Podcasts about guis

In this episode of the PowerShell Podcast, we sit down with Brock Bingham, a longtime PowerShell enthusiast, educator, and community advocate. Recorded live from PDQ Headquarters in Salt Lake City, Utah, this episode captures the high energy and camaraderie of a PowerShell Wednesday in person. Brock shares his journey from PowerShell beginner to mentor, his passion for community building, and the power of sharing knowledge with others. Key topics in this episode include: Overcoming Stage Fright and Imposter Syndrome – How PowerShell Wednesday and live presentations have helped Brock gain confidence. The Power of Documentation and Knowledge Sharing – Why good documentation and teaching others are critical for long-term growth. Community Connection and Growth – How engaging with the PowerShell community can transform your career and personal development. Exploring PowerShell Tools and Projects – From using Pester for testing to building cool GUIs with MDGRS, Brock dives into the creative side of PowerShell. Learning from Failure and Embracing Red Text – Why mistakes are a critical part of the learning journey. Finding Your Voice in the PowerShell World – Brock's advice for building confidence, sharing your work, and making an impact. From caffeine-fueled coding sessions to discovering the power of collaboration, this episode is a heartfelt conversation about growth, mentorship, and building a career around PowerShell. Join the conversation: Connect with Brock Bingham on LinkedIn: https://www.linkedin.com/in/jonathanbrockbingham/ Connect with Brock on BlueSky: https://bsky.app/profile/brockbingham.bsky.social Connect with Andrew: https://andrewpla.tech/links Join PowerShell Wednesdays every Wednesday at 2 PM EST on discord.gg/pdq The PowerShell Podcast: https://pdq.com/the-powershell-podcast The PowerShell Podcast on YouTube: The PowerShell Podcast: https://pdq.com/the-powershell-podcast 

Depuis les débuts de l'agriculture et de l'élevage, il y a 11.000 ans, depuis ce passage des chasseurs-cueilleurs aux agro-pasteurs, l'humain a cessé de vivre AVEC ou dans le Vivant, la Nature, mais CONTRE.Conscient des ravages perpétrés contre la biodiversité, de la 6e extinction de masse, inédite par sa vitesse et son accélération, certains Homo sapiens essaient de cultiver autrement, durablement. C'est la permaculture et l'agroforesterie par exemple. Dans ces façons de nous nourrir et de cultiver respectueuses du Vivant, les pesticides et la chimie destructrice, y compris pour nous, sont remplacés par des AUXILIAIRES de culture. Des êtres vivants qui nous aident à réguler les ravageurs de cultures.AVEC plutôt que CONTRE. ENTRAIDE plutôt que COMPÉTITION.Certains de ces auxiliaires, comme la célèbre Coccinelle, sont des prédateurs et des régulateurs d'autres êtres vivants. D'autres sont des pollinisateurs. Et pas seulement les Papillons et les Abeilles, mais beaucoup d'autres, comme des Mouches, des Syrphes voire des Oiseaux ou des Chauves-souris nectarivores. Enfin, certains, comme les Vers de terre, aèrent les sols et contribuent à les maintenir vivants et productifs.Notre invité est Hugues Mouret, un des fondateurs et dirigeants de l'association Arthropologia, une copine de notre propre asso Baleine sous Gravillon. _______

Marc Lelièvre, remorqueur depuis 30 ans, dénonce les contrats d’exclusivité accordés par la Ville de Montréal à certaines compagnies. Résultat : les automobilistes n'ont plus toujours le droit de faire affaire avec leur remorqueur privé en cas de panne. Une décision qui chamboule l’industrie et soulève la grogne des indépendants. Entrevue avec Marc Lelièvre, remorqueur pour la compagnie Top Speed. Regardez aussi cette discussion en vidéo via https://www.qub.ca/videos ou en vous abonnant à QUB télé : https://www.tvaplus.ca/qub.Pour de l'information concernant l'utilisation de vos données personnelles - https://omnystudio.com/policies/listener/fr

Ecoutez L'angle éco de François Lenglet du 29 avril 2025.Distribué par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Ecoutez L'angle éco de François Lenglet du 29 avril 2025.Distribué par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Depuis quelques jours, c'est l'effervescence politique autour d'une invention qui n'a rien d'innocent : la taxe sur les plus-values. Traduction pour les non initiés : si vos actions, vos cryptomonnaies, vos assurances ou vos obligations prennent de la valeur, et que vous les vendez, l'Etat peut, ou veut même, prélever 10% sur la plus-value. Mais dans le grand laboratoire belge, rien n'est jamais simple. Yanis Albane, le ministre des Finances N-VA, a dégainé une idée digne d'une recette de grand-mère : celui qui garde ses actions pendant dix ans sera exonéré. Le message est clair : sois patient, petit épargnant, et nous ne te mangerons pas tout cru. Mais cette carotte fiscale fait hurler Vooruit, les socialistes flamands. Pour eux, pas de pitié pour les riches. Ils avaient signé pour une taxe sur les plus-values sans exception, sans passe-droit. Pour eux, autoriser une exonération après dix ans, c'est dérouler le tapis rouge à celles et ceux qui ont les reins assez solides pour immobiliser de l'argent aussi longtemps. En coulisse la menace est réelle. Si Vooruit claque la porte, le gouvernement risque de tomber. Et si la N-VA plie, elle perd son électorat entrepreneur. Bref, pour sauver la coalition actuelle Arizona, il faudra taxer, mais avec des gants de soie. Et pendant que les politiques rejouent leur éternel ballet, des promesses trahies et des compromis boiteux, nous, petits épargnants, nous avançons sur un fil tendu au-dessus du vide en espérant que d'ici dix ans, personne n'ait changé encore une fois les règles du jeu. Car, ici en Belgique, l'épargne n'est plus une vertu, c'est un sport de combat. Et visiblement, la patience est devenue aussi une niche fiscale. Mots clés : Belgique, portefeuille, patients, impatients, contribuables modèles, profiteurs, taxe, plus-values, actions, cryptomonnaies, assurances, obligations, valeur, vendre, Etat, prélèvement, prélever, pourcentage, ministre des Finances N-VA, Yanis Albane, finance, financier, financière, décennie, dix ans, épargne, épargnant, épargner, fiscalité, recette, fiscale, socialistes flamands, riches, exception, passe-droit, exonération, exonérer, argent, millionnaires, entrepreneurs, fortune, vooruit, classe moyenne, présidente, Valérie Van Pelt, investisseur, investir, investissement, déficit, budget, retraité, retraite, fonds, dividende, entreprise, rendement, fortunes liquides, marché, compromis gouvernemental, million, euros, société, taxe progressive, donations familiales, start-ups, fonds de pension, menace, gouvernement, chute, électorat, coalition, arizona, politiques, taxer, niche fiscale, fiscalité, coalition fédérale, déclaration, impôts, revenus, actionnaires, imposition, vente, réforme, revenus professionnels, personnes physiques, taux progressif, tranches, revenu imposable, montant, contribuable, revenus, capital --- La chronique économique d'Amid Faljaoui, tous les jours à 8h30 et à 17h30. Merci pour votre écoute Pour écouter Classic 21 à tout moment i: https://www.rtbf.be/radio/liveradio/classic21 ou sur l'app Radioplayer Belgique Retrouvez tous les épisodes de La chronique économique sur notre plateforme Auvio.be :https://auvio.rtbf.be/emission/802 Et si vous avez apprécié ce podcast, n'hésitez pas à nous donner des étoiles ou des commentaires, cela nous aide à le faire connaître plus largement. Découvrez nos autres podcasts : Le journal du Rock : https://audmns.com/VCRYfsPComic Street (BD) https://audmns.com/oIcpwibLa chronique économique : https://audmns.com/NXWNCrAHey Teacher : https://audmns.com/CIeSInQHistoires sombres du rock : https://audmns.com/ebcGgvkCollection 21 : https://audmns.com/AUdgDqHMystères et Rock'n Roll : https://audmns.com/pCrZihuLa mauvaise oreille de Freddy Tougaux : https://audmns.com/PlXQOEJRock&Sciences : https://audmns.com/lQLdKWRCook as You Are: https://audmns.com/MrmqALPNobody Knows : https://audmns.com/pnuJUlDPlein Ecran : https://audmns.com/gEmXiKzRadio Caroline : https://audmns.com/WccemSkAinsi que nos séries :Rock Icons : https://audmns.com/pcmKXZHRock'n Roll Heroes: https://audmns.com/bXtHJucFever (Erotique) : https://audmns.com/MEWEOLpEt découvrez nos animateurs dans cette série Close to You : https://audmns.com/QfFankxDistribué par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Tous les jours dans la matinale d'Europe 1, Olivier de Lagarde scrute et analyse la presse du jour. Aujourd'hui, La France championne d'Europe de la dette, la chasse aux économies, le retour déguisé de la texe d'habitation, la spiritualité française. Distribué par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Tous les jours dans la matinale d'Europe 1, Olivier de Lagarde scrute et analyse la presse du jour. Aujourd'hui, La France championne d'Europe de la dette, la chasse aux économies, le retour déguisé de la texe d'habitation, la spiritualité française. Distribué par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Amid Faljaoui nous dévoile les coulisses des entreprises et passe en revue les grands événements de l'actualité économique. Merci pour votre écoute Vous pouvez nous écouter à tout moment sur www.rtbf.be/musiq3 Retrouvez tous les contenus de la RTBF sur notre plateforme Auvio.be : Et si vous avez apprécié ce podcast, n'hésitez pas à nous donner des étoiles ou des commentaires, cela nous aide à le faire connaître plus largement. Distribué par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Display Beautiful GUIs. Riverdi, a TouchGFX Expert, is celebrating the availability of the STM32C071 with the release of a new Nucleo-64 display kit which keeps BOM costs low.

Security, GUIs, and cloud connectivity. Digi jumped on the STM32MP25 bandwagon with its newly released Digi ConnectCore MP2, its first system-on-module (SoM) based on our new series of microprocessors.

Le niqab dans l’isoloir: incohérences d’une laïcité à la canadienne. On n’applique même pas cette vision dans les pays musulmans! Entrevue avec Romain Gagnon, ingénieur, essayiste et auteur du livre “La biologie de l’amour”. Regardez aussi cette discussion en vidéo via https://www.qub.ca/videos ou en vous abonnant à QUB télé : https://www.tvaplus.ca/qub Pour de l'information concernant l'utilisation de vos données personnelles - https://omnystudio.com/policies/listener/fr

Trop souvent, les gens se livrent à l'inquiétude sans réaliser à quel point celle-ci est mortelle. Lorsque vous creusez, vous découvrez que l'inquiétude est un péché. Elle ne provient certainement pas de la foi et Romains 14.23 déclare que " tout ce qui ne résulte pas de la foi est péché. " La plupart du temps, l'inquiétude prend racine dans un péché spécifique : l'égoïsme. Ce sont en général nos désirs charnels encore insatisfaits qui font l'objet de nos préoccupations. Plus vous avez de sujets d'inquiétude, plus vous avez de quoi vous inquiéter et plus votre vie est compliquée. Dieu veut que nous nous concentrions simplement sur le fait de le servir. Sa volonté est que nous vivions nos vies en étant libres de toute anxiété et de tout stress. Il veut également que nous soyons libres de le servir sans " nous inquiéter des choses du monde " (1 Corinthiens 7.34). Nous ne devons pas permettre aux inquiétudes de ce monde de détourner notre attention de son but pour notre vie. Cherchez à vous débarrasser de vos désirs charnels. Cela gardera votre vie dans la simplicité et vous libérera de vos préoccupations. Vous pourrez ainsi poursuivre de tout votre cœur les grands plans de Dieu pour votre vie.

Ce matin sur Skyrock, Difool et Rémi nous font une compil' de voleurs déguisés qui ont fait la une de l'actu !

Une journée noire a commencé lundi 7 avril sur les marchés boursiers mondiaux. En Asie, les Bourses ont dévissé ; Taïwan a fermé à presque -10% et Hong Kong à -13%. Le choc est moins dur en Europe, mais la tendance pas plus optimiste : -5% à Francfort et Paris. Les marchés sont paniqués à cause de l'offensive douanière lancée par Donald Trump et les représailles chinoises qui font craindre davantage une escalade destructrice pour l'économie mondiale. Les cours du pétrole s'enfoncent quant à eux de 3%, à des niveaux plus vus depuis quatre ans. Quelles conséquences les Américains vont-ils tirer des bénéfices de cette nouvelle donne ? L'analyse d'Alexandre Baradez, responsable analyse des marchés pour la société IG France.

What are the current Python graphical user interface libraries? Should you build everything in the terminal and create a text-based user interface instead? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder's Weekly articles and projects.

C'est un retour en fanfare pour Elton John, qui publie un nouvel album. Le chanteur a toujours arboré un look excentrique Mention légales : Vos données de connexion, dont votre adresse IP, sont traités par Radio Classique, responsable de traitement, sur la base de son intérêt légitime, par l'intermédiaire de son sous-traitant Ausha, à des fins de réalisation de statistiques agréées et de lutte contre la fraude. Ces données sont supprimées en temps réel pour la finalité statistique et sous cinq mois à compter de la collecte à des fins de lutte contre la fraude. Pour plus d'informations sur les traitements réalisés par Radio Classique et exercer vos droits, consultez notre Politique de confidentialité.Hébergé par Ausha. Visitez ausha.co/politique-de-confidentialite pour plus d'informations.

Tous les matins, 8h50 sur Chérie FM, Alex et Tiffany l'équipe du Réveil Chérie vont chacun vous donner une info ! Une seule est vraie ! L'autre est complètement fausse !" A vous de trouver qui dit vrai !

Tous les matins, 8h50 sur Chérie FM, Alex et Tiffany l'équipe du Réveil Chérie vont chacun vous donner une info ! Une seule est vraie ! L'autre est complètement fausse !" A vous de trouver qui dit vrai !

Karina vous dévoile les décisions de justice les plus improbables. Distribué par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Salut c'est Ibby,Dans cet épisode, on parle de ces moments où tout semble s'effondrer. Ces instants où la vie nous arrache quelque chose, où l'on croit avoir tout perdu… alors qu'en réalité, elle nous prépare à mieux.Je partage avec toi des réflexions sur ce que j'appelle le bien déguisé en mal. Ces situations douloureuses qui, avec du recul, se révèlent être des bénédictions. Ce n'est pas toujours facile à voir sur le moment, mais parfois, les détours les plus sombres mènent aux endroits les plus lumineux.Tu n'es pas seul(e), et tu n'es pas en train d'échouer. Tu es en train d'apprendre, de grandir, de te rediriger. Alors prends un moment pour respirer, te recentrer, et accueillir ce que la vie t'envoie… même si pour l'instant, tu ne comprends pas encore pourquoi.Souviens-toi : ce que tu vis maintenant est peut-être exactement ce dont tu avais besoin pour te révéler.N'hésite pas à lâcher un 5 ⭐️⭐️⭐️⭐️⭐️ et un petit commentaire

Pickup ou SUV déguisé ? Le vrai visage du Honda RidgelineEssai hivernal : Honda Ridgeline Trailsport 2025 TORQ PODCAST - Épisode 358Honda Ridgeline : Un pick-up unique en son genre ? Jul Torq analyse les caractéristiques du Ridgeline et vous dit s'il s'agit d'un vrai pick-up ou d'un SUV déguisé.YOUTUBE Membres VIP :https://www.youtube.com/channel/UCbha0iHrKImRyDXbDNO-EJw/joinSpotify Membres VIP :https://podcasters.spotify.com/pod/show/torqpodcast/subscribeTORQ MEDIASite Web : https://torqmedia.ca FAST WHEELS https://fastco.ca/Fast-Wheels/HomeONEBONE Site Web : https://onebonebrand.com/jultorqCode : JULTORQ ( - 15% Rabais )Suivez-Nous sur Instagram :@JulTorq : https://www.instagram.com/jultorq/@EveTorq : https://www.instagram.com/evetorq/#HondaRidgeline #PickUp #TorqPodcast

Le romancier, scénariste et réalisateur français David Foenkinos est notre invité pour son nouveau roman "Tout le monde aime Clara" (Gallimard). Clara voit au-delà des apparences. Ceux qui la connaissent la redoutent autant qu'ils l'admirent. Car elle ne prédit pas seulement l'avenir, elle l'éveille. Merci pour votre écoute Entrez sans Frapper c'est également en direct tous les jours de la semaine de 16h à 17h30 sur www.rtbf.be/lapremiere Retrouvez l'ensemble des épisodes et les émission en version intégrale (avec la musique donc) de Entrez sans Frapper sur notre plateforme Auvio.be : https://auvio.rtbf.be/emission/8521 Abonnez-vous également à la partie "Bagarre dans la discothèque" en suivant ce lien: https://audmns.com/HSfAmLDEt si vous avez apprécié ce podcast, n'hésitez pas à nous donner des étoiles ou des commentaires, cela nous aide à le faire connaître plus largement. Vous pourriez également apprécier ces autres podcasts issus de notre large catalogue: Le voyage du Stradivarius Feuermann : https://audmns.com/rxPHqEENoir Jaune Rouge - Belgian Crime Story : https://feeds.audiomeans.fr/feed/6e3f3e0e-6d9e-4da7-99d5-f8c0833912c5.xmlLes Petits Papiers : https://audmns.com/tHQpfAm Des rencontres inspirantes avec des artistes de tous horizons. Galaxie BD: https://audmns.com/nyJXESu Notre podcast hebdomadaire autour du 9ème art.Nom: Van Hamme, Profession: Scénariste : https://audmns.com/ZAoAJZF Notre série à propos du créateur de XII et Thorgal. Franquin par Franquin : https://audmns.com/NjMxxMg Ecoutez la voix du créateur de Gaston (et de tant d'autres...)

In this episode of the PowerShell Podcast, we sit down with Steven Wight, known online as PowerShell Young Team, to discuss his journey in PowerShell, automation, and the impact of the PowerShell community. Steven shares how PowerShell transformed his workflow, his approach to solving IT problems, and how he went from lurking in the background to actively contributing and engaging with the community. Key topics in this episode include: How PowerShell changed Steven's IT career – From his early days avoiding manual tasks to building automation solutions. The importance of documentation, blogging, and sharing scripts – How keeping track of work helped in job interviews and personal growth. Creating PowerShell tools with flexibility – Designing functions, using pipelines, and building user-friendly GUIs. Community engagement and learning from others – How PowerShell Discord, blogs, and social media have helped shape his expertise. PowerShell profiles, productivity, and efficiency – Leveraging PSReadLine, profiles, and workflow enhancements to get more done. Steven also shares advice for those just starting with PowerShell, emphasizing the value of small wins, continuous learning, and participating in the community to accelerate skill growth.   Bio and Links:   Steven Wight is an active PowerShell community member, blogger, and the mind behind PowerShell Young Team. With a diverse IT background spanning desktop & application support, system administration, development, OS migrations, and equipment refreshes, Steven thrives on problem-solving and automation. His passion for PowerShell, monitoring, and scripting fuels his mission to "automate himself to a quiet life." Follow Stephen on BlueSky at @poshyoungteam.bsky.social Read his blog at https://powershellyoungteam.github.io/ Connect with Steven on LinkedIn: https://www.linkedin.com/in/steven-wight-79aa0525/ Join PowerShell Wednesdays every Wednesday at 2 PM EST in the PDQ Discord (discord.gg/pdq) for live discussions and demos. The PowerShell Podcast on YouTube: https://youtu.be/klsOxHtG3KE The PowerShell Podcast: https://pdq.com/the-powershell-podcast

C'est mardi gras. Une fête attendue chaque année, par les petits, les grands, et l'occasion de se déguiser. Qu'est ce qu'on vit quand on est invité à une soirée déguisée ?

Derrière la devanture trompeuse de certains salons de massage, une réalité bien plus sombre se déguise : La prostitution déguisée. Face à ce fléau, Aurore Bergé fait de sa mission, de fermer ces établissements tout en protégeant les réelles victimes de ces salons, les femmes prostituées.

David Foenkinos nous parle de son 20ème livre “Tout le monde aime Clara” disponible aux éditions GallimardTous les soirs, du lundi au vendredi à 20h sur France 5, Anne-Elisabeth Lemoine et toute son équipe accueillent les personnalités et artistes qui font l'actualité.

Au cœur de la nuit, les auditeurs se livrent en toute liberté aux oreilles attentives et bienveillantes de Valérie Darmon. Pas de jugements ni de tabous, une conversation franche, mais aussi des réponses aux questions que les auditeurs se posent. Un moment d'échange et de partage propice à la confidence pour repartir le cœur plus léger.

"Paroles, Paroles" de Sébastien Ministru : "Bohemian Rhapsody" de Queen. Merci pour votre écoute Entrez sans Frapper c'est également en direct tous les jours de la semaine de 16h à 17h30 sur www.rtbf.be/lapremiere Retrouvez l'ensemble des épisodes et les émission en version intégrale (avec la musique donc) de Entrez sans Frapper sur notre plateforme Auvio.be : https://auvio.rtbf.be/emission/8521 Abonnez-vous également à la partie "Bagarre dans la discothèque" en suivant ce lien: https://audmns.com/HSfAmLDEt si vous avez apprécié ce podcast, n'hésitez pas à nous donner des étoiles ou des commentaires, cela nous aide à le faire connaître plus largement. Vous pourriez également apprécier ces autres podcasts issus de notre large catalogue: Le voyage du Stradivarius Feuermann : https://audmns.com/rxPHqEENoir Jaune Rouge - Belgian Crime Story : https://feeds.audiomeans.fr/feed/6e3f3e0e-6d9e-4da7-99d5-f8c0833912c5.xmlLes Petits Papiers : https://audmns.com/tHQpfAm Des rencontres inspirantes avec des artistes de tous horizons. Galaxie BD: https://audmns.com/nyJXESu Notre podcast hebdomadaire autour du 9ème art.Nom: Van Hamme, Profession: Scénariste : https://audmns.com/ZAoAJZF Notre série à propos du créateur de XII et Thorgal. Franquin par Franquin : https://audmns.com/NjMxxMg Ecoutez la voix du créateur de Gaston (et de tant d'autres...)

Tous les matins à 7H10, on vous donne des bonnes nouvelles.

Redwood is a state-of-the-art graphical interface that defines the look and feel of the new Oracle Cloud Redwood Applications.   In this episode, hosts Lois Houston and Nikita Abraham, along with Senior Principal OCI Instructor Joe Greenwald, take a closer look at the intent behind the design and development aspects of the new Redwood experience. They also explore Redwood page templates and components.   Survey: https://customersurveys.oracle.com/ords/surveys/t/oracle-university-gtm/survey?k=focus-group-2-link-share-5   Developing Redwood Applications with Visual Builder: https://mylearn.oracle.com/ou/learning-path/developing-redwood-applications-with-visual-builder/112791   Oracle University Learning Community: https://education.oracle.com/ou-community   LinkedIn: https://www.linkedin.com/showcase/oracle-university/   X (formerly Twitter): https://twitter.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, and the OU Studio Team for helping us create this episode.   ---------------------------------------------------------   Episode Transcript:   00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started. 00:26 Nikita: Hello and welcome to the Oracle University Podcast! I'm Nikita Abraham, Team Lead: Editorial Services with Oracle University, and with me is Lois Houston, Director of Innovation Programs. Lois: Hi everyone! Thanks for joining us for this Best of 2024 series, where we're playing for you our four most popular episodes of the year.    Nikita: Today's episode is #3 of 4 and is a throwback to another conversation with Joe Greenwald, our Senior Principal OCI Instructor. We asked Joe about Oracle's Redwood design system and how it helps us create stunning, world-class enterprise applications and user experiences.  01:04 Lois: Yeah, Redwood is the basis for all the new Oracle Cloud Applications being re-designed, developed, and delivered. Joe is the best person to ask about all of this because he's been working with our Oracle software development tools since the early 90s and is responsible for OU's Visual Builder Studio and Redwood course content. So, let's dive right in! Joe: Hi Lois. Hi Niki. I am excited to join you on this episode because with the release of 24A Fusion applications, we are encouraging all our customers to adopt the new Redwood design system and components, and take advantage of the world-class look and feel of the new Redwood user experience. Redwood represents a new approach and direction for us at Oracle, and we're excited to have our customers benefit from it. 01:49 Nikita: Joe, you've been working with Oracle user interface development tools and frameworks for a long time. How and why is Redwood different? Joe: I joined Oracle in 1992, and the first Oracle user interface I experienced was Oracle Forms. And that was the character mode. I came from a background of Smalltalk and its amazing, pioneering graphical user interface (GUI) design capabilities. I worked at Apple and I developed my own GUIs for a few years on PCs and Macs. So, Character Mode Forms, what we used to call DMV (Department of Motor Vehicles) screens, was a shock, to say the least. Since then, I've worked with almost every user interface and development platform Oracle has created: Character Mode Forms, GUI Forms, Power Objects, HyperCard on the Macintosh, that was pre-OS X by the way, Sedona, written in native C++ and ActiveX and OLE, which didn't make it to a product but appeared in other things later, ADF Faces, which uses Java to generate HTML pages, and APEX, which uses PL/SQL to generate HTML pages. And I've worked with and wrote training classes for Java Swing, an excellent GUI framework for event-driven desktop and enterprise applications, but it wasn't designed for the web. So, it's with pleasure that I introduce you to the Redwood design system, easily the best effort I've ever seen, from the look and feel of holistic user-goal-centered design philosophy and approach to the cutting-edge WYSIWYG design tools.  03:16 Lois: Joe, is Redwood just another set of styles, colors, and fonts, albeit very nice-looking ones? Joe: The Redwood platform is new for Oracle, and it represents a significant change, not just in the look and feel, colors, fonts, and styles, I mean that too, but it's also a fundamental change in how Oracle is creating, designing, and imagining user interfaces. As you may be aware, all Oracle Cloud Applications are being re-designed, re-engineered, and re-rebuilt from the ground up, with significant changes to both back-end and front-end architectures. The front end is being redesigned, re-developed, and re-created in pure HTML5, CSS3, and JavaScript using Visual Builder Studio and its design-time browser-based Integrated Development Environment. The back end is being re-architected, re-designed, and implemented in a modern microservice architecture for Oracle Cloud using Kubernetes and other modern technologies that improve performance and work better in the cloud than our current legacy architecture. The new Oracle Cloud Applications platform uses Redwood for its design system—its tools, its patterns, its components, and page templates. Redwood is a richer and more productive platform to create solutions while still being cost-effective for Oracle. It encourages a transformation of the fundamental user experience, emphasizing identifying, meeting, and understanding end users' goals and how the applications are used.  04:39 Nikita: Joe, do you think Oracle's user interface has been improved with Redwood? In what ways has the UI changed? Joe: Yes, absolutely. Redwood has changed a lot of things. When I joined Oracle back in the '90s, there was effectively no user interface division or UI team. Everybody just did their own thing. There was no user interface lab—and that was started in the mid-‘90s—and I was asked to give product usability feedback and participate in UI tests and experiments in those labs. I also helped test the products I was teaching at the time. I actually distinctly remember having to take a week to train users on Oracle's Designer CASE tool product just to prep the participants enough to perform usability testing. I can still hear the UI lab manager shaking her head and saying any product that requires a week of training to do usability testing has usability issues! And if you're like me and you've been around Oracle long enough, you know that Oracle's not always been known for its user interfaces and been known to release products that look like they were designed by two or more different companies. All that has changed with Redwood. With Redwood, there's a new internal design group that oversees the design choices of all development teams that develop products. This includes a design system review and an ongoing audit process to ensure that all the products being released, whether Fusion apps or something else, all look and feel similar so it looks like it's designed by a single company with a single thought in mind. Which it is. There's a deeper, consistent commitment in identifying user needs, understanding how the applications are being used, and how they meet those user needs through things like telemetry: gathering metrics from the actual components and the Redwood system itself to see how the applications are being used, what's working well, and what isn't.  This telemetry is available to us here at Oracle, and we use it to fine tune the applications' usability and purpose.  06:29 Lois: That's really interesting, Joe. So, it's a fundamental change in the way we're doing things. What about the GUI components themselves? Are these more sophisticated than simple GUI components like buttons and text fields? Joe: The graphical components themselves are at a much higher level, more comprehensive, and work better together. And in Redwood, everything is a component. And I'm not just talking about things like input text fields and buttons, though it applies to these more fine-grained components as well. Leveraging Oracle's deep experience in building enterprise applications, we've incorporated that knowledge into creating page templates so that the structure and look and feel of the page is fixed based on our internal design standards. The developer has control over certain portions of it, but the overall look and feel of the page is controlled by Oracle. So there is consistency of look and feel within and across applications. These page templates come with predefined functionalities: headers, titles, properties, and variables to manipulate content and settings, slots for other components to hold like search fields, collections, contextual information, badges, and images, as well as primary and secondary actions, and variables for events and event handling through Visual Builder action chains, which handle the various actions and processing of the request on the page. And all these page templates and components are responsive, meaning they respond to the change in the size of the page and the orientation. So, when you move from a desktop to a handheld mobile device or a tablet, they respond appropriately and consistently to deliver a clean, easy-to-use interface and experience. 08:03 Nikita: You mentioned WYSIWYG design tools and their integration with Visual Builder Studio's integrated development environment. How does Redwood work with Visual Builder Studio? Joe: This is easily one of my most favorite aspects about Redwood and the integration with Visual Builder Studio Designer. The components and page templates are responsive at runtime as well as responsive at design time! In over 30 years of working with Oracle software development products, this is the first development system and integrated development environment I've seen Oracle produce where what you see is what you get at design time. Now, with products such as Designer and JDeveloper ADF Faces and even APEX—all those page-generation types of products—you have to generate the page, deploy it, and only then can you view the final page to see whether it meets the needs of your user interface. For example, with Designer, there were literally hundreds of configuration parameters that you could set to control how forms and reports looked when they were generated —down to how many buttons on a row or how many rows to a page, that sort of thing, all done in text mode. Then you'd generate and run the page to see what the result was and then go back and modify things until you got what you wanted. I remember hearing the product managers for Oracle ADF Faces being asked…well, a customer asked, “What happens if I put this component here and this component here? What will the page look like?” and they'd say, “I don't know. Render the page and let's see.” That's just crazy talk. With Redwood and its integration with Visual Builder Studio Designer, what you see on the page at design time is literally what you get. And if I make the page narrower or I even convert it to a mobile display while in the Designer itself, I immediately see what the page looks like in that new mode. Everything just moves accordingly, at design time. For example, when changing to a mobile UI, everything stacks up nicely; the components adjust to the page size and change right there in the design environment. Again, I can't emphasize enough the simple luxury of being able to see exactly what the user is going to see on my page and having the ability to change the resolution, orientation, and screen size, and it changes right there immediately in my design environment. 10:06 Lois: I'm intrigued by the idea of page templates that are managed by Oracle but still leave room for the developer to customize aspects of the look and feel and functionality. How does that work? Joe: Well, the page templates themselves represent the typical pages you would most likely use in an enterprise application. Things like a welcome page, a search page, and edit and create pages, and a couple of different ways to display summary information, including foldout pages, though this is not an exhaustive list of course. Not only do they provide a logical and complete starting point for the layout of the page itself, but they also include built-in functionality. These templates include functionality for buttons, primary and secondary actions, and areas for holding contextual information, badges, avatars, and images. And this is all built right into the page, and all of them use variables to describe the contents for the various parts, so the contents can change programmatically as the variables' contents change, if necessary. 11:04 Do you have an idea for a new course or learning opportunity? We'd love to hear it! Visit the Oracle University Learning Community and share your thoughts with us on the Idea Incubator. Your suggestion could find a place in future development projects. Visit mylearn.oracle.com to get started.  11:24 Nikita: Welcome back! So, Joe, let's say I'm a developer. How do I get started working with Redwood? Joe: One of the easiest ways to do it is to use Visual Builder Studio Designer and create a new visual application. If you're creating a standalone, bespoke custom application, you can choose a Redwood starter template, which will include all the Redwood components and page templates automatically. Or, if you're extending and customizing an Oracle Fusion application, Redwood is already included.  Either way, when you create a new page, you have a choice of different page templates—welcome page templates, edit pages, search pages, etc. —and all you have to do is choose a page that you want and begin configuring it. And actually if you make a mistake, it's easy to switch page templates. All the components, page templates, and so on have documentation right there inside Visual Builder Studio Designer, and we do recommend that you read through the documentation first to get an understanding of what the use case for that template is and how to use it. And some components are more granular, like a collection container which holds a collection of rows of a list or a table and provides capabilities like toolbars and other actions that are already built and defined. You decide what actions you want and then use predefined event listeners that are triggered when an event occurs in the application—like a button being clicked or a row being selected—which kicks off a series of actions to be performed. 12:42 Lois: That sounds easy enough if you know what you're doing. Joe, what are some of the more common pages and what are they used for?  Joe: Redwood page templates can be broken down into categories. There are overview templates like the welcome page template, which has a nice banner, colors, and illustrations that can be used for a welcoming page—like for entering a new application or a new logical section of the application. The dashboard landing page template displays key information values and their charts and graphs, which can come from Oracle Analytics, and automatically switches the display depending on which set of data is selected.  The detail templates include a general overview, which presents read-only information related to a single record or resource. The item overview gives you a small panel to view summary information (for example, information on a customer) and in the main section, you can view details like all the orders for that customer. And you can even navigate through a set of customers, clicking arrows for next-previous navigation. And that's all built in. There's no programming required. The fold-out page template folds out horizontally to show you individual panels with more detail that can be displayed about the subject being retrieved as well as overflow and drill-down areas. And there's a collection detail template that will display a list with additional details about the selected item (for example, an order and its order line items). The smart search page does exactly what it says. It has a search component that you use to filter or search the data coming back from the REST data sources and then display the results in a list or a table. You define the filter yourself and apply it using different kinds of comparators, so you can look for strings that start with certain values or contain values, or numerical values that are equal to or less than, depending on what you're filtering for. And then there are the transactional templates, which are meant to make changes. This includes both the simple create and edit and advanced create and edit templates.  The simple create and edit page template edits a single record or creates a single record. And the advanced page template works well if you're working with master-detail, parent-child type relationships. Let's say you want to view the parent and create children for it or even create a parent and the children at the same time. And there's a Gantt chart page for project management–type tracking and a guided process page for multiple-step processes and there's a data management page template specifically for viewing and editing data collections like Excel spreadsheets. 14:55 Nikita: You mentioned that there's a design system behind all this. How is this used, and how does the customer benefit from it? Joe: Redwood comprises both a design system and a development system. The design system has a series of steps that we follow here at Oracle and can suggest that you, our customers and partners, can follow as well. This includes understanding the problem, articulating the vision for the page and the application (what it should do), identifying the proper Redwood page templates to use, adding detail and refining the design and then using a number of different mechanisms, including PowerPoint or Figma design tools to specify the design for development, and then monitor engagement in the real world. These are the steps that we follow here at Oracle. The Redwood development process starts with learning how to use Redwood components and templates using the documentation and other content from redwood.oracle.com and Visual Builder Studio. Then it's about understanding the design created by the design team, learning more about components and templates for your application, specifically the ones you're going to use, how they work, and how they work together. Then developing your application using Visual Builder Studio Designer, and finally improving and refining your application. Now, right now, as I mentioned, telemetry is available to us here at Oracle so we can get a sense of the feedback on the pages of how components are being used and where time is being spent, and we use that to tune the designs and components being used. That telemetry data may be available to customers in the future. Now, when you go to redwood.oracle.com, you can access the Redwood pattern book that shows you in detail all the different page templates that are available: smart search page, data grid, welcome page, dashboard landing page, and so on, and you can select these and read more about them as well as the actual design specifications that were used to build the pages—defining what they do and what they respond to. They provide a lot of detailed information about the templates and components, how they work and how they're intended to be used. 16:50 Lois: That's a lot of great resources available. But what if I don't have access to Visual Builder Studio Designer? Can I still see how Redwood looks and behaves? Joe: Well, if you go to redwood.oracle.com, you can log in and work with the Redwood reference application, which is a live application working with live data. It was created to show off the various page templates and components, their look and feel and functionality from the Redwood design and development systems. This is an order management application, so you can do things like view filtered pending orders, create new orders, manage orders, and view information about customers and inventory. It uses the different page templates to show you how the application can perform. 17:29 Nikita: I assume there are common aspects to how these page templates are designed, built, and intended to be used. Is that a good way to begin understanding how to work with them? Becoming familiar with their common properties and functionality? Joe: Absolutely! Good point! All pages have titles, and most have primary and secondary actions that can be triggered through a variety of GUI events, like clicking a button or a link or selecting something in a list or a table. The transactional page templates include validation groups that validate whether the data is correct before it is submitted, as well as a message dialog that can pop up if there are unsaved changes and someone tries to leave the page. All the pages can use variables to display information or set properties and can easily display specific contextual information about records that have been retrieved, like adding the Order Number or Customer Name and Number to the page title or section headers. 18:18 Lois: If I were a developer, I'd be really excited to get started! So, let's say I'm a developer. What's the best way to begin learning about Redwood, Joe? Joe: A great place to start learning about the Redwood design and development system is at the redwood.oracle.com page I mentioned. We have many different pages that describe the philosophy and fundamental basis for Redwood, the ideas and intent behind it, and how we're using it here at Oracle. It also has a list of all the different page templates and components you can use and a link to the Redwood reference application where you can sign in and try it yourself. In addition, we at Oracle University offer a course called Design and Develop Redwood Applications, and in there, we have both lecture content as well as hands-on practices where you build a lightweight version of the Redwood reference application using data from the Fusion apps application, as well as the pages that I talked about: the welcome page, detail pages, transactional pages, and the dashboard landing page.  And you'll see how those pages are designed and constructed while building them yourself.  It's very important though to take one of the free Visual Builder Developer courses first: either Build Visual Applications Using Visual Builder Studio and/or Develop Fusion Applications Using Visual Builder Studio before you try to work through the practices in the Redwood course because it uses a lot of Visual Builder Designer technology.  You'll get a lot more out of the Redwood practices if you understand the basics of Visual Builder Studio first. The Build Visual Applications Using Visual Builder Studio course is probably a better place to start unless you know for a fact you will be focusing on extending Oracle Fusion Applications using Visual Builder Studio. Now, a lot of the content is the same between the two courses as they share much of the same technology and architectures. 19:58 Lois: Ok, so Build Visual Applications Using Visual Builder Studio and Develop Fusion Applications Using Visual Builder Studio…all on mylearn.oracle.com and all free for anyone who wants to take them, right? Joe: Yes, exactly. And the free Redwood learning path leads to an Associate certification. While our courses are a great place to start in preparing for your certification exam, they are not, of course, by themselves sufficient to pass and you will want to study and be familiar with the redwood.oracle.com content as well. The learning path is free, but you do have to pay for the certification exam. Nikita: We hope you enjoyed that conversation. A quick reminder about the short survey we've created to gather your insights and suggestions for the podcast. It's really quick. Just click the link in the show notes to complete the survey. Thank you so much for helping us make the show better. Join us next week for another throwback episode. Until then, this is Nikita Abraham... Lois: And Lois Houston, signing off! 20:58 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

//Abstract This panel speaks about the diverse landscape of AI agents, focusing on how they integrate voice interfaces, GUIs, and small language models to enhance user experiences. They'll also examine the roles of these agents in various industries, highlighting their impact on productivity, creativity, and user experience and how these empower developers to build better solutions while addressing challenges like ensuring consistent performance and reliability across different modalities when deploying AI agents in production. //Bio Host: Diego Oppenheimer Co-founder @ Guardrails AI Jazmia Henry Founder and CEO @ Iso AI Rogerio Bonatti Researcher @ Microsoft Julia Kroll Applied Engineer @ Deepgram Joshua Alphonse Director of Developer Relations @ PremAI A Prosus | MLOps Community Production

Assez de vivre l'Halloween dans sa tête! Découvre l'égo déguisé et retrouve ton "sage" ! Quand on marche sur les traces du sage, on dépasse les vérités qu'on avait assimilées et on commence à découvrir celles qui ne s'appréhendent pas par les sens, mais qui peuvent seulement être expérimentés. En fait, la plupart de nos pensées sont des souvenirs déguisés d'expériences qu'on a vécues au cours des premières années de notre vie, avant notre naissance et même lors de vies antérieures. Quand on est petit, on goûte le monde en introduisant tout dans notre bouche et c'est comme ça aussi qu'on s'évade dans nos rêves. Puis, vers l'âge de 7 ans, les pensées apparaissent en force. On trouve notre sens du soi et on apprend à se situer par rapport au monde. J'espère que cet épisode te donnera la goût de découvrir ton égo déguisé et de retrouver ton sage afin de rêver ton monde. De mon coeur au tien, Gaïa Charline

Karina vous dévoile les décisions de justice les plus improbables.

Nikolay and Michael discuss some cool things you can do with psql, the official CLI that ships with Postgres. Here are some links to things they mentioned:psql docs https://www.postgresql.org/docs/current/app-psql.html Our episode on psql vs GUIs https://postgres.fm/episodes/psql-vs-guispostgres_dba https://github.com/NikolayS/postgres_dbaOur episode on massive deletes https://postgres.fm/episodes/massive-deletesPostgres hacking session on watch with limited number of loops https://www.youtube.com/watch?v=vTV8XhWf3mo pspg https://github.com/okbob/pspg Our episode on Postgres gotchas https://postgres.fm/episodes/postgres-gotchascurrent_setting() and set_config() docs https://www.postgresql.org/docs/current/functions-admin.html#FUNCTIONS-ADMIN-SETpsql tips (site by Lætitia Avrot) https://psql-tips.org~~~What did you like or not like? What should we discuss next time? Let us know via a YouTube comment, on social media, or by commenting on our Google doc!~~~Postgres FM is produced by:Michael Christofides, founder of pgMustardNikolay Samokhvalov, founder of Postgres.aiWith special thanks to:Jessie Draws for the elephant artwork 

Zoom, a company that helped change the way people work during the COVID-19 pandemic, is continuing to reimagine the future of work by transforming itself into an AI-first communications and productivity platform. In this episode of NVIDIA's AI Podcast, Zoom CTO Xuedong (XD) Huang shares how the company is reshaping productivity with AI, including through its Zoom AI Companion 2.0, unveiled recently at the Zoomtopia conference. Designed to be a productivity partner, the AI companion is central to Zoom's “federated AI” strategy, which focuses on integrating multiple large language models. Huang also introduces the concept of “AUI,” combining conversational AI and graphical user interfaces (GUIs) to streamline collaboration and supercharge business performance.

Tous les matins juste après le journal de 6h30, un fait divers repéré et raconté par les journalistes du service Police-Justice de RMC.

Kate Middleton a récemment partagé une vidéo illustrant sa guérison du cancer et la joie de sa famille dans un cadre champêtre doré. Bien que l'ambiance semble authentique, la vidéo est en fait une production minutieusement orchestrée par le publicitaire Will Marr. Merci pour votre écoute N'héistez pas à vous abonner également aux podcasts des séquences phares de MAtin Première: L'Invité Politique : https://audmns.com/LNCogwP L'édito politique « Les Coulisses du Pouvoir » : https://audmns.com/vXWPcqx L'humour de Matin Première : https://audmns.com/tbdbwoQ Retrouvez tous les contenus de la RTBF sur notre plateforme Auvio.be Retrouvez également notre offre info ci-dessous : Le Monde en Direct : https://audmns.com/TkxEWME Les Clés : https://audmns.com/DvbCVrH Le Tournant : https://audmns.com/moqIRoC 5 Minutes pour Comprendre : https://audmns.com/dHiHssr Et si vous avez apprécié ce podcast, n'hésitez pas à nous donner des étoiles ou des commentaires, cela nous aide à le faire connaître plus largement.

#278: In today's tech landscape, developers often find themselves caught in the middle of a debate that never seems to age: GUI or CLI? While the tools and interfaces we use may evolve, the core question remains. How do we balance the efficiency and familiarity of graphical user interfaces (GUIs) with the raw power and flexibility of command-line interfaces (CLIs)? In this episode, Darin and Viktor discuss a blog post by Ian Miell titled In Praise of Low Tech DevEx.   In Praise of Low Tech DevEx https://blog.container-solutions.com/in-praise-of-low-tech-devex   YouTube channel: https://youtube.com/devopsparadox   Review the podcast on Apple Podcasts: https://www.devopsparadox.com/review-podcast/   Slack: https://www.devopsparadox.com/slack/   Connect with us at: https://www.devopsparadox.com/contact/

Bob from RetroRGB joins us this week to talk SEGA Mega Drive/Genesis games, our memories of early GUIs and a Game Boy with a CRT screen which is still portable but VERY battery hungry. Once again Ctrl-Alt-Rees steps in to cover for Neil while he is on his break. There are more retro computing news nuggets in Dave's Briefs and the Community Question Of The Week.   Bob asks that you please visit https://www.retrorgb.com/  Rees has lots of good retro stuff over at https://ctrl-alt-rees.com/   This week's show is bought to you by the letters P and A and the number 22. These stand for Pixel Addict issue 22 which is a magazine full of news and stories about our fave older computer and gaming systems. Take a look at  https://www.pixel.addict.media/ 00:00 - Show Opening 04:15 - The Mega Of Mega Drive Story Link: https://www.gamesradar.com/best-sega-genesis-games-all-time/ 23:02 - 1986 Battle Of The GUIs - Will Windows Win, Or Will It Be GEM's Time To Shine? Story Link: https://www.youtube.com/watch?v=Q2PNLsvDxqw How Apple Ruined GEM: https://youtu.be/aAAU5S1irP0?si=2vB9wmjCprVwefOb 36:48 - Dave's Housekeeping - News links found below 47:44 - The World's First Proper Game Boy Story Link: https://www.youtube.com/watch?v=irHI_2WdQXc 53:17 - Community Question of the Week

Rerun is an open source SDK and viewer for visualizing and interacting with multimodal data streams. The SDK lets you send data from anywhere, and the viewer collects the data and aligns it so the user can scroll back and forth in time to interpret it. The tools have been applied in spatial computing, augmented The post Creating GUIs in Rust with Emil Ernerfeldt appeared first on Software Engineering Daily.

Rerun is an open source SDK and viewer for visualizing and interacting with multimodal data streams. The SDK lets you send data from anywhere, and the viewer collects the data and aligns it so the user can scroll back and forth in time to interpret it. The tools have been applied in spatial computing, augmented The post Creating GUIs in Rust with Emil Ernerfeldt appeared first on Software Engineering Daily.

Chaque jour, Olivier Guenec nous fait vivre différemment la quinzaine des Jeux olympiques.

Chaque jour, Olivier Guenec nous fait vivre différemment la quinzaine des Jeux olympiques.

Topics covered in this episode: Marimo: “Future of Notebooks” pytest 8.3.0 & 8.3.1 are out Python Language Summit 2024 bash-dungeon Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org Brian: @brianokken@fosstodon.org Show: @pythonbytes@fosstodon.org Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesdays at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Michael #1: Marimo: “Future of Notebooks” via Matt Wilkie An open-source reactive notebook for Python Run one cell and marimo reacts by automatically running affected cells, eliminating the error-prone chore of managing notebook state. Marimo's reactive UI elements, like dataframe GUIs and plots, make working with data feel refreshingly fast, futuristic, and intuitive. Rapidly experiment with code and models Bind UI elements to Python values Pick-up-and-play design, with depth for power users See the FAQ Brian #2: pytest 8.3.0 & 8.3.1 are out Real excited to get --xfail-tb flag added This detaches xfail tracebacks from -rx/-ra (which was how it was pre-8.0) Keyword matching for marker expressions, that's fun. pytest -v -m "device(serial='123')" --no-fold-skipped allows for explit reporting of names of skipped tests Plus many more improvements, bug fixes, and doc improvements Michael #3: Python Language Summit 2024 Should Python adopt Calendar Versioning?: talk by Hugo van Kemenade Python's security model after the xz-utils backdoor: talk by Pablo Galindo Salgado Native Interface and Limited C API: talks by Petr Viktorin and Victor Stinner Free-threading ecosystems: talk by Daniele Parmeggiani Python on Mobile: talk by Malcolm Smith PyREPL -- New default REPL written in Python: talk by Pablo Galindo Salgado, Łukasz Langa, and Lysandros Nikolaou Should we make pdb better?: talk by Tian Gao Limiting yield in async generators: talk by Zac Hatfield-Dodds Annotations as Transforms: talk by Jason R. Coombs Lightning Talks, featuring talks by Petr Viktorin, David Hewitt, Emily Morehouse, Łukasz Langa, Pablo Galindo Salgado, and Yury Selivanov Brian #4: bash-dungeon “This game is intended to teach new users how to use their shell in a fun and interactive way.” Just clone the repo and start exploring with cd, ls, and cat. First moves cd bash-dungeon ls cd Enter ls cat parchment A fun way to learn some commands you might need and/or might have forgotten about. Extras Brian: Python 3.12.0b4, final beta, is out If hanging out on discuss.python.org, please checkout Community Guidelines And if it's still not clear why we need these, check out Inclusive communications expectations in Python spaces Google Chrome news Michael: PySimpleGUI goes commercial with obfuscated “source open”? Still have seats for Code in a Castle event Reactive Dashboards with Shiny for Python free course Joke: 40 Million in in Series A Funding - may be a lot of reading, but I found it funny Thanks to VM Brasseur for sharing this one. Also a few from pyjokes 0.7.2 (first new version since 2019) If at first you don't succeed, call it version 1.0. A product manager walks into a bar, asks for drink. Bartender says no, but will consider adding later. Triumphantly, Beth removed Python 2.7 from her server in 2030. 'Finally!' she said with glee, only to see the announcement for Python 4.4.1 Although, if CalVer, PEP 2026, happens, that'll just be Python 3.30.0.

Editor's note: One of the top reasons we have hundreds of companies and thousands of AI Engineers joining the World's Fair next week is, apart from discussing technology and being present for the big launches planned, to hire and be hired! Listeners loved our previous Elicit episode and were so glad to welcome 2 more members of Elicit back for a guest post (and bonus podcast) on how they think through hiring. Don't miss their AI engineer job description, and template which you can use to create your own hiring plan! How to Hire AI EngineersJames Brady, Head of Engineering @ Elicit (ex Spring, Square, Trigger.io, IBM)Adam Wiggins, Internal Journalist @ Elicit (Cofounder Ink & Switch and Heroku)If you're leading a team that uses AI in your product in some way, you probably need to hire AI engineers. As defined in this article, that's someone with conventional engineering skills in addition to knowledge of language models and prompt engineering, without being a full-fledged Machine Learning expert.But how do you hire someone with this skillset? At Elicit we've been applying machine learning to reasoning tools since 2018, and our technical team is a mix of ML experts and what we can now call AI engineers. This article will cover our process from job description through interviewing. (You can also flip the perspectives here and use it just as easily for how to get hired as an AI engineer!)My own journeyBefore getting into the brass tacks, I want to share my journey to becoming an AI engineer.Up until a few years ago, I was happily working my job as an engineering manager of a big team at a late-stage startup. Like many, I was tracking the rapid increase in AI capabilities stemming from the deep learning revolution, but it was the release of GPT-3 in 2020 which was the watershed moment. At the time, we were all blown away by how the model could string together coherent sentences on demand. (Oh how far we've come since then!)I'd been a professional software engineer for nearly 15 years—enough to have experienced one or two technology cycles—but I could see this was something categorically new. I found this simultaneously exciting and somewhat disconcerting. I knew I wanted to dive into this world, but it seemed like the only path was going back to school for a master's degree in Machine Learning. I started talking with my boss about options for taking a sabbatical or doing a part-time distance learning degree.In 2021, I instead decided to launch a startup focused on productizing new research ideas on ML interpretability. It was through that process that I reached out to Andreas—a leading ML researcher and founder of Elicit—to see if he would be an advisor. Over the next few months, I learned more about Elicit: that they were trying to apply these fascinating technologies to the real-world problems of science, and with a business model that aligned it with safety goals. I realized that I was way more excited about Elicit than I was about my own startup ideas, and wrote about my motivations at the time.Three years later, it's clear this was a seismic shift in my career on the scale of when I chose to leave my comfy engineering job at IBM to go through the Y Combinator program back in 2008. Working with this new breed of technology has been more intellectually stimulating, challenging, and rewarding than I could have imagined.Deep ML expertise not requiredIt's important to note that AI engineers are not ML experts, nor is that their best contribution to a tech team.In our article Living documents as an AI UX pattern, we wrote:It's easy to think that AI advancements are all about training and applying new models, and certainly this is a huge part of our work in the ML team at Elicit. But those of us working in the UX part of the team believe that we have a big contribution to make in how AI is applied to end-user problems.We think of LLMs as a new medium to work with, one that we've barely begun to grasp the contours of. New computing mediums like GUIs in the 1980s, web/cloud in the 90s and 2000s, and multitouch smartphones in the 2000s/2010s opened a whole new era of engineering and design practices. So too will LLMs open new frontiers for our work in the coming decade.To compare to the early era of mobile development: great iOS developers didn't require a detailed understanding of the physics of capacitive touchscreens. But they did need to know the capabilities and limitations of a multi-touch screen, the constrained CPU and storage available, the context in which the user is using it (very different from a webpage or desktop computer), etc.In the same way, an AI engineer needs to work with LLMs as a medium that is fundamentally different from other compute mediums. That means an interest in the ML side of things, whether through their own self-study, tinkering with prompts and model fine-tuning, or following along in #llm-paper-club. But this understanding is so that they can work with the medium effectively versus, say, spending their days training new models.Language models as a chaotic mediumSo if we're not expecting deep ML expertise from AI engineers, what are we expecting? This brings us to what makes LLMs different.We'll assume already that our ideal candidate is already inspired by, and full of ideas about, all the new capabilities AI can bring to software products. But the flip side is all the things that make this new medium difficult to work with. LLM calls are annoying due to high latency (measured in tens of seconds sometimes, rather than milliseconds), extreme variance on latency, high error rates even under normal operation. Not to mention getting extremely different answers to the same prompt provided to the same model on two subsequent calls!The net effect is that an AI engineer, even working at the application development level, needs to have a skillset comparable to distributed systems engineering. Handling errors, retries, asynchronous calls, streaming responses, parallelizing and recombining model calls, the halting problem, and fallbacks are just some of the day-in-the-life of an AI engineer. Chaos engineering gets new life in the era of AI.Skills and qualities in candidatesLet's put together what we don't need (deep ML expertise) with what we do (work with capabilities and limitations of the medium). Thus we start to see what Elicit looks for in AI engineers:* Conventional software engineering skills. Especially back-end engineering on complex, data-intensive applications.* Professional, real-world experience with applications at scale.* Deep, hands-on experience across a few back-end web frameworks.* Light devops and an understanding of infrastructure best practices.* Queues, message buses, event-driven and serverless architectures, … there's no single “correct” approach, but having a deep toolbox to draw from is very important.* A genuine curiosity and enthusiasm for the capabilities of language models.* One or more serious projects (side projects are fine) of using them in interesting ways on a unique domain.* …ideally with some level of factored cognition, e.g. breaking the problem down into chunks, making thoughtful decisions about which things to push to the language model and which stay within the realm of conventional heuristics and compute capabilities.* Personal studying with resources like Elicit's ML reading list. Part of the role is collaborating with the ML engineers and researchers on our team. To do so, the candidate needs to “speak their language” somewhat, just as a mobile engineer needs some familiarity with backends in order to collaborate effectively on API creation with backend engineers.* An understanding of the challenges that come along with working with large models (high latency, variance, etc.) leading to a defensive, fault-first mindset.* Careful and principled handling of error cases, asynchronous code (and ability to reason about and debug it), streaming data, caching, logging and analytics for understanding behavior in production.* This is a similar mindset that one can develop working on conventional apps which are complex, data-intensive, or large-scale apps. The difference is that an AI engineer will need this mindset even when working on relatively small scales!On net, a great AI engineer will combine two seemingly contrasting perspectives: knowledge of, and a sense of wonder for, the capabilities of modern ML models; but also the understanding that this is a difficult and imperfect foundation, and the willingness to build resilient and performant systems on top of it.Here's the resulting AI engineer job description for Elicit. And here's a template that you can borrow from for writing your own JD.Hiring processOnce you know what you're looking for in an AI engineer, the process is not too different from other technical roles. Here's how we do it, broken down into two stages: sourcing and interviewing.SourcingWe're primarily looking for people with (1) a familiarity with and interest in ML, and (2) proven experience building complex systems using web technologies. The former is important for culture fit and as an indication that the candidate will be able to do some light prompt engineering as part of their role. The latter is important because language model APIs are built on top of web standards and—as noted above—aren't always the easiest tools to work with.Only a handful of people have built complex ML-first apps, but fortunately the two qualities listed above are relatively independent. Perhaps they've proven (2) through their professional experience and have some side projects which demonstrate (1).Talking of side projects, evidence of creative and original prototypes is a huge plus as we're evaluating candidates. We've barely scratched the surface of what's possible to build with LLMs—even the current generation of models—so candidates who have been willing to dive into crazy “I wonder if it's possible to…” ideas have a huge advantage.InterviewingThe hard skills we spend most of our time evaluating during our interview process are in the “building complex systems using web technologies” side of things. We will be checking that the candidate is familiar with asynchronous programming, defensive coding, distributed systems concepts and tools, and display an ability to think about scaling and performance. They needn't have 10+ years of experience doing this stuff: even junior candidates can display an aptitude and thirst for learning which gives us confidence they'll be successful tackling the difficult technical challenges we'll put in front of them.One anti-pattern—something which makes my heart sink when I hear it from candidates—is that they have no familiarity with ML, but claim that they're excited to learn about it. The amount of free and easily-accessible resources available is incredible, so a motivated candidate should have already dived into self-study.Putting all that together, here's the interview process that we follow for AI engineer candidates:* 30-minute introductory conversation. Non-technical, explaining the interview process, answering questions, understanding the candidate's career path and goals.* 60-minute technical interview. This is a coding exercise, where we play product manager and the candidate is making changes to a little web app. Here are some examples of topics we might hit upon through that exercise:* Update API endpoints to include extra metadata. Think about appropriate data types. Stub out frontend code to accept the new data.* Convert a synchronous REST API to an asynchronous streaming endpoint.* Cancellation of asynchronous work when a user closes their tab.* Choose an appropriate data structure to represent the pending, active, and completed ML work which is required to service a user request.* 60–90 minute non-technical interview. Walk through the candidate's professional experience, identifying high and low points, getting a grasp of what kinds of challenges and environments they thrive in.* On-site interviews. Half a day in our office in Oakland, meeting as much of the team as possible: more technical and non-technical conversations.The frontier is wide openAlthough Elicit is perhaps further along than other companies on AI engineering, we also acknowledge that this is a brand-new field whose shape and qualities are only just now starting to form. We're looking forward to hearing how other companies do this and being part of the conversation as the role evolves.We're excited for the AI Engineer World's Fair as another next step for this emerging subfield. And of course, check out the Elicit careers page if you're interested in joining our team.Podcast versionTimestamps* [00:00:24] Intros* [00:05:25] Defining the Hiring Process* [00:08:42] Defensive AI Engineering as a chaotic medium* [00:10:26] Tech Choices for Defensive AI Engineering* [00:14:04] How do you Interview for Defensive AI Engineering* [00:19:25] Does Model Shadowing Work?* [00:22:29] Is it too early to standardize Tech stacks?* [00:32:02] Capabilities: Offensive AI Engineering* [00:37:24] AI Engineering Required Knowledge* [00:40:13] ML First Mindset* [00:45:13] AI Engineers and Creativity* [00:47:51] Inside of Me There Are Two Wolves* [00:49:58] Sourcing AI Engineers* [00:58:45] Parting ThoughtsTranscript[00:00:00] swyx: Okay, so welcome to the Latent Space Podcast. This is another remote episode that we're recording. This is the first one that we're doing around a guest post. And I'm very honored to have two of the authors of the post with me, James and Adam from Elicit. Welcome, James. Welcome, Adam.[00:00:22] James Brady: Thank you. Great to be here.[00:00:23] Hey there.[00:00:24] Intros[00:00:24] swyx: Okay, so I think I will do this kind of in order. I think James, you're, you're sort of the primary author. So James, you are head of engineering at Elicit. You also, We're VP Eng at Teespring and Spring as well. And you also , you have a long history in sort of engineering. How did you, , find your way into something like Elicit where, , it's, you, you are basically traditional sort of VP Eng, VP technology type person moving into a more of an AI role.[00:00:53] James Brady: Yeah, that's right. It definitely was something of a Sideways move if not a left turn. So the story there was I'd been doing, as you said, VP technology, CTO type stuff for around about 15 years or so, and Notice that there was this crazy explosion of capability and interesting stuff happening within AI and ML and language models, that kind of thing.[00:01:16] I guess this was in 2019 or so, and decided that I needed to get involved. , this is a kind of generational shift. And Spent maybe a year or so trying to get up to speed on the state of the art, reading papers, reading books, practicing things, that kind of stuff. Was going to found a startup actually in in the space of interpretability and transparency, and through that met Andreas, who has obviously been on the, on the podcast before asked him to be an advisor for my startup, and he countered with, maybe you'd like to come and run the engineering team at Elicit, which it turns out was a much better idea.[00:01:48] And yeah, I kind of quickly changed in that direction. So I think some of the stuff that we're going to be talking about today is how actually a lot of the work when you're building applications with AI and ML looks and smells and feels much more like conventional software engineering with a few key differences rather than really deep ML stuff.[00:02:07] And I think that's one of the reasons why I was able to transfer skills over from one place to the other.[00:02:12] swyx: Yeah, I[00:02:12] James Brady: definitely[00:02:12] swyx: agree with that. I, I do often say that I think AI engineering is about 90 percent software engineering with like the, the 10 percent of like really strong really differentiated AI engineering.[00:02:22] And that might, that obviously that number might change over time. I want to also welcome Adam onto my podcast because you welcomed me onto your podcast two years ago.[00:02:31] Adam Wiggins: Yeah, that was a wonderful episode.[00:02:32] swyx: That was, that was a fun episode. You famously founded Heroku. You just wrapped up a few years working on Muse.[00:02:38] And now you've described yourself as a journalist, internal journalist working on Elicit.[00:02:43] Adam Wiggins: Yeah, well I'm kind of a little bit in a wandering phase here and trying to take this time in between ventures to see what's out there in the world and some of my wandering took me to the Elicit team. And found that they were some of the folks who were doing the most interesting, really deep work in terms of taking the capabilities of language models and applying them to what I feel like are really important problems.[00:03:08] So in this case, science and literature search and, and, and that sort of thing. It fits into my general interest in tools and productivity software. I, I think of it as a tool for thought in many ways, but a tool for science, obviously, if we can accelerate that discovery of new medicines and things like that, that's, that's just so powerful.[00:03:24] But to me, it's a. It's kind of also an opportunity to learn at the feet of some real masters in this space, people who have been working on it since it was, before it was cool, if you want to put it that way. So for me, the last couple of months have been this crash course, and why I sometimes describe myself as an internal journalist is I'm helping to write some, some posts, including Supporting James in this article here we're doing for latent space where I'm just bringing my writing skill and that sort of thing to bear on their very deep domain expertise around language models and applying them to the real world and kind of surface that in a way that's I don't know, accessible, legible, that, that sort of thing.[00:04:03] And so, and the great benefit to me is I get to learn this stuff in a way that I don't think I would, or I haven't, just kind of tinkering with my own side projects.[00:04:12] swyx: I forgot to mention that you also run Ink and Switch, which is one of the leading research labs, in my mind, of the tools for thought productivity space, , whatever people mentioned there, or maybe future of programming even, a little bit of that.[00:04:24] As well. I think you guys definitely started the local first wave. I think there was just the first conference that you guys held. I don't know if you were personally involved.[00:04:31] Adam Wiggins: Yeah, I was one of the co organizers along with a few other folks for, yeah, called Local First Conf here in Berlin.[00:04:36] Huge success from my, my point of view. Local first, obviously, a whole other topic we can talk about on another day. I think there actually is a lot more what would you call it , handshake emoji between kind of language models and the local first data model. And that was part of the topic of the conference here, but yeah, topic for another day.[00:04:55] swyx: Not necessarily. I mean , I, I selected as one of my keynotes, Justine Tunney, working at LlamaFall in Mozilla, because I think there's a lot of people interested in that stuff. But we can, we can focus on the headline topic. And just to not bury the lead, which is we're talking about hire, how to hire AI engineers, this is something that I've been looking for a credible source on for months.[00:05:14] People keep asking me for my opinions. I don't feel qualified to give an opinion and it's not like I have. So that's kind of defined hiring process that I'm super happy with, even though I've worked with a number of AI engineers.[00:05:25] Defining the Hiring Process[00:05:25] swyx: I'll just leave it open to you, James. How was your process of defining your hiring, hiring roles?[00:05:31] James Brady: Yeah. So I think the first thing to say is that we've effectively been hiring for this kind of a role since before you, before you coined the term and tried to kind of build this understanding of what it was.[00:05:42] So, which is not a bad thing. Like it's, it was a, it was a good thing. A concept, a concept that was coming to the fore and effectively needed a name, which is which is what you did. So the reason I mentioned that is I think it was something that we kind of backed into, if you will. We didn't sit down and come up with a brand new role from, from scratch of this is a completely novel set of responsibilities and skills that this person would need.[00:06:06] However, it is a A kind of particular blend of different skills and attitudes and and curiosities interests, which I think makes sense to kind of bundle together. So in the, in the post, the three things that we say are most important for a highly effective AI engineer are first of all, conventional software engineering skills, which is Kind of a given, but definitely worth mentioning.[00:06:30] The second thing is a curiosity and enthusiasm for machine learning and maybe in particular language models. That's certainly true in our case. And then the third thing is to do with basically a fault first mindset, being able to build systems that can handle things going wrong in, in, in some sense.[00:06:49] And yeah, the I think the kind of middle point, the curiosity about ML and language models is probably fairly self evident. They're going to be working with, and prompting, and dealing with the responses from these models, so that's clearly relevant. The last point, though, maybe takes the most explaining.[00:07:07] To do with this fault first mindset and the ability to, to build resilient systems. The reason that is, is so important is because compared to normal APIs, where normal, think of something like a Stripe API or a search API or something like this. The latency when you're working with language models is, is wild, like you can get 10x variation.[00:07:32] I mean, I was looking at the stats before, actually, before, before the podcast. We do often, normally, in fact, see a 10x variation in the P90 latency over the course of, Half an hour, an hour when we're prompting these models, which is way higher than if you're working with a, more kind of conventional conventionally backed API.[00:07:49] And the responses that you get, the actual content and the responses are naturally unpredictable as well. They come back with different formats. Maybe you're expecting JSON. It's not quite JSON. You have to handle this stuff. And also the, the semantics of the messages are unpredictable too, which is, which is a good thing.[00:08:08] Like this is one of the things that you're looking for from these language models, but it all adds up to needing to. Build a resilient, reliable, solid feeling system on top of this fundamentally, well, certainly currently fundamentally shaky foundation. The models do not behave in the way that you would like them to.[00:08:28] And yeah, the ability to structure the code around them such that it does give the user this warm, reassuring, Snappy, solid feeling is is really what we're driving for there.[00:08:42] Defensive AI Engineering as a chaotic medium[00:08:42] Adam Wiggins: What really struck me as we, we dug in on the content for this article was that third point there. The, the language models is this kind of chaotic medium, this, this dragon, this wild horse you're, you're, you're riding and trying to guide in the direction that is going to be useful and reliable to users, because I think.[00:08:58] So much of software engineering is about making things not only high performance and snappy, but really just making it stable, reliable, predictable, which is literally the opposite of what you get from from the language models. And yet, yeah, the output is so useful, and indeed, some of their Creativity, if you want to call it that, which is, is precisely their value.[00:09:19] And so you need to work with this medium. And I guess the nuanced or the thing that came out of Elissa's experience that I thought was so interesting is quite a lot of working with that is things that come from distributed systems engineering. But you have really the AI engineers as we're defining them or, or labeling them on the illicit team is people who are really application developers.[00:09:39] You're building things for end users. You're thinking about, okay, I need to populate this interface with some response to user input. That's useful to the tasks they're trying to do, but you have this. This is the thing, this medium that you're working with that in some ways you need to apply some of this chaos engineering, distributed systems engineering, which typically those people with those engineering skills are not kind of the application level developers with the product mindset or whatever, they're more deep in the guts of a, of a system.[00:10:07] And so it's, those, those skills and, and knowledge do exist throughout the engineering discipline, but sort of putting them together into one person that is That feels like sort of a unique thing and working with the folks on the Elicit team who have that skills I'm quite struck by that unique that unique blend.[00:10:23] I haven't really seen that before in my 30 year career in technology.[00:10:26] Tech Choices for Defensive AI Engineering[00:10:26] swyx: Yeah, that's a Fascinating I like the reference to chaos engineering. I have some appreciation, I think when you had me on your podcast, I was still working at Temporal and that was like a nice Framework, if you live within Temporal's boundaries, you can pretend that all those faults don't exist, and you can, you can code in a sort of very fault tolerant way.[00:10:47] What is, what is you guys solutions around this, actually? Like, I think you're, you're emphasizing having the mindset, but maybe naming some technologies would help? Not saying that you have to adopt these technologies, but they're just, they're just quick vectors into what you're talking about when you're, when you're talking about distributed systems.[00:11:03] Like, that's such a big, chunky word, , like are we talking, are Kubernetes or, and I suspect we're not, , like we're, we're talking something else now.[00:11:10] James Brady: Yeah, that's right. It's more at the application level rather than at the infrastructure level, at least, at least the way that it works for us.[00:11:17] So there's nothing kind of radically novel here. It is more a careful application of existing concepts. So the kinds of tools that we reach for to handle these kind of slightly chaotic objects that Adam was just talking about, are retries and fallbacks and timeouts and careful error handling. And, yeah, the standard stuff, really.[00:11:39] There's also a great degree of dependence. We rely heavily on parallelization because, , these language models are not innately very snappy, and , there's just a lot of I. O. going back and forth. So All these things I'm talking about when I was in my earlier stages of a career, these are kind of the things that are the difficult parts that most senior software engineers will be better at.[00:12:01] It is careful error handling, and concurrency, and fallbacks, and distributed systems, and, , eventual consistency, and all this kind of stuff and As Adam was saying, the kind of person that is deep in the guts of some kind of distributed systems, a really high, high scale backend kind of a problem would probably naturally have these kinds of skills.[00:12:21] But you'll find them on, on day one, if you're building a, , an ML powered app, even if it's not got massive scale. I think one one thing that I would mention that we do do yeah, maybe, maybe two related things, actually. The first is we're big fans of strong typing. We share the types all the way from the Backend Python code all the way to the to the front end in TypeScript and find that is I mean We'd probably do this anyway But it really helps one reason around the shapes of the data which can going to be going back and forth and that's really important When you can't rely upon You you're going to have to coerce the data that you get back from the ML if you want if you want for it to be structured basically speaking and The second thing which is related is we use checked exceptions inside our Python code base, which means that we can use the type system to make sure we are handling, properly handling, all of the, the various things that could be going wrong, all the different exceptions that could be getting raised.[00:13:16] So, checked exceptions are not, not really particularly popular. Actually there's not many people that are big fans of them. For our particular use case, to really make sure that we've not just forgotten to handle, , This particular type of error we have found them useful to to, to force us to think about all the different edge cases that can come up.[00:13:32] swyx: Fascinating. How just a quick note of technology. How do you share types from Python to TypeScript? Do you, do you use GraphQL? Do you use something[00:13:39] James Brady: else? We don't, we don't use GraphQL. Yeah. So we've got the We've got the types defined in Python, that's the source of truth. And we go from the OpenAPI spec, and there's a, there's a tool that you work and use to generate types dynamically, like TypeScript types from those OpenAPI definitions.[00:13:57] swyx: Okay, excellent. Okay, cool. Sorry, sorry for diving into that rabbit hole a little bit. I always like to spell out technologies for people to dig their teeth into.[00:14:04] How do you Interview for Defensive AI Engineering[00:14:04] swyx: One thing I'll, one thing I'll mention quickly is that a lot of the stuff that you mentioned is typically not part of the normal interview loop.[00:14:10] It's actually really hard to interview for because this is the stuff that you polish out in, as you go into production, the coding interviews are typically about the happy path. How do we do that? How do we, how do we design, how do you look for a defensive fault first mindset?[00:14:24] Because you can defensive code all day long and not add functionality. to your to your application.[00:14:29] James Brady: Yeah, it's a great question and I think that's exactly true. Normally the interview is about the happy path and then there's maybe a box checking exercise at the end of the candidate says of course in reality I would handle the edge cases or something like this and that unfortunately isn't isn't quite good enough when when the happy path is is very very narrow and yeah there's lots of weirdness on either side so basically speaking, it's just a case of, of foregrounding those kind of concerns through the interview process.[00:14:58] It's, there's, there's no magic to it. We, we talk about this in the, in the po in the post that we're gonna be putting up on, on Laton space. The, there's two main technical exercises that we do through our interview process for this role. The first is more coding focus, and the second is more system designy.[00:15:16] Yeah. White whiteboarding a potential solution. And in, without giving too much away in the coding exercise. You do need to think about edge cases. You do need to think about errors. The exercise consists of adding features and fixing bugs inside the code base. And in both of those two cases, it does demand, because of the way that we set the application up and the interview up, it does demand that you think about something other than the happy path.[00:15:41] But your thinking is the right prompt of how do we get the candidate thinking outside of the, the kind of normal Sweet spot, smooth smooth, smoothly paved path. In terms of the system design interview, that's a little easier to prompt this kind of fault first mindset because it's very easy in that situation just to say, let's imagine that, , this node dies, how does the app still work?[00:16:03] Let's imagine that this network is, is going super slow. Let's imagine that, I don't know, like you, you run out of, you run out of capacity in, in, in this database that you've sketched out here, how do you handle that, that, that sort of stuff. So. It's, in both cases, they're not firmly anchored to and built specifically around language models and ways language models can go wrong, but we do exercise the same muscles of thinking defensively and yeah, foregrounding the edge cases, basically.[00:16:32] Adam Wiggins: James, earlier there you mentioned retries. And this is something that I think I've seen some interesting debates internally about things regarding, first of all, retries are, can be costly, right? In general, this medium, in addition to having this incredibly high variance and response rate, and, , being non deterministic, is actually quite expensive.[00:16:50] And so, in many cases, doing a retry when you get a fail does make sense, but actually that has an impact on cost. And so there is Some sense to which, at least I've seen the AI engineers on our team, worry about that. They worry about, okay, how do we give the best user experience, but balance that against what the infrastructure is going to, , is going to cost our company, which I think is again, an interesting mix of, yeah, again, it's a little bit the distributed system mindset, but it's also a product perspective and you're thinking about the end user experience, but also the.[00:17:22] The bottom line for the business, you're bringing together a lot of a lot of qualities there. And there's also the fallback case, which is kind of, kind of a related or adjacent one. I think there was also a discussion on that internally where, I think it maybe was search, there was something recently where there was one of the frontline search providers was having some, yeah, slowness and outages, and essentially then we had a fallback, but essentially that gave people for a while, especially new users that come in that don't the difference, they're getting a They're getting worse results for their search.[00:17:52] And so then you have this debate about, okay, there's sort of what is correct to do from an engineering perspective, but then there's also what actually is the best result for the user. Is giving them a kind of a worse answer to their search result better, or is it better to kind of give them an error and be like, yeah, sorry, it's not working right at the moment, try again.[00:18:12] Later, both are obviously non optimal, but but this is the kind of thing I think that that you run into or, or the kind of thing we need to grapple with a lot more than you would other kinds of, of mediums.[00:18:24] James Brady: Yeah, that's a really good example. I think it brings to the fore the two different things that you could be optimizing for of uptime and response at all costs on one end of the spectrum and then effectively fragility, but kind of, if you get a response, it's the best response we can come up with at the other end of the spectrum.[00:18:43] And where you want to land there kind of depends on, well, it certainly depends on the app, obviously depends on the user. I think it depends on the, feature within the app as well. So in the search case that you, that you mentioned there, in retrospect, we probably didn't want to have the fallback. And we've actually just recently on Monday, changed that to Show an error message rather than giving people a kind of degraded experience in other situations We could use for example a large language model from a large language model from provider B rather than provider A and Get something which is within the A few percentage points performance, and that's just a really different situation.[00:19:21] So yeah, like any interesting question, the answer is, it depends.[00:19:25] Does Model Shadowing Work?[00:19:25] swyx: I do hear a lot of people suggesting I, let's call this model shadowing as a defensive technique, which is, if OpenAI happens to be down, which, , happens more often than people think then you fall back to anthropic or something.[00:19:38] How realistic is that, right? Like you, don't you have to develop completely different prompts for different models and won't the, won't the performance of your application suffer from whatever reason, right? Like it may be caused differently or it's not maintained in the same way. I, I think that people raise this idea of fallbacks to models, but I don't think it's, I don't, I don't see it practiced very much.[00:20:02] James Brady: Yeah, it is, you, you definitely need to have a different prompt if you want to stay within a few percentage points degradation Like I, like I said before, and that certainly comes at a cost, like fallbacks and backups and things like this It's really easy for them to go stale and kind of flake out on you because they're off the beaten track And In our particular case inside of Elicit, we do have fallbacks for a number of kind of crucial functions where it's going to be very obvious if something has gone wrong, but we don't have fallbacks in all cases.[00:20:40] It really depends on a task to task basis throughout the app. So I can't give you a kind of a, a single kind of simple rule of thumb for, in this case, do this. And in the other, do that. But yeah, we've it's a little bit easier now that the APIs between the anthropic models and opening are more similar than they used to be.[00:20:59] So we don't have two totally separate code paths with different protocols, like wire protocols to, to speak, which makes things easier, but you're right. You do need to have different prompts if you want to, have similar performance across the providers.[00:21:12] Adam Wiggins: I'll also note, just observing again as a relative newcomer here, I was surprised, impressed, not sure what the word is for it, at the blend of different backends that the team is using.[00:21:24] And so there's many The product presents as kind of one single interface, but there's actually several dozen kind of main paths. There's like, for example, the search versus a data extraction of a certain type, versus chat with papers, versus And each one of these, , the team has worked very hard to pick the right Model for the job and craft the prompt there, but also is constantly testing new ones.[00:21:48] So a new one comes out from either, from the big providers or in some cases, Our own models that are , running on, on essentially our own infrastructure. And sometimes that's more about cost or performance, but the point is kind of switching very fluidly between them and, and very quickly because this field is moving so fast and there's new ones to choose from all the time is like part of the day to day, I would say.[00:22:11] So it isn't more of a like, there's a main one, it's been kind of the same for a year, there's a fallback, but it's got cobwebs on it. It's more like which model and which prompt is changing weekly. And so I think it's quite, quite reasonable to to, to, to have a fallback that you can expect might work.[00:22:29] Is it too early to standardize Tech stacks?[00:22:29] swyx: I'm curious because you guys have had experience working at both, , Elicit, which is a smaller operation and, and larger companies. A lot of companies are looking at this with a certain amount of trepidation as, as, , it's very chaotic. When you have, when you have , one engineering team that, that, knows everyone else's names and like, , they, they, they, they meet constantly in Slack and knows what's going on.[00:22:50] It's easier to, to sync on technology choices. When you have a hundred teams, all shipping AI products and all making their own independent tech choices. It can be, it can be very hard to control. One solution I'm hearing from like the sales forces of the worlds and Walmarts of the world is that they are creating their own AI gateway, right?[00:23:05] Internal AI gateway. This is the one model hub that controls all the things and has our standards. Is that a feasible thing? Is that something that you would want? Is that something you have and you're working towards? What are your thoughts on this stuff? Like, Centralization of control or like an AI platform internally.[00:23:22] James Brady: Certainly for larger organizations and organizations that are doing things which maybe are running into HIPAA compliance or other, um, legislative tools like that. It could make a lot of sense. Yeah. I think for the TLDR for something like Elicit is we are small enough, as you indicated, and need to have full control over all the levers available and switch between different models and different prompts and whatnot, as Adam was just saying, that that kind of thing wouldn't work for us.[00:23:52] But yeah, I've spoken with and, um, advised a couple of companies that are trying to sell into that kind of a space or at a larger stage, and it does seem to make a lot of sense for them. So, for example, if you're trying to sell If you're looking to sell to a large enterprise and they cannot have any data leaving the EU, then you need to be really careful about someone just accidentally putting in, , the sort of US East 1 GPT 4 endpoints or something like this.[00:24:22] I'd be interested in understanding better what the specific problem is that they're looking to solve with that, whether it is to do with data security or centralization of billing, or if they have a kind of Suite of prompts or something like this that people can choose from so they don't need to reinvent the wheel again and again I wouldn't be able to say without understanding the problems and their proposed solutions , which kind of situations that be better or worse fit for but yeah for illicit where really the The secret sauce, if there is a secret sauce, is which models we're using, how we're using them, how we're combining them, how we're thinking about the user problem, how we're thinking about all these pieces coming together.[00:25:02] You really need to have all of the affordances available to you to be able to experiment with things and iterate rapidly. And generally speaking, whenever you put these kind of layers of abstraction and control and generalization in there, that, that gets in the way. So, so for us, it would not work.[00:25:19] Adam Wiggins: Do you feel like there's always a tendency to want to reach for standardization and abstractions pretty early in a new technology cycle?[00:25:26] There's something comforting there, or you feel like you can see them, or whatever. I feel like there's some of that discussion around lang chain right now. But yeah, this is not only so early, but also moving so fast. , I think it's . I think it's tough to, to ask for that. That's, that's not the, that's not the space we're in, but the, yeah, the larger an organization, the more that's your, your default is to, to, to want to reach for that.[00:25:48] It, it, it's a sort of comfort.[00:25:51] swyx: Yeah, I find it interesting that you would say that , being a founder of Heroku where , you were one of the first platforms as a service that more or less standardized what, , that sort of early developer experience should have looked like.[00:26:04] And I think basically people are feeling the differences between calling various model lab APIs and having an actual AI platform where. , all, all their development needs are thought of for them. , it's, it's very much, and, and I, I defined this in my AI engineer post as well.[00:26:19] Like the model labs just see their job ending at serving models and that's about it. But actually the responsibility of the AI engineer has to fill in a lot of the gaps beyond that. So.[00:26:31] Adam Wiggins: Yeah, that's true. I think, , a huge part of the exercise with Heroku, which It was largely inspired by Rails, which itself was one of the first frameworks to standardize the SQL database.[00:26:42] And people had been building apps like that for many, many years. I had built many apps. I had made my own templates based on that. I think others had done it. And Rails came along at the right moment. We had been doing it long enough that you see the patterns and then you can say look let's let's extract those into a framework that's going to make it not only easier to build for the experts but for people who are relatively new the best practices are encoded into you.[00:27:07] That framework, , Model View Controller, to take one example. But then, yeah, once you see that, and once you experience the power of a framework, and again, it's so comforting, and you can develop faster, and it's easier to onboard new people to it because you have these standards. And this consistency, then folks want that for something new that's evolving.[00:27:29] Now here I'm thinking maybe if you fast forward a little to, for example, when React came on the on the scene, , a decade ago or whatever. And then, okay, we need to do state management. What's that? And then there's, , there's a new library every six months. Okay, this is the one, this is the gold standard.[00:27:42] And then, , six months later, that's deprecated. Because of course, it's evolving, you need to figure it out, like the tacit knowledge and the experience of putting it in practice and seeing what those real What those real needs are are, are critical, and so it's, it is really about finding the right time to say yes, we can generalize, we can make standards and abstractions, whether it's for a company, whether it's for, , a library, an open source library, for a whole class of apps and it, it's very much a, much more of a A judgment call slash just a sense of taste or , experience to be able to say, Yeah, we're at the right point.[00:28:16] We can standardize this. But it's at least my, my very, again, and I'm so new to that, this world compared to you both, but my, my sense is, yeah, still the wild west. That's what makes it so exciting and feels kind of too early for too much. too much in the way of standardized abstractions. Not that it's not interesting to try, but , you can't necessarily get there in the same way Rails did until you've got that decade of experience of whatever building different classes of apps in that, with that technology.[00:28:45] James Brady: Yeah, it's, it's interesting to think about what is going to stay more static and what is expected to change over the coming five years, let's say. Which seems like when I think about it through an ML lens, it's an incredibly long time. And if you just said five years, it doesn't seem, doesn't seem that long.[00:29:01] I think that, that kind of talks to part of the problem here is that things that are moving are moving incredibly quickly. I would expect, this is my, my hot take rather than some kind of official carefully thought out position, but my hot take would be something like the You can, you'll be able to get to good quality apps without doing really careful prompt engineering.[00:29:21] I don't think that prompt engineering is going to be a kind of durable differential skill that people will, will hold. I do think that, The way that you set up the ML problem to kind of ask the right questions, if you see what I mean, rather than the specific phrasing of exactly how you're doing chain of thought or few shot or something in the prompt I think the way that you set it up is, is probably going to be remain to be trickier for longer.[00:29:47] And I think some of the operational challenges that we've been talking about of wild variations in, in, in latency, And handling the, I mean, one way to think about these models is the first lesson that you learn when, when you're an engineer, software engineer, is that you need to sanitize user input, right?[00:30:05] It was, I think it was the top OWASP security threat for a while. Like you, you have to sanitize and validate user input. And we got used to that. And it kind of feels like this is the, The shell around the app and then everything else inside you're kind of in control of and you can grasp and you can debug, etc.[00:30:22] And what we've effectively done is, through some kind of weird rearguard action, we've now got these slightly chaotic things. I think of them more as complex adaptive systems, which , related but a bit different. Definitely have some of the same dynamics. We've, we've injected these into the foundations of the, of the app and you kind of now need to think with this defined defensive mindset downwards as well as upwards if you, if you see what I mean.[00:30:46] So I think it would gonna, it's, I think it will take a while for us to truly wrap our heads around that. And also these kinds of problems where you have to handle things being unreliable and slow sometimes and whatever else, even if it doesn't happen very often, there isn't some kind of industry wide accepted way of handling that at massive scale.[00:31:10] There are definitely patterns and anti patterns and tools and whatnot, but it's not like this is a solved problem. So I would expect that it's not going to go down easily as a, as a solvable problem at the ML scale either.[00:31:23] swyx: Yeah, excellent. I would describe in, in the terminology of the stuff that I've written in the past, I describe this inversion of architecture as sort of LLM at the core versus LLM or code at the core.[00:31:34] We're very used to code at the core. Actually, we can scale that very well. When we build LLM core apps, we have to realize that the, the central part of our app that's orchestrating things is actually prompt, prone to, , prompt injections and non determinism and all that, all that good stuff.[00:31:48] I, I did want to move the conversation a little bit from the sort of defensive side of things to the more offensive or, , the fun side of things, capabilities side of things, because that is the other part. of the job description that we kind of skimmed over. So I'll, I'll repeat what you said earlier.[00:32:02] Capabilities: Offensive AI Engineering[00:32:02] swyx: It's, you want people to have a genuine curiosity and enthusiasm for the capabilities of language models. We just, we're recording this the day after Anthropic just dropped Cloud 3. 5. And I was wondering, , maybe this is a good, good exercise is how do people have Curiosity and enthusiasm for capabilities language models when for example the research paper for cloud 3.[00:32:22] 5 is four pages[00:32:23] James Brady: Maybe that's not a bad thing actually in this particular case So yeah If you really want to know exactly how the sausage was made That hasn't been possible for a few years now in fact for for these new models but from our perspective as when we're building illicit What we primarily care about is what can these models do?[00:32:41] How do they perform on the tasks that we already have set up and the evaluations we have in mind? And then on a slightly more expansive note, what kinds of new capabilities do they seem to have? Can we elicit, no pun intended, from the models? For example, well, there's, there's very obvious ones like multimodality , there wasn't that and then there was that, or it could be something a bit more subtle, like it seems to be getting better at reasoning, or it seems to be getting better at metacognition, or Or it seems to be getting better at marking its own work and giving calibrated confidence estimates, things like this.[00:33:19] So yeah, there's, there's plenty to be excited about there. It's just that yeah, there's rightly or wrongly been this, this, this shift over the last few years to not give all the details. So no, but from application development perspective we, every time there's a new model release, there's a flow of activity in our Slack, and we try to figure out what's going on.[00:33:38] What it can do, what it can't do, run our evaluation frameworks, and yeah, it's always an exciting, happy day.[00:33:44] Adam Wiggins: Yeah, from my perspective, what I'm seeing from the folks on the team is, first of all, just awareness of the new stuff that's coming out, so that's, , an enthusiasm for the space and following along, and then being able to very quickly, partially that's having Slack to do this, but be able to quickly map that to, okay, What does this do for our specific case?[00:34:07] And that, the simple version of that is, let's run the evaluation framework, which Lissa has quite a comprehensive one. I'm actually working on an article on that right now, which I'm very excited about, because it's a very interesting world of things. But basically, you can just try, not just, but try the new model in the evaluations framework.[00:34:27] Run it. It has a whole slew of benchmarks, which includes not just Accuracy and confidence, but also things like performance, cost, and so on. And all of these things may trade off against each other. Maybe it's actually, it's very slightly worse, but it's way faster and way cheaper, so actually this might be a net win, for example.[00:34:46] Or, it's way more accurate. But that comes at its slower and higher cost, and so now you need to think about those trade offs. And so to me, coming back to the qualities of an AI engineer, especially when you're trying to hire for them, It's this, it's, it is very much an application developer in the sense of a product mindset of What are our users or our customers trying to do?[00:35:08] What problem do they need solved? Or what what does our product solve for them? And how does the capabilities of a particular model potentially solve that better for them than what exists today? And by the way, what exists today is becoming an increasingly gigantic cornucopia of things, right? And so, You say, okay, this new model has these capabilities, therefore, , the simple version of that is plug it into our existing evaluations and just look at that and see if it, it seems like it's better for a straight out swap out, but when you talk about, for example, you have multimodal capabilities, and then you say, okay, wait a minute, actually, maybe there's a new feature or a whole new There's a whole bunch of ways we could be using it, not just a simple model swap out, but actually a different thing we could do that we couldn't do before that would have been too slow, or too inaccurate, or something like that, that now we do have the capability to do.[00:35:58] I think of that as being a great thing. I don't even know if I want to call it a skill, maybe it's even like an attitude or a perspective, which is a desire to both be excited about the new technology, , the new models and things as they come along, but also holding in the mind, what does our product do?[00:36:16] Who is our user? And how can we connect the capabilities of this technology to how we're helping people in whatever it is our product does?[00:36:25] James Brady: Yeah, I'm just looking at one of our internal Slack channels where we talk about things like new new model releases and that kind of thing And it is notable looking through these the kind of things that people are excited about and not It's, I don't know the context, the context window is much larger, or it's, look at how many parameters it has, or something like this.[00:36:44] It's always framed in terms of maybe this could be applied to that kind of part of Elicit, or maybe this would open up this new possibility for Elicit. And, as Adam was saying, yeah, I don't think it's really a I don't think it's a novel or separate skill, it's the kind of attitude I would like to have all engineers to have at a company our stage, actually.[00:37:05] And maybe more generally, even, which is not just kind of getting nerd sniped by some kind of technology number, fancy metric or something, but how is this actually going to be applicable to the thing Which matters in the end. How is this going to help users? How is this going to help move things forward strategically?[00:37:23] That kind of, that kind of thing.[00:37:24] AI Engineering Required Knowledge[00:37:24] swyx: Yeah, applying what , I think, is, is, is the key here. Getting hands on as well. I would, I would recommend a few resources for people listening along. The first is Elicit's ML reading list, which I, I found so delightful after talking with Andreas about it.[00:37:38] It looks like that's part of your onboarding. We've actually set up an asynchronous paper club instead of my discord for people following on that reading list. I love that you separate things out into tier one and two and three, and that gives people a factored cognition way of Looking into the, the, the corpus, right?[00:37:55] Like yes, the, the corpus of things to know is growing and the water is slowly rising as far as what a bar for a competent AI engineer is. But I think, , having some structured thought as to what are the big ones that everyone must know I think is, is, is key. It's something I, I haven't really defined for people and I'm, I'm glad that this is actually has something out there that people can refer to.[00:38:15] Yeah, I wouldn't necessarily like make it required for like the job. Interview maybe, but , it'd be interesting to see like, what would be a red flag. If some AI engineer would not know, I don't know what, , I don't know where we would stoop to, to call something required knowledge, , or you're not part of the cool kids club.[00:38:33] But there increasingly is something like that, right? Like, not knowing what context is, is a black mark, in my opinion, right?[00:38:40] I think it, I think it does connect back to what we were saying before of this genuine Curiosity about and that. Well, maybe it's, maybe it's actually that combined with something else, which is really important, which is a self starting bias towards action, kind of a mindset, which again, everybody needs.[00:38:56] Exactly. Yeah. Everyone needs that. So if you put those two together, or if I'm truly curious about this and I'm going to kind of figure out how to make things happen, then you end up with people. Reading, reading lists, reading papers, doing side projects, this kind of, this kind of thing. So it isn't something that we explicitly included.[00:39:14] We don't have a, we don't have an ML focused interview for the AI engineer role at all, actually. It doesn't really seem helpful. The skills which we are checking for, as I mentioned before, this kind of fault first mindset. And conventional software engineering kind of thing. It's, it's 0. 1 and 0.[00:39:32] 3 on the list that, that we talked about. In terms of checking for ML curiosity and there are, how familiar they are with these concepts. That's more through talking interviews and culture fit types of things. We want for them to have a take on what Elisa is doing. doing, certainly as they progress through the interview process.[00:39:50] They don't need to be completely up to date on everything we've ever done on day zero. Although, , that's always nice when it happens. But for them to really engage with it, ask interesting questions, and be kind of bought into our view on how we want ML to proceed. I think that is really important, and that would reveal that they have this kind of this interest, this ML curiosity.[00:40:13] ML First Mindset[00:40:13] swyx: There's a second aspect to that. I don't know if now's the right time to talk about it, which is, I do think that an ML first approach to building software is something of a different mindset. I could, I could describe that a bit now if that, if that seems good, but yeah, I'm a team. Okay. So yeah, I think when I joined Elicit, this was the biggest adjustment that I had to make personally.[00:40:37] So as I said before, I'd been, Effectively building conventional software stuff for 15 years or so, something like this, well, for longer actually, but professionally for like 15 years. And had a lot of pattern matching built into my brain and kind of muscle memory for if you see this kind of problem, then you do that kind of a thing.[00:40:56] And I had to unlearn quite a lot of that when joining Elicit because we truly are ML first and try to use ML to the fullest. And some of the things that that means is, This relinquishing of control almost, at some point you are calling into this fairly opaque black box thing and hoping it does the right thing and dealing with the stuff that it sends back to you.[00:41:17] And that's very different if you're interacting with, again, APIs and databases, that kind of a, that kind of a thing. You can't just keep on debugging. At some point you hit this, this obscure wall. And I think the second, the second part to this is the pattern I was used to is that. The external parts of the app are where most of the messiness is, not necessarily in terms of code, but in terms of degrees of freedom, almost.[00:41:44] If the user can and will do anything at any point, and they'll put all sorts of wonky stuff inside of text inputs, and they'll click buttons you didn't expect them to click, and all this kind of thing. But then by the time you're down into your SQL queries, for example, as long as you've done your input validation, things are pretty pretty well defined.[00:42:01] And that, as we said before, is not really the case. When you're working with language models, there is this kind of intrinsic uncertainty when you get down to the, to the kernel, down to the core. Even, even beyond that, there's all that stuff is somewhat defensive and these are things to be wary of to some degree.[00:42:18] Though the flip side of that, the really kind of positive part of taking an ML first mindset when you're building applications is that you, If you, once you get comfortable taking your hands off the wheel at a certain point and relinquishing control, letting go then really kind of unexpected powerful things can happen if you lean on the, if you lean on the capabilities of the model without trying to overly constrain and slice and dice problems with to the point where you're not really wringing out the most capability from the model that you, that you might.[00:42:47] So, I was trying to think of examples of this earlier, and one that came to mind was we were working really early when just after I joined Elicit, we were working on something where we wanted to generate text and include citations embedded within it. So it'd have a claim, and then a, , square brackets, one, in superscript, something, something like this.[00:43:07] And. Every fiber in my, in my, in my being was screaming that we should have some way of kind of forcing this to happen or Structured output such that we could guarantee that this citation was always going to be present later on that the kind of the indication of a footnote would actually match up with the footnote itself and Kind of went into this symbolic.[00:43:28] I need full control kind of kind of mindset and it was notable that Andreas Who's our CEO, again, has been on the podcast, was was the opposite. He was just kind of, give it a couple of examples and it'll probably be fine. And then we can kind of figure out with a regular expression at the end. And it really did not sit well with me, to be honest.[00:43:46] I was like, but it could say anything. I could say, it could literally say anything. And I don't know about just using a regex to sort of handle this. This is a potent feature of the app. But , this is that was my first kind of, , The starkest introduction to this ML first mindset, I suppose, which Andreas has been cultivating for much longer than me, much longer than most, of yeah, there might be some surprises of stuff you get back from the model, but you can also It's about finding the sweet spot, I suppose, where you don't want to give a completely open ended prompt to the model and expect it to do exactly the right thing.[00:44:25] You can ask it too much and it gets confused and starts repeating itself or goes around in loops or just goes off in a random direction or something like this. But you can also over constrain the model. And not really make the most of the, of the capabilities. And I think that is a mindset adjustment that most people who are coming into AI engineering afresh would need to make of yeah, giving up control and expecting that there's going to be a little bit of kind of extra pain and defensive stuff on the tail end, but the benefits that you get as a, as a result are really striking.[00:44:58] The ML first mindset, I think, is something that I struggle with as well, because the errors, when they do happen, are bad. , they will hallucinate, and your systems will not catch it sometimes if you don't have large enough of a sample set.[00:45:13] AI Engineers and Creativity[00:45:13] swyx: I'll leave it open to you, Adam. What else do you think about when you think about curiosity and exploring capabilities?[00:45:22] Do people are there reliable ways to get people to push themselves? for joining us on Capabilities, because I think a lot of times we have this implicit overconfidence, maybe, of we think we know what it is, what a thing is, when actually we don't, and we need to keep a more open mind, and I think you do a particularly good job of Always having an open mind, and I want to get that out of more engineers that I talk to, but I, I, I, I struggle sometimes.[00:45:45] Adam Wiggins: I suppose being an engineer is, at its heart, this sort of contradiction of, on one hand, yeah,

#259: Terminals have been around for decades, serving as the backbone of many workflows and operations in the tech world. From managing servers to local file manipulation, terminals offer a direct line to the heart of computing. However, with the advent of graphical user interfaces (GUIs), the terminal's prominence has waned among the general user base, though it remains a powerhouse for those who know how to wield it. Wave Terminal has emerged as a beacon of innovation in the static terminal landscape, bringing with it a host of features that leverage today's technology without abandoning the terminal's foundational principles. This modern terminal solution integrates technology, specifically Electron and Go, to create a user interface that feels familiar yet vastly more powerful. In this episode, Darin and Viktor discuss these topics in depth with Mike Sawka, the founder of Wave Terminal, shedding light on the innovative features and the vision for Wave Terminal's future.   Mike's contact information: LinkedIn: https://www.linkedin.com/in/mikesawka/   Wave Terminal https://www.waveterm.dev/   YouTube channel: https://youtube.com/devopsparadox   Review the podcast on Apple Podcasts: https://www.devopsparadox.com/review-podcast/   Slack: https://www.devopsparadox.com/slack/   Connect with us at: https://www.devopsparadox.com/contact/

Même les nazis étaient parfois obligés de ménager les apparences. Pour éviter de passer, aux yeux du monde, pour des tortionnaires sans pitié, il leur arrivait de maquiller la vérité. Notamment à propos de leur politique génocidaire et d'un des lieux où elle était appliquée, les camps de concentration.C'est ainsi qu'ils tentent de donner une image présentable de l'un de ces camps, Theresienstadt. Situé dans l'actuelle République tchèque, ce camp reçoit des déportés juifs venus de l'Europe entière.Après un bref séjour, beaucoup sont transférés vers d'autres camps, comme Auschwitz. Mais Theresienstadt est aussi un camp d'extermination, où des dizaines de milliers de détenus sont morts de mauvais traitements ou de privations.Les dirigeants nazis sont conscients de la nécessité de redorer le blason du IIIe Reich, souvent présenté comme un régime barbare. Ils rencontreront ainsi moins d'oppositions dans les pays qu'ils sont amenés à occuper.Aussi ne s'opposent-ils pas à une demande du Danemark, visant à faire visiter le camp de Theresienstadt par une équipe de la Croix-Rouge. Mais ils demandent un délai.Le temps de transformer cet enfer en un lieu accueillant. Un ancien acteur juif est chargé de recruter des figurants, bien nourris si possible. On construit une banque, un café et on prévoit même une scène de théâtre.Les façades sont ravalées et des fleurs donnent à ce lieu de mort un aspect presque pimpant. Aussi, quand les délégués de la Croix-Rouge visitent le camp, en juin 1944, ils sont impressionnés par ce qu'ils voient.Pari gagné pour les nazis qui décident, dans la foulée, de faire un documentaire sur ce "camp modèle". Connu sous le titre "le Führer offre une ville aux juifs", que lui donnent, par ironie, des rescapés du camp, le film montre les scènes tranquilles d'un lieu où il fait bon vivre.Les magasins regorgent de produits, un concert est donné dans la rue et, dans un hôpital bien équipé, les malades reçoivent tous les soins nécessaires. Cet étonnant documentaire est devenu depuis l'un des meilleurs exemples des mystifications nazies. Hébergé par Acast. Visitez acast.com/privacy pour plus d'informations.

Ce 16 janvier, les Grosses Têtes vous donnaient rendez-vous depuis l'un des plus célèbres cabarets de France, situé sur les Champs-Elysées : le Lido de Paris. Retrouvez tous les jours le meilleur des Grosses Têtes en podcast sur RTL.fr et l'application RTL.