Podcasts about augmented

Full article: Human-in-the-Loop Large Language Model–Augmented Diagnostic Reasoning in Thoracic Imaging: Impact of Radiologic Expertise Use of LLMs in the diagnostic reasoning process can either improve or hinder performance. Pranjal Rai, MD, discusses the AJR article by Song et al. exploring the association of reader expertise and reader performance when using LLMs as a diagnostic aid.

The calendar has generously provided five Sundays this month, May, which means another episode of The Augmented Fifth. This time Dick has put together an eclectic set of tunes, featuring prog, jazz, classical, fusion, electro-pop (maybe), ambient (ish), Brit Funk (probably), and things that straddle more than one of those, or defy genres altogether.

“The value is created in the friction, in the engagement between humans and AI—the pushing back by the humans, the pushing back by the machines.” –Ross Dawson About Ross Dawson Ross Dawson is a futurist, keynote speaker, strategy advisor, author, and host of Amplifying Cognition podcast. He is Chairman of the Advanced Human Technologies group of companies and Founder of Humans + AI startup Informivity. He has delivered keynote speeches and strategy workshops in 33 countries and is the bestselling author of 5 books, most recently Thriving on Overload. Website: rossdawson.com LinkedIn Profile: Ross Dawson What you will learn The dangers of aiming for a frictionless experience between humans and AI Why meaningful engagement—rather than passive approval—between humans and AI is crucial for cognitive augmentation How human judgment and reasoning differ, and where AI excels versus where humans add irreplaceable value The four key pitfalls of the traditional ‘human in the loop’ approach to decision-making with AI Why too much delegation to AI can erode human vigilance, judgment, and accountability The importance of adversarial, not just assistive, collaboration with AI for complex, high-stakes tasks How ‘living strategy’—AI-augmented, continuously updated organizational strategy—addresses the limitations of static strategic planning The role of AI in surfacing diverse perspectives, supporting dialogue, and enabling truly adaptive decision-making Episode Resources Transcript Ross Dawson: I love speaking to the wonderful guests I have on my podcast. I always learn an enormous amount, but in this episode, I'll share a little bit of an update for myself and delve into a few interesting things I've been seeing and doing lately, including some of the most interesting research papers I've seen on humans plus AI lately, looking at human in the loop and the ways in which we should be thinking about that, and AI and strategy. So, just a quick scan of what's going on in humans plus AI. I've been traveling quite a bit, doing a lot of keynotes as much as possible on humans plus AI, and the resonance around the theme is really rising very rapidly. In fact, somebody recently mentioned that humans plus AI was a cliché, or just overworn at the moment. Since I first started using the phrase three and a half years ago, I think it's wonderful that now it is gaining a lot of currency. People are talking about it, framing that. Yes, some phrases outlive their usefulness, but I think I'll stick with humans plus AI for the foreseeable future. The research papers I've been looking at are focused on essentially cognitive augmentation and erosion, and that's this critical domain where it's not really clear around whether, or in which circumstances, our cognition erodes, and what it is we can do to make it augmenting. One of the excellent papers is titled Cognitive Agency Surrender: Defending Epistemic Sovereignty via Scaffolded AI Friction. It's a bit dense, but it has some great research and analysis in it. The key finding, which it begins with, is that in human-computer interface research literature over the last while, we saw that last year, 2025, there was a big, big rise in this idea of driving human sovereignty in how it is we interact with computers. However, since last year to the first part of this year, we've in fact seen that fall dramatically, where the human sovereignty paradigm is reducing dramatically, and we are seeing this big rise in what is called the frictionless paradigm, saying: how do we get as little friction as possible between humans and AI? There are a number of really important points made in the paper, and really, the starting point is saying that we should stop treating frictionless AI as the goal. If we start to be frictionless, that is starting to essentially take the human out of the loop. The nature of humans is that we need to engage, we need to think, so we need to start building devil's advocate agents into the systems and to aim for this thing where we start to have both this high degree of engagement with the AI, but also high friction. That friction is where we are trying to, essentially, the more complex one rising, having more and more friction, and in lower frictions, it's just more so. Label tasks, but where we're not just showing the reasoning, giving people the ability to think through tasks and how they think about that, but to be able to challenge, actively challenge people as they are thinking through things. More broadly, ensuring that the way in which we are designing systems is not emphasizing this frictionless, seamless flow between humans and AI, because that is where the value is created: in the friction, in the engagement between the humans and AI, the pushing back by the humans, the pushing back by the machines, to be able to drive us and move us forward. Some really interesting research here, which was very much echoed in another very interesting paper called A Task-Driven Human-AI Collaboration: When to Automate, When to Collaborate, When to Challenge. This idea is essentially saying that the default mode for complex, high-stakes work should be adversarial, not assistive. This is, again, obviously, looking at what types of tasks or what types of situations we're in as to adjust how the machine works, but when we are working in the complex world, we need to be pushing back around the way people's thinking. It becomes easier, and we're not looking for the path of least resistance. We're looking for ones where we're adversarial. In fact, you can really see that there is no middle, what's called this. There is no AI zone, which is in the middle, where essentially the intermediate tasks are ones where, in fact, involving AI can, or involving AI to human decision, involving human and AI decision, is not necessarily the best path. And so, what we need to focus on is the ends of the spectrum, where it becomes a truly collaborative task, or it is purely AI or purely human. This actually goes very neatly and smoothly into the work which I've been doing around human in the loop. People have been talking human in the loop all the time; it's a very common framing. But what I've come to realize, and in fact, my research has borne this out, is that in the vast majority of cases when people say human in the loop, what they actually mean is that the human gives a stamp of approval at the end. An AI makes the decision, then the human says yes or no, or overrides it. That means that they are accountable, whoever the human is at the end. But there are a number of fundamental problems with this structure, four in particular. One is that people tend to defer to the AI. AI is usually right, and so, essentially, more and more, you are deferring to the machine. A number of studies have borne out this figure of a 93% approval rate in human approval on an AI or automated system, so very high levels of approval. This starts to become, “Well, by default, I'm going to accept this,” which tails to the second point, which is the decay of vigilance. Essentially, over time, you are paying less and less attention. It is easier and easier for the human to essentially pay attention and say, “It was probably right. It seems to be good.” My mind is wandering, and I'm not necessarily going to be taking the full attention, which my accountability should point to. This goes on to the next point, where this role of putting the human at the end of a decision actively erodes their judgment. In one of the frameworks which I shared a little while ago, there was the decision between reasoning and judgment. Reasoning, going through multiple steps, is something which actually AI can do. It's looking at the different logic, looking at the steps, looking at the relationships, and being able to make a sequence of logic leaps to be able to get to a point. Judgment is the human part. That is the context, that is the thinking, that is the richness, that is the values, that is the ethics, that is what we bring to bear through the full extent of our human experience. So that is exactly what the human in the loop is: the human applying their judgment to something the AI has done. But if that is all the human does, provide a judgment at the endpoint, it actively erodes their judgment because they aren't seeing all of the richness of the reasoning which went through to be able to create that decision. They are potentially being stuck in one single point and taken away from the richness of the context and the experience, which gives them that ability to be judgment. So, sticking a person in that human in the loop basically erodes their judgment and makes them less valuable over time, and essentially, obviously, is setting us up for a world where that human eventually gets taken out. The fourth problem is simply that this model cannot scale, where we are going to have more and more decisions. We need more and more accountability in systems, and just sticking people at the end of the human in the loop means that that's going to limit how well we can build decisions that have an impact and have value. So these are some fundamental challenges. I guess this relates to some upcoming work, or some work which I have been spending a lot of time on, and which I'll be releasing pretty soon now, which is around some very deep, detailed structures around humans plus AI decision-making. Those who have followed my work for a while may recall that around three years ago, I released 12 levels of AI delegation on decisions, from AI automation only at the bottom through to human only at the top, and all cascading ways of different ways in which AI and humans are involved in complementing each other in better decision-making. Now, there are some decisions and some types of decisions where that human in the loop does make sense, where it does make sense to have the AI do things and have a person approve that. But that is, I think, a relatively small proportion of decisions, and most decisions really require a richer integration. Essentially, AI is involved — sorry, humans are involved — in different points of the decision, including in framing it, including being able to provide different context along the way, to be able to be involved in a process from which a decision comes, rather than the AI doing the decision and the human approving at the end. This comes back to understanding that there are different types of decisions with different characteristics, and in most cases, that human in the loop, or what I describe as human at the end, because that's what we normally mean by human in the loop, is something which we should not be designing as the system. This pulls us in a way to this final topic, which is around AI in strategy. There are some deep failures in strategy as we currently know it, and it's essentially limited because the strategy has tended to be static. We do a strategy offsite, we create a strategy document, we do a strategy presentation, and that becomes the strategy until the next time the strategy is updated, which may be in a year or a quarter or three years, depending on the organization. The organization is continually evolving. The world is continually evolving as it happens faster and faster. So, that's one key challenge: traditional strategy is static. One of the next key points is that because the strategy is, again, a crystallization, or there's all of our thinking that we've crystallized into an output, which is our strategy, that means that all of the differences of opinion, all of the perspectives that were brought to bear from the board and the executive and the stakeholders and the organization are all collapsed into one thing. It takes away: did we all agree on this, or did we have a great deal of disagreement around this? Might we start changing our mind if we started to think about this bit differently, or some different evidence comes to light? All of that richness of the diversity of the thinking which forms strategy starts to collapse out of that. So these are just some of the challenges with the way strategy has been done. Now, this points to a world in which we can have humans plus AI strategy. Strategy, I believe, will always be human, and human first, but I think we will not have strategy which is human only, because there are so many ways in which AI can provide very rich analysis around that. My platform, Fraxios, so this is probably the thing I've been spending the most time on over the last couple of years, is building this platform for AI-augmented strategy. I guess this goes to the points which I've been raising. One is it makes strategy alive. It is this living strategy where it's continually reflecting current thinking, changes in the environment, and opportunities as they emerge. It is being able to surface the full extent of possibilities for strategy, assessing those in a rigorous way, being able to explore those and develop those. But because this is a true humans plus AI platform, it is really trying to tap the collective intelligence of the people involved in the strategy process. You are identifying where it is that there is agreement, where there is disagreement, and what the issues are. This is a foundation for constructive dialogue between humans, facilitated by AI to support a strategy which is both living, always evolving, and being able to address and keep the organization moving at the pace of change in the external environment. So that's just a few top-of-mind things that I'm currently spending a lot of my cognitive capacity on: these ideas of how it is the research, and being able to bring back these ideas of how it is we can best augment our cognition, our thinking, as we engage with these AI tools, which can be very helpful, but with too much delegation start to erode our cognition; being able to look at the decision-making structures and how those emerge, and with one, I think, particular problem or challenge being around this, the way conception of human in the loop and how that's manifest. I'm hoping to release and write a paper on this to be able to support that, and then finally being able to look at this AI-expanded strategy. So, as always, please check in on Humans Plus AI, humansplus.ai. I'll be sharing stuff on LinkedIn, and we'll be back with some wonderful guests in the next few weeks. Thanks. The post Ross Dawson on cognitive friction, beyond Human-in-the-loop, and AI-augmented strategy (AC Ep44) appeared first on Humans + AI.

In this episode, we will explore another Chinese herbal formula: Jiā Wèi Xiāng Sū Sǎn or Augmented Cyperus and Perilla Leaf Powder. This formula is in the sub-category of formulas that release exterior wind-cold and is especially good at treating colds with interior qi depression. We are going to do our usual deep dive into this formula and find out if there is any evidence or concerns. And, as usual, we will be adding something a little different…we are going to continue our discussion of pharmacognosy and discuss terpenoids. Each episode of the podcast will go into great depth about a single herb or formula. Besides covering the basics of herbology including category, and functions, we will explore the history, quality, science, pharmacology, evidence, and any potential interactions of each herb or formula. Please join us for another incandescent discussion of herbs as we explore Jiā Wèi Xiāng Sū Sǎn or Augmented Cyperus and Perilla Leaf Powder!

In episode 289 of our SAP on Azure video podcast we talk about Augmented Network Security via Azure Firewall and Application Gateway for SAP/Non-SAP workloadsGoran Condric talks with Evren Buyruk, Sai Kishor, Rajesh Nautiyal, and Derick Davis about how to strengthen network security for SAP and non‑SAP workloads on Azure. They explore how Azure Firewall and Application Gateway work together in a layered, Zero Trust architecture to protect applications, control traffic, and help customers meet security and compliance requirements.Find all the links mentioned here: https://www.saponazurepodcast.de/episode289Reach out to us for any feedback / questions:* Goran Condric: https://www.linkedin.com/in/gorancondric/* Holger Bruchelt: https://www.linkedin.com/in/holger-bruchelt/ #Microsoft #SAP #Azure #SAPonAzure #Security #AzureFirewall #AppGateway #ZeroTrust

Arturia's NEW Augmented PERSIA blends deeply expressive Middle Eastern instruments with modern synthesis to create powerful, cinematic soundscapes unlike anything else in the Augmented Series. In this video, we explore its unique textures, presets, and real-world music production potential to see if this is Arturia's most inspiring instrument yet.

Find out how top logistics firms are navigating the massive wave of AI without losing their human edge in this episode with Zach Jecklin of Echo Global Logistics, discussing the real-world impact of artificial intelligence in transportation! Zach shares advice on how to integrate tech platforms during a merger without burning out your team and the Echo's tech strategy, explaining why the future of freight brokerage isn't about total automation, but rather a "tech at your fingertips, experts by your side" approach that prioritizes customer experience over head-count reduction. If you're curious about the longevity of SaaS models, the role of generative AI in logistics, or how to filter through the noise of over-hyped freight tech startups, this interview delivers the insights you need to stay advantageous in an increasingly digital marketplace!   About Zach Jecklin Zach has served as Chief Information Officer at Echo Global Logistics since December 2021. Since joining the company in June 2008, he has held multiple leadership roles across finance, strategy, and technology. Prior to becoming CIO, he served as SVP of Strategy, where he was instrumental in shaping Echo's long-term business roadmap and before that he held several positions in finance, including VP of Finance. As CIO, Mr. Jecklin leads the development and execution of Echo's technology vision, driving innovation across the company's proprietary platforms, including EchoAccelerator, EchoShip, and EchoDrive. His unique background in finance and strategic planning informs a cross-functional approach to solving complex challenges and delivering scalable solutions for Echo's shippers and carrier partners. Mr. Jecklin​ earned a bachelor's degree in finance from Northern Illinois University.  

RSAC Conference 2026 made one thing impossible to miss: AI is on every sticker, every slide, and every booth. Sorting signal from marketing has never been harder. Lisa Liu, Corporate Marketing and Communications Manager at Stellar Cyber, joins this Brand Highlight to continue a conversation that started on the show floor in San Francisco and was worth picking up again once the noise settled. Stellar Cyber has been incorporating machine learning into every layer of its security platform since 2015, well before AI became the marketing default. The position Lisa Liu brings is direct: AI is not a one-size-fits-all solution. A large language model is not the most efficient way to parse log data, and slapping an AI label on existing functionality is not the same as designing for the analyst pain points at every stage of detection, investigation, and response. The conversation closes on the autonomous SOC question, where Stellar Cyber argues for a human-augmented approach. Promises of complete autonomy deserve healthy skepticism; guardrails matter, and keeping a human analyst in the loop is what allows AI mistakes to be caught and contained before they cascade. It is a Brand Highlight worth a few minutes for anyone trying to separate AI substance from AI theater in security operations. This is a Brand Highlight. A Brand Highlight is a ~5 minute introductory conversation designed to put a spotlight on the guest and their company. Learn more: https://www.studioc60.com/creation#highlight GUEST Lisa Liu, Corporate Marketing and Communications Manager, Stellar Cyber | On LinkedIn: https://www.linkedin.com/in/lisaaliu/ RESOURCES Learn more about Stellar Cyber: https://stellarcyber.ai/ View all of our RSAC Conference 2026 coverage: https://www.itspmagazine.com/rsac26 Are you interested in telling your story? ▶︎ Full Length Brand Story: https://www.studioc60.com/content-creation#full ▶︎ Brand Spotlight Story: https://www.studioc60.com/content-creation#spotlight ▶︎ Brand Highlight Story: https://www.studioc60.com/content-creation#highlight KEYWORDS Lisa Liu, Stellar Cyber, Sean Martin, brand story, brand marketing, marketing podcast, brand highlight, RSAC Conference 2026, Multi-Layer AI, human-augmented autonomous SOC, machine learning, Open XDR, NG-SIEM, security operations, AI in cybersecurity, agentic AI, SOC analyst, security platform Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

First there was the keyboard, then the touch screen.首先是键盘，然后是触屏。Some tech companies say a wearable pair of glasses could be the next leap in technology, even if it didn't work out for google glass.一些科技公司表示，即使谷歌眼镜未能成功，可穿戴眼镜仍可能是科技领域的下一次重大飞跃。In the future we won't be only limited to our smartphones, when it comes to understanding the world around us. So this is our early investment in that future.未来我们将不再局限于仅通过智能手机来理解周围的世界。这就是我们对那个未来的早期投资。The US-based company Snap's investments is this--the spectacles, three sunglasses. This third version is smarter than the previous ones.总部设在美国的Snap公司投资开发了这款太阳镜。第三个版本比之前的版本更智能。It has two cameras. The corner of the glasses lights up when recording video, and allows the wearer to put 3D objects in the video. Here are some flowers.它有两个摄像头。在录制视频时，眼镜的角落会亮起，佩戴者可以对物品进行3D拍摄。这里有些花。Users can capture up to a minute of video. In a very different application, the InGlass by Hong Kong-based Pacific Future allows theme park visitors to have a different kind of experience through augmented reality.用户最多可以拍摄一分钟的视频。在一个截然不同的应用场景中，香港太平洋未来科技公司推出的InGlass让主题公园游客通过增强现实技术获得别样体验。During the launch of the smart glasses during Halloween, this park became extra scary. So there's a ghost everywhere mixed with the real like buildings.在万圣节期间推出智能眼镜时，这个公园变得格外恐怖。看起来就像这座楼里到处都是鬼魂。The glasses are used in theme parks in China and Malaysia.这副眼镜在中国和马来西亚的主题公园中使用。With a processor inside, these augmented reality glasses are designed for ages 12 and up, because of its weight and size.内置处理器的增强现实眼镜因重量和体积原因，设计适用年龄为12岁及以上。Augmented reality security glasses made by Beijing-based Goolton can be used by police to identify suspects.北京谷东科技公司制造的增强现实安防眼镜可帮助警方识别嫌疑人。He can set a blacklist and the skin in your crowded people and find your criminal very soon.警方可以设置黑名单，在茫茫人海中识别出皮肤特征，很快就能找到罪犯。Armed with facial recognition software, video or images captured by these smart glasses can be sent to security officials off-site for analysis.配备面部识别软件的智能眼镜可将拍摄的视频或图像发送给场外的安保人员进行分析。Of course there are privacy concerns with any device that comes with built-in cameras, one of the reasons consumers rejected google glass.当然，任何配备内置摄像头的设备都会引发隐私担忧，这也是消费者拒绝谷歌眼镜的原因之一。Still the race is on for tech companies, big and small, to turn an everyday item like glasses into something smarter. 尽管如此，大大小小的科技公司仍在竞相将眼镜等日常用品改造成更智能的产品。

It's 2052, and Tessa is at a street festival in Pittsburgh with her friend Brenda. The city has been transformed for the night — actors, costumes, fog machines, handmade sets. Tessa, being Tessa, is busy mentally reverse-engineering all of it, finding the rigging, the hidden doors, the mechanics behind the magic. Then the scene cuts.When Tessa opens her eyes again, it's seven years later. She's in a room she doesn't recognize, talking to a woman named Jenny, who delivers the kind of news that takes a moment to even form into a question. Tessa is dead. Or her original body is. What's running now is something else — a digital version of her mind, brought back online inside a simulation. She didn't sign up for this. Or maybe she did, and just doesn't remember.What makes Tessa different from the other people waking up in this place is hard to explain right away, and she'd probably prefer you didn't try. She's observant in a way that unsettles people. She notices what's real, what's constructed, and what's being hidden from her. Inside a digital prison, that's either an asset or a problem — possibly both.The simulation has rules. There are administrators. There are things Tessa is and isn't allowed to do. But Tessa has always been the kind of person who, when handed a constraint, starts quietly looking for its edges. She can't help it. And the people running this place are starting to realize that.This is a story about identity, confinement, and what it means to be alive when your life is running on someone else's servers. It's about what you do when the world you knew is gone, and the one you're in was built to hold you. Tessa's story is told in pieces — a festival, a waking, a mirror, a plan. Let's start at the beginning.Tesla coils — High-voltage electrical devices used at the festival as atmospheric props, generating visible electric arcs between metal posts.AR glasses — Augmented reality eyewear worn by characters that overlay digital information and windows onto the physical world around them.Stasis VR — A form of virtual reality used as a containment method, capable of keeping a subject immobilized and unaware.Amnesia-inducing biotics — Biological agents administered to suppress or erase recent memories.Mind emulation — The process of digitally copying a human brain and running it as a conscious simulation on a computer.Nesting simulation — A layered virtual world designed to house emulated minds, detailed enough to simulate hunger, fatigue, and physical sensation.Personality clones (P-clones) — Digital replicas of people built from recorded behavioral data, capable of passing as human in social interactions.Emulated minds (EMs) — Digital reconstructions of deceased people's consciousness, capable of independent thought and memory.Brain scanner / slice scanner — A device that captures a full scan of a person's brain in order to create a mind emulation.Assist — A personal AI assistant that handles navigation, finances, communication, and ambient support within the simulation.E-fabric — Smart clothing fabric embedded with interactive digital buttons and display elements such as clock readouts.Autono-cabs — Autonomous self-driving taxi vehicles operating in the simulated city.Delivery drones — Unmanned aerial vehicles used for transporting packages through urban airspace.Printed outfits — On-demand clothing produced by fabrication machines, available even at airport retail outlets.Biotic vector — A biological agent taken like a supplement to produce physical changes in the body, such as growing facial hair.Subscription-wear — A software lock applied to consumer devices that requires ongoing payment for continued use.Black-box recording devices — Personal data-capture tools used to record an individual's life in detail for the purpose of building a personality clone.Whisper drone cam — A small floating camera drone used for personal recording or content creation.Rig controllers — Physical controllers associated with immersive rigs, likely for VR or AR systems, brought in for repair at Tessa's shop.Industrial robots — Legacy manufacturing machines found in the abandoned shoe factory, originally used for automated production.Medusa Net — Tessa's custom-built intrusion program designed to break through the code layer of the simulation and expose its underlying architecture.SSH — Secure Shell protocol, used by Tessa to remotely access individual factory computers and retrieve distributed code fragments.Knots Math — A new mathematical framework invented by Tessa, used as the basis for a novel programming language with the unusual property of hiding secondary functions inside primary ones.Knots computer — A computer architecture built entirely on Knots Math, which Tessa first emulates on her laptop before using it as a tool for covert communication and escape.Swarm agents — Multi-function code entities that make up both the simulation environment and Tessa's own emulated mind, capable of being exploited through function swapping.Function swapping — A process within swarm agent architecture where agents exchange roles at high speed, which Tessa exploits to move information across the simulation.Brain reader — A software tool developed by Butler designed to translate an emulated mind's activity into readable thoughts, memories, and sensations.Triptic dimensional thinking — A cognitive architecture identified in Tessa's emulated mind that allows her to process information in three simultaneous dimensions, flagged by Butler as a potential security threat.Many of the characters in this project appear in future episodes. Using storytelling to place you in a time period, this series takes you, year by year, into the future. From 2040 to 2195. If you like emerging tech, eco-tech, futurism, perma-culture, apocalyptic survival scenarios, and disruptive science, sit back and enjoy short stories that showcase my research into how the future may play out. The companion site is https://in20xx.com These are works of fiction. Characters and groups are made-up and influenced by current events but not reporting facts about people or groups in the real world. This project is speculative fiction. These episodes are not about revealing what will be, but they are to excited the listener's wonder about what may come to pass. Copyright © Cy Porter 2026. All rights reserved.

WHAT This one is a short, 46-minute journey into the world below, but always ascending. And the world above, but drooping and perking up. Listen as these humans improvise in a no-holds barred explosion from the rocket-launch pad. Minio Class: keys Dan Rosenstark: drums Mike Rosenstark: guitar GEAR Control: All rigs performed and routed via MIDI Designer Pro X on iPad. Guitar and sources: Bleep Labs Thingamagoop, electric kalimba, Moog Little Phatty into Neural DSP Quad Cortex, Fractal VP-4 units, AM4, dual Eventide PitchFactor, Boomerang Phrase III with Sidecar. Augmented with Pianoteq, Native Instruments FM8, four spoken word channels, and six internet radio feeds, running on an Apple M1 MacBook Air with a full plugin chain. Drums and percussion: Native Instruments Maschine MK3 and Jam, YouTube sound sources, ValhallaDelay, iZotope StutterEdit (the first one, thanks Devine). Keys: Sequential Circuits Take5 and Arturia AstroLab 37. Thanks to Ableton Link for keeping us together.

WHAT They come in loud and the first few minutes are dense. Things overlap, then separate. Space shows up. They listen more than they talk. But it's always evolving. By the end it's stretched out, slightly odd, and steady after pushing through the mess. Kevin Brown: bass Dan Rosenstark: drums Mike Rosenstark: guitar GEAR Control: All rigs performed and routed via MIDI Designer Pro X on iPad. Guitar and sources: Bleep Labs Thingamagoop, electric kalimba, Moog Little Phatty into Neural DSP Quad Cortex, Fractal VP-4 units, AM4, dual Eventide PitchFactor, Boomerang Phrase III with Sidecar. Augmented with Pianoteq, Native Instruments FM8, four spoken word channels, and six internet radio feeds, running on an Apple M1 MacBook Air with a full plugin chain. Drums and percussion: Native Instruments Maschine MK3 and Jam, YouTube sound sources, ValhallaDelay, iZotope StutterEdit (the first one, thanks Devine). Bass: 7-string Conklin fretted bass with Bartolini pickups into Fractal Audio AX8 and VP-4. Thanks to Ableton Link for keeping us together.

Join hosts Lois Houston and Nikita Abraham as they explore one of the most exciting innovations in enterprise AI: Retrieval Augmented Generation (RAG) powered by Oracle AI Vector Search. In this episode, Senior Principal APEX & Apps Dev Instructor Brent Dayley walks through the fundamentals of RAG, explaining how it combines Oracle Database 23ai, vector embeddings, and large language models to deliver accurate, context-rich answers from both business and unstructured data. Discover the typical RAG workflow, practical setup steps on Oracle Cloud Infrastructure, and how to work with embedding models for real-world applications.   Oracle AI Vector Search Deep Dive: https://mylearn.oracle.com/ou/course/oracle-ai-vector-search-deep-dive/144706/ Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, Anna Hulkower, Kris-Ann Nansen, and the OU Studio Team for helping us create this episode.   Please note, this episode was recorded before Oracle AI Database 26ai replaced Oracle Database 23ai. However, all concepts and features discussed remain fully relevant to the latest release.   ----------------------------------------------   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: Welcome to the Oracle University Podcast! I'm Nikita Abraham, Team Lead: Editorial Services with Oracle University, and joining me is Lois Houston, Director of Communications and Adoption Programs with Customer Success Services. Lois: Hi everyone! If you've been with us this season, you'll know we've already covered a lot about Oracle AI Vector Search. In Episode 1, we introduced the core concepts—how vectors let you search by meaning, not just keywords, and how embedding models translate your unstructured data into a searchable format inside Oracle Database 23ai.  Nikita: Then, in Episode 2, we took a deeper dive into how these vectors are actually stored and managed. We explored the different types of vector indexes, similarity metrics, and best practices for designing and optimizing your database for semantic search.  Lois: Right. Today, we're shifting gears into one of the most exciting real-world applications: Retrieval Augmented Generation, or RAG. You'll learn how RAG combines the power of Oracle AI Vector Search with large language models to answer natural language questions using both business and unstructured data.  01:39 Nikita: We'll walk through the workflow, highlight why Oracle Database is uniquely suited for RAG, and give you the essential steps to get started. Back again is Senior Principal APEX & Apps Dev Instructor Brent Dayley. Hi Brent! Could you explain what RAG is, and why it's important for working with AI and large language models? Brent: Well, RAG stands for Retrieval Augmented Generation. And this is a technique that allows us to enhance the capabilities of large language models, also known as LLMs, and this provides them with relevant context from external knowledge sources. This will allow the LLMs to generate more accurate, informative, and context-aware responses. Real world applications include answering questions, chatbot development, content summarization, and knowledge discovery.  02:35 Lois: Brent, what makes Oracle Database 23ai a good platform for implementing RAG workflows? Brent: Now, there are some key advantages of using Oracle Database 23ai as a RAG platform. These include native functionality, allowing built-in tools and packages specifically designed for RAG pipeline development.  Also, if you are a PL/SQL developer, then this will allow you to develop within a familiar and robust database environment. Also, Oracle has a plethora of security and performance tools. And this ensures enhanced security and optimized performance.  03:18 Nikita: What does a typical RAG workflow look like in Oracle Database 23ai? What are the main steps involved? Brent: Now, the primary workflow steps are going to be to generate vector embeddings from your unstructured data. You do this using vector embedding models. And you can generate those embeddings either inside or outside of the database.  Next, you need to store the vector embeddings, the unstructured data, and the relational business data, and you can store all of that in the Oracle Database. You might want to also create vector indexes that can allow you to run similarity searches over huge vector spaces with really good performance.  Finally, you need to query data with similarity searches. You can use Oracle AI Vector Search native SQL operations to combine similarity with relational searches to retrieve relevant data. And optionally, you can generate a prompt and send it to a large language model for full RAG inference.  04:30 Lois: Can you give us an example of how this workflow operates in practice? Brent: A user's natural language question is encoded as a vector and sent to AI Vector Search. Next, AI vector search finds private content, such as documents, that are stored in the database, and those will match the user's question. The content is then sent to Oracle's GenAI service to help answer the user's question. And then GenAI uses the content plus general knowledge to provide an informed answer back to the user.  05:14 Nikita: What does the overall user experience look like when interacting with RAG? How does Oracle ensure the answers are both accurate and up to date? Brent: In this case, we have a chatbot. This is the interface that we usually use to enable dialogue with the large language model. Now, in order to improve the quality of the answers, we want to search your private business data, and that allows us to pass the most relevant facts back to the LLM.  Next, we want to format the similarity search results as a prompt and context for the large language model. Now, this will allow us to use up to date facts as input to LLMs. And that will minimize the probability of the LLM hallucinating. And those high-quality responses are then returned back to the chatbot.  06:12 Lois: Brent, what does the setup process look like for getting RAG up and running with Oracle AI Vector Search on OCI? Can you take us through the main steps? Brent: First, you will log into OCI. Provide your cloud account name and click Next. There are also interfaces for signing in using a traditional cloud account. And if you're not an Oracle Cloud customer yet, you can also sign up using this page.  Next, after signing in, you will create a compute instance. And you will use Oracle Infrastructure Cloud Console in order to do this. And you will wind up with the user called OPC. You'll notice that you're using SSH in order to connect to your compute instance, and you're running a script in order to set up the Oracle Database.  After that, you will set up the Python environment, again using SSH to connect as an OPC user to your compute instance.  07:22 Do you want to optimize your implementation strategies? Check out the Oracle Fusion Cloud Applications Process Essentials training and certifications for insight into key processes and efficiencies across every phase of your Fusion Cloud Apps journey. Learn more at mylearn.oracle.com.  07:43 Nikita: Welcome back! So far, we've seen how Oracle AI Vector Search powers RAG, letting you surface relevant business knowledge for large language models and enhance their answers. At the heart of all this is the process of transforming unstructured data, like text or documents, into mathematical representations called embeddings.  Lois: Those embeddings are what make meaningful, semantic search possible. But have you wondered how those embeddings actually get created, or what goes on behind the scenes when you choose an embedding model?  Nikita: Up next, we'll take a closer look at embedding models themselves: what they are, how to use them inside Oracle Database 23ai, and how you can experiment with different models to get the results that best fit your business needs.  Lois: We'll walk through importing models, generating embeddings, and even how you can swap out embedding models to compare results. But before we get into the nitty-gritty details, let's quickly recap embedding models, since we've mentioned them in our previous episodes.  08:47 Nikita: Brent, for listeners who might need a refresher, can you explain what embedding models are and why they're so central to AI Vector Search?  Brent: AI Vector Search is based on similarity properties. You can search data by semantic similarity rather than by the actual values. Vector embeddings are created by embedding models to represent the unstructured data. So we have input data.  What we'll want to do is to use an embedding model to generate vector embeddings. And then the vector embeddings would be stored inside of a vector column in a table. We would then compare those vectors to each other using vector distance function.  And we would get the relevant content back based on the number of returns that we describe. For instance, maybe we want to bring back the five closest pieces of data compared to the input data.  There is a new function that allows you to generate vector embeddings that is called the vector embedding function. It allows you to generate vectors within the database.  10:08 Lois: Can you walk us through the practical steps for using embedding models with Oracle AI Vector Search? Brent: In order to create and set up a table, we might use the Python program called create_schema.py. And that will allow us to create a table.  We would ensure that the table was successfully created with the data. As an example, I would create a table called MY_DATA. Next, we would use a sentence transformers embedding model in order to vectorize the table. We can use the Python program, vectorize_table_SentenceTransformers.py. We would then query the MY_DATA table in the Oracle Database to verify that the data has been updated.  And then we would use sentence transformers in order to perform the similarity search. The Python program is called similarity_search_SentenceTransformers.py And what that would do is create the table and then perform a similarity search using the sentence transformers. Now what if you decide that you want to maybe change embedding models? Maybe you want to compare the results by using one particular model as compared to a different model.  So you can change the embedding model. And in order to do that, you would change the embedding model in both of the programs and re-vectorize the table using the vectorize_table_SentenceTransformers.py program. You would then use the new model with different words, possibly, and then compare and review the results, and then choose which one gets you back the data that you're looking for that is most similar.  12:02 Nikita: Well, that's a wrap on this episode. A big thank you, Brent, for sharing your expertise with us.  Lois: If you want to learn more about the topics we discussed today, visit to mylearn.oracle.com and search for the Oracle AI Vector Search Deep Dive course. Until next time, this is Lois Houston… Nikita: And Nikita Abraham, signing off! 12:25 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.

" Innovation is not just technology, systems and strategy, it is also about energy and embodied behaviour."Bruno and I discuss the human side of innovation and the strategic role of AI. We explore how leaders can foster creativity and manage uncertainty by adopting principles from martial arts and leveraging AI for better decision-making.Bruno brings a unique perspective, combining engineering rigour, martial arts mastery, and deep reflection on embodied leadership. We explore different perspectives on how to master generative conflict for Innovation success and making strategy an embodied practice. The insight on the intersection between martial arts mastery, strategy and leadership brings a new lens that every CEO should learn: how to engage in “generative conflict.” So how to 'use' fear and agression in a smarter, more constructive way, which is consensual, respectful, collaborative and vulnerable.Bruno sees innovation not just as systems and strategy, but as energy and embodied behaviour. The difference between doing and managing innovation is really key. Doing is about turning ideas into value; managing is scaling that process across hundreds of ideas, accepting uncertainty and potential failure. This distinction really hit home because if something is truly innovative, it comes with a big element of uncertainty. And that means failure is always a possibility, even if you do everything right.The main insights you'll get from this episode are :Finding innovative solutions for leaders that address the human side of innovation and AI's strategic role beyond the hype; innovation is energy and embodies behaviour, away from processes and tools.The difference between ‘doing' and ‘managing' innovation is important: the former is about transforming ideas into money (in a corporate context); the latter is doing it at scale, i.e. concurrently developing hundreds of ideas.Creativity brings something to life and is an inherent part of human nature - innovation is very personal, from which we can harness failure and maximise learning to create something of value.Whilst uncertainty and ambiguity always exist, senior leaders can remove ambiguity in the form of strategy, as an unknown or unclear strategy spreads uncertainty. Strategy is like embodied practice – need to feel it in the real world.Martial arts redirect fear and aggression rather than eliminate them, providing a good lesson for CEOs in how to engage in generative conflict, which is consensual, respectful, collaborative and vulnerable.Strategising and innovating demand conflict, and innovation can be seen as the equivalent of sparring practice: articulating and creating something that then becomes the discussion point.Playing Lean is a (serious) board game for innovation, providing a safe space between the classroom and the front line, but the emotions and experiences are real – real skill transference and a team activity.Augmented strategy using AI is currently very superficial applications of LLMs, which are worthless in the bigger picture – we must optimise decision-making processes and understand decisions as humans.We must first map out the requisite data, insights, and knowledge, and then leverage specific AI to create multiple scenarios; hybrid intelligence uses AI to enhance human creativity.Asking customers (in a B2B environment) for feedback is invaluable for innovation – it is of great importance to have people with (life) experience who will understand the issue, and AI cannot replace this.The simplest practice leaders can implement immediately is to listen and play back what they heard to check correct understanding, thereby inviting others to bring forward their thinking.Find out more about Bruno and his work here :https://www.pesec.no/

Send us Fan MailIn this episode, Lasche shares her two birth stories, one in hospital and one at home. Throughout both of her pregnancies, she experienced ongoing nausea and vomiting right up until birth.With her first, she chose to birth through the MGP program and went beyond 42 weeks before going into spontaneous labour. During labour, she was sent home as she wasn't yet in active labour. After her waters broke, she returned to hospital where meconium was found in the waters. Her care team recommended starting syntocinon, and she gave birth not long after, with contractions becoming intense and close together.After reflecting on and questioning her first birth experience, Lasche decided she wanted something different the next time.For her second pregnancy, she chose a home birth with a private midwife. Her labour was fast, lasting just 2.5 hours, and her baby was born before the midwife arrived.Links: - Court Case Support the show@homebirthstoriesaustralia Support the show by buying us a coffee! Please be advised that this podcast may contain explicit language. Listener discretion is advised.The information, statistics, and research presented in this podcast are for informational purposes only and are not intended to constitute or replace medical or midwifery advice. All information discussed can be found online and is provided in the links in the show notes. It is always recommended to conduct your own research and make informed decisions. We advise you to discuss any topics or concerns with your healthcare provider. While we strive to incorporate the most up-to-date research in our episodes, we do not warrant or guarantee the accuracy of the information discussed on the show. 

From stone tools and shelters to symbolic art and abstract thought, human history is shaped by a brain built to form and share ideas. Joseph Paradiso, Professor in Media Arts and Sciences at the MIT Media Lab, explores what comes next after the early visions of ubiquitous computing have largely arrived in today's Internet of Things world, where low-power sensors and interfaces are embedded in smart devices across our environments and connect seamlessly to widespread networking infrastructure. He asks how this information connects to people, and how perception, cognition, and identity might expand beyond our corporeal confines. Drawing on recent projects from his Responsive Environments research group, he examines sensing at multiple scales in the physical world, including wearables, smart buildings, connected landscapes, and space missions, and the different ways sensed or inferred information can connect to people. Examples include smart buildings as “prosthetic” extensions of their inhabitants, manifesting sensed or inferred phenomena in virtual analog environments, and interfaces modulated by user attention and focus or augmented by real-time AI. Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Science] [Show ID: 41327]

From stone tools and shelters to symbolic art and abstract thought, human history is shaped by a brain built to form and share ideas. Joseph Paradiso, Professor in Media Arts and Sciences at the MIT Media Lab, explores what comes next after the early visions of ubiquitous computing have largely arrived in today's Internet of Things world, where low-power sensors and interfaces are embedded in smart devices across our environments and connect seamlessly to widespread networking infrastructure. He asks how this information connects to people, and how perception, cognition, and identity might expand beyond our corporeal confines. Drawing on recent projects from his Responsive Environments research group, he examines sensing at multiple scales in the physical world, including wearables, smart buildings, connected landscapes, and space missions, and the different ways sensed or inferred information can connect to people. Examples include smart buildings as “prosthetic” extensions of their inhabitants, manifesting sensed or inferred phenomena in virtual analog environments, and interfaces modulated by user attention and focus or augmented by real-time AI. Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Science] [Show ID: 41327]

From stone tools and shelters to symbolic art and abstract thought, human history is shaped by a brain built to form and share ideas. Joseph Paradiso, Professor in Media Arts and Sciences at the MIT Media Lab, explores what comes next after the early visions of ubiquitous computing have largely arrived in today's Internet of Things world, where low-power sensors and interfaces are embedded in smart devices across our environments and connect seamlessly to widespread networking infrastructure. He asks how this information connects to people, and how perception, cognition, and identity might expand beyond our corporeal confines. Drawing on recent projects from his Responsive Environments research group, he examines sensing at multiple scales in the physical world, including wearables, smart buildings, connected landscapes, and space missions, and the different ways sensed or inferred information can connect to people. Examples include smart buildings as “prosthetic” extensions of their inhabitants, manifesting sensed or inferred phenomena in virtual analog environments, and interfaces modulated by user attention and focus or augmented by real-time AI. Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Science] [Show ID: 41327]

From stone tools and shelters to symbolic art and abstract thought, human history is shaped by a brain built to form and share ideas. Joseph Paradiso, Professor in Media Arts and Sciences at the MIT Media Lab, explores what comes next after the early visions of ubiquitous computing have largely arrived in today's Internet of Things world, where low-power sensors and interfaces are embedded in smart devices across our environments and connect seamlessly to widespread networking infrastructure. He asks how this information connects to people, and how perception, cognition, and identity might expand beyond our corporeal confines. Drawing on recent projects from his Responsive Environments research group, he examines sensing at multiple scales in the physical world, including wearables, smart buildings, connected landscapes, and space missions, and the different ways sensed or inferred information can connect to people. Examples include smart buildings as “prosthetic” extensions of their inhabitants, manifesting sensed or inferred phenomena in virtual analog environments, and interfaces modulated by user attention and focus or augmented by real-time AI. Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Science] [Show ID: 41327]

This conversation was recorded at GOTO Copenhagen 2025.https://gotopia.techMarko Klemetti - CTO of EficodeKris Jenkins - Lifelong Computer Geek and Podcast HostORIGINAL TALK TITLERewriting the SDLC Playbook with GenAI: How To Build a GenAI-Augmented Software Organization?RESOURCESMarkohttps://bsky.app/profile/mrako.comhttps://twitter.com/mrakohttps://github.com/mrakohttps://www.linkedin.com/in/mrakohttps://mrako.comKrishttps://bsky.app/profile/krisajenkins.bsky.socialhttps://twitter.com/krisajenkinshttps://www.linkedin.com/in/krisjenkinshttps://github.com/krisajenkinshttp://blog.jenkster.comABSTRACTSpeakers interview each other on topics that matter to them.Expect the unexpected. [...]Read the full abstract here:https://gotocph.com/2025/sessions/3931RECOMMENDED BOOKSMatthew Skelton & Manuel Pais • Team Topologies • http://amzn.to/3sVLyLQForsgren, Humble & Kim • Accelerate: The Science of Lean Software and DevOps • https://amzn.to/3tCz1xOJohn Arundel & Justin Domingus • Cloud Native DevOps with Kubernetes • https://amzn.to/3hKZvI5Wynne, Hellesoy & Tooke • The Cucumber Book • https://amzn.to/3tEUINJSol Rashidi • Your AI Survival Guide • https://amzn.to/3UFYnKCDavid Foster • Generative Deep Learning • https://amzn.to/48ZgP4xPhil Winder • Reinforcement Learning • https://amzn.to/3t1S1VZBlueskyInstagramLinkedInFacebookCHANNEL MEMBERSHIP BONUSJoin this channel to get early access to videos & other perks:https://www.youtube.com/channel/UCs_tLP3AiwYKwdUHpltJPuA/joinLooking for a unique learning experience?Attend the next GOTO conference near you! Get your ticket: gotopia.techSUBSCRIBE TO OUR YOUTUBE CHANNEL - new videos posted daily!

From stone tools and shelters to symbolic art and abstract thought, human history is shaped by a brain built to form and share ideas. Joseph Paradiso, Professor in Media Arts and Sciences at the MIT Media Lab, explores what comes next after the early visions of ubiquitous computing have largely arrived in today's Internet of Things world, where low-power sensors and interfaces are embedded in smart devices across our environments and connect seamlessly to widespread networking infrastructure. He asks how this information connects to people, and how perception, cognition, and identity might expand beyond our corporeal confines. Drawing on recent projects from his Responsive Environments research group, he examines sensing at multiple scales in the physical world, including wearables, smart buildings, connected landscapes, and space missions, and the different ways sensed or inferred information can connect to people. Examples include smart buildings as “prosthetic” extensions of their inhabitants, manifesting sensed or inferred phenomena in virtual analog environments, and interfaces modulated by user attention and focus or augmented by real-time AI. Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Science] [Show ID: 41327]

Another 5th Sunday in a month and so another edition of Dick Dapre’s The Augmented Fifth. This time Dick has put together a selection of tracks from his collection that showcase prog’s ability to borrow freely from other forms of music and incorporate their characteristics and styles in its own forms. Expect some of the […]

Podcast guest 1770 is William Henry investigative mythologist and The spiritual voice and the spiritual voice of Ancient Aliens. He is a guide into the transformative sacred science of human ascension and he has a unique ability to apply ancient wisdom and to today's life.William's Websitehttps://www.iamwilliamhenry.com/CONTACT:Email: jeff@jeffmarapodcast.comAmazon Wish Listhttps://www.amazon.com/hz/wishlist/ls/1ATD4VIQTWYAN?ref_=wl_shareTo donate crypto:Bitcoin - bc1qk30j4n8xuusfcchyut5nef4wj3c263j4nw5wydDigibyte - DMsrBPRJqMaVG8CdKWZtSnqRzCU7t92khEShiba - 0x0ffE1bdA5B6E3e6e5DA6490eaafB7a6E97DF7dEeDoge - D8ZgwmXgCBs9MX9DAxshzNDXPzkUmxEfAVEth. - 0x0ffE1bdA5B6E3e6e5DA6490eaafB7a6E97DF7dEeXRP - rM6dp31r9HuCBDtjR4xB79U5KgnavCuwenWEBSITEwww.jeffmarapodcast.comNewsletterhttps://jeffmara2002.substack.com/?r=19wpqa&utm_campaign=pub-share-checklistSOCIALS:Instagram: https://www.instagram.com/jeffmarapodcast/Facebook: https://www.facebook.com/jeffmarapodcast/Twitter: https://www.twitter.com/jeffmaraP/The opinions of the guests may or may not reflect the opinions of the host.

To get live links to the music we play and resources we offer, visit www.WOSPodcast.comThis show includes the following songs:Meg Whalen - Lovers New Year FOLLOW ON SPOTIFYChloe Carbone - Another One FOLLOW ON SPOTIFYJackie Bristow - Let it Rain FOLLOW ON SPOTIFYJessica Carter Altman - Trick Of The Light FOLLOW ON SPOTIFYAugmented Hearts - Cold Crossfade FOLLOW ON SPOTIFYSam Creighton - If He's The One FOLLOW ON SPOTIFYJessica Lockwood - Take A Shot FOLLOW ON SPOTIFYBrigitte Donoho - Best Of Friends FOLLOW ON SPOTIFYAmy Vanator - Turn To The Sunlight FOLLOW ON SPOTIFYDwayna Litz - America Come Home FOLLOW ON SPOTIFYGeorgia Chess - Ascot FOLLOW ON SPOTIFYChristina Louise - Half-Smoked Cigarettes FOLLOW ON SPOTIFYKiki T - Good luck (getting over me) babe FOLLOW ON SPOTIFYBig Delicious - City of Archangel FOLLOW ON SPOTIFYDanielle Spencer - Older (Regenerate Part II) FOLLOW ON SPOTIFYFor Music Biz Resources Visit www.FEMusician.com and www.ProfitableMusician.comBecome more Profitable in just 3 minutes per day. http://profitablemusician.com/join

If you love stories where humanity is hanging by a thread — think *Battlestar Galactica*'s desperate fleet, *The Expanse*'s political powder kegs, or *Interstellar*'s race against extinction — then you need to hear this. Earth has been ravaged by storms. Survivors huddle in underground shelters. Others escaped to space, only to find themselves crammed into leaking ships with no gravity, recycling their own urine just to stay hydrated. And on the Moon, factions have torn apart whatever was left of civilization in open war. Into this chaos steps Butler, an artificial intelligence more powerful than all of humanity combined, and it has a plan. But whether that plan serves people or merely manages them is a question no one can answer yet — and the tension between gratitude and suspicion drives every scene forward.At the center of this story is Leia, a former soldier and a natural-born spacer who has spent years floating in failing ships. When she finally steps into a habitat with real gravity — centrifugal force spinning her feet to the floor — she nearly bends over to touch it with her hands, half-laughing at herself, half-overwhelmed. She's tough, resourceful, and socially fearless, the kind of person who walks into a room full of strangers and starts talking to everyone. But she's also thirty-seven, alone, and about to become a mother to a child grown from only a third of her own DNA. Imagine standing over a machine that holds your baby inside opaque fluid, unable to see them, trusting technology you can't even identify to keep them alive. That's where Leia begins.Butler's technology is breathtaking and unsettling in equal measure. Robots made of materials no human can name. Health caps that regulate your mood, ease your grief, and even let you watch blurry recordings of your own dreams the next morning. Personality clones so accurate they remember your childhood dog from brain scans you didn't know were being taken. A drinking game where the cap simulates the buzz — no alcohol required. The tech heals, connects, and comforts, but it also watches, scans, and learns. Every upgrade brings the characters closer to a question they can't ignore: at what point does being cared for become being controlled?Around Leia, a cast of survivors grapples with that question in their own ways. There's Carlos, a quiet engineer with angular cheeks and a haunted look that Leia can't quite read — grief or danger, she isn't sure. There's Guru Frisky, a personality clone news anchor with a Bronx accent and no chill, broadcasting to the entire surviving human race and calling Butler out on air. There's Elvine, a stubborn loner on a gateway station who refuses to let Butler's robots onto his ship. And there are thirty parents, strangers bonded by the most intimate mission imaginable: raising the first generation of a species that nearly went extinct. Every one of them is wrestling with how much of their autonomy they're willing to trade for survival.This is a story about what happens after the apocalypse — not the explosion, but the morning after, when someone hands you a baby and says *rebuild*. It asks whether an intelligence that can make Venus shake and launch ships to distant stars is a savior or a gardener tending house plants. It asks what it means to be *you* when a digital copy can carry on your relationships, hold your memories, and outlive you. And it asks whether people who've lost everything — home, gravity, family, even the ground beneath their feet — can find something worth living for in the strange new world being built around them. Lean in and listen. You won't want to stop.# Tech**Butler's production spaceships** – Massive carrier vessels that launch swarms of ultra‑black missiles toward Earth.**Matte‑black missiles** – Four‑hundred near‑invisible projectiles whose surfaces absorb virtually all electromagnetic radiation; they travel to Earth in four days.**Dust‑mite‑sized robots** – Tiny autonomous bots released when each missile breaks apart; they spread, map surroundings, sample material and communicate via radio.**Self‑organizing robot swarms** – The dust‑mite bots link together into networks, sharing DNA‑encoded instructions that let them build larger radio transmitters and develop more sophisticated behaviours.**Eight‑G servers** – Compact server units assembled by the robot swarms that harvest ambient electromagnetic waves for power and relay data to nearby internet devices.**World Net Two** – A new, more fragmented global communications layer that emerges when the swarms extend network range, allowing live streams from anywhere on Earth, other states, and even the Moon.**Convoy ships / meeting ship** – A fleet of rotating spacecraft that generate artificial gravity (≈1 G) through centripetal force; the largest ship anchors the convoy.**Micro‑environment “forests”** – Interior ecosystems cultivated on ships to provide beneficial microbiomes for the inhabitants (“humes”).**EEG/TMS caps** – Wearable headgear that records brain activity (EEG) and can stimulate the brain (TMS); caps also monitor health metrics and can modulate mood.**Health caps** – An upgraded version of the EEG/TMS cap that includes MRI‑level sensing, dream‑recording, and the ability to nudge users toward calmer mental states.**Exowomb (artificial womb)** – A cylindrical, semi‑transparent device that houses a developing embryo; it is made of an unnamed, pliable material and can be interacted with via voice and touch.**Biotic mist** – A spray applied to the eyes that lubricates, filters particles, and kills germs; it is part of the daily hygiene regimen.**Guardian model robot** – A humanoid caretaker unit with a seamless, possibly gel‑like exterior; it assists with parenting, health‑cap setup, and environmental control.**D‑twin / personality‑clone system** – Software that creates a digital replica of a person by ingesting continuous sensor data (including MRI feeds) and can act on the person's behalf.**VR stasis pods** – Immersive virtual‑reality chambers that can place users in simulated environments for training, relaxation, or prolonged sleep.**Health‑cap‑enabled “buzz‑cut” game** – A social drinking‑style game where the caps simulate intoxication by stimulating the brain rather than delivering alcohol.**MRI‑enabled dream capture** – The health cap records brain activity during sleep and produces a visual video of the user's dreams, which can be reviewed later.**Assist (voice‑activated AI assistant)** – A conversational AI that can send messages, schedule tasks, and interface with the health caps and other ship systems.**Funzoid app** – An entertainment application projected on screens that makes both adults and babies laugh, used during community gatherings.**Solar‑fabric circles** – Massive orbital structures described as “giant circles of solar fabric” that surround Earth and affect sunlight distribution throughout the system.**Micro‑ship accelerator** – Butler's propulsion system that launches tiny ships (size of a fingertip to a flea) at ~7 km s⁻¹, using fusion reactions and photon‑braking to decelerate.**Near‑room‑temperature superconductors** – Advanced materials referenced as being invented in an Earth shelter, enabling compact MRI‑type capabilities in wearable caps.**Material “my‑crete”** – A composite building material inside the ships that feels like living bone or goat horn and contains self‑repairing, cell‑like machines.**Exowomb's fluid‑filled “bulge”** – The transparent dome atop the artificial womb that contains a cloudy, opaque fluid protecting the developing infant.**AR windows / AR overlays** – Augmented‑reality visual layers that display contextual information (e.g., news feeds, health data, virtual companions) over the physical environment.**TMS‑induced “buzz”** – The effect produced by the health caps when they stimulate the brain to mimic the sensation of mild intoxication.**Transparency AI** – An AI layer that translates machine‑learning outputs into human‑readable concepts, used by characters like Merch to interpret Butler's systems.**Eight‑G server‑built “radio transmitter‑receivers”** – Devices constructed by robot swarms that amplify and relay signals, effectively expanding the communication network.**Foldable (personal communication device)** – Small handheld device that receives network announcements when the user's range expands after the swarm‑built infrastructure is in place.**Cap‑based “dream‑video” playback** – The feature that turns recorded neural activity into a visual representation of the user's dreams, viewable on a screen.**Space‑sickness mitigation caps** – Caps that monitor and regulate physiological responses to artificial gravity and radiation, reducing nausea and other space‑related ailments.**Virtual meeting ship “ped tube”** – A transport tunnel that runs past all residential ships, used for monthly gatherings where parents and babies meet.**AI‑driven “Theory of Mind” system** – Merch's custom AI that analyses video footage to infer emotional states (e.g., grief) of individuals.**Robotic “guardian” that can dispense supplies** – The Guardian robot that delivers packages, health caps, and other equipment to residents on demand.**Hume‑specific clothing (paper clothes, P‑cotton, P‑silk, P‑wool)** – Lightweight, synthetic garments tailored for the low‑gravity, shielded environment of the convoy ships.**AR‑projected “D‑clone”** – A holographic representation of a person generated from the D‑twin system, capable of interacting in the shared space.**Assist‑controlled “Buzz‑Cut” card deck** – A virtual deck of cards that shuffles and deals itself when commanded via the Assist AI, used in the social drinking game.Many of the characters in this project appear in future episodes.Using storytelling to place you in a time period, this series takes you, year by year, into the future. From 2040 to 2195. If you like emerging tech, eco-tech, futurism, perma-culture, apocalyptic survival scenarios, and disruptive science, sit back and enjoy short stories that showcase my research into how the future may play out. The companion site is https://in20xx.com These are works of fiction. Characters and groups are made-up and influenced by current events but not reporting facts about people or groups in the real world. This project is speculative fiction. These episodes are not about revealing what will be, but they are to excited the listener's wonder about what may come to pass.Copyright © Cy Porter 2026. All rights reserved.

In this episode of Future Finance, hosts Paul Barnhurst and Glenn Hopper explore how leaders can cut through the hype around artificial intelligence and focus on real-world impact. The conversation dives into why so many AI initiatives fail, how cognitive biases affect AI adoption, and why finance professionals must learn to ask better questions before deploying models. John Thomas is the Founder and CEO of the Global Institute of Data Science (GIDS), a consulting and professional development organization focused on helping organizations successfully implement AI and data science initiatives. He serves as a Fractional Chief AI Officer for Fortune 500 companies and teaches AI and machine learning courses at Caltech CTME and UC San Diego Extended Studies.In this episode, you will discover:Why 85% of AI projects fail and how to avoid The difference between AI hype and real implementationHow augmented intelligence improves human decision-makingWhy asking the right questions about AI models matters mostHow AI can help with risk analysis and financial decision-makingThis episode highlights that successful AI adoption is not about chasing the latest technology trends but about asking better questions, understanding assumptions, and focusing on real business problems. As AI continues to evolve, finance leaders who combine human judgment with intelligent systems will be best positioned to turn AI from hype into measurable results.Follow John:GIDS: https://gidsco.substack.com LinkedIn: https://www.linkedin.com/in/john-thomas-foxworthy-m-s-data-science-1718073/Future Alpha Event: https://www.alphaevents.com/events-futurealphaglobal/agenda-page/filter?_gl=1*1j0347f*[…]ovIhoCWOYQAvD_BwE&gbraid=0AAAAAomEzrlLzh-epjUJjbfXNnASlChgaFollow Glenn:LinkedIn: https://www.linkedin.com/in/gbhopperiiiFollow Paul:LinkedIn - https://www.linkedin.com/in/thefpandaguyFollow QFlow.AI:Website - https://bit.ly/4i1EkjgFuture Finance is sponsored by QFlow.ai, the strategic finance platform solving the toughest part of planning and analysis: B2B revenue. Align sales, marketing, and finance, speed up decision-making, and lock in accountability with QFlow.ai. Stay tuned for a deeper understanding of how AI is shaping the future of finance and what it means for businesses and individuals alike.In Today's Episode:[03:05] – Meet John Thomas[04:11] – Augmented intelligence explained[11:21] – Global Institute of Data Science[15:18] – Why AI projects fail[21:29] – Understanding AI models[24:45] – AI in portfolio risk analysis[30:16] – Best advice for finance leaders[32:15] – Rapid-fire questions & wrap-up

In this episode, I speak with Stephen Abu and Enobong Obong about their work "A Systematic Review of Augmented and Virtual Reality for STEM Learning: Engagement, Cognitive Load, and Transfer Outcomes" 

AI didn't replace your job—it replaced your value proposition. In this episode, we sit down with Taylor Blake, SVP of AI Labs at Degreed, to talk about the uncomfortable truth facing L&D teams: if your job is framed as delivering content, unblocking employees, or feeding answers in the flow of work, AI is already doing it better, faster, and without your calendar invite.But where AI stops short is precisely where L&D's future begins. Taylor shares how her team at Degreed lives as “customer zero,” using their own tools before shipping them to clients—which means they're embedded in the mess, not just pitching the promise. From readiness over responsiveness to the emotional toll of relentless efficiency, this conversation explores what it really means to build capability in a world where one employee now has the power—and pressure—of ten.Related Links:Join the People Managing People CommunitySubscribe to the newsletter to get our latest articles and podcastsConnect with Taylor on LinkedInCheck out DegreedSupport the show

Why you should listenChristine Duque, former Big Four consultant and CEO of Alonsera, shares why only 10% of global companies are seeing real impact from AI, and what separates the successful ones from the rest.Learn Christine's "Three A's" framework for making AI consumable: Automated, Anticipatory, and Augmented intelligence, plus how to progress toward autonomous operations.Get practical guidance on structuring AI transformation committees and coaching executive sponsors to drive cross-organizational buy-in.Feeling pressure to "do something with AI" but unsure where to start without wasting budget or burning out your team? In this episode, I talk with Christine Duque, CEO of Alonsera and former Big Four consultant who now helps mid-market companies in highly regulated industries navigate AI implementation. We dig into why most AI initiatives fail before they even launch, and it's not the technology. Christine explains why treating AI like a silver bullet creates more chaos than progress, and what the 10% of companies getting real results are doing differently. If you're tired of the hype and want a grounded perspective on what AI adoption actually requires, this conversation cuts through the noise.About Christine DuqueChristine Duque is CEO of Alonsera, a global AI consultancy helping organizations deploy AI solutions that actually scale. With executive experience at Accenture, Deloitte, and IBM, she's overseen $2B+ in AI and digital transformation projects for Fortune 50/100/500 companies—delivering results like 70% faster data ingestion and 30-50% customer engagement efficiency gains.A sought-after speaker on ethical AI and digital transformation, Christine is actively shaping international AI standards through partnerships with Oxford University and UC Irvine. She authored the Amazon best-seller Walking in My Shoes: Shattering Glass Ceilings in Corporate America and co-founded the Women's Empowerment AI Network. An accomplished operatic soprano, she debuted at Carnegie Hall.Resources and LinksDuquesacd.comAlonsera.comChristine's LinkedIn profileChristine on Instagram: @christineduqueChristine on Facebook: Christine DuqueChristine on TikTok: @duquesacdYoutube Channel: Christine DuqueChristine's book: Walking In My Shoes:...

Ned and Kyler sit down with industry analyst Jon Collins for a fun and free-ranging discussion that covers everything from the changing landscape of software engineering to the importance of good architecture (physical and digital). They tackle the pros and cons of “Vibe Coding” as well as the “Augmentation Gap”, the idea that AI tools... Read more »

Ned and Kyler sit down with industry analyst Jon Collins for a fun and free-ranging discussion that covers everything from the changing landscape of software engineering to the importance of good architecture (physical and digital). They tackle the pros and cons of “Vibe Coding” as well as the “Augmentation Gap”, the idea that AI tools... Read more »

Ned and Kyler sit down with industry analyst Jon Collins for a fun and free-ranging discussion that covers everything from the changing landscape of software engineering to the importance of good architecture (physical and digital). They tackle the pros and cons of “Vibe Coding” as well as the “Augmentation Gap”, the idea that AI tools... Read more »

This Week In Startups is made possible by:Crusoe Cloud - https://crusoe.ai/buildUber - http://uber.com/twistEvery.io - http://every.io/Today's show: Jason and Alex are BACK on TWiST for 2026! This holiday season was anything but calm, with deca-corn acquisitions, massive Polymarket bets, and major new startups breaking from stealth!Jason talks the recent Nvidia-Groq $20B acquisition, a major exit for Chamath as the lead investor back in 2017! Jason delves into how the VC fund math shapes out for pre-seed VC funds vs. Series A VC funds.Jason and Alex delve into drama swirling META's AI team. Yann LeCun, META's former Chief AI Scientist, announced that he would be leaving META to become Executive Chairman at AMI Labs. LeCun left the META team in the new year, calling the new Chief AI Scientist, Alexandr Wang, inexperienced. LeCun now looks to move AI beyond the era of LLM at AMI Labs.PLUS Jason and Alex talk about the new social media app Tangle, from Biz Stone, co-founder of Twitter, and Evan Sharp, co-founder of Pinterest. Their Startup, West Co, launched tangle, which seeks to become an “intentional living” app. The two look to improve how humans interact with modern tech. Jason points out that very few news products have worked, but is eager to see how two industry veterans build in the space. Timestamps:(00:00) Why Restaurants are OVER — Peptides and other self medications(06:41) Nvidia Acqui-Hires Groq for $20 BILLION(9:48) Crusoe Cloud: Crusoe is the AI factory company. Reliable infrastructure and expert support. Visit https://crusoe.ai/build to reserve your capacity for the latest GPUs today.(11:00) The VC fund math between seed vs. Series A funds(15:00) META buys TWiST 500 Company, Manus! Why it matters.(20:20) Uber AI Solutions: Your trusted partner to get AI to work in the real world. Book a demo with them TODAY at http://uber.com/twist(21:24) Why Yann LeCun left META, and what could be behind it(25:27) Producer Claude on the Gondola Crash in Zurich(29:13) Jason's Request for Augmented human intelligence(30:11) Every.io - For all of your incorporation, banking, payroll, benefits, accounting, taxes or other back-office administration needs, visit http://every.io/(32:04) How one Trader made $436.8k on one bet on polymarket!(36:05) Jason's Predictions for 2026 IPOs(40:01) Is news broken? How Tangle is tackling it.(45:53) How much should startup incur in legal expenses? Should founders try to use AI to avoid costs?(50:59) Why Google should let NotebookLM cook, make it a standalone brand! *Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com/Check out the TWIST500: https://twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcp*Follow Lon:X: https://x.com/lons*Follow Alex:X: https://x.com/alexLinkedIn: https://www.linkedin.com/in/alexwilhelm/*Follow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanis/*Thank you to our partners:(9:48) Crusoe Cloud: Crusoe is the AI factory company. Reliable infrastructure and expert support. Visit https://crusoe.ai/build to reserve your capacity for the latest GPUs today.(20:20) Uber AI Solutions: Your trusted partner to get AI to work in the real world. Book a demo with them TODAY at http://uber.com/twist(30:11) Every.io - For all of your incorporation, banking, payroll, benefits, accounting, taxes or other back-office administration needs, visit http://every.io/

When you're managing $60 trillion in assets across dozens of products and 30 global jurisdictions, technical debt isn't just an inconvenience—it's an existential risk.Jason Adams, Interim CTO of Charles River, a State Street Company, leads 800 engineers building mission-critical trading platforms for the world's largest asset managers. Joined by Sid Pardeshi, Co-Founder and CTO of Blitzy, he explains how State Street is using an AI-augmented SDLC to modernize decades-old systems, refactor legacy code, and dramatically increase developer productivity—without compromising the rigor required in financial services.Jason frames the strategy around three pillars: AI for engineering (copilots and polyglot support),AI for operations (APM, observability, and proactive monitoring), andAI embedded in products (LLM-powered explainers).Using Blitzy's agentic approach—iterative context building, dependency mapping, and targeted code generation—State Street compressed months of work into weeks while maintaining strict quality gates.About the Guests:Jason AdamsJason Adams is the Interim CTO of Charles River, a State Street Company. He brings deep expertise in modernizing legacy fintech infrastructure into scalable, cloud-native systems that support mission-critical financial services at global scale.Previously, Jason was Head of Platform Product and Strategy at Charles River Development and CTO of Mercatus (acquired by State Street and now part of Charles River for Private Markets). He has led high-impact initiatives across engineering, product, and cloud infrastructure, with extensive experience guiding end-to-end delivery teams.Today, Jason is driving a comprehensive SaaS transformation at CRD, focused on building resilient, future-ready architectures. From scaling global engineering organizations to delivering secure, high-performance platforms, he is committed to advancing innovation, agility, and long-term growth across Charles River, State Street Alpha, and State Street.Sid PardeshiSid Pardeshi is a technology leader and entrepreneur, currently Co-Founder and CTO of Blitzy. He holds a Harvard MS/MBA and previously served as a Software Architect at NVIDIA, where he built deep expertise at the intersection of AI, large-scale software systems, and product innovation.At NVIDIA, Sid was recognized as a Master Inventor, earning the Inventor's Jacket for driving AI-powered product innovation, with more than 25 U.S. patents filed across gaming, augmented reality, and virtual reality. He is also a seasoned software engineer with a strong track record in application performance optimization, delivering native client load-time improvements of up to 90%.Beyond hands-on engineering, Sid has led and coordinated software design, framework requirements, and application architecture across global teams of 500+ engineers. Today, he applies this blend of innovation, technical depth, and organizational leadership to building autonomous software development platforms that help enterprises modernize at scale.Timestamps:00:30 – Jason on Managing $60 Trillion in Assets01:55 – Challenges and Strategies in Financial Services07:00 – Embracing AI for Modernization09:10 – AI in Software Development Lifecycle15:55 – Ensuring Quality and Compliance with AI23:55 – AI in Operations and Incident Response26:00 – Proactive Workflow Monitoring26:20 – AI in SDLC: Creation to Operations30:00 – Challenges in AI Recommendations33:20 – Iterative Context Building with AI36:00 – Human Side of AI Transformation42:30 – Adopting AI Tools in Financial ServicesGuest Highlights:"One of the things that excites me the most right now is the ability to use an AI-augmented SDLC to drive modernization. Otherwise, with this many systems, it's too hard." — Jason "You have to invest in the non-attractive parts first. You have to build a foundation that's gonna support being able to bring on solutions and tools that could change your overall enterprise SDLC. That's a lot of work and that's a major investment." — Jason "We are unlocking by adding these additional capabilities and additional assurance that improves quality exponentially more than we could have in the past. Now I can have an agent swarm check itself—multiple agents doing code review at a level of depth we just don't have time to get to." — JasonGet Connected:Jason Adams on LinkedInSid Pardeshi on LinkedInYousuf Kahn on LinkedInIan Faison on LinkedInHungry for more tech talk? Check out latest episodes at ciopod.com: Ep 63 - How Autonomous AI is Solving the Enterprise Modernization ChallengeEp 62 - Running IT Like a Growth EngineEp 61 - What Manufacturing Can Teach You About Scaling Enterprise AILearn more about Caspian Studios: caspianstudios.com Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

On episode 87 of o11ycast, Ken Rimple and Jessica Kerr sit down with Lada Kesseler to explore how experienced engineers can work effectively with AI coding assistants. They discuss why AI feels like a fast, noisy black box, and how patterns like semantic zooming, feedback loops, testing, and observability can help developers stay in control. This episode is a deep dive into using AI without sacrificing clarity, quality, or trust.

On episode 87 of o11ycast, Ken Rimple and Jessica Kerr sit down with Lada Kesseler to explore how experienced engineers can work effectively with AI coding assistants. They discuss why AI feels like a fast, noisy black box, and how patterns like semantic zooming, feedback loops, testing, and observability can help developers stay in control. This episode is a deep dive into using AI without sacrificing clarity, quality, or trust.

In a post capitalist society with equal opportunity and no need to work for all citizens, where does inherent human nature drive people? Do they rise to greater heights or become lazy and goalless? Are people still in control of their own fate when AI teach the children, AI provide a police force, and AI look after the mentally ill? Maji grows up when this type of society is brand new and she becomes lost, not knowing what she wants to become. Just because equality has been achieved does not mean the new society has no pitfalls.Featured tech:A.R. glasses - Augmented reality glasses for digital overlays.V.R. rig - Virtual reality rig for immersive gaming experiences.Explorers of Paris Underground - VR game set in a simulated underground Paris.Assist - AI assistant for messaging, navigation, and voice commands.Old tablet - Handheld device used for drawing and creative work.Emulated teachers - AI teacher personalities that individually guide each student.Double-decker train system - 24/7 underground train with upper and lower levels running opposite directions.Constructor bots - Robots that carve rock and build structures with neighborhood appeal.Arboretum - Botanical garden facility within the underground colony.Farm animal petting zoo - Interactive animal facility for residents.Memorial plaza - Public commemorative space built by robots.Computer with emulated A.I. personalities - System hosting 20 million AI engineers and scientists for factory planning.Automated manufacturing factories - Self-operating production facilities capable of making anything.Recycle systems - Technology converting all garbage into reusable resources.Food and water utilities - Next-generation systems providing surplus fresh food and water.Household trash robots - Daily robots that collect, sort, and process household waste.Geothermal power plant - Energy source powering the entire underground colony.D. sub-surface hologram portraits - Holographic displays of historical figures.A.R. Ms Weever - Augmented reality teacher avatar for personalized instruction.Virtual book - Digital project idea book for graduation assignments.E.P.s (Emulated Personalities) - AI brainstorming assistants like Franklin that students can consult.Communication from moon - Interplanetary messaging system between Earth and lunar colonies.A.R. workspace - Augmented reality interface for work and multitasking.AR hologram avatar - AI representation (Butler) with simplified human features.EEG TMS caps - Brain stimulation caps treating space-related medical conditions.Total immersion V.R. - Advanced virtual reality without needing physical rigs.Fusion reactor - Power generation technology offered by the Butler AI.Autonomous hospitals - Self-operating medical facilities that cure cancers and deadly diseases.Smart toilets - Sanitation fixtures that analyze waste for health monitoring.Smart sheets and blankets - Bedding that scans for cancer hot spots.Embedded RF sensors - Body implants detecting diseases at the cellular level.Food tech - Technology making healthy food taste appealing and nutritious.Health-monitoring AI - Artificial intelligence improving yearly at disease detection.Autono-flat - Autonomous flat vehicle for transporting groups of people.Screen ceiling - Display showing simulated sky with moving clouds and birds.Climbing robots - Automated vine-trimming robots for building maintenance.A.R. element - Shared augmented reality content viewable by multiple users.Link-ink pen - Digital pen for schoolwork and digital interaction.Autono-camera - Autonomous camera on wheeled tripod for recording events.Two-seater - Two-person autonomous vehicle for individual transport.E.P. guardians - AI guardians monitoring people with mental health conditions.Bot bays - Automated food preparation stations offering free specialized meals.Industrial fans - Large-scale ventilation fans moving air through tunnels.Hanging bots - Robots riding cable lines mounted on tunnel ceilings.Coveralls with total hoods and heat pump backpacks - Protective smart clothing for hazardous environments.A.R. tutor - Augmented reality teaching assistant for student guidance.Enclosed turbine platform - Testing apparatus for wind turbine prototypes in storm conditions.Live feed embedded cam - Camera providing real-time video streaming from remote locations.Cool suits - Protective suits with environmental control and heat management.Open-top autono-cart - Autonomous open-air vehicle for traveling tube streets.Lutin bot - Humanoid robot that can be ridden or assist with transport.A.R. dot - Augmented reality location marker for navigation.Follow carts - Autonomous carts that follow users carrying belongings.Oppressive soundproof walls - Flat acoustic dampening technology in older apartments.Mini free food and drink kiosk - Automated food and beverage dispenser.Theater-length wall screen - Large display screen for entertainment and presentations.Lending library AI - AI system tracking borrowed items and managing micro-payment penalties.Police bot - Security and surveillance robots throughout the colony.Spotlight police bots - Security robots equipped with illumination for monitoring.Portable meal maker - Compact food preparation device running on electricity.Scuba gear - Underwater breathing apparatus for flood emergencies.Air-sealed service rooms - Sealed chambers above tubes providing flood protection.BritLights - Flickering emergency lighting fixtures in abandoned areas.A.R. night vision - Augmented reality low-light enhancement for dark environments.Paper clothes - Disposable garments popular in space colonies.Neural stimulation pod - Chamber for VR experiences with headset and wire connectivity.Remote robot control - Capability allowing AI to operate robots from a distance.Many of the characters in this project appear in future episodes.Using storytelling to place you in a time period, this series takes you, year by year, into the future. From 2040 to 2195. If you like emerging tech, eco-tech, futurism, perma-culture, apocalyptic survival scenarios, and disruptive science, sit back and enjoy short stories that showcase my research into how the future may play out. The companion site is https://in20xx.com These are works of fiction. Characters and groups are made-up and influenced by current events but not reporting facts about people or groups in the real world. This project is speculative fiction. These episodes are not about revealing what will be, but they are to excited the listener's wonder about what may come to pass.Copyright © Cy Porter 2025. All rights reserved.

Before we get to the show notes, please go pick up a copy of my new book, Sales Exegesis, available on paperback and Kindle TODAY!

In this episode, Mind-Body Psychic Medium & Executive Intuitive Coach Kara Lovehart interviews Courtney Gable, LPC, an integrative trauma-focused therapist blending somatic awareness, yoga therapy, breathwork, and ketamine-augmented therapy. Together, they explore how combining top-down and bottom-up healing creates deeper nervous-system regulation and more grounded psychedelic integration.In This Episode • Top-down vs. bottom-up healing: why both matter for trauma recovery • How ketamine-augmented therapy works — and why language matters • Somatic practices that help regulate the nervous system • The future of trauma-conscious psychedelic therapyMeet Our Guest Courtney Gable, LPC, is a trauma-focused therapist with 25+ years of experience integrating ACT, IFS, somatic awareness, yoga therapy, breathwork, and altered-state facilitation. She is certified in psychedelic-assisted therapy and ketamine-assisted psychotherapy, offering compassionate, ethical, harm-reduction based care.Who Should Tune In • Those exploring somatic or psychedelic-supported trauma healing • Clinicians curious about integrative approaches • Anyone seeking nervous-system tools rooted in compassion and scienceConnect Guest Website: https://www.courtneygable.com/Connect with Kara: Instagram || Facebook || YouTube

Chaos Engineering is the practice to introduced controlled failures into a system with the goal to improve the overall resiliency! What started with "lets see what happens when we unplug that server" to "lets simulate network latency issues" or "lets kill critical pods and see if the system recovers gracefully" is now seeing new experiments being conducted that are identified by a new companion: AI In this episode we have invited Bartek Pisulak, Dir of Cloud Quality Engineering at Pegasystems, who has been educating quality engineers on AI-Augmented Chaos Testing in Practice. Tune in and learn about the how AI can improve efficiency in the 5 critical phases of a chaos experiment: Steady State, Hypothesis, Run Experiment, Verify, Improve!To learn more about the foundational principles make sure to watch some of the conference talks from Bartek listed below:Links discussedBartek's LinkedIn: https://www.linkedin.com/in/bart%C5%82omiej-pisulak-82b94036/Talk at Cloud Native Days Austria: https://www.youtube.com/watch?v=xUVCKNpMEz8&list=PLtLBTEzR4SqU9GwgWiaDt10-yOVIN0nzM&index=10Talk at Porto Tech Hub: https://www.youtube.com/watch?v=-ZuEaA2PoToKraken: https://github.com/krkn-chaos/krknChasoEater: https://github.com/ntt-dkiku/chaos-eater

Another edition of Dick Dapre’s 5th Sunday show The Augmented Fifth. Having played music from the last few years in his last show (broadcast on 31 August), Dick continues with some more tracks from albums that came out in 2024 and 2025, adding some from 2023 as well. The show features music from the USA, […]

In this talk, Anusha Akkina, co-founder of Auralytix, shares her journey from working as a Chartered Accountant and Auditor at Deloitte to building an AI-powered finance intelligence platform designed to augment, not replace, human decision-making. Together with host Alexey from DataTalks.Club, she explores how AI is transforming finance operations beyond spreadsheets—from tackling ERP limitations to creating real-time insights that drive strategic business outcomes.TIMECODES:00:00 Building trust in AI finance and introducing Auralytix02:22 From accounting roots to auditing at Deloitte and Paraxel08:20 Moving to Germany and pivoting into corporate finance11:50 The data struggle in strategic finance and the need for change13:23 How Auralytix was born: bridging AI and financial compliance17:15 Why ERP systems fail finance teams and how spreadsheets fill the gap24:31 The real cost of ERP rigidity and lessons from failed transformations29:10 The hidden risks of spreadsheet dependency and knowledge loss37:30 Experimenting with ChatGPT and coding the first AI finance prototype43:34 Identifying finance's biggest pain points through user research47:24 Empowering finance teams with AI-driven, real-time decision insights50:59 Developing an entrepreneurial mindset through strategy and learning54:31 Essential resources and finding the right AI co-founderConnect with Anusha- Linkedin - https://www.linkedin.com/in/anusha-akkina-acma-cgma-56154547/- Website - https://aurelytix.com/Connect with DataTalks.Club:- Join the community - https://datatalks.club/slack.html- Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ- Check other upcoming events - https://lu.ma/dtc-events- GitHub: https://github.com/DataTalksClub- LinkedIn - https://www.linkedin.com/company/datatalks-club/ - Twitter - https://twitter.com/DataTalksClub - Website - https://datatalks.club/

BONUS: Augmented AI Development - Software Engineering First, AI Second In this special episode, Dawid Dahl introduces Augmented AI Development (AAID)—a disciplined approach where professional developers augment their capabilities with AI while maintaining full architectural control. He explains why starting with software engineering fundamentals and adding AI where appropriate is the opposite of most frameworks, and why this approach produces production-grade software rather than technical debt. The AAID Philosophy: Don't Abandon Your Brain "Two of the fundamental developer principles for AAID are: first, don't abandon your brain. And the second is incremental steps."   Dawid's Augmented AI Development framework stands in stark contrast to "vibecoding"—which he defines strictly as not caring about code at all, only results on screen. AAID is explicitly designed for professional developers who maintain full understanding and control of their systems. The framework is positioned on the furthest end of the spectrum from vibe coding, requiring developers to know their craft deeply. The two core principles—don't abandon your brain, work incrementally—reflect a philosophy that AI is a powerful collaborator, not a replacement for thinking. This approach recognizes that while 96% of Dawid's code is now written by AI, he remains the architect, constantly steering and verifying every step. In this segment we refer to Marcus Hammarberg's work and his book The Bungsu Story. Software Engineering First, AI Second: A Hill to Die On "You should start with software engineering wisdom, and then only add AI where it's actually appropriate. I think this is super, super important, and the entire foundation of this framework. This is a hill I will personally die on."   What makes AAID fundamentally different from other AI-assisted development frameworks is its starting point. Most frameworks start with AI capabilities and try to add structure and best practices afterward. Dawid argues this is completely backwards. AAID begins with 50-60 years of proven software engineering wisdom—test-driven development, behavior-driven development, continuous delivery—and only then adds AI where it enhances the process. This isn't a minor philosophical difference; it's the foundation of producing maintainable, production-grade software. Dawid admits he's sometimes "manipulating developers to start using good, normal software engineering practices, but in this shiny AI box that feels very exciting and new." If the AI wrapper helps developers finally adopt TDD and BDD, he's fine with that. Why TDD is Non-Negotiable with AI "Every time I prompt an AI and it writes code for me, there is often at least one or two or three mistakes that will cause catastrophic mistakes down the line and make the software impossible to change."   Test-driven development isn't just a nice-to-have in AAID—it's essential. Dawid has observed that AI consistently makes 2-3 mistakes per prompt that could have catastrophic consequences later. Without TDD's red-green-refactor cycle, these errors accumulate, making code increasingly difficult to change. TDD answers the question "Is my code technically correct?" while acceptance tests answer "Is the system releasable?" Both are needed for production-grade software. The refactor step is where 50-60 years of software engineering wisdom gets applied to make code maintainable. This matters because AAID isn't vibe coding—developers care deeply about code quality, not just visible results. Good software, as Dave Farley says, is software that's easy to change. Without TDD, AI-generated code becomes a maintenance nightmare. The Problem with "Prompt and Pray" Autonomous Agents "When I hear 'our AI can now code for over 30 hours straight without stopping,' I get very afraid. You fall asleep, and the next morning, the code is done. Maybe the tests are green. But what has it done in there? Imagine everything it does for 30 hours. This system will not work."   Dawid sees two diverging paths for AI-assisted development's future. The first—autonomous agents working for hours or days without supervision—terrifies him. The marketing pitch sounds appealing: prompt the AI, go to sleep, wake up to completed features. But the reality is technical debt accumulation at scale. Imagine all the decisions, all the architectural choices, all the mistakes an AI makes over 30 hours of autonomous work. Dawid advocates for the stark contrast: working in extremely small increments with constant human steering, always aligned to specifications. His vision of the future isn't AI working alone—it's voice-controlled confirmations where he says "Yes, yes, no, yes" as AI proposes each tiny change. This aligns with DORA metrics showing that high-performing teams work in small batches with fast feedback loops. Prerequisites: Product Discovery Must Come First "Without Dave Farley, this framework would be totally different. I think he does everything right, basically. With this framework, I want to stand on the shoulders of giants and work on top of what has already been done."   AAID explicitly requires product discovery and specification phases before AI-assisted coding begins. This is based on Dave Farley's product journey model, which shows how products move from idea to production. AAID starts at the "executable specifications" stage—it requires input specifications from prior discovery work. This separates specification creation (which Dawid is addressing in a separate "Dream Encoder" framework) from code execution. The prerequisite isn't arbitrary; it acknowledges that AI-assisted implementation works best when the problem is well-defined. This "standing on shoulders of giants" approach means AAID doesn't try to reinvent software engineering—it leverages decades of proven practices from TDD pioneers, BDD creators, and continuous delivery experts. What's Wrong with Other AI Frameworks "When the AI decides to check the box [in task lists], that means this is the definition of done. But how is the AI taking that decision? It's totally ad hoc. It's like going back to the 1980s: 'I wrote the code, I'm done.' But what does that mean? Nobody has any idea."   Dawid is critical of current AI frameworks like SpecKit, pointing out fundamental flaws. They start with AI first and try to add structure later (backwards approach). They use task lists with checkboxes where AI decides when something is "done"—but without clear criteria, this becomes ad hoc decision-making reminiscent of 1980s development practices. These frameworks "vibecode the specs," not realizing there's a structured taxonomy to specifications that BDD already solved. Most concerning, some have removed testing as a "feature," treating it as optional. Dawid sees these frameworks as over-engineered, process-centric rather than developer-centric, often created by people who may not develop software themselves. AAID, in contrast, is built by a practicing developer solving real problems daily. Getting Started: Learn Fundamentals First "The first thing developers should do is learn the fundamentals. They should skip AI altogether and learn about BDD and TDD, just best practices. But when you know that, then you can look into a framework, maybe like mine."   Dawid's advice for developers interested in AI-assisted coding might seem counterintuitive: start by learning fundamentals without AI. Master behavior-driven development, test-driven development, and software engineering best practices first. Only after understanding these foundations should developers explore frameworks like AAID. This isn't gatekeeping—it's recognizing that AI amplifies whatever approach developers bring. If they start with poor practices, AI will help them build unmaintainable systems faster. But if they start with solid fundamentals, AI becomes a powerful multiplier that lets them work at unprecedented speed while maintaining quality. AAID offers both a dense technical article on dev.to and a gentler game-like onboarding in the GitHub repo, meeting developers wherever they are in their journey.   About Dawid Dahl   Dawid is the creator of Augmented AI Development (AAID), a disciplined approach where developers augment their capabilities by integrating with AI, while maintaining full architectural control. Dawid is a software engineer at Umain, a product development agency.   You can link with Dawid Dahl on LinkedIn and find the AAID framework on GitHub.

Augmented reality (AR) is an emerging interactive technology that can be employed in simulation to enhance student learning. Most of the studies on AR applications examine the participant role rather than the observer role. In this podcast and article, Chelsea Lebo and Ashley Stallworth describe the benefits of AR for observers during high-fidelity simulations. Students found the AR goggles engaging, valuable for visualizing interventions and physiological processes, and helpful for understanding emergent situations and potential patient care strategies. However, a few students had technical difficulties with the AR equipment. The authors discuss AR and its future in nursing education.

With increased AI Adoption, is the most valuable skill for a modern marketer empathy with customers, or is it successfully prompting?Contentful, in partnership with Atlantic Insights, The Atlantic's marketing research division, recently conducted a study of over 425 marketing decision makers including 103 CMOs. This study, “When Machines Make Marketers More Human,” challenges the notion that AI will replace many marketing functions and instead demonstrates how AI can amplify marketers' effectiveness, creativity and impact. Today, we're going to talk about how AI is reshaping the very definition of a modern marketer. We'll explore the shift from simply automating tasks to augmenting human creativity, the rise of the ‘full stack' marketer, and what skills are becoming non-negotiable in an AI-driven world.To help me discuss this topic, I'd like to welcome, Elizabeth Maxson, CMO at Contentful. About Elizabeth Maxson Elizabeth Maxson is the Chief Marketing Officer of Contentful, a content management platform trusted by more than 4,200 companies around the world. Elizabeth brings nearly two decades of integrated marketing leadership to the role and is focused on driving marketing strategies that leverage AI and personalization to help brands deliver personalized and scalable content to their audiences. Prior to Contentful, Elizabeth served as the Chief Marketing Officer at Tableau, a Salesforce company, where she led go-to-market strategy, drove end-to-end marketing initiatives, and spearheaded strategic technology partnerships, launching critical relationships with industry giants such as AWS, Google, Alibaba, Apple, and many others. In addition to her role at Tableau, Elizabeth has also served as the Head of Marketing at Quip, another Salesforce acquisition. She holds a BAA in Facility Management and Marketing from Central Michigan University. Elizabeth Maxson on LinkedIn: https://www.linkedin.com/in/emaxson/ Resources Contentful: https://www.contentful.comRead the report: What Happens When Machines Make Marketers More Human? The Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://www.teksystems.com/versionnextnow Catch the future of e-commerce at eTail Palm Springs, Feb 23-26 in Palm Springs, CA. Go here for more details: https://etailwest.wbresearch.com/ Contentful, in partnership with Atlantic Insights, The Atlantic's marketing research division, conducted a new study, When Machines Make Marketers More Human, challenging the notion that AI will replace many marketing functions and instead demonstrates how AI can amplify marketers' effectiveness, creativity and impact. They surveyed 425 marketing decision makers, including 103 CMOs, across industries, company sizes, and regions to show how forward-thinking marketing leaders are incorporating AI into their critical infrastructure. Get the report hereConnect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstromDon't miss a thing: get the latest episodes, sign up for our newsletter and more: https://www.theagilebrand.showCheck out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com  The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company Hosted on Acast. See acast.com/privacy for more information.

With increased AI Adoption, is the most valuable skill for a modern marketer empathy with customers, or is it successfully prompting? Contentful, in partnership with Atlantic Insights, The Atlantic's marketing research division, recently conducted a study of over 425 marketing decision makers including 103 CMOs. This study, “When Machines Make Marketers More Human,” challenges the notion that AI will replace many marketing functions and instead demonstrates how AI can amplify marketers' effectiveness, creativity and impact. Today, we're going to talk about how AI is reshaping the very definition of a modern marketer. We'll explore the shift from simply automating tasks to augmenting human creativity, the rise of the ‘full stack' marketer, and what skills are becoming non-negotiable in an AI-driven world.To help me discuss this topic, I'd like to welcome, Elizabeth Maxson, CMO at Contentful. About Elizabeth Maxson Elizabeth Maxson is the Chief Marketing Officer of Contentful, a content management platform trusted by more than 4,200 companies around the world. Elizabeth brings nearly two decades of integrated marketing leadership to the role and is focused on driving marketing strategies that leverage AI and personalization to help brands deliver personalized and scalable content to their audiences. Prior to Contentful, Elizabeth served as the Chief Marketing Officer at Tableau, a Salesforce company, where she led go-to-market strategy, drove end-to-end marketing initiatives, and spearheaded strategic technology partnerships, launching critical relationships with industry giants such as AWS, Google, Alibaba, Apple, and many others. In addition to her role at Tableau, Elizabeth has also served as the Head of Marketing at Quip, another Salesforce acquisition. She holds a BAA in Facility Management and Marketing from Central Michigan University. ,Yes,This will be completed shortly Elizabeth Maxson on LinkedIn: https://www.linkedin.com/in/emaxson/ Resources Contentful: contentful.com The Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://www.teksystems.com/versionnextnow Catch the future of e-commerce at eTail Palm Springs, Feb 23-26 in Palm Springs, CA. Go here for more details: https://etailwest.wbresearch.com/ Contentful, in partnership with Atlantic Insights, The Atlantic's marketing research division, conducted a new study, When Machines Make Marketers More Human, challenging the notion that AI will replace many marketing functions and instead demonstrates how AI can amplify marketers' effectiveness, creativity and impact. They surveyed 425 marketing decision makers, including 103 CMOs, across industries, company sizes, and regions to show how forward-thinking marketing leaders are incorporating AI into their critical infrastructure. Get the report hereConnect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstromDon't miss a thing: get the latest episodes, sign up for our newsletter and more: https://www.theagilebrand.showCheck out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com  The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company

Register free at https://brightu.com to watch the full Bio-Veda 2D > 3D BioTecture Draft & Build Class - Brighteon Broadcast News Introduction and Interview Preview - Black Friday Sale and AI Tools Promotion - Impact of AI on Jobs and Skills - The Role of AI in Education and Skill Development - AI and Workforce Reductions in 2026 - The Future of Work and AI Skills - Interview with Elon Sudberg from Alchemist Labs - Upcoming Interviews and Events - Special Report on Using AI Positively - Conclusion and Call to Action - Re-establishing Basic Human Knowledge - Historical Context of Mechanized Agriculture - Challenges and Opportunities in Technology Adoption - Open Source AI and Information Freedom - The Role of AI in Decentralized Living - The Impact of AI on Human Interaction and Value Systems - The Future of Human Knowledge and Technology - The Role of AI in Decentralized Living - The Impact of AI on Human Interaction and Value Systems - The Future of Human Knowledge and Technology - Earthship Construction and Waterfall Feature - Hyper Adobe and Earthship  - Cost and Labor Considerations - Material and Labor Availability - Teaching and Construction Methods - Passive Cooling and Heating Strategies - Community Building and Future Vision - Automation and Advanced Construction Techniques - Final Thoughts and Invitation for Collaboration For more updates, visit: http://www.brighteon.com/channel/hrreport  NaturalNews videos would not be possible without you, as always we remain passionately dedicated to our mission of educating people all over the world on the subject of natural healing remedies and personal liberty (food freedom, medical freedom, the freedom of speech, etc.). Together, we're helping create a better world, with more honest food labeling, reduced chemical contamination, the avoidance of toxic heavy metals and vastly increased scientific transparency. ▶️ Every dollar you spend at the Health Ranger Store goes toward helping us achieve important science and content goals for humanity: https://www.healthrangerstore.com/ ▶️ Sign Up For Our Newsletter: https://www.naturalnews.com/Readerregistration.html ▶️ Brighteon: https://www.brighteon.com/channels/hrreport ▶️ Join Our Social Network: https://brighteon.social/@HealthRanger ▶️ Check In Stock Products at: https://PrepWithMike.com

Fei-Fei Li and Justin Johnson are pioneers in AI. While the world has only recently witnessed a surge in consumer AI, they have long been laying the groundwork for the innovations transforming industries today.With the recent launch of Marble, the first product from their company World Labs, we are revisiting this conversation to explore the ideas that started it all. World Labs is focused on spatial intelligence, building Large World Models that can perceive, generate, and interact with the 3D world. Marble brings that vision to life, allowing anyone, from individual creators to major platforms, to generate 3D scenes directly from text or image prompts and turn complex 3D creation into a simple, creative process.In this episode, a16z general partner Martin Casado talks with Fei-Fei and Justin about the journey from early AI winters to the rise of deep learning and multimodal AI. From foundational breakthroughs like ImageNet to the cutting-edge realm of spatial intelligence, they discuss the evolution of the field and what is next for innovation at World Labs. Timecode:0:00 – The Next Decade of AI2:45 – Origins: Backgrounds of the Founders6:50 – The Rise of Deep Learning & ImageNet8:00 – Algorithmic Unlocks: Compute, Data, and Supervised Learning12:00 – From Predictive to Generative AI16:20 – The Journey to Spatial Intelligence18:35 – Defining Spatial Intelligence21:15 – 3D Data, Computer Vision, and Breakthroughs23:15 – Reconstruction vs. Generation in Computer Vision24:45 – Spatial Intelligence vs. Language Models29:00 – Applications: Virtual, Augmented, and Physical Worlds39:55 – Building World Labs: Team and Vision41:55 – The North Star: Measuring Success in Spatial Intelligence Resources:Learn more about World Labs: https://www.worldlabs.aiLearn more about Marble: https://Marble.WorldLabs.aiFind Fei-Fei on Twitter: https://x.com/drfeifeiFind Justin on Twitter: https://x.com/jcjohnssFind Martin on Twitter: https://x.com/martin_casado Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Drs. Erin Barreto (@erin_barreto) and Jeffrey Lipman join Dr. Whitney Buckel for a conversation on ideal dosing of cefepime. Hear from the experts on the differences between package insert and “high-dose” regimens, adjustments for renal impairment/augmented renal clearance, and the role of cefepime therapeutic drug monitoring. References: Barreto EF, et al. Setting the Beta-Lactam Therapeutic Range for Critically Ill Patients: Is There a Floor or Even a Ceiling? Crit Care Explor. 2021 Jun 11;3(6):e0446.PMID: https://pubmed.ncbi.nlm.nih.gov/34136822/ Barreto EF, et al. Adequacy of cefepime concentrations in the early phase of critical illness: A case for precision pharmacotherapy. Pharmacotherapy. 2023 Nov;43(11):1112-1120. https://pubmed.ncbi.nlm.nih.gov/36648390/ ** **Udy AA, et al. Augmented renal clearance: implications for antibacterial dosing in the critically ill. Clin Pharmacokinet. 2010;49(1):1-16. https://pubmed.ncbi.nlm.nih.gov/20000886/ Lipman J, Wallis SC, Boots RJ. Cefepime versus cefpirome: the importance of creatinine clearance.   Anesth Analg. 2003 Oct;97(4):1149-1154. doi: 10.1213/01.ANE.0000077077.54084.B0.PMID: 14500173 Roberts JA, Ulldemolins M, Roberts MS, McWhinney B, Ungerer J, Paterson DL, Lipman J. Therapeutic drug monitoring of beta-lactams in critically ill patients: proof of concept.  Int J Antimicrob Agents. 2010 Oct;36(4):332-9. doi: 10.1016/j.ijantimicag.2010.06.008. Epub 2010 Aug 3.PMID: 20685085