stable infrastructure. I think now we need to move fast with, responsible infrastructure. People are going to ask where the impact is. There was a really In our class yesterday, Scott Nolan, who's the founder of General Matter, came by at Stanford to speak about energy bottlenecks. And he had a phenomenal idea. He said, “if you look at the marginal unit economics of compute per hour,” he goes, “let's call it, $4 an hour. If you're having to bring up a new data center in a new community, why not just say we're going to charge 4.50 an hour, and that marginal impact or that marginal increase, we just literally take that and give it to the local community as cash?” I can tell you as a customer of that compute, I would love that. I'd be happy to pay an additional 50 cents per hour at scale.Swyx [00:03:57]: Wow. Yeah.Anjney [00:03:58]: Because if that means the public benefit is so clear to the communities that the data centers are coming up in, I'm going to feel like that compute is much more reliable. Up to 20% of all data centers this year in the US, my understanding is are at risk.Swyx [00:04:13]: Of community backlash?Anjney [00:04:14]: Correct. Of not getting the community support they need to get brought up.Swyx [00:04:19]: Wow. That's a huge number.Anjney [00:04:20]: Yeah. Now, we, I think we should dig into what that number is. I think it's a little bit of overstated. These things can get over-reported, but it-Swyx [00:04:27]: They don't just care about jobs. They care about all the other stuff around it, right? They care about power grid, they care about environments-Anjney [00:04:33]: Power grid, permitting, and so on. And imagine I think if you said there's a new AI deal. If we're bringing up a data center in your community, we're actually going to reduce the cost of your electricity bill. Okay, now we're talking. Right? The community's going, “Okay. Now this is a deal. I feel like a partner in this.” Right now that's not happening. There will be audits, there will be investigations, and when the, when the regulators come, I don't know when it's going to be, the folks who are moving fast and breaking things in the name of AI progress better be prepared. That's certainly not how we're procuring compute. Or we're, we're trying as much as we can to work with partners who have long-term track records. Many of whom, by the way, are not, AI providers. I think this whole idea of neoclouds being somehow this new category is a lot of marketing speak. There are really good, reliable, trusted data center providers in America who've been around 20 plus years. I love those folks. They know how to Sure. Are they sponsoring happy hours at NeurIPS? No. Are they legibly listed in Build? No. Are they hanging out in my, in, situational awareness parties? No. But they're adults. I trust them.Swyx [00:05:44]: They can run LAN. They can run power.Anjney [00:05:45]: They can run LAN, power, and shell. They have credit histories. We sit down, we have a conversations. Many of them live in Silicon Valley. They've, they've had to deal with the boom and bust cycles of the internet, and I love those folks. They are stable infrastructure partners and thinkers. And I think there's a lot of short-term thinking going on in the compute layer, and it's going to catch up to us. It's not going to be good.AMP Grid: Making FLOPs Flow Like MegawattsSwyx [00:06:07]: You talk about aligning incentives, and, I would think that aligning incentives means you have the full stack in one company, which is xAI and OpenAI, right? So you as a standalone infrastructure layer, why are you somehow more aligned to your portfolio companies than people who just own the whole thing?Anjney [00:06:28]: In systems design, right, there's, there's two regimes of, architecture, right? You have integration, and then you have pooling and utilization, right? So the Or rather, the way to increase utilization often is you can do systems integration where you collapse a lot of process into one node, or you can pull out a process from a node and share that amongst various That resource amongst several different nodes. And so we see the AMP grid, which is, the, what, the system we're building here, which is basically a compute grid. We're trying to do for compute what the electric grid-Swyx [00:07:02]: PowerAnjney [00:07:02]: Yeah, what the power grid did for electricity. It-- this is a pooling and utilization layer across clouds, And so we're actually the opposite of a full stack integration like approach.Swyx [00:07:12]: Super horizontal.Anjney [00:07:13]: Where it's much more horizontal and it's, it's multi-cloud, it's multi-silicon. The goal is to try to make FLOPs flow like megawatts, and that is very hard to do today for many reasons. There's stranded pools of compute all over the place and there's no fungibility. And so right now we do it at the level of scheduling, and we often do it at the economic layer. But as we start to announce what we're working on, it's extraordinary like how many folks are coming out of the woodworks and saying, “Hey, I'm actually working on a way to make compute fungible at this part of the stack and that part of the stack.” And as a grid, we'd like all of these folks to participate on the grid. There's, people often ask me, “Andra, are you a new cloud?” And I go, “No, actually neoclouds are suppliers.” sometimes they'll ask, “Are you a venture capital firm?” I go, “No, actually they are, they are demand like sort of off-takers of the grid.” We see ourselves as what's called an independent system operator. So if you study the history of the electric grid, once it became legible to a lot of factories and industrial sort of participants that, hey, actually it turns out pooling is a good idea. We should pool our generators instead of all having a generator running at half capacity in our backyard. There was a need for an independent entity who could coordinate all these parties. Transmission line, power generation, facilities, transmission lines, factories, and that neutral coordination mechanism is very critical. In order-- If you study like the history of grids, the most enduring ones were those that never owned their own assets. They were ones that had, or often started with long-term anchors who are uncorrelated sources of demand, a steel factory, a shoe mill or whatever in a particular town who weren't competitive, where the steel factory want to spike up at night, the shoe mill wanted to spike up during the day. So then you pool and you share, right? So each of you is guaranteed some base load, but then you kind of schedule your spikes to drive a peak utilization across the town. The gold standard, so to speak, historically, has been these utility companies like PJM Interconnect in the northeast of America, where they, over many years became this what's called an ISO, an independent system operator of the grid. So that's how we see ourselves. Economically, that's what we are. From a technical perspective, we started at the scheduling layer because Seb and Mihai, who, run engineering here, built that at-Swyx [00:09:28]: Did your schedulingAnjney [00:09:28]: They did that at Google. And, -Swyx [00:09:32]: And you have infra shops from Discord as well.Anjney [00:09:35]: I have some.Swyx [00:09:35]: I don't know, I don't know if Discord is like the primary identity, but what-whatever, I'm just kind of-Anjney [00:09:39]: No, D-Discord was-Swyx [00:09:40]: Choosing a well-known name.Anjney [00:09:42]: Well, I So I was running the developer platform there. The internal infrastructure I was not responsible for. That was actually a guy by the name of Mark Smith, who was extraordinary. And yes, Discord did pool So Discord is actually a counter example. I had the chance to learn a lot about fully, full stack infra there because-Swyx [00:09:56]: It's the same thing, yeahAnjney [00:09:57]: It's the, it's the other architecture which is, Discord built its own WebRTC vo-voice and video infra. So like Discord did not use-Swyx [00:10:08]: For the calls, yeah.Anjney [00:10:09]: Yeah, did not For communication, Discord did not use third party infra. It was all built in-house. And then the way you maximize utilization was you pool demand from the world's 200 million plus monthly active gamers, right? And so that's, that's how those stacks were constructed. Again, in systems design, the two concepts that keep coming up over and over again are abstraction and composition, right? And-Swyx [00:10:31]: Bundling and unbundlingAnjney [00:10:33]: Bundling and unbundling, abstraction, composition, like verticalization and-Swyx [00:10:36]: HorizontalAnjney [00:10:36]: Horizontalization. So in that sense, AMP is an independent system operator of the grid. We pool demand, we pool supply from a number of partners we trust At about 1.3 gigawatt scale over four years. And then we pool demand from some of the world's best, research labs and so on. We're sitting at one, periodic labs who need extraordinary long-term demand. And the idea is that, each of them is guaranteed base load on the grid, but they can spike up and down flexibly on, for compute, with much shorter timelines as needed. That was roughly the design of the program I came up with at a16z called Oxygen. The same-- That was the same design of the GQM, BorgX, Borg GQM implementation at Google that Mihai and Seb had built. Which was that how do you allow, teams inside of Google, on the internal infrastructure to be guaranteed capacity, for their base workloads? But when they need to spike up on research, how could they ensure that was sufficiently there? And of course, the big innovation that was not discovered, but kind of implemented in the space, this infra space maybe three, four years ago at Google was the idea of interruptible demand, right? Where you just queue up a bunch of jobs and through this like sort of credit system, there can be a bidding mechanism.Swyx [00:11:53]: Like priorities.Anjney [00:11:54]: It's a dynamic prioritization Basically. And jobs can get interrupted based on somebody else who's saying, “what? I have 10 tokens, 10 credits I want to spend on this job.” Another like team lead, research lead is “Genie 3 or whatever is only worth five, credits, and NanoBanana2 is worth 10 credits,” and so the NanoBanana job gets priority. That's a, that's a made up example.Swyx [00:12:15]: It's very real. Brain Marketplace was real. And, we've, we've covered this on the pod with David Luan, who was-Anjney [00:12:20]: Oh, great. OkaySwyx [00:12:20]: Was there. And the criticism is that, well, actually sometimes you need central command to go all in on a thing. And actually sometimes capitalism via credits doesn't work. Not, this is not a criticism of AMP. I'm just saying, this is a thing that has been tried, internally within Google, and it led to Google missing GPT.Foundry, Frontier Labs, and Research HoardingAnjney [00:12:41]: Like, we structured ourself essentially very similarly to Google. We are structured as a holdings company. So, Alphabet holdings is Alphabet holdings, and then they've got these subsidiaries called Google and-Swyx [00:12:51]: Other betsAnjney [00:12:52]: Other bets and so on. We've got, AMP holdings, and we've got our infrastructure business, and then we've got a capital business called Foundry that incubates new frontier AI labs or invests in them as venture capital, like Periodic. We put a few hundred million dollars into Anthropic from our fund earlier this year. So wherever we feel like teams are making progress, especially researchers and so on who've pushed the frontier inside of existing labs like DeepMind, I find, there comes a point where they feel misaligned with the dictatorship of Alphabet holdings. And at that point, sometimes the dictatorship doesn't want them anymore. And they're “Thank you. You've done your job here. You've kind of helped us through the zero to one phase, and for whatever reason, we're going to deprioritize your amazing, omni model or whatever it is, and instead we're going to prioritize coding.” And, I think that's a tragedy, but I get it. They're Sergey and team are running their own business there. But that doesn't mean we the rest of us should sit around waiting for that progress to get unlocked for the rest of the world and humanity. If you think about how much extraordinary research has happened inside of DeepMind over the last 10 years, I, Demis and Sergey and those guys did such a great job. But at the end of the day, so much of that has never seen the light of day?Swyx [00:14:00]: Or they're like papers only, but they never actually shipped it to production or-Anjney [00:14:03]: What's worse is the paper is actually not even being published anymore ‘cause there's a six-month embargo inside of DeepMind, right? We've heard about this where a paper comes out, and then I think there's a six-month embargo window where if anybody on the business team says, “This could be interesting” It's embargoed for life.Swyx [00:14:18]: Exactly. So the stuff that gets published is the stuff that's not good enough.Anjney [00:14:21]: There's an adverse selection problem, basically. Yeah. At this point-Swyx [00:14:25]: It's, it's a common complaint at NeurIPS, by the way, that's “Well, why would I look at the papers that are the trash of GDM?”Anjney [00:14:31]: Again, I think it's a tragedy. I get it. They're running their business, but the rest of the I think there's negative externalities of research being hoarded, and so that'there's a market failure. And somebody needs to unlock that research, and we can't do it on our own. We only have 1.2 gigawatts of compute. That's nothing. That's about $40 billion of cloud spend. We're going to need a lot-Gigawatt-Scale Compute and End-of-Life PredictionSwyx [00:14:51]: By the way, is that's a new number. I haven't, haven't come across that gigawatt number. That's huge.Anjney [00:14:56]: Yeah. And to be clear, we haven't secured all of it. That's how much demand we have started to secure. I think publicly we haven't actually confirmed how much we have for this year. In order-Swyx [00:15:04]: Where do you want to get to?Anjney [00:15:06]: I think the steady state would be that we have a base load pool Of 1.2 gigawatts at all times Of base load capacity. For spike capacity, right now my estimate is we need roughly six gigawatts over the next four years for all our teams to feel like they were able to keep moving the frontier, whatever they're working on, whether it's, like superconductor discovery over here. There's a new investment we're working on right now, which is in the end of life prediction space in healthcare. It's extraordinary how much you can, you can give this was actually my graduate school work. I went to grad school for bioinformatics at Stanford Med. And I know we-Swyx [00:15:40]: Econ, MCS, bio.Anjney [00:15:41]: So my-- I was this really weird cat where, I was never satisfied with my major options. So at one point I was an econ major, then I was a CS major, then I was a MCS major called mathematical computational science, and they decided they were going to end that major. So I took all that coursework, and I applied it to grad school, my graduate degree in bioinformatics, which was the master's program, and then I thought I was going to do a PhD. I never ended up doing it. I dropped out and went to work at Kleiner. But I was lucky enough to apprentice with this professor at, Stanford Med. His name is Nigam Shah, and he was working on end of life prediction. Stanford is one of the only research facilities in America that has a longitudinal patient data set that's larger at scale. I think it's at least 12 million patient lives. The only larger data set is at the VA, the Veterans Affairs, of America. And to do research, like do any deep learning and so on that data set, it was called the STRIDE data set at that time, you had to be a Stanford Med School affiliate, which is why I went and enrolled in the bioinformatics department. End of deep learning was early. Nigam Shah had the visibility-- the vision to see that, you could do end of life prediction to help palliative care. In America, the, over 30% of all Medicare, Medicaid spend, at least at that time, was spent on end of life care. And what's we grew up in Asia, so we all-- Yeah, at least I won't speak for you, but I have A very different relationship with death than I find folks who grew up in America do. In America, spiritually and culturally, especially in Western societies where Christianity, the Christian tradition sort of frames death as this terminal point, there's often a judgment day and so on. The way we view death is with a finality. In Indian culture, in Hindu culture, death is one-Swyx [00:17:35]: Also, he's Buddhist as well.Anjney [00:17:36]: You're Buddhist, yeah. So it's one, it's one step in a journey of many lives, right? And so, I grew up in this city called Chennai in the south of India, and when people die, you dance on the street. There's like a procession where your body is carried to be cremated and your family, like celebrates and there's drums and so on. It's this huge thing. And, It's because the idea is that you're going to be reincarnated. You've been liberated from the responsibilities of this life, and now you're onto your next. It's a new It's like going off to a new college or whatever, right? And so it was so alien to me when I got here as an undergrad- That the medical system works backwards from that assumption that we have to view death as this terminal thing and delay it, postpone it's a bad thing. And so at the time, clinical decision support in the United States was this very primitive field. Even to this day, physicians in the United States often will tell you when you have a terminal disease, this is your, we've diagnosed you, which is great. Our ability to diagnose you is extraordinary. You have somewhere between six months to six years to live. What do you do with that information? The error bars are so high that then you In times of uncertainty, we default to culture, and when the culture is let's-- this is a bad thing, I've got to prolong my life, then you start doing things like And just to, just sort of from a systems perspective, what's going on there is Physicians often feel like they need to provide such high error bars because there's always some uncertainty in end of life diagnosis, and if you provide the wrong Diagnosis or recommendation to your patient, you can be sued for medical malpractice. And then your license can be taken away. It can be catastrophic for your career. In contrast, if in countries where that's not the case, what you often observe is that patients, physicians are quite prescriptive with their recommendation. They say, “Hey, this is your condition. The literature says that you probably have this much time on Earth left. My expert opinion is that you are an outlier or whatever.” And they try to be more prescriptive, and that empowers a patient, right? ‘Cause then a patient can say, “I trust my doctor. They said on average, I have six months to live, but if I do these things, I may have a shot because of my particular predispositions or my genetic history or whatever.” And that empowers you to go about your life in a actually more scientific way than leaning on religion, culture, spirituality, and so on. In contrast, here, because of that medical malpractice sort of thing looming over your head, a physician never gives you a clear recommendation. So instead you say, “Okay, Doc, well, let's try it all.” And then you start a whole regime of drugs and therapies, and then you often spend weeks and weeks in the hospital, and that deteriorates your quality of life. And when that deteriorates your quality of life, you instead of spending your last few days doing the things you love with your family, you're spending it on a hospital bed. And that ends up being thirty percent of Medicare and Medicaid. So it's worse for the patients. The doctors feel terrible. The American taxpayer is paying a huge amount of money. And so this is why Nigam Shah, who was this professor at Stanford, said, “Anjney, if there's “ I kind of sat down with him. I was this young, I'd, I was twenty-one, and I was “I want to work on a big problem.” He's “The big problem is end of life care.” And so we tried to do deep learning to say, to-- So we started trying to run deep learning on these tried patient data sets to say, “Could you have an AI system make a recommendation that is orders of magnitude more precise about how much time you have left once you've been diagnosed with a terminal condition than a human?” And then if we can get that precision to be high enough, then you can empower the patient. And it turns out the tech works. Like it's-- Once you get the data set, like RL works. Honestly, even regression models work. You don't need to get that fancy. At the time, we were just trying, doing like very simple neural nets.Swyx [00:21:54]: Simple solutions, yeah.Anjney [00:21:54]: Today, what we can do with RL is extraordinary. The problem remains then and now is regulatory, because you actually can't shift the burden of the wrong clinical diagnoses from the physician to the AI system. And so at that time, I got quite disillusioned ten years ago for, twelve years ago where, ‘cause I felt I just didn't have the resources to influence regulation. Today, I'm very lucky. I'm in a different place. I've, I'm a lot older, and so I've been spending a lot of time on my next incubation, which is how can we unlock the, patient empowerment by training AI models to do end of life prediction much, with much more precision and ac-Swyx [00:22:37]: Oh, wow. You're still focused on this the whole time.Anjney [00:22:40]: The-- I haven't been able to get, this out of my mind a single day for the last fourteen years. This is the hill I want, I would like to die on. There's two, I would say. What? I actually, I'd prefer not to die.Swyx [00:22:51]: Yeah, exactly.Anjney [00:22:52]: But I think two bipartisan issues, I think two issues that should be bipartisan in America are how do we empower patients to make the right clinical decisions at the end of their life, such that we're reducing the taxpayer burden with science? It's just good old science, and AI can help here. And the second is, net positive data centers, ‘cause I think that's the biggest critical bottleneck on training and good enough AI models to help people at the end of their life. So there's sort of two sides of the, of the same scaling bottleneck curve, but those two, we formed AMP as a public benefit corporation. My wife and I, who you've met, you've met Viv. Her passion is education. Her family is a long line of educators and so on, and, of physicists. And so this class is my attempt to stop being the black sheep of the family and be a, an educator. But if I'm not educating, the thing I would be doing is working, on these two problems, whether on the political spectrum or as a researcher back at, in some lab. And my hope is if anyone's listening to this podcast, if they're passionate about either of those two topics, I'd love to hear from them. We'll, we'll we can share the contact in the show notes, but, we're looking for people to join both of those missions on the, on the political side as well as on the medical side, on the research side.Frontier Systems, Output Maxing, and AlignmentSwyx [00:24:08]: You said, this is a discipline that you want to form. You call it's called variously called Frontier System. It's variously called One Person Frontier Lab. What is the ideal name or shape of this? Like the, what is the mission?Anjney [00:24:24]: Of the class?Swyx [00:24:26]: Of the discipline that you're, exploring, right? I The class is called Frontier Systems. But like for me, maybe one phrase is you're, you're just anti-waste, right? Which is wasting GPUs, wasting in human and Medicare. But is there, is there a broader theme that I'm, that maybe you can encapsulate more succinctly?Anjney [00:24:45]: Yeah. The, from an engineering perspective, it's very simple. It's output maxing. It's the, it's the department of output maxing.Swyx [00:24:51]: Making the most of what we have.Anjney [00:24:52]: Exactly. I'm a huge believer in optimal outcomes. I think both in America and other countries, we are losing our appreciation for nuance, and this is the thing of And AI is the same case, right? Oh, the bitter lesson holds. Okay, fine. But that doesn't mean you just like throw 500 GB300, 500,000 GB300s at your suboptimal model scaling and you waste a bunch of compute. It also doesn't mean that, the most optimal is to have like 50 different architectures where there isn't enough standardization. One of the reasons Anthropic has had extraordinary sort of velocity is ‘cause they picked the transform architecture and said, “This is simple. Let's double down on it,” right? And now luckily there's enough investment going to the space that we can afford other architectures, but at the time, investment was just too fragmented into other architectures, so that arguably unlocked scaling. So I think there's a philosophy. I think we all owe it to ourselves to do output maxing with a new capability called AI on a global level. I think if I was starting a new department at Stanford, depending on how fuzzy or technical I wanted to be, I'd probably call it the Department of Alignment. Like-Swyx [00:25:59]: It's an overloaded termAnjney [00:26:01]: But it is, But alignment really Is a hard problem. And I think when you unlock it, full stack alignment is super hard in any organization and in any system. Like in a, in a venture capital firm, if you can have full stack alignment between your limited partners and your, the founders who are creating the value and ultimately the public that owns the IPO stock, that is a gift that keeps giving. And when you study the history of these systems, when they start off, they usually start out small scale where the feedback loop is actually so tight that there's alignment. And then the more you try to scale, the more division of labor happens, the more specialization happens, and at each step you add abstractions. And wherever there's an API interface, there's like loss. There's communication loss. And so I think a really cool thing would be for us to figure out is there a way for us to have our cake and eat it too as an engineering discipline? Is there a way to actually scale up and scale out Without losing any alignment, without lossy transmission?Swyx [00:27:01]: You mean standards?Anjney [00:27:02]: So standards is one way. The other way is you just have net new capabilities. So like what we're trying to do here is discover new superconductors. A room temperature superconductor would be a lossless transmission mechanism for energy. We would have flying cars. We are right within a few years of having a new room temperature superconductor. So I think those are the two. You either have to standardize On protocols or API specs that allow lossless communication, or you can come up with a whole new capability that unlocks so much abundance, the standardization doesn't matter ‘cause you just unlock net new capacity. This, the, so this is what I spend my days thinking about these days.Compute Markets, SF Compute, and Non-NVIDIA ChipsSwyx [00:27:38]: No, I think every infra person at, who wants scale and wants to output max does eventually end up thinking about this. We don't have time to go into it, but we have done an episode with SF Compute-Anjney [00:27:50]: Oh, coolSwyx [00:27:50]: That is trying to standardize The futures contract for compute. I don't, I don't know how that's going by the way, but like at some point this will be public.Anjney [00:27:57]: Oh, I think Evan is awesome and SF Compute is the kind of effort that I hope we can accelerate because what often happens is these exchanges are very hard to get, they, it's hard to bootstrap them, right? Because they often require-- There's many inefficiencies between parties. There's trust boundary inefficiencies in infrastructure because you don't trust, one part of the stack doesn't trust another part of the stack to give them visibility. There's capital markets inefficiencies, there's operational efficiencies. So if you can inject like a single shock to the system of a ton of compute demand or supply, then you can accelerate, these new flywheels. And so my hope is one day, or soon, if SF Compute needs extra like has excess capacity, they just hook it up to the grid and they get flooded with demand from us. And on the other side, if they have a ton of demand but they don't have supply, they just again hook up to the grid and it's a two-way protocol where they can just hook up to our capacity. And I don't think we're too far from that. Today our working implementation of it is mostly through a group of labs, universities, and a few sort of trusted parties who are, who all feel like they're in alignment to borrow an over sort of used word. But our hope is to just have it be an open protocol that anyone can hook up to on-Swyx [00:29:20]: Hook up for demand or hook up for supply? In primarily demand, it sounds like. Like you-Anjney [00:29:25]: No, bothSwyx [00:29:26]: You would want to offer demand.Anjney [00:29:27]: Both. Yeah. Unfortunately, what's happened in the last six weeks is, we thought we'd have a bunch of excess capacity by the end of this year. It's all gone.Swyx [00:29:37]: It's exploding.Anjney [00:29:38]: It, yeah. It's all gone. And so I have, my text messages are full of friends, we know many of these people, these are founders who've raised billions of dollars in San Francisco going, “Oh, any chance you have like 50 nodes in the next few weeks?”Swyx [00:29:51]: What is the scope for, non-Nvidia, right? You have Lisa Su coming and, Rainer Pope as well. And so There is a lot of demand for, more performance Alternative architectures and all that. At the same time, this hurts your standardization.Anjney [00:30:11]: I don't think so. So actually Rainer's a great example, right? Rainer is a CEO and founder of, MatX. I actually had him by for office hours in the class earlier today, and there was an insight he brought up that I hadn't considered before, which is when they decided to pick the standard For their data center, they picked the NVIDIA reference architecture. So the MatX chips Just plug in to any site that has an NVIDIA bring up planned. And, the-Swyx [00:30:42]: It's just software then. It's, it's not the-Anjney [00:30:44]: A-Swyx [00:30:44]: Hardware.Anjney [00:30:46]: Well, from an input and IO perspective It's the same footprint as an NVIDIA rack.Swyx [00:30:52]: That makes sense.Anjney [00:30:53]: Where they have done, innovated a bunch from what I can tell is on systems co-design. Which is where a lot of the gains are to be had. And so he picked He was “Anjney, we, there's just so much work to do when you're building a new chip company.”Swyx [00:31:08]: Can't fight every front.Anjney [00:31:08]: You just can't fight on every front. So my question to him was, “Well, you're working on this new chip. Their tape-out is next year. What, who are you going to partner with to host the chips?” And he said, “Whoever will host them. That's just not, that's not my focus.” And I said, “But how did you “ you decided back to our earlier systems design question, he decided that, he didn't want to be a full, fully integrated chip provider. The bottleneck they're focused on is the logic die, and they, he feels they can crank out a ton of performance gains through co-design there. But then that means you delegate, to our question earlier, it, you he's the data center provider is a different part of the stack, and so then he's dependent on that part of the ecosystem to host his chips to get the performance gains to the customer. So now you have another abstraction, and you might have loss. So I asked him, “How do you prevent loss?” And back to your point, he said, “I just picked the NVIDIA standard ‘cause I didn't want to Like I wanted to piggyback off of an existing protocol.” And that, what's great about NVIDIA is that reference architecture is known.Swyx [00:32:15]: Open.Anjney [00:32:15]: It's open. They've published it. So Jensen's actually enabled someone like Rainer to build a chip company like MatX, and I don't see them as competitive. The compute demand is so high. Like, I don't I think NVIDIA's not able to meet the demands of production, so we just need more chips. And I think it's very smart what MatX has done, which is say, “We're just going to we're not going to innovate on the data center design ‘cause actually, thank you, Jensen, you've done all the hard work. Where we can innovate is somewhere else.” And I think that's, that's very healthy. I think that's how we unblock new bottlenecks. And my view is these, the, chip teams like MatX, who have arrived at the insight that co-design is the way, The primary bottleneck for them is trust boundary. To do co-design well, you need visibility into the next model generation as soon as possible ‘cause it takes two years to tape out. So if by the time I bring my chip to market, your model architecture's changed, I'm host. Now, when he was inside Google, he was sitting next to the Gemini team. He was on Palm or whatever.Trust Boundaries, Co-Design, and Researcher CEOsSwyx [00:33:19]: His co-founder was the, was one, was one of the Palm guys, I think.Anjney [00:33:23]: Yes. Yes, exactly. So when you're inside the trust boundary of Google, then your systems co-design loop is super tight. When you leave as a founder, one of the biggest risks you take is now you're outside the trust boundary. And so what I love doing is helping chip teams who can help us unlock more capacity for the independent ecosystem access to trust. Because when I If I've been, involved with a lab from day one, and I was lucky enough to work with Anthropic, and then I'm on the board of Mistral and helped Black Forest Labs get started. I think at this point I'm on six or seven different teams.Swyx [00:33:57]: Only six? I feel like my mental number was going to be 13, but yeah, it's-Anjney [00:34:02]: No, I go deep with one at a time.Swyx [00:34:04]: You're founding CEO of Arena.Anjney [00:34:07]: Nah, that was an, that was an-Swyx [00:34:08]: Administrative CEOAnjney [00:34:09]: It was an administrative five-month gig where Whalen and Anastasios were graduating from their PhDs, and they didn't need a product team. So I helped recruit the head of engineering product and design. But Anastasios has always been the CEO of that company. I played a pinch-hitting I'm an intern. I was CEO intern For five months. -Swyx [00:34:33]: I interviewed him, and he's he's very well-spoken. I think he's a debate, former debate, champion. But also very quantitative and mathematical, which is-Anjney [00:34:41]: He-Swyx [00:34:41]: Such a unicorn.Anjney [00:34:43]: See, what's amazing about him? If you look at his output, he's an output maxer. By the time he was graduating from his PhD, which he only graduated last year, he had published more work with a citation count than, people twice his age. But at the same time, he'd already started a project called LLM Arena that was being used by millions of people As a side project. And time and time again, what I've realized is venture capitalists suck at seeing human beings as, dynamic agents where-Swyx [00:35:14]: They want to put you in a boxAnjney [00:35:15]: They want to put you in a box.Swyx [00:35:15]: This is your thing.Anjney [00:35:16]: So the first time I got introduced to Anastasios, somebody had told me “Oh, he's amazing, but he's a researcher.” I was “what? What do you mean he's a researcher?” That's what-Swyx [00:35:28]: Like he's not a CEO, not a founder.Anjney [00:35:29]: Not a CEO, exactly. I was “Are you crazy? Do you Have you met Dario?” Dario's a scientist. He's gone from zero to, what will soon be a trillion-dollar company in four years. Being a CEO, nominally speaking, is not that hard. Being a good CEO is hard. Being a great CEO actually requires a level of performance that scientists who have already published at the top of their field have accomplished. It is super hard to be a competitive scientist. To publish in academia over the last 20, 30 years, to make it to the top of your discipline at a place like Berkeley, you are a star athlete. Like, you are an athlete of the mind, and you perform at the highest levels. And to get there, whether you're, Anastasios or Whalen at Berkeley, or you are Robin, who-Swyx [00:36:23]: BFL, yeahAnjney [00:36:24]: With Black Forest, who created Stable Diffusion, or if you're, like Guillaume at Meta, who created Llama before he started Mistral. The amount of human leadership you have to demonstrate to get the resources, like get the trust of the organization, publish it, put it up. I would just fund researchers all day Right? If who have contributed already to the field. If they've, if they've put SOTA out there, they're, they're star athletes already. If they haven't done SOTA Look, they can still be good CEOs, but then I find the failure mode is that they just don't want to be CEOs, they primarily want to publish, and that's okay, too. One of the things we do with the AMP Grid is we donate excess compute. We have two nonprofits, like university labs. We carved out like a couple thousand H100s. But I do think there's extraordinary research being done on university campuses. My father-in-law's a physicist. He's a professor. Extraordinary work in physics, and we need that. But if you want to be a CEO, what you need to be willing To do is be super confrontational, outside of science. Like within the scientific community, some of the best researchers are very confrontational about their convictions, right? This architecture is right. To be a great CEO, you basically have to be willing to be confrontational up and down the stack.Swyx [00:37:41]: To your own team.Anjney [00:37:42]: To your own team-Swyx [00:37:43]: To customersAnjney [00:37:43]: Hiring, recruiting customers. Well, I would say, Yeah, pretty much to everyone Everybody. Of course-Swyx [00:37:50]: I see, I feel a little bit of that in my own work, but yeah, I can't imagine the stakes that Dario has had to go through. It's, it's pretty insane.Anjney [00:37:56]: No, I don't think the stakes are that different From how you're feeling it, right? Stakes are personal scaling vectors, right? The stakes that seem so low to you, like having this podcast where you can talk to somebody and just have a you're an extraordinary communicator, right? Like already in this conversation, you've pulled more out of me than most people, and I've been on 12 podcasts in the last two weeks.AI Coachella and First-Principles ThinkingSwyx [00:38:17]: I think I, we've just seen each other enough that there's some base trust.Anjney [00:38:20]: There's base trust.Swyx [00:38:20]: And I think, and I know that you, that I've done my homework and like I know that trust is a big deal for you, so.Anjney [00:38:27]: I think trust is about consistency, and you and I have seen each other In the community for years, right? Like, I remember the first time we met was at NeurIPS in New Orleans. I don't know if you remember that, luncheon.Swyx [00:38:38]: Oh my God.Anjney [00:38:39]: Reiko had set up this Reiko's amazing, and he set up this luncheon and-Swyx [00:38:43]: Yeah, I was “Who's this Discord guy?” I'm “Okay.” But-Anjney [00:38:45]: No, you weren't-Swyx [00:38:46]: You were just “You made some investments.”Anjney [00:38:47]: You were much less polite. You were “Who's this VC?” You're like-Swyx [00:38:51]: No, I Was I? Oh my God.Anjney [00:38:53]: It was-Swyx [00:38:53]: I'm so sorryAnjney [00:38:53]: It was visible on your face.Swyx [00:38:54]: I'm so sorry. But you weren't, you weren't The introduction was bad. I was I didn't know who you were.Anjney [00:39:00]: The, see, this is the thing about context, right? Like, but then I think I heard your accent. And I was “Are you-”Swyx [00:39:06]: Singapore, yeahAnjney [00:39:06]: “Are you Singaporean?” And you're “Yeah.” And I said, “I went to high school, JC, in Singapore.” And then the ice broke. But This is the there are in the scientific community, sometimes the stakes are very high for people who haven't had the emotional, what is called EQ Coaching and mentorship, right? Which is like to have scientific impact, you often need to be a extraordinary emotional, like emotionally in tune person with the folks you're trying to influence. And so what comes so naturally to you is actually a super high stakes thing to other people. And so I wouldn't assume that Dario's more stressed out than you. These things are you'd be surprised how similar and small sometimes the problems are to you That some of the world's biggest, leaders are facing. And that's what I've learned from this class. The guest speakers are Sam, Satya, Jensen.Swyx [00:40:01]: AI Coachella.Anjney [00:40:02]: Yeah. It's AI Coachella, right? So we got to get all the headliners, and they're I'm very lucky that some of these people have either mentored me over the years or I've done business with them. And when you, take the performative stuff out and any assumptions you may have about these people that you read in the press or on Twitter, We're all just humans. We're all trying to get along. And what's so special about this moment is AI is forcing, like scaling, the bitter lesson is forcing a lot of people to revise their assumptions for how the world works and go back to first principles or go and educate themselves. So the kind of people I was, I won't name who this person is, but I was at an event last week in Texas and, ran to somebody who said, “Anjney, I came across the class. What do you think about real time action prediction models?” And I was, don't know how happy it made me feel when they asked me that question. I know they've done the work. They've challenged themselves. I'm, they didn't ask me, “What do you think of world models?” They said, “What do you think of n-”Swyx [00:41:04]: Real time action predictionAnjney [00:41:05]: “action, real time action prediction models?” World models, don't get me wrong, are cool and everything, but you and I both know that is a layer of abstraction that is sometimes not usefully precise enough. Right? Ours-Swyx [00:41:16]: There's like four different kinds of world models.Anjney [00:41:17]: Yes, exactly.Swyx [00:41:18]: We've done the part with general intuition, by the way, which is very focused on, -Anjney [00:41:22]: Oh, cool. Yes. I love Pim. Pim is great. And this is what I love about people who've done that level of work. They realize they're not in competition with people who the rest of the world thinks they're in competition with.Swyx [00:41:34]: Because they're not in the category, they're in the specific thing they're trying to do.Anjney [00:41:37]: They're focused on their mission, and they have a systems understanding of the bottleneck they're trying to solve. And when somebody else says, “I'm working on real time, action prediction models too,” Pim goes, “Oh, I love that person. I want, I can learn from them.” But the minute they're “Oh, that person's a world model person,” it's “like which type of world model person?” But mostly they're just trying to figure out if it's a waste of their time, because we don't have enough time. So, Pim, for example, is super, loves this other company I work with we've talked about called Black Forest Labs. And he's mentioned to me multiple times that he's so, He thinks what Flux is doing is really cool. Andy Blattman came by and spoke in the class. And what I find over and over again is for people who do the work, who can be usefully precise enough about like what is actually going on in the world of frontier research, The sense of camaraderie is still well and alive, but it gets lost sometimes when you have to like abstract The technical complexities in, business terms And then the VCs are “How are you different from that world model?” I'm going to say Where do I even start to explain this stuff? And then the misalignment creeps in.Leading vs. Winning in Frontier AISwyx [00:42:43]: This is good. Yeah, I think, people listening get a sense of, what it is like to operate at a real level, like yourself, rather than at, the journalist level, where you have to sort of put everyone in, a rough category and create a narrative of competition, and who's winning today, who's behind.Anjney [00:42:58]: It-- this idea of winning is so Weird to me.Swyx [00:43:03]: You do want to win. You want you want competitiveness.Anjney [00:43:06]: No, I think you want to lead.Swyx [00:43:07]: You want SOTA.Anjney [00:43:07]: No, I think you want to lead. Yes, so you want to push the frontier. You want to push the SOTA. You want to do something that hasn't been done before. You want to capture value, but you don't want to capture so much value that, people think you're unaligned with your mission or trying to do what's best for the world. You want to capture enough value that you can keep innovating, right? And I think that people want to lead, they don't really This idea of winning and losing, again, I love Jensen. He's a, he's a leader. The mindset that he talked about on Dwarkesh's podcast, right? He's “I didn't wake up with a loser mindset.” I think that was awesome, right? Because he's, he's an engineer. Dwarkesh has done the work. So there's at least-- even though the, to me, it was very obvious they're talking about the same thing, they just passed each other. They just had to basically, Jensen has this, five-layer cake abstraction of how the industry works. And Dwarkesh had, I think from that podcast, had more of, a pre-training, mid-training, post-training systems loop concept.Swyx [00:44:04]: It's just a factor of who he talks to, right? Again, it's very clear.Anjney [00:44:06]: It's the systems It's the abstraction, the mental models, the It's the whole-- Dude, so much of the problem in the world is reasoning by analogy. And then the assumptions that are held invisibly.Swyx [00:44:19]: Yeah, I've, I've said, this is actually the best time in human history for first principles thinkers. Because everything you think will happen is actually now coming true.Anjney [00:44:28]: Correct. And the venture capital community is, notorious for this, where people look-- In times of uncertainty, they, cling to axioms that ended up being true from the previous era, and they kind of like proclaim them with confidence as if they're truths, but they're not. And it's very important to see the distinction between a heuristic and an axiom. An axiom can be proven-Swyx [00:44:55]: Like from internal consistency point of viewAnjney [00:44:56]: With internal consistency. A heuristic is a way you kind of a shortcut. And my God, the number of people I have had to put up with over the last few years who proclaim-- use heuristics As axioms to judge people, to judge which companies are going to succeed or the number of people who are “Oh, yeah, Anthropic, they're just training models right now,” but this one continue.Swyx [00:45:22]: Because that's a B2B SaaS?Anjney [00:45:23]: Yeah, the, like Which over the fullness of time, if you squint at it, maybe. But the way you arrive there is so important that you can-- you just, you can dismiss people. Here's what happened, right? What happened is Anthropic basically achieved takeoff in October of last year. That training run-Swyx [00:45:41]: Whatever, three seven?Anjney [00:45:42]: I forget the numbers now, but whatever that checkpoint was-Swyx [00:45:45]: We saw the cognition.Anjney [00:45:46]: Yeah. Right? You probably-- The, to those of us in the community, especially once post-training was done and it was released in December-Swyx [00:45:52]: Yeah. Can I sneak a sneaky question in there? I don't know if you have a perspective, maybe you don't, I just The number one question is how did Anthropic crack coding, right? Because Claude One, Claude Two, okay, like it was part of it, but it wasn't a big deal. And the leading hypothesis, it's a lucky dice roll that was then compounded, right? Like it was like Mildly better, but then they saw it and they were “Okay, let's really invest.”How Anthropic Cracked CodingAnjney [00:46:17]: I had this very annoying teacher. I went to this boarding school called Rishi Valley in India, which is like this, bird preserve. It's like three hundred and fifty acres of bird preserve in rural India, and there was no technology for seven years. There was this teacher, I won't name them, but they would have this-- I hated it every time he said this to me. He was “Luck fa-favors the prepared mind,” which is like a common saying, but the way he delivered it, always grated me, ‘cause he was always I was always one of those kids who got, a good grade without trying very hard. ‘Cause like high middle school is not that hard if you, if you're generally, paying attention and so on. And there was this one time where I-- But then I would get an eighty percent grade, and he would keep pushing me to say “The reason you didn't get the ninety-five plus percent is because you're not that lucky.” And I would say, “What do you mean?” ‘Cause I would think that I deserved that grade, and I would sometimes argue with him. And he'd say, “You didn't have a prepared mind. If you want to get lucky again “ There was basically one time where I got like ninety-five or ninety-six on this, on this subject, and I, now that I felt entitled. I was “Okay, I'm going to keep doing this,” and I didn't. And then he was “Luck favors a prepared mind. You got lucky last time, but you got to stay prepared.” And I didn't understand what he meant. Now, as I'm older, I'm okay, these adults actually knew a thing or two. Anthropic has been the most prepared company for four years. And so then when the right, context data comes in, the right developers start sending in, the right context diffs, Sure, you could say you got lucky, but if you ask me, they're pr-pretty damn prepared with paranoia for like four years. And you have to remember, it was so hard for them to get going early on that they had to do so much more with so much less that you just have to be prepared to be so efficient.Swyx [00:48:06]: Yes. There's numbers on their burn compared to OpenAI. I've, I've written about it, but they are so much more efficient in their, in their tech stack.Anjney [00:48:14]: It's not even It's not funny.Swyx [00:48:14]: Not even close.Anjney [00:48:15]: Yeah. But it's so clear, right? Like how to output max for the world. They have been prepared, and you could call that luck, but Luck favors the prepared mind.Culture, Hardship, and Anthropic's P0Swyx [00:48:25]: This is one of those things that I was going over some of your old lectures and, you were data, people think it's a moat and actually it's culture and actually it's team Actually. And I, it's-- there's different levels of moats, and this is the ultimate one that determines everything else. Which you can then compoundAnjney [00:48:43]: You're saying culture is the ultimate moat? Yeah. But the thing about culture is it's very fragile. So moats, I don't think they're-- there's very few moats I found that are actually moats. They're-- It's, it's a nice concept, but in reality, you have to replenish your culture. Ben Horowitz was, the speaker in CS153 on Tuesday, and I asked him this question about the culture bottleneck in teams because, there are several AI teams-Swyx [00:49:09]: His book, Hard Things About Hard ThingsAnjney [00:49:11]: Hard Thing About Hard Things. But more concretely, there are so many AI labs today that have all the cash they need, they have all the compute they need, and they're still not able to ship anything SOTA. And then you start seeing people leave and so on, and my diagnosis, it's, is it's the culture. And so I asked him, Ben, they're-- He's been one of the most aggressive investors in AI labs. He goes back to this thing which resonates in my mind a lot. It-- When I used to work at a16z, I would, book a conference room, and right outside the conference room, which is closest to the toilet ‘cause it was the fastest way for me to go use the bathroom between Zoom meetings-Swyx [00:49:45]: Oh my God, I'll put maxing my toilet optimization. Okay, never mind.Anjney [00:49:48]: It was not healthy in hindsight, but maybe this is TMI. But anyway, outside that conference on the wall was this quote that was printed that said, “Culture is not a set of beliefs, it's a set of actions.” And it's by Bushido, is this, Japanese philosopher. And if you stop taking the actions that demonstrate the mission alignment to what you've said to your team and to your-- the world matters to you, then your culture starts to fray. So it's not actually a moat, I would say. It's a very brittle, fragile thing that requires daily tending to like a garden. But if you figure out the system to keep that garden tended, which I think ultimately comes down to knowing yourself ‘cause you most naturally, if you're authentic and so on, you'll naturally make trade-offs that seem effortless to you, but that reinforce your culture. And then That becomes this very hard thing for other people to catch up to. And at Anthropic, from day one, there was this mission like-- missionary like zeal and belief that, hey, these capabilities will scale. These systems are stochastic, not deterministic. There will be error bars, and until we crack interpretability, there's risk. And at some point, people will go-- stop using Claude just for coding. They'll use it in some mission-critical context where there's-- it'll throw off a bug, and then people are going to come blame them, and they want to be on the right side of history where they said, “Yes, this is a powerful technology. We think it's going to change the world, And we want to be very measured and scientific about the fact that, ‘Hey, guys, these are stats models, statistical models.' That's how statistics works.” ultimately, when you're training neural nets, it is just a statistical system. And I think that Belief that safety is important and that it might seem toy-like in the early days, and sometimes, you could say, “Anjney, they totally over-exaggerated the risk,” like two years ago when they said, “Let's not launch Claude One,” or whatever. Well, okay, maybe in hindsight, but hindsight is twenty/twenty. And at the time, they didn't know how that model would be used, and to them it felt existential if somebody came and said, “You weren't responsible. It-- This wrote a bug.” The liability associated with that is massive. So how do you prevent against that? Well, day in, day out, you say safety. And when you start deviating from that, you have the team hold you accountable, you have the world hold you accountable, and I think that becomes a moat over time. At some point, that moat will get challenged and so on, and then it become fragile. I hope it endures because that's the beauty of having founders run the show, ‘cause they can make really hard trade-offs to do mission alignment. The hardest part is in the earliest days when you don't have a group of people who are going through difficulty, stress, crisis together, then your culture doesn't get defined sharply enough, and that's what I'm worried about right now, is there's so much money going to these labs. There's no hardship. There's no-Swyx [00:52:50]: To anyone who knowsAnjney [00:52:51]: There's no to anyone who knows. And that, in hindsight, was a feature, not a bug for Anthropic. The number of people who said no, the number of people who said, “Sorry, we're all doing investors in OpenAI,” that is competitive difference. It forces you to really understand, what is the hill you want to die on at the expense of everything else. What's the P zero? And there, P zero from day one was coding. The reason, the mechanism system there was if we crack coding, Then we will crack AGI. Our mission is AGI. We want to get there safely. If we focus on codin

Les filles surprennent Guillaume pour la fête des pères, on en apprend davantage sur les sushis, Marida nous dévoile le top 10 des sons les plus énervants, on se parle en toute bienveillance de la pression qu’on met à nos enfants dans le sport et on s'offre un petit jeudi sexu.

A Evian-les-Bains, le défi du G7 était de trouver des consensus dans le contexte économique et géopolitique actuel, avec un Donald Trump imprévisible. Dans « La Story », le podcast d'actualité des « Echos », Pierrick Fay fait le bilan de ce sommet avec les envoyés spéciaux du journal à Evian.« La Story » est un podcast des « Echos » présenté par Pierrick Fay. Cet épisode a été enregistré en juin 2026. Rédaction en chef : Clémence Lemaistre. Invités : Richard Hiault et Guillaume de Calignon (journalistes au service international des « Echos »). Réalisation : Willy Ganne. Chargée de production et d'édition : Clara Grouzis. Musique : Théo Boulenger. Identité graphique : Upian. Photo : Ludovic Marin/Reuters. Sons : BFMTV, Elysée, extrait de « La folie des grandeurs », France 24, LCI, Emmanuel Macron.Retrouvez l'essentiel de l'actualité économique grâce à notre offre d'abonnement Access : abonnement.lesechos.fr Hébergé par Acast. Visitez acast.com/privacy pour plus d'informations.

Monastère Notre Dame de la Sainte Espérance avec Frère Guillaume

Guest BioSally Guillaume is the founder of Undiscovered Mountains, a specialist adventure travel company based in the Southern French Alps. Originally from the UK, Sally's path has included work as a science teacher, outdoor pursuits instructor, and BBC journalist before her love of mountain life led her to France in 2005.Through Undiscovered Mountains, Sally helps travellers experience a quieter, more authentic side of the Alps through walking, cycling, climbing, canyoning, ski touring, snowshoeing, cross-country skiing, wildlife tracking, and tailor-made mountain adventures. Her work is rooted in responsible tourism, local partnerships, and a deep respect for the landscapes and communities of the Southern French Alps.Sally's commitment to sustainable travel began long before she founded the company, including undergraduate research into tourism's impact in Ladakh. Today, she continues that mission through Undiscovered Mountains France, which was among the first French travel companies to achieve Travelife certification.Show SummaryIn this episode of the Big World Made Small Adventure Travel Podcast, host Jason Elkins speaks with Sally Guillaume, founder of Undiscovered Mountains, about building a life and business around the mountains of the Southern French Alps. Sally shares how her early love of snow, outdoor adventure, and wild landscapes eventually drew her away from city-based work in the UK and into a lesser-known region of France where she could raise her family close to nature.The conversation explores what makes the Southern French Alps different from the more famous Alpine destinations. Sally describes a place shaped by authentic villages, locally run guesthouses, strong French and Italian cultural influences, a stable mountain climate, and a slower style of tourism that extends far beyond the traditional ski season. From ski touring and cross-country skiing to via ferrata, canyoning, hiking, biking, wolf tracking, and local food experiences, Undiscovered Mountains introduces travellers to a more personal and less crowded side of Alpine adventure.Sally also reflects on the challenges of starting a tourism business in a new country without speaking the language, raising a young child while learning French, and slowly finding her way in the adventure travel industry. Her story is one of determination, resilience, and a deep belief that travel can support both visitors and the communities they come to experience. Big World Made Small guest features are invitation-only and selected based on story, experience, and fit with the show. Some guests support the show through paid production features, cross-promotion, referrals, or other partnerships. This helps keep the show free of third-party ads and interruptions while keeping the focus on real, story-driven conversations.Learn more about the Big World Made Small Podcast and join our private community to get episode updates, special access to our guests, and exclusive adventure travel offers on our website.

What makes you trust someone enough to hand them your business? It's rarely a cold pitch or a clever ad. It's a relationship. The feeling that you already know someone, that you've heard them think out loud, that you understand how they see the world. But how do you build that at scale without personally getting on a thousand calls?That's exactly what Guillaume Jouvencel figured out and it led him to launching a podcast agency. In this episode of Embrace the Squiggle, Guillaume shares the non-linear path that brought him here, and why podcasts have become the most powerful trust-building tool for high-ticket service firms that most people are underusing.Guillaume breaks down how he helps companies stop chasing vanity metrics and start showing up in front of their actual ideal clients.If you've ever thought about if a podcast could actually move the needle for your business (or your career), this conversation will change how you think about it.

"D'avoir de meilleures données d'entraînement, plus pertinentes, ça reste le nerf de la guerre, même avec les plus gros modèles." Le D.E.V. de la semaine est Guillaume Laforge, Developer Advocate AI chez Google. Dans cet épisode, Guillaume revient sur l'évolution du RAG, loin d'être enterré malgré l'agrandissement des fenêtres de contexte des LLM. Il partage pourquoi, même avec un million de tokens, les besoins des entreprises dépassent largement les capacités actuelles des modèles. On parle de découpage sémantique, de context engineering et des nouveaux défis liés à la hiérarchisation des données. Enfin, Guillaume détaille comment, face à la multiplication des données et la chasse à la pertinence, la qualité prime sur la quantité. Un tour d'horizon pragmatique et technique du futur des architectures RAG.Chapitrages00:00:53 : Introduction Inspirante00:01:59 : Présentation de Guillaume00:03:44 : Évolution du RAG00:05:13 : Importance du Chunking00:10:26 : Techniques de Tokenisation00:13:09 : Avantages de Notion00:16:18 : Modèles d'Embedding Multilingues00:18:03 : Recommandations de Modèles00:19:47 : Pertinence des Questions00:23:42 : Approche des Questions Générées00:30:18 : Hybridation des Contextes00:32:17 : Émergence du Contexte Engineering00:35:07 : Coûts de l'Inférence00:38:51 : Qualité des Données00:40:40 : Recommandations et Clôture Liens évoqués pendant l'émission Glaforge.dev: Site de Guillaume avec tous ses articles autour du RAG

Sébastien est gérant de stations de lavage auto et exploite trois sites. L'un d'eux, situé à Seclin, a définitivement fermé le 31 mars 2025. Pourtant, malgré cette fermeture, il continue d'être prélevé chaque mois d'environ 220€ par son fournisseur d'électricité. Depuis, Sébastien multiplie les démarches pour faire valoir ses droits, mais son dossier n'avance pas. Aujourd'hui, le préjudice dépasse les 3.100€. Guillaume Fournier, journaliste pour l'émission, revient sur les coulisses de son enquête. Au micro d'Alban Tardy, un membre de l'équipe de "Ça peut vous arriver" revient sur les négociations difficiles et les moments off de ces 2h d'antenne !Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Avec : Jean-Philippe Doux, journaliste et libraire. Yael Mellul, ancienne avocate. Et Frédéric Hermel, journaliste et écrivain. - Accompagnée de Charles Magnien et sa bande, Estelle Denis s'invite à la table des français pour traiter des sujets qui font leur quotidien. Société, conso, actualité, débats, coup de gueule, coups de cœurs… En simultané sur RMC Story.

Mesdames et Messieurs !!!Ladies & GentlemenAnnonce importante : FIFTY STATES IS OUT !!Voici en effet le TOUT DERNIER numéro du podcast Qui tire sa révérence avec un épisode COLLECTOR80 minutes pour les 80 ans de Donald !!HAPPY BIRTHDAY MISTER PRESIDENT !!!!!!Dimanche, vous le savez, Trump a soufflé ses 80 bougiesL'occasion de célébrer son anniv... à notre façon !Préparez-vous pour un ÉPISODE pépite, avec tout le savoir faire de la TEAM FIFTY STATESPour ce GRAND FINAL, vous saurez tout sur la jeunesse de Donald, sur ses mariages, ses divorces, son rapport à l'argent, à l'image, au pouvoir, à la politiqueSortez les pop-cornInstallez-vous confortablement1 h 20 pour l'épisode 120 du podcast, c'était logique non ????Merci à vous pour votre fidélité(120 épisodes, c'est dingue quand même non ????)Ce fut un plaisir d'être dans vos oreilles tous les mardis depuis bientôt 2 ansMERCI MERCIMERCIMERCIMERCIMERCI !!!!!!!!!!!!!!!!!!!!!!!LOVE YA & SEE YA !!!!!!Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Ornella et Guillaume ont prévu de se marier dans les Cévennes en mai 2025. Le couple s'entend avec un traiteur et règle les 10.000€ du devis proposé. Mais le jour J, le service est chaotique. Seule la moitié de l'équipe est présente, les invités doivent faire le service et il manque certains plats prévus au devis. Le dîner se finit avec trois heures de retard et cela gâche l'ambiance. Pour compenser, le traiteur signe une reconnaissance de dette et promet de rembourser 6.000€ avant novembre. Mais pour l'instant, un seul virement de 1.500€ a été effectué. Ayant enquêté sur le dossier, la journaliste Lina Fourneau revient sur cette cérémonie qui a peu à peu viré au fiasco. Au micro d'Alban Tardy, un membre de l'équipe de "Ça peut vous arriver" revient sur les négociations difficiles et les moments off de ces 2h d'antenne ! Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Merci à Manu Payet d'être venu sur Legend. Deux ans après sa première venue sur Legend, Manu Payet est de retour pour présenter son nouveau film, « Deviens Génial », qui sortira le 17 juin 2026. Entre anecdotes hilarantes et réactions aux pires sosies de lui et de Guillaume, préparez-vous à plus de 2 heures de fous rires !Retrouvez les informations concernant notre invité par ici ⬇️Son compte Instagram ➡️ https://www.instagram.com/manupayetSon compte FaceBook ➡️ https://www.facebook.com/p/Manu-PayetSon compte TikTok ➡️ https://www.tiktok.com/@manupayetoffLes infos sur le film « Deviens génial » ➡️ https://www.allocine.fr/film/fichefilm_gen_cfilm=1000023414.html Retrouvez la première émission avec Manu Payet par ici ➡️ https://www.youtube.com/watch?L'émission avec Kad Mérad ➡️ https://youtu.be/IJIuaRarULoL'émission avec Clovis Cornillac ➡️ https://youtu.be/JjqUcmDHZyM

Guillaume Grand - Toi & moi Matmatah - Lambé An Dro Lancelot - Un homme seul Arcadian - Bonjour merci Renan Luce - La lettre Indochine - Les nouveaux soleils Étienne Daho - Bleu comme toi Jérémy Frérot - Frérot Sébastien Tellier & Juliette Armanet - Attraction Niagara - J'ai vu John Mamann - Love Life Dolly - Je n'veux pas rester sage Clara Luciani - Tout pour moi Aliocha Schneider - Ensemble -M- - Mama Sam (Live 2005) Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Avec : Élise Goldfarb, entrepreneure. Jacques Legros, journaliste. Et Pierre Rondeau, économiste. - Accompagnée de Charles Magnien et sa bande, Estelle Denis s'invite à la table des Français pour traiter des sujets qui font leur quotidien. Société, conso, actualité, débats, coup de gueule, coups de cœurs… En simultané sur RMC Story.

The BPO Industry Isn't Dying. But It May Need to Reinvent Itself Faster Than Anyone Expected. Yuma AI CEO Guillaume Luccisano argues that customer experience providers must evolve from labor arbitrage specialists into AI orchestrators and systems integrators—or risk becoming irrelevant. For years, critics of the business process outsourcing industry have predicted its demise. First it was robotic process automation. Then conversational AI. Then Generative AI. Yet the industry survived every previous wave of disruption because technology changed the way work was delivered rather than eliminating the need for the service itself. In episode 420 of the CX Files, Guillaume talks to Mark Hillary about these changes and how BPOs may need to adapt. https://www.linkedin.com/in/guillaumeluccisano/ https://yuma.ai/ -------------- Summary: Mark Hillary and Peter Ryan discuss the impact of AI on the BPO industry, featuring Guillaume Luccisano, CEO of Yuma AI. Luccisano argues that traditional BPO models are outdated, emphasizing AI's potential to automate 100% of customer service within 2-3 years. He highlights Yuma AI's success in deploying AI agents since 2023, achieving automation rates up to 89%. Luccisano predicts a significant shift in the job market due to AI, suggesting BPOs must evolve into systems integrators to survive. He also notes the cost efficiency of AI, with interactions costing under $1 compared to $4-$8 for human agents. ---- The BPO Industry Isn't Dying. But It May Need to Reinvent Itself Faster Than Anyone Expected. Yuma AI CEO Guillaume Luccisano argues that customer experience providers must evolve from labor arbitrage specialists into AI orchestrators and systems integrators—or risk becoming irrelevant. For years, critics of the business process outsourcing industry have predicted its demise. First it was robotic process automation. Then conversational AI. Then Generative AI. Yet the industry survived every previous wave of disruption because technology changed the way work was delivered rather than eliminating the need for the service itself. But according to Guillaume Luccisano, founder and CEO of Yuma AI, this time may be different. Speaking on Episode 420 of the CX Files podcast, Luccisano argued that the traditional BPO model—selling customer service through large pools of human agents—is facing a challenge unlike anything it has encountered before. His view is stark: AI is no longer just helping agents do their jobs better. It is increasingly capable of doing the job itself. And if that trend continues, the industry will need to redefine its purpose. The End of the "Cost Per Interaction" Era Luccisano's company specializes in AI-powered customer service automation for retail and e-commerce brands. He claims some clients are already automating the vast majority of customer interactions. What has changed, he argues, is that AI is no longer limited to answering questions from a knowledge base. Modern AI agents can access customer records, understand context, follow workflows, execute transactions, and complete tasks. In other words, they are moving beyond information retrieval and into operational execution. This matters because the traditional BPO business model has largely been built around charging for human effort—whether measured in agents, hours, seats, or interactions. If AI can handle increasing volumes of customer contacts at a fraction of the cost, then the economics begin to shift dramatically. A contact that once required several dollars of human labor may eventually be resolved for a few cents in computing costs. Even if those figures are debated, the direction of travel is becoming difficult to ignore. The Problem Isn't Technology. It's Incentives. One of Luccisano's most interesting observations is that many outsourcing providers are already talking extensively about AI. The question is whether they are deploying AI to genuinely transform operations or merely adding enough AI to satisfy customer demand while protecting existing revenue streams. That creates an uncomfortable tension. A provider whose business depends on thousands of agents has little incentive to aggressively deploy technology that could reduce the number of agents required. As Luccisano noted, many providers find themselves caught between serving today's business model and preparing for tomorrow's. The challenge is not technical. It is organizational. And perhaps even existential. Why Investors Are Nervous The sharp decline in the share prices of several publicly traded CX providers has fuelled speculation about the sector's future. Luccisano believes investors are not simply reacting to hype. They are attempting to price in a future where customer service becomes significantly more automated, more efficient, and therefore less dependent on large labor-intensive operations. Whether investors have overreacted remains open to debate. But the market is clearly asking a difficult question: What happens to a company built around managing tens of thousands of customer service agents when customers increasingly expect AI-driven efficiency? The answer remains uncertain. But it is a question every provider now has to confront. The Hidden Complexity Most Critics Ignore To his credit, Luccisano does not dismiss the value that BPOs create today. Customer interactions are only one piece of a much larger operational puzzle. Large CX providers manage compliance requirements, regulatory obligations, security controls, multilingual operations, workforce management, governance frameworks, quality assurance, and complex integrations across dozens of markets. Replacing an individual customer service interaction with AI is one thing. Replacing the entire operational framework surrounding customer service is something else entirely. This is where many simplistic predictions about the "death of BPO" fall apart. The institutional knowledge accumulated by major outsourcing firms still has value. The question is whether that value can be repackaged. From Outsourcer to Systems Integrator Perhaps the most important idea from the conversation was Luccisano's belief that the future role of the BPO may look less like a labor provider and more like a systems integrator. Rather than selling headcount, providers could sell expertise. Rather than managing agents, they could manage AI agents. Rather than staffing operations, they could design, orchestrate, govern, optimize, and continuously improve AI-enabled customer experience ecosystems. This is a subtle but profound shift. It moves the provider higher up the value chain. The emphasis shifts from execution to orchestration. From labor to outcomes. From workforce management to intelligent systems management. Ironically, this would bring some BPOs closer to the role that companies like IBM, Accenture, and other major technology integrators evolved into years ago. A Difficult Transition The challenge, of course, is that transformation is easier to describe than to execute. Reinventing a startup is one thing. Reinventing a global organization employing hundreds of thousands of people is another. Many of today's largest CX providers are highly successful businesses with established customer relationships and predictable revenue streams. That success can become a barrier to change. The dilemma is obvious. How aggressively should a company invest in technologies that could cannibalize its own business? History suggests that incumbents often struggle with precisely this problem. The Bigger Question Perhaps the most controversial part of Luccisano's argument extends beyond outsourcing entirely. He believes AI is creating a broader economic transformation that will affect many knowledge-based professions, not just customer service. Software engineering, consulting, administration, legal services, and customer experience are all beginning to feel the effects. If he is right, then the debate is no longer about whether AI will change customer service. The debate is about how quickly institutions can adapt to a world where intelligence itself becomes abundant and inexpensive. The Future May Belong to the Adaptable The most important takeaway from this discussion is not that BPOs are doomed. In fact, Luccisano repeatedly acknowledged that some providers will survive and potentially thrive. But survival may depend on abandoning the assumption that customer service is primarily a labor business. The providers that succeed could be those that become trusted advisors, AI operators, governance experts, and systems integrators. The providers that fail may be those that continue selling people when customers increasingly want outcomes. The outsourcing industry has reinvented itself before. The question now is whether it can do so again—at the speed AI demands.

"C'est important que je comprenne le code qui a été généré." Le D.E.V. de la semaine est Guillaume Lours, Software Engineer chez Docker. Avec lui, on plonge dans les coulisses de Docker Sandbox, cette solution pensée pour sécuriser l'automatisation et l'exécution de code par IA. Guillaume nous explique comment limiter les risques sans sacrifier l'efficacité, et détaille l'architecture technique : micro VM légère, man-in-the-middle pour la gestion des credentials, profils de sécurité personnalisables, le tout pour une expérience fluide. Il partage aussi des astuces d'usage au quotidien pour tester, reviewer ou itérer plus sereinement. Un éclairage concret sur le futur du développement outillé par l'IA.Chapitrages00:00:53 : Docker et Magie Noire00:01:32 : Présentation de Guillaume00:03:15 : Docker et les Générations00:04:50 : Résumé de Docker00:07:12 : Utilisation de Docker pour Tous00:08:51 : Écosystèmes et Docker00:12:43 : Complexité vs Simplicité00:17:20 : Introduction à Docker Compose00:20:23 : Fonctionnement de Docker Compose00:22:43 : Responsabilités de Compose et Engine00:28:19 : Ordonnancement et Réconciliation00:32:45 : Conteneurisation vs Virtualisation00:37:31 : Introduction à Docker Sandbox00:40:04 : Fonctionnement de Docker Sandbox00:45:58 : Usages de Docker Sandbox00:52:28 : Philosophie de Docker sur le Code00:58:44 : Recommandations et Conclusion Liens évoqués pendant l'émission YT Devoxx France Construire une application indépendante de la tech US en 2025 | Eventuallycoding2025, Europe Vs USA : la tech à l'heure des choix | EventuallycodingLe mythe de la neutralité : quand la tech devient politique

Le 16 avril 2013, Anaïs Guillaume, 21 ans, quitte le domicile familial de Blagny, dans les Ardennes, pour passer la soirée avec des amis. Elle ne rentrera jamais chez elle… Inquiets, ses parents découvrent qu'à cette soirée, elle est venue accompagnée de Philippe Gillet, qui est à la fois son employeur et son amant. Interrogé, il affirme avoir passé la nuit avec Anaïs. Mais il ajoute que la jeune fille était déjà partie à son réveil. Alors où est passée la jeune fille ? Accident ? Suicide ? Enlèvement ? Il faudra plus de trois ans d'enquête et d'incroyables rebondissements pour enfin connaitre de la vérité… Une vérité qui brisera à jamais la famille d'Anaïs…L'affaire Anaïs Guillaume, un podcast inédit de Chroniques Criminelles, raconté par Jacques Pradel.Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

"NEW AND EXCITING CLUB HOUSE SET COMING OUT ON NEXT WEDNESDAY JUNE 3rd AT 12PM EST only at ibizastardustradio, track list: Content (RC Dream Deep Remix), Roland Clark, @rolandclarkmusic KEENE, Eli Fola - Gbese (Original Mix), KEENE, Eli Fola, @eli.fola No Tire-Blackk Rip, Shino Blackk Music, @shinoblackk Electric Stew (We Can Get Down) (Terry Hunter Remix feat. Teefa), DJ Scratch, Terry Hunter, Teefo, @djscratch, @djterryhunter, Ozim! ATL Smooth Mix, Musici Scales Blackk Soxx, Shino Blackk Music Form Follow Function, Guillaume & the Coutu Dumonts Mörda By Mörda (Louie Vega Original Version Remix), MÖRDA, Louie Vega, @louievega I Cling (Yoruba Soul Mix), Deetron feat. Ovasoul7, deetronofficial Let It Blow (All Me Mix), Stacy Kidd, Tiffany Jenkins, @djstacykidd A1 - BTTBeat, Joss Moog, @jossmoog Special Kind Of Love (Extended Mix), Arnold Jarvis, Dam Swindle, damswindle"

Un acteur du monde du foot est l'accusé du soir. Il est ensuite défendu avant le verdict du juge.

Phil et Karl reçoivent Guillaume Morin afin de jaser de compétition de montage de mouches. Les différences de concours, les différents niveaux sont des points qui peuvent influencer les attentes des participants. Bonne écoute.

durée : 01:00:07 - par : Nathalie Piolé -

Merci à Daniel Riolo, consultant de RMC Sport et l'After Foot, est venu faire un point sur les histoires secrètes du football français.

LumineuseSexySolaireSensuelleFragileTourmentéeMélancoliqueInsaisissableInoubliableVous aussi, vous pouvez ajouter des adjectifs pour décrire Marilyn Monroe !!Une femme, une légende, une icône qui est née en 1926.C'était il y a 100 ans. Tout pile.Pour l'occasion, il fallait bien un épisode SPECIAL VIP Avec plein d'infos sur : sa jeunesse, ses origines, ses 3 mariages, ses 3 divorces, ses plus grands rôles, ses plus belles scènes, son "POU POU PIDOU", son sourire, son statut de sex-symbol, sa mort étrange et mystérieuse à l'âge de 36 ans.Pour en savoir plus, une seule adresseLe podcast FIFTY STATES !Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Merci à Jérôme d'être venu sur Legend.En 2020, ce commercial s'est fait passé pour un faux gagnant de l'EuroMillions. Il a trompé son village, ses amis et même les médias, jusqu'à prendre la fuite. Il raconte aujourd'hui son histoire pour Legend.

Peut-on sortir du capitalisme sans passer par l'étatisme ? C'est la question centrale que pose Guillaume Etievant dans Autogestion Générale, paru dans la collection Frustration Magazine x Les Liens qui Libèrent.▶ Le Média doit réunir 10 000 donateurs mensuels avant le 30 juillet. Sa survie en dépend.

Guillaume Gomez a longtemps été le chef cuisinier de l'Elysée sous François Hollande. De quoi se permettre de féliciter l'ancien président, et de le taquiner au passage... Retrouvez tous les jours le meilleur des Grosses Têtes en podcast sur RTL.fr et l'application RTL.Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Plaintes, compliments, interrogations... Cette saison encore, les Grosses Têtes répondent aux différentes questions et messages des auditeurs à l'antenne. Retrouvez tous les jours le meilleur des Grosses Têtes en podcast sur RTL.fr et l'application RTL.Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Nouveaux pilotes, un brin déjantés, à bord de la Libre Antenne sur RMC ! Jean-Christophe Drouet et Julien Cazarre prennent le relais. Après les grands matchs, quand la lumière reste allumée pour les vrais passionnés, place à la Libre Antenne : un espace à part, entre passion, humour et dérision, débats enflammés, franc-parler et second degré. Un rendez-vous nocturne à la Cazarre, où l'on parle foot bien sûr, mais aussi mauvaise foi, vannes, imitations et grands moments de radio imprévisibles !

Bienvenue en haute altitude !!Vous aimez la vitesse ? Les records ?Les traversées fantastiques ?Bienvenue à bord ! Voici l'histoire d'une femme qui n'avait peur de rienUne casse-cou qui fut la première femme à traverser l'Atlantique en soloQui fut reçue et décorée à la Maison BlancheVous avez son nom ??AMELIA EARHART !Probablement l'une des plus grandes célébrités de son époqueElle fait la UNE des magazinesEt enchaîne les exploitsEn 1937, elle disparaît dans le Pacifique alors qu'elle tente une nouvelle dinguerie : le tour du monde Personne n'a jamais retrouvé le corpsPersonne n'a jamais retrouvé l'appareilPour en savoir plus sur cette femme et sur ce mystère Une seule adresse : le podcast FIFTY STATES !Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

En 1066, à Hastings, sur la côte anglaise, c'est tout un royaume qui bascule en quelques heures. Cette bataille fait entrer l'Angleterre dans une nouvelle ère, celle de Guillaume de Normandie qui s'empare du trône et devient Guillaume le Conquérant. Revivez cette bataille mythique racontée sur la célèbre tapisserie de Bayeux, souvent considérée comme la première BD de l'histoire. Crédits : Lorànt Deutsch, Bruno Calvès.Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

La grande victoire de Guillaume le Conquérant, l'icône de la révolution grecque, la véritable histoire du "Rocher"... Découvrez le programme de la semaine du 1er au 5 juin 2026. Chaque dimanche dans un podcast inédit, au micro de Chloé Lacrampe, Lorànt Deutsch présente le programme à venir dans "Entrez dans l'Histoire". Retrouvez l'émission du lundi au vendredi, de 15h à 15h30 sur RTL. Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Host Matt Fisher talks to Guillaume de Zwirek, CEO and Co-Founder of Artera, about evolution of technology in recent years; stages of agentic AI utilization; consideratins for effective deployment of AI tools and how to develop comfort and skills for use of AI tools. To stream our Station live 24/7 visit www.HealthcareNOWRadio.com or ask your Smart Device to “….Play Healthcare NOW Radio”. Find all of our network podcasts on your favorite podcast platforms and be sure to subscribe and like us. Learn more at www.healthcarenowradio.com/listen

Merci à Yoan Drahy d'être venu sur Legend.Co-fondateur de Limova.ai, il nous raconte comment des agents IA peuvent désormais travailler aux côtés des utilisateurs et prendre en charge de nombreuses tâches du quotidien, de la comptabilité au marketing, en passant par les réseaux sociaux ou encore le standard téléphonique multilingue.Merci également à Cris, en couple avec une IA, d'être venue partager son histoire.Et merci à Marie-Christine qui a sauvé sa mère grâce à ChatGPT alors que les médecins ne trouvaient aucune solution…Pour découvrir Limova ➡️ https://link.influxcrew.com/limova-legend3 Avec le code LEGEND10 : 10% de réduction sur l'abonnement mensuelAvec le code LEGEND25 : 25% de réduction sur l'abonnement annuelAvec le code LEGEND50 : 50% de réduction sur l'abonnement pluriannuel (valable sur l'offre Business +, contacter l'équipe commercialePour investir dans Limova ➡️ https://link.influxcrew.com/investir-limova Collaboration commercialeL'investissement comporte des risques, notamment de perte en capital et d'illiquidité. Les performances passées ne préjugent pas des performances futures.Collaboration commerciale - Pour découvrir la solution de facturation électronique et tout savoir sur cette réforme importante, rendez vous sur mabanquepro.bnpparibas, voir détail des conditions et tarifs sur mabanquepro.bnpparibasRetrouvez toutes les informations concernant notre invité par ici ⬇️Leur compte Instagram : https://www.instagram.com/limova.ai/ Leur compte Facebook : https://www.facebook.com/profile.php?id=61566877540393 Leur compte LinkedIn : https://www.linkedin.com/company/limova/ Guillaume porte une surchemise noire Lacoste : https://www.lacoste.com/fr/et un pantalon et des chaussures Gant : https://www.gant.fr/Retrouvez l'émission avec Korben (robot humanoide) ici ➡️ https://www.youtube.com/watch?v=sFgm6y4uqSQ Pour prendre vos billets pour le LEGEND TOUR c'est par ici ➡️ https://www.legend-tour.fr/ Retrouvez la boutique LEGEND ➡️ https://shop.legend-group.fr/

Saints du jour 2026-05-28 Saint Germain de Paris et Saint Guillaume de Gellone by Radio Maria France

On joue ensemble au "Jeu Des 3 As" pour tenter de gagner 2 Nintendo Switch 2.

Interview with Rob Allen from Threatlocker This week, Rob Allen from Threatlocker is with us to discuss the importance of EDR and MDR visibility. We discuss some real world attacks and anecdotes where EDR was able to save the day when threats were missed by other controls. Topic: Do the basics, they said. Easier said than done. Guillaume and Adrian discuss the futility of attempting to do all the foundational work standards, best practices, and regulations expect of organizations. Adrian has given up. Fortunately, Guillaume has some excellent advice and hope to share on this front. The weekly enterprise news Finally, in the enterprise security news, a really interesting vibe check funding acquisitions the verizon DBIR we give a tutorial on how to leak AWS keys on github OH NEVERMIND, SOMEONE AT CISA ALREADY MADE THE TUTORIAL agents versus agents exploitbench the vulnpocalypse robot dogs are SO EASY to take out, we don't need to be too scared of them yet All that and more, on this episode of Enterprise Security Weekly. Visit https://www.securityweekly.com/esw for all the latest episodes! Show Notes: https://securityweekly.com/esw-460

Interview with Rob Allen from Threatlocker This week, Rob Allen from Threatlocker is with us to discuss the importance of EDR and MDR visibility. We discuss some real world attacks and anecdotes where EDR was able to save the day when threats were missed by other controls. Topic: Do the basics, they said. Easier said than done. Guillaume and Adrian discuss the futility of attempting to do all the foundational work standards, best practices, and regulations expect of organizations. Adrian has given up. Fortunately, Guillaume has some excellent advice and hope to share on this front. The weekly enterprise news Finally, in the enterprise security news, a really interesting vibe check funding acquisitions the verizon DBIR we give a tutorial on how to leak AWS keys on github OH NEVERMIND, SOMEONE AT CISA ALREADY MADE THE TUTORIAL agents versus agents exploitbench the vulnpocalypse robot dogs are SO EASY to take out, we don't need to be too scared of them yet All that and more, on this episode of Enterprise Security Weekly. Visit https://www.securityweekly.com/esw for all the latest episodes! Show Notes: https://securityweekly.com/esw-460

Bienvenue dans l'espace !!!Nous partons à 384 000 kilomètres de la TerreDirection : la LUNE !En anglais : the MOON !Pour nous servir de guide, on vous présente Buzz AldrinLe deuxième homme à avoir posé son empreinte de pied (taille 44) sur la surface lunaireUn ancien pilote de la guerre de CoréeUn type brillantUn parcours dingueUne histoire géniale, dans laquelle vous pourrez croiser Buzz l'Eclair, JFK, Georges Pompidou, l'aéroport d'Orly, Sputnik et plein de réacteurs de fuséePour en savoir plus, une seule adresse : Le podcast FIFTY STATESHébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Interview with Rob Allen from Threatlocker This week, Rob Allen from Threatlocker is with us to discuss the importance of EDR and MDR visibility. We discuss some real world attacks and anecdotes where EDR was able to save the day when threats were missed by other controls. Topic: Do the basics, they said. Easier said than done. Guillaume and Adrian discuss the futility of attempting to do all the foundational work standards, best practices, and regulations expect of organizations. Adrian has given up. Fortunately, Guillaume has some excellent advice and hope to share on this front. The weekly enterprise news Finally, in the enterprise security news, a really interesting vibe check funding acquisitions the verizon DBIR we give a tutorial on how to leak AWS keys on github OH NEVERMIND, SOMEONE AT CISA ALREADY MADE THE TUTORIAL agents versus agents exploitbench the vulnpocalypse robot dogs are SO EASY to take out, we don't need to be too scared of them yet All that and more, on this episode of Enterprise Security Weekly. Show Notes: https://securityweekly.com/esw-460

Dans ce nouvel épisode, on raconte l'histoire totalement improbable du basket

What can uncontacted tribes teach us about trust, status, and connection? Psychologist Guillaume Dulude treks into the wild to find out.Full show notes and resources can be found here: jordanharbinger.com/1318What We Discuss with Guillaume Dulude:Guillaume Dulude doesn't use language to build trust with uncontacted tribes — he relies on eye contact, body language, and patience, proving that human connection is fundamentally nonverbal and precedes words.Giving gifts to isolated communities often backfires: it shifts the dynamic from relationship to transaction, conditions tribes to expect objects from outsiders, and corrupts future interactions — even well-intentioned ones.Traditional tribes operate on earned respect rather than self-declared worth. Status requires proof — skills, contributions, demonstrated value — a stark contrast to modern culture's obsession with self-esteem untethered from action.Tribal communities have clear rites of passage that mark transitions between life stages. Modern Western culture largely lacks these — leaving people without meaningful, socially recognized ways to grow from one phase of life to the next.Anyone can learn to build meaningful cross-cultural connection. Guillaume's methods — mirroring, earning trust before asking anything, staying curious — are trainable skills. Approach new people with humility, let them teach you something, and let the relationship lead.And much more...And if you're still game to support us, please leave a review here — even one sentence helps! Sign up for Six-Minute Networking — our free networking and relationship development mini course — at jordanharbinger.com/course!Subscribe to our once-a-week Wee Bit Wiser newsletter today and start filling your Wednesdays with wisdom!Do you even Reddit, bro? Join us at r/JordanHarbinger!This Episode Is Brought To You By Our Fine Sponsors: Lufthansa Allegris: Go to Lufthansa.com and search for "Allegris" to learn moreAura Frames: $35 off: auraframes.com, code JORDANPaka: Paka hoodie & crew socks: go.pakaapparel.com/jordanAT&T: iPhone 17 Pro for $0: att.com/iphone or visit an AT&T store for detailsBetterHelp: 10% off first month: betterhelp.com/jordanSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.