Podcasts about ai ml

The international business group RedCore invites SIGMA Rome participants to meet their investment team, who will also be present at the conference stand. RedCore specialists will be delighted to meet and discuss potential partnerships with representatives of promising projects from November 3 to 6. RedCore invites anyone interested in investing in a business group that combines technology products and services for digital markets to visit booth 1045. RedCore at SIGMA Rome "SIGMA Rome is the perfect place to meet teams that are changing the future of technology. We are looking for projects in the areas of iGaming, MarTech, FinTech, Web3, AI/ML, and technology analytics," comments Ihor Denysov, COO Investments at RedCore. - We offer more than just financing; we provide projects with comprehensive expert support, operational resources, and integration into the infrastructure of an international business group. Our goal is not just to invest funds, but to become a catalyst for growth for ambitious projects." RedCore's investment division focuses on projects that have already moved from the MVP stage with market testing to readiness to scale and grow their business. The business group collaborates with teams and technologies that have a working MVP and demonstrate growth potential, offering not only capital but also a full range of support to accelerate growth. You can submit your project for consideration by the team via the link: Pitch your project to the RedCore team. Discuss the details at SIGMA Rome 2025 from November 3 to 6 at the booth 1045. See more breaking stories here. More about Irish Tech News Irish Tech News are Ireland's No. 1 Online Tech Publication and often Ireland's No.1 Tech Podcast too. You can find hundreds of fantastic previous episodes and subscribe using whatever platform you like via our Anchor.fm page here: https://anchor.fm/irish-tech-news If you'd like to be featured in an upcoming Podcast email us at Simon@IrishTechNews.ie now to discuss. Irish Tech News have a range of services available to help promote your business. Why not drop us a line at Info@IrishTechNews.ie now to find out more about how we can help you reach our audience. You can also find and follow us on Twitter, LinkedIn, Facebook, Instagram, TikTok and Snapchat.

Developing Custom AI-ML models with Amazon Sagemaker

Stephen Ryu, a neurosurgeon and key figure in the Stanford Neuroprosthetics Lab joins Tjaša Zajc on Faces of Digital Health to demystify brain–computer interfaces (BCIs): how they work, why invasive systems outperform non-invasive ones, realistic use cases (motor control and speech), timelines and durability, safety and MRI trade-offs, cybersecurity, business models, and what Paradromics is building as a high-bandwidth BCI platform. Throughout, Stephen separates science fact from sci-fi, stressing near-term potential to restore communication and movement for people living with paralysis, while noting earlier-stage areas like mental health and pain. What we cover: - Invasive vs. non-invasive BCIs, and why electrode proximity to neurons matters for performance - Decoding motor intent and speech: training, language considerations, and LLM-enabled synthesis - Safety, surgery, and durability (why 10-year implant lifespans are a meaningful target) - MRI/CT compatibility trade-offs (and parallels to pacemakers/DBS) - Cybersecurity realities (what BCIs can not do today) - Business models, regulation, and reimbursement paths for medical-grade BCIs - Paradromics' differentiation: a high-bandwidth platform designed to scale across use cases - Future indications: pain, sensory restoration; earlier stage: mental health biomarkers - The human impact: restoring connection for people who can't move or speak Chapters: 01:37 How BCIs work; signals, decoding, invasive vs. non-invasive 07:13 Surgery basics, risks, and why proximity boosts performance 09:36 Decoding speech & language considerations 13:31 What's most advanced today: motor + speech 14:58 Mental health: biomarkers and why it's early 17:48 Longevity, MRI/CT limits, realistic replacement intervals 21:16 Patient perception: fear, performance, and value vs. alternatives 25:04 Paradromics' platform & high-bandwidth approach 29:22 Platform use cases by brain area (motor, auditory, etc.) 31:18 Cybersecurity: risks today vs. sci-fi 32:35 Business models, regulation, and access 36:42 Trials landscape; Paradromics' timeline 37:53 Biggest concerns: hype vs. reality 39:50 Three things everyone should know about BCIs 42:10 Potential in pain management 44:41 Role of AI/ML in decoding and assistive apps 46:36 Final thoughts www.facesofdigitalhealth.com Newsletter: https://fodh.substack.com/

 How AI is Changing Deals & Global Development with Jeff Kafka and Brian Rogers     Jeff Kafka Bay Area entrepreneur, cybersecurity startup founder, and medical device/supply chain import partner. Internationally renowned professional kiteboarder and big wave safety expert. Brian Rogers Design and business thinker, expert in AI/ML, IoT, big data, fintech, and platform development. Author of patents, guest lecturer, and industry leader in blockchain. Episode Summary In this episode, we dive deep into how technology, infrastructure, and strong personal networks converge to drive capital and growth in sectors from medical devices to public works. We speak with Jeff Kafka, the founder behind the famous Silicon Valley kite surfing pitch events, about the value of relationships in business growth, and with Brian Rogers, an expert in AI, IoT, and digital transformation, about the future of finance and government partnerships. We explore how their new venture, Storyboard Capital, focuses on opportunities in areas typically ignored by traditional tech investors. Key Discussion Points & Topics I. The Power of Relationships and Networking (Jeff Kafka) Kite Surfing Pitch Events: The origin story of the famous Silicon Valley kite surfing pitch events and the key lessons learned while observing early-stage companies raising capital. Missed Opportunities: Jeff shares his list of companies he met early on but passed on investing in, and the reasons why those opportunities were missed at the time. The Role of People: How Jeff's diverse career—from cybersecurity to big wave safety to medical supply chain—has consistently revolved around people and relationships. Business Growth: The crucial importance of relationships when scaling a business. II. Technology, Government, and Global Development (Brian Rogers & Jeff Kafka) Public/Private Partnerships (P3s): A detailed explanation of what Public/Private Partnerships are and how companies currently go about identifying these government opportunities. AI in Government Financing: How Artificial Intelligence can help streamline the process for companies to find and obtain government contracts. Technology for Development: How technology, public/private partnerships, and infrastructure development are creating opportunities in remote or "off the grid" areas globally. III. The Future of Finance and Investment Banking AI and Financing: How Jeff and Brian see AI changing the landscape for companies obtaining financing, particularly in how deals are sourced and structured. Investment Banker's Role: The evolving role of the investment banker in the future and how they will integrate AI into transaction processes. The Future of Outreach: How customized, AI-driven outreach will change the success or failure rates for projects and deal sourcing. Beyond the Interview: Key concepts related to AI that the audience should be thinking about moving forward. Learn More Storyboard Capital Website: https://storyboardcapital.com/ Jeff Kafka's Contact: Jeffkafka8@gmail.com Jeff Kafka's LinkedIn: https://www.linkedin.com/in/jeffkafka/ Brian Rogers' LinkedIn: https://www.linkedin.com/in/brogers/ Affiliate Companies: https://grapheene.com http://www.strongwatertech.com Disclaimer The views expressed on this podcast are for informational purposes only and not financial or legal advice. Consult with a professional for your specific situation and do not necessarily reflect the views of Finalis Inc. or Finalis Securities LLC, Member FINRA/SIPC.

Arctic Wolf's Dean Teffer reveals how they transformed security operations by processing one trillion daily alerts with AI, and shares hard-won lessons from operationalizing AI in production SOC environments Topics Include:Arctic Wolf processes one trillion security alerts daily across 10,000 global customersSecurity operations remained stubbornly human-mediated due to constantly evolving threats and infrastructure complexityDean explains why platformizing data creates a virtuous cycle enabling AI automationTraditional ML models couldn't handle SOC's situational complexity, leading to LLM adoptionArctic Wolf's unique advantage: direct access to 1000+ SOC analysts for continuous feedbackAWS partnership began with governance concerns about data privacy and model training"Centaur Chess" approach: AI-human teams consistently outperform either alone in cybersecurityThree-generation AI evolution: from personal use to prompt engineering to expert-tuned modelsThree-day AWS hackathon achieved breakthroughs that would've taken months independentlySOC analysts actively shaped AI responses through iterative feedback during live operationsObservability proved critical: tracking performance, quality metrics, and response times for continuous improvementMeasurable impact achieved: automated alert orientation dramatically increased analyst efficiency and response quality Participants:Dean Teffer - VP of AI/ML, Arctic WolfAswin Vasudevan - Senior ISV Solution Architect, Amazon Web ServicesSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

In this special live episode of The Data Minute, recorded in San Francisco, Peter is joined by Janelle Teng from Bessemer Venture Partners for a data-driven look at the state of AI fundraising.Peter and Janelle walk through the data on everything from the AI valuation premium to the new benchmarks for growth, breaking down Bessemer's "Supernovas" and "Shooting Stars" framework. They discuss why fundraising timelines have gotten longer, how dilution remains steady despite soaring valuations, and why San Francisco is still the undisputed center of the AI boom. Plus, they take questions from an audience of AI founders on everything from calculating TAM to navigating a potential AI bubble.This is your front-row seat to the conversation every AI founder needs to hear.The State of AI 2025 - Bessemer Venture Partners:https://www.bvp.com/atlas/the-state-of-ai-2025Subscribe to Carta's weekly Data Minute newsletter: https://carta.com/subscribe/data-newsletter-sign-up/Explore interactive startup and VC data, with Carta's Data Desk: https://carta.com/data-desk/01:03 – A look back: Venture funding since 202102:35 – Pre-ChatGPT vs. Post-ChatGPT funding waves04:18 – How long should your runway be today?04:54 – "Nail it before you scale it": The philosophy of efficient growth06:15 – The new reality of Seed-to-Series-A graduation rates07:31 – Is every software company now an AI company?09:27 – The AI valuation premium at the Seed stage11:14 – AI infrastructure vs. application layer companies13:06 – Bessemer's benchmarks: "Supernovas" vs. "Shooting Stars"14:36 – Why top-line growth can be misleading17:10 – Why retention is table stakes, but gross margins can wait21:12 – The new benchmark: Revenue per employee22:48 – Advice for founders who aren't a "Supernova"26:45 – Why dilution has remained steady at ~20%30:39 – Valuation is not a badge of honor—it's a hurdle33:20 – Why the Bay Area is still the center of the AI universe35:56 – The hiring slowdown and the rise of lean teams38:51 – The soaring cost of AI/ML engineering talent40:00 – Bessemer's key takeaways on the future of AI43:13 – Audience Q&A starts43:33 – Q1: How should founders think about calculating TAM?46:44 – Q2: As a frontier tech company, how do we compete with app-layer startups?48:48 – Q3: How do we compete against incumbents who are adding native AI features?51:31 – Q4: Should VCs back fewer "good" companies to chase the "Supernovas"?55:03 – Q5: Are we in an AI bubble, and when will it pop?This presentation contains general information only and eShares, Inc. dba Carta, Inc. (“Carta”) is not, by means of this publication, rendering accounting, business, financial, investment, legal, tax, or other professional advice or services, and is for informational purposes only.  This presentation is not a substitute for such professional advice or services nor should it be used as a basis for any decision or action that may affect your business or interests. © 2025 eShares, Inc., dba Carta, Inc. All rights reserved.

In this special edition of the Karma School of Business, Sean Mooney, Founder and CEO of BluWave, breaks down key findings from BluWave's Q3 2025 Private Equity Insights Report. Drawing parallels between his son's fencing lessons and today's economic climate, Sean explains how the best investors are shifting from a defensive stance to an offensive one. Seeing through the noise, leaning forward, and playing to win. He shares fresh data showing that deal activity, due diligence spending, and AI investment are all surging—signs of an industry on the offense. From the manufacturing renaissance to the rise of flatter, AI-enabled organizations, Sean offers a grounded, data-backed view of where private equity and the broader economy are heading next. Episode Highlights 1:07 – The Sport of Fencing and PE: what private equity can learn from shifting from defense to offense 4:40 – Why the U.S. economy is “good enough” and accelerating despite the noise 11:45 – Deal data shows confidence returning: due diligence projects up 43% year-over-year 14:33 – PE firms' AI and analytics demand surges 300% and 1,600% for AI/ML advisory 18:39 – Manufacturing reshoring, venture collaboration, and the next wave of innovation 21:06 – The coming of flatter, AI-enabled organizations and what it means for talent 25:39 – Sticky inflation, rate cuts, and why the next economic cycle is already underway   For more on BluWave, visit: https://www.bluwave.net/ To request the full Q3 2025 Insights Report, visit: https://www.bluwave.net/insights-report/

In this episode we are discussing the groundbreaking partnership between SAP Business Data Cloud and SAP Databricks. We discuss how SAP BTP is driving AI-first enterprise transformation through seamless SAP Datasphere integration, zero-copy data sharing, and advanced AI/ML workflows. Also, how Business Data Fabric and SAP Business AI are enabling future-ready enterprise IT, making it easier than ever to turn enterprise data into real business value. From hands-on use cases like cash flow forecasting, margin analysis, and attrition analysis to practical tips for engineers and data scientists, you'll get a front-row seat to digital transformation outcomes that matter.

In this episode we are discussing the groundbreaking partnership between SAP Business Data Cloud and SAP Databricks. We discuss how SAP BTP is driving AI-first enterprise transformation through seamless SAP Datasphere integration, zero-copy data sharing, and advanced AI/ML workflows. Also, hear how Business Data Fabric and SAP Business AI are enabling future-ready enterprise IT, making it easier than ever to turn enterprise data into real business value. From hands-on use cases like cash flow forecasting, margin analysis, and attrition analysis to practical tips for engineers and data scientists, you'll get a front-row seat to digital transformation outcomes that matter.

AI Daily Rundown: October 22, 2025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AIIn Today's edition:

“If responses aren't near real-time, the bot won't feel human.” — Ruchir Brahmbhatt, Co-Founder & CTO, Ecosmob Ruchir Brahmbhatt, Co-Founder and CTO of Ecosmob, joined Doug Green, Publisher of Technology Reseller News, to discuss the engineering behind human-like voicebots—where milliseconds make the difference between a smooth conversation and a frustrating one. With more than 18 years in VoIP and AI/ML development, Ecosmob builds custom voicebots for MSPs, ITSPs, and UCaaS/CCaaS providers seeking real-time automation and compliance. Brahmbhatt outlined how Ecosmob's architecture achieves sub-second latency through: Python async orchestration for thousands of concurrent sessions Redis in-memory queues for ultra-low-latency streaming NVIDIA Canary ASR and Kokoro TTS for fast, natural speech llama.cpp LLM engine with dynamic quantization for efficient processing In a live healthcare demo, Ecosmob's voicebot scheduled an appointment in natural, human-like dialogue—with total round-trip latency under 600 milliseconds. Brahmbhatt emphasized that modern contact centers are shifting from IVRs to AI-driven self-service, and that on-prem and GDPR-compliant deployments are increasingly essential. Learn more at ecosmob.com.

The Qualcomm AMR is powered by Qualcomm's Aikri System-on-Module (SoM) and ST advanced motion control and sensing technologies. It is equipped with a 360-degree vision system, LiDAR sensors, and AI/ML processing and is compatible with ROS2 and Linux.

บทความเหล่านี้มาจากหนังสือ "Quantitative Trading: How to Build Your Own Algorithmic Trading Business" โดย Ernest P. Chan ซึ่งเป็นฉบับพิมพ์ครั้งที่สอง โดยให้ภาพรวมที่ครอบคลุมเกี่ยวกับการสร้างธุรกิจการซื้อขายเชิงปริมาณที่เป็นอิสระ ผู้เขียนเริ่มต้นด้วยการกำหนดการซื้อขายเชิงปริมาณและกล่าวถึงว่าเทรดเดอร์อิสระสามารถประสบความสำเร็จได้อย่างไรเมื่อเทียบกับสถาบันขนาดใหญ่ เนื้อหาส่วนใหญ่สำรวจ กระบวนการแบ็คเทสติ้ง (backtesting) อย่างละเอียด โดยเน้นการใช้ภาษาโปรแกรมมิ่งยอดนิยมอย่าง MATLAB, Python, และ R พร้อมทั้งชี้ให้เห็นถึงข้อผิดพลาดทั่วไปเช่น อคติมองไปข้างหน้า (look-ahead bias) นอกจากนี้ยังมีการอภิปรายที่สำคัญเกี่ยวกับ การบริหารความเสี่ยง (risk management)โดยเฉพาะอย่างยิ่งการใช้ สูตร Kelly (Kelly formula) เพื่อกำหนดการใช้เลเวอเรจที่เหมาะสมที่สุด ตลอดจนหัวข้อพิเศษเกี่ยวกับการปรับกลยุทธ์ตามสภาวะตลาดที่เปลี่ยนแปลงและการใช้ ปัญญาประดิษฐ์/การเรียนรู้ของเครื่อง (AI/ML) โดยเฉพาะเทคนิค metalabeling เพื่อเพิ่มประสิทธิภาพในการซื้อขาย

We love to hear from our listeners. Send us a message.Welcome to Episode 113 of Cell & Gene: The Podcast. Host Erin Harris is joined by Thorsten Gorba, Ph.D., VP Process Development at Aspen Neuroscience to explore how the company is advancing the field of cell therapy manufacturing. Aspen Neuroscience stands at the forefront of integrating machine vision and AI/ML to assess induced pluripotent stem cell (iPSC) colony quality by offering a transformative approach to move beyond the subjective nature of manual evaluation. Dr. Gorba discusses how these technologies bolster reproducibility and scalability and help reduce variability in starting materials. He also covers the regulatory angle, including how the FDA is evaluating digital quality control tools. Subscribe to the podcast!Apple | Spotify | YouTube Visit my website: Cell & Gene Connect with me on LinkedIn

Send us a textDr. Aliza Apple, Ph.D. is a Vice President of Catalyze360 AI ( https://www.lilly.com/science/partners/catalyze-360 ) and Global Head of Lilly TuneLab ( https://tunelab.lilly.com/ ) at Eli Lilly where she leads the strategy, build and launch of Lilly's external-facing AI/ML efforts for drug discovery.Lilly Catalyze360 represents a comprehensive approach to enabling the early-stage biotech ecosystem, agnostic of the therapeutic area, designed to accelerate emerging and promising science, strategically removing barriers to support biotech innovation.In her previous role at Lilly, Dr. Apple served as the COO and head of Lilly Gateway Labs West Coast, where she supported the local biotech ecosystem through early engagement and providing tailored offerings to meet their needs. Prior to Lilly,  Dr. Apple served as a co-founder at Santa Ana Bio, a venture-backed precision biologics company focused on autoimmune disease, and as an advisor to the founders of Firefly Biologics. Prior to biotech, Dr. Apple was a partner in McKinsey & Co's life sciences practice. During her nine years at McKinsey in New York and San Francisco, she collaborated with leaders from over 20 biopharma companies to develop their corporate and portfolio strategies, evaluate business development opportunities and improve their organizational effectiveness. Dr. Apple completed her Ph.D. in bioengineering at UC Berkeley and UCSF, and holds a Bachelor of Science in physics from Georgetown University. She completed a postdoctoral fellowship at Cornell Medical College supported by the NIH Kirschtein National Research Service Award.#AlizaApple #Catalyze360 #TuneLab #EliLilly #LillyGatewayLabs #DrugDiscoveryModels #SmallMolecules #AntibodyTherapeutics #InSilicoPropertyPredictions #AI #ML #ArtificialIntelligence #MachineLearning #LillyVentures #InnovationHubs #Preclinical #DiscoveryChemistry #StructuralBiology #Toxicology #Immunogenicity #DrugMetabolism #Pharmacokinetics #Pharmacodynamics #ClinicalOperations #SmallMoleculeDrugDevelopment #LargeMoleculeDiscoveryProcess #CorporateVentureCapital #STEM #Innovation #Science #Technology #Research #ProgressPotentialAndPossibilities #IraPastor #Podcast #Podcaster #Podcasting #ViralPodcastSupport the show

In this episode of From the Crows' Nest, host Ken Miller unpacks one of the key challenges with using  artificial intelligence and machine learning (AI/ML) in combat: How can human agents trust AI in a live, complex military operation?Jeff Druce, Senior Scientist, Human-Centered AI at  Charles River Analytics, is at the heart of trying to answer this question. Jeff says that neural networks are inherently opaque; a system can perform millions of computations in seconds with a user being in the dark of how a system arrived at a certain recommendation or action. He tells Ken that their RELAX (Reinforcement Learning with Adaptive Explainability) research effort aims to add ways that AI systems can explain their decision making to human operators. Jeff says that efforts to improve transparency and trust in these AI tools are key, arguing bottlenecks for AI use soon may not be from the technology plateauing but operators being unprepared and ill-equipped to effectively use this technology.To learn more about today's topics or to stay updated on EMSO and EW developments, visit our homepage.

In this episode of the Data Science Salon Podcast, we sit down with Swati Tyagi, an AI/ML expert and responsible AI advocate. With deep expertise in large language models (LLMs), generative AI, and AI automation, Swati has led AI-driven innovation in FinTech, healthcare, and finance, helping organizations build scalable, ethical AI systems. Currently at JPMorgan Chase, Swati's work focuses on automating financial applications and leveraging LLMs for real-time inferencing. Her passion for responsible AI is central to her approach, ensuring that AI systems are not only powerful but also ethical and scalable. Key Highlights: -AI and FinTech: Swati discusses her work in credit risk and predictive modeling to optimize financial decision-making and risk assessment. -Responsible AI: Insight into how to design AI systems that are both scalable and ethical, addressing challenges around bias and NLP. -AI Automation in Finance: Learn how LLMs are transforming FinTech, and how MLOps and cloud solutions play a role in scaling these applications.

Dana Love, founder of PoobahAI (exited 5 companies, PhD in economics), breaks down why Web3 lags mainstream adoption and how AI-built software can unlock the space: “the future of Web3 is coding without coders.” We cover: the zero→one grind, macro shifts (globalization → nationalization), inflation realities, and why blockchains need to drop the barrier to projects, devs, and users. Dana shares Poobah's approach—virtual co-founder, multi-chain no/low-code, pre-audited on-chain digital objects, and real showcases (NFT ticketing, RWA real estate, car auction). We also talk go-to-market (students & exec MBAs), chain partnerships, and their seed round.Timestamps[00:00] Dana's thesis: coding without coders is Web3's future[00:01] Background: exits, policy PhD, AI/ML → crypto since 2011[00:02] Patterns from 5+ exits: first $1 of revenue + investment; hearing “your baby is ugly”[00:04] Macro: globalization → nationalization; inflation dynamics & wages[00:07] Startup stages: 0→1 vs 1→10 vs 10→50—don't over-process the first customer[00:08] Why Web3 adoption lags: tooling, UX, paucity of devs/projects/users[00:10] Public vs private chains; why transparency is a feature for upstarts[00:11] Naming Poobah & the “many hats” founder[00:12] Poobah overview: virtual co-founder, on-chain generation, digital objects (pre-audited contracts)[00:15] Code quality: making no-code generate good code; best-practice RAG/context[00:17] Focus: Web3 first—massive untapped value[00:18] GTM: students, MBAs, exec MBAs → enterprise wedge[00:19] Case: Princeton CS student ships NFT ticketing as a vibe-coder[00:20] B2B: chain licenses to drop coding barrier to near-zero[00:22] The “hackathon circus” & why broadening the builder base matters[00:23] Non-dev creators as founders: fine-arts → sticky NFTs[00:24] The Shopify moment for Web3 (payments/regulatory context)[00:27] RWAs: real estate fractionalization; car auctions; built in weeks[00:30] Will AI replace devs? Senior vs junior leverage; law firm analogy[00:36] Market will rebalance skills & pay; seniors x AI = force multiplier[00:37] Roadmap (6–12 mo): low-code launch → no-code, multi-chain MCP, virtual co-founder[00:38] The ask: chain partnerships, seed syndication, universities & exec MBAsConnecthttps://poobah.ai/https://www.linkedin.com/company/poobahai/https://www.linkedin.com/in/danalove/https://x.com/DanaFLoveDisclaimerNothing mentioned in this podcast is investment advice and please do your own research. Finally, it would mean a lot if you can leave a review of this podcast on Apple Podcasts or Spotify and share this podcast with a friend.Be a guest on the podcast or contact us - https://www.web3pod.xyz/

Join Chief Technologist, John Janek, and Tiffany Ceasor, Technical Director for Partnerships, discuss her new role at the company and tech projects. Tiffany shares her background as a data scientist and AI/ML engineer at Microsoft, and her journey through various roles at Dev Technology, including business development and data architecture. The discussion highlights her latest project, the Executive Monitoring Service, which is a serverless, cloud-native AI solution that generates personalized summaries based on executive orders and other governmental documents. Tiffany also talks about her experience at the recent Congressional Hackathon and the rapidly evolving landscape of AI, emphasizing the transformative power of AI tools in software development. The conversation also touches on the future of software engineering, the importance of critical thinking and problem-solving skills, and how AI is making software more accessible and scalable.

Send us a textLeadership Development | Executive Career Track | Career Pivot | AWS | In this Femme Lead episode, Melanie McGrory, Director of the EMEA Tech team at Amazon Web Services, shares her unique career journey spanning cybersecurity, defense, and tech leadership. Known for her “zig-zag” career path, Melanie discusses pivotal moments of risk-taking, overcoming challenges in male-dominated industries, and the evolving nature of leadership in today's digital world.Melanie and her team at AWS support digital native companies and enterprises by enabling digital transformation, innovation, and new customer experiences. With expertise across 175+ AWS services, including AI/ML, migration, security, and hybrid cloud, Melanie is a recognized leader in driving business outcomes through technology.Before AWS, Melanie held leadership roles at HP and the UK Ministry of Defence, bringing two decades of experience in strategy, consulting, and general management across sectors such as travel, transport, logistics, and retail.A STEM advocate and veteran charity participant, Melanie holds a Bachelor's degree in Physics and Operational Research from the University of Cranfield. Tune in for career insights, leadership lessons, and practical advice for women forging paths in tech and beyond!Follow Melanie on LinkedIn: https://www.linkedin.com/in/melanie-mcgrory-4684757/

On-Device AI Agents in Production: Privacy, Performance, and Scale // MLOps Podcast #340 with NimbleEdge's Varun Khare, Founder/CEO and Neeraj Poddar, Co-founder & CTO.Join the Community: https://go.mlops.community/YTJoinInGet the newsletter: https://go.mlops.community/YTNewsletter// AbstractAI agents are transitioning from experimental stages to performing real work in production; however, they have largely been limited to backend task automation. A critical frontier in this evolution is the on-device AI agent, enabling sophisticated, AI-native experiences directly on mobile and embedded devices. While cloud-based AI faces challenges like constant connectivity demands, increased latency, privacy risks, and high operational costs, on-device breaks through these trade-offs.We'll delve into the practical side of building and deploying AI agents with “DeliteAI”, an open-source on-device AI agentic framework. We'll explore how lightweight Python runtimes facilitate the seamless orchestration of end-to-end workflows directly on devices, allowing AI/ML teams to define data preprocessing, feature computation, model execution, and post-processing logic independently of frontend code. This architecture empowers agents to adapt to varying tasks and user contexts through an ecosystem of tools natively supported on Android/iOS platforms, handling all the permissions, model lifecycles, and many more.// BioVarun KhareVarun is the Founder and CEO of NimbleEdge, an AI startup pioneering privacy-first, on-device intelligence. With an academic foundation in AI and neuroscience from UC Berkeley, MPI Frankfurt, and IIT Kanpur, Varun brings deep expertise at the intersection of technology and science. Before founding NimbleEdge, Varun led open-source projects at OpenMined, focusing on privacy-aware AI, and published research in computer vision.Neeraj PoddarNeeraj Poddar is the Co-founder and CTO at NimbleEdge. Prior to NimbleEdge, he was the Co-founder of Aspen Mesh, VP of Engineering at Solo.io, and led the Istio open source community. He has worked on various aspects of AI, networking, security, and distributed systems over the span of his career. Neeraj focuses on the application of open source technologies across different industries in terms of scalability and security. When not working on AI, you can find him playing racquetball and gaining back the calories spent playing by trying out new restaurants. // Related LinksWebsite: https://www.nimbleedge.com/https://www.nimbleedge.com/blog/why-ai-is-not-working-for-youhttps://www.nimbleedge.com/blog/state-of-on-device-aihttps://www.youtube.com/watch?v=Qqj_Nl2MihEhttps://www.linkedin.com/events/7343237917982527488/comments/~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our Slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Varun on LinkedIn: /vkkhare/Connect with Neeraj on LinkedIn: /nrjpoddar/Timestamps:[00:00] On-device AI skepticism[02:47] Word suggestion for AI[06:40] Optimizing unique challenges[13:39] LLM on-device challenges[20:34] Agent overlord tension[23:56] AI app constraints[29:23] Siri limitations and trust gap[32:01] Voice-driven app privacy[35:49] Platform lock-in vs aggregation[42:26] On-device AI optimizations[45:38] Wrap up

Welcome to Sridhar's newsletter & Podcast (Click Play button for Audio version of the Post). Appreciate you being here, so we can connect weekly on interesting topics. Add your email id here to get this directly to your inbox.Do subscribe to show Minimalist Techie over Apple Or Spotify Or YouTube podcast (Click on Hyperlinks for Apple Or on Spotify Or on YouTube) or hear it over email you received through my subscription or on my website.This weekly newsletter is mostly about the article, books, videos etc. I read or watch or my views on different topics which revolves around my head during the week.Point discussed in this Podcast,Why So Few Tech Jobs for Recent Grads?  • The promise vs. the reality  • Data showing how entry-level tech hiring has contracted  • Why companies demand high experience from newcomers  • Role of AI / tooling in shifting the job landscape  • What grads and educational systems can do differentlyData Point & Implication* Entry-level hiring by top tech firms dropped by 50% since 2019 San Francisco StandardImplication - The largest tech companies are hiring far fewer fresh grads, undermining the promise of entry-level paths.* The share of tech job ads requiring ≥5 years' experience rose from ~37% to ~42% from 2022 → 2025 Indeed Hiring LabImplication - More roles are shifting toward “mid/senior-level only,” squeezing the bottom tier.* Projections show ~317,700 new job openings per year in U.S. tech & IT occupations through 2034 Bureau of Labor StatisticsImplication - The volume is there—jobs exist—but many are not entry-level or accessible.* Reports show that many grads (esp. CS grads) now face unemployment rates over 6% — double some liberal arts majors The Economic TimesImplication - It's a disruption: even in “hot” fields, grads aren't guaranteed jobs.* Indications that tech postings are down ~36% vs. pre-pandemic levels RedditImplication - The number of roles overall has contracted, increasing competition.Why This Gap Is Widening * Raising experience bars: Companies prefer safer bets — hiring those with track records, rather than investing in freshers. (Data: experience requirement rising)* Risk aversion & cost of training: Startup budgets and corporate HR often don't want or can't afford ramp-up time for newcomers.* AI & automation's shadow:  • Some entry-level tasks (simple code, scripts, basic data cleaning) are increasingly tackled by AI/ML tools, reducing demand for junior labor.  • This doesn't eliminate the need for human developers — but shifts the requirements higher.* Mismatch of curriculum & industry needs: Education sometimes lags behind tech trends. Graduates might know older languages but not the niche frameworks or cloud / ML / architecture knowledge companies now expect.* Selective hiring & “brand bias”: Companies often prioritize grads from elite universities or known tech schools, exacerbating inequality.* Market cycles & contraction: When the tech bubble deflates or macroeconomic headwinds rise, companies cut or freeze junior hiring first.What Grads / Postgrads Can Do * Build a portfolio of real-world projects  • Open-source contributions, personal apps, data projects, internships—even unpaid or side work.  • Projects that solve real problems, not toy examples.* Learn the in-demand skills & tools  • Cloud (AWS, Azure, GCP), ML/AI basics, infrastructure, modern frameworks (e.g. React, Node.js), DevOps tools.  • Certifications, bootcamps, micro-credentials.  • Embrace continuous learning—because tech evolves.* Target smaller companies, startups, non-tech firms  • These roles may have lower brand prestige but offer more flexibility and opportunities to learn.  • Many “non-tech” companies need developers for automation, internal dashboards, ML, etc.* Network aggressively & find mentors  • Use LinkedIn, meetups, hackathons.  • Reach out to people in your niche, ask for code reviews, mock interviews, advice.* Be flexible in location / remote work  • Don't confine your job search to top-tier cities only. Remote roles open more doors.  • Be open to contract / freelance gigs to build experience.* Show results, not credentials  • In interviews, emphasize outcomes, metrics, and problem-solving over “courses taken.”  • Demonstrate how your work impacted something, however small.* Consider non-traditional entry paths  • Apprenticeships, technical residencies, bootcamp-plus internships.  • Some tech fellowships let you “earn while learning.”What Institutions & Industry Must DoTo make systemic change, certain players must act:* Universities / colleges:  • Update curricula quicker; partner with industry; offer more work-integrated learning programs.  • Bridge the gap between theory and current tools.* Tech companies / recruiters:  • Re-evaluate job descriptions: reduce arbitrary thresholds (years of experience, brand school).  • Build robust junior hire programs; commit to “grow-your-own” talent.  • Use transparency in hiring pipelines (publish how many fresh grads hired).* Government / policy makers:  • Incentivize companies to hire entry-level talent (tax credits, subsidies for training).  • Support tech education & apprenticeships.To conclude, The tech industry can't thrive if new talent is blocked at the door. To preserve innovation, companies must open pathways; graduates must be strategic about learning and positioning themselves.That is all for this week. See you again.Do let me know in comments or reply me over email to share what is your view on this post. So, Share, Like, subscribe whatever these days' kids say :-)Stay Connected, Share Ideas, Spread Happiness. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit sridhargarikipati.substack.com

Cisco's Distance Zero rethinks hybrid collaboration with meeting equity, AI at the edge, and cinematic framing that keeps every participant “at eye height”—plus live 3D object discussion with Apple Vision Pro. SVP/GM Snorre Kjesbu explains how Cisco defines “Distance Zero”: everyone gets a true seat at the table—being seen, heard, and included in the room dynamics, whether they're remote or on-site. Subtle but powerful touches—like equalizing participant size and eye level—remove hierarchy cues and improve equity. He frames where hybrid work stands now: bring people together for creativity, mentoring, culture, and serendipity (yes, the coffee line matters), and let focused grind work happen anywhere. For offices to “earn the commute,” rooms must outperform home setups—for those in the room and those remote. Technically, this is enabled by a decade of AI/ML at the edge (a long-running partnership with Nvidia), now combined with newer large-language-model capabilities. Cisco's “cinematic” system behaves like an AI producer—understanding who's speaking and how a conversation moves—while noise suppression can differentiate lawnmowers, dogs, and even prioritize a specific speaker's voice. On accessibility, live translation, captions, and annotation lower barriers for varied accents and learning needs. IT and facilities teams also get AI “superpowers” for reliability and scale since collaboration is now mission-critical. Kjesbu notes that these capabilities are largely available on existing deployments (backward compatible where possible, with cloud assist), and adoption is strong: features like cinematic framing are on in 100% of meetings where available, and LLM-powered summaries, actions, and translation are surging. If this helped clarify the future of hybrid collaboration, like the video, leave a comment with your biggest meeting-equity challenge, and subscribe for more deep dives on accessible, human-centered workplace tech. Cisco Distance Zero, meeting equity, hybrid collaboration, AI at the edge, cinematic framing, Webex meetings, Apple Vision Pro 3D, Nvidia partnership, live translation, captions and annotation, noise suppression, remote work, earn the commute, inclusive meetings, IT manageability, voice optimization, backward compatibility, employee experience, collaboration devices Learn more about your ad choices. Visit megaphone.fm/adchoices

In this episode of the podcast, members of the InfoQ editorial staff and friends of InfoQ discuss the current trends in the domain of AI, ML and Data Engineering. One of the regular features of InfoQ are the trends reports, which each focus on a different aspect of software development. These reports provide the InfoQ readers and listeners with a high-level overview of the topics to pay attention to this year. InfoQ AI, ML and Data Engineering editorial team met with external guests to discuss the trends in AI and ML areas, and what to watch out for the next 12 months. In addition to the written report and trends graph, this podcast provides a recording of a discussion where expert panelists discuss how innovative AI technologies are disrupting the industry. Read a transcript of this interview: http://bit.ly/4nRpvlF Subscribe to the Software Architects' Newsletter for your monthly guide to the essential news and experience from industry peers on emerging patterns and technologies: https://www.infoq.com/software-architects-newsletter Upcoming Events: InfoQ Dev Summit Munich (October 15-16, 2025) Essential insights on critical software development priorities. https://devsummit.infoq.com/conference/munich2025 QCon San Francisco 2025 (November 17-21, 2025) Get practical inspiration and best practices on emerging software trends directly from senior software developers at early adopter companies. https://qconsf.com/ QCon AI New York 2025 (December 16-17, 2025) https://ai.qconferences.com/ QCon London 2026 (March 16-19, 2026) https://qconlondon.com/ The InfoQ Podcasts: Weekly inspiration to drive innovation and build great teams from senior software leaders. Listen to all our podcasts and read interview transcripts: - The InfoQ Podcast https://www.infoq.com/podcasts/ - Engineering Culture Podcast by InfoQ https://www.infoq.com/podcasts/#engineering_culture - Generally AI: https://www.infoq.com/generally-ai-podcast/ Follow InfoQ: - Mastodon: https://techhub.social/@infoq - X: https://x.com/InfoQ?from=@ - LinkedIn: https://www.linkedin.com/company/infoq/ - Facebook: https://www.facebook.com/InfoQdotcom# - Instagram: https://www.instagram.com/infoqdotcom/?hl=en - Youtube: https://www.youtube.com/infoq - Bluesky: https://bsky.app/profile/infoq.com Write for InfoQ: Learn and share the changes and innovations in professional software development. - Join a community of experts. - Increase your visibility. - Grow your career. https://www.infoq.com/write-for-infoq

Jimmy Secretan, CTO of JustWin, explores the latest innovations in privacy-preserving neural networks, and explains how JustWin is leveraging AI to help small businesses win government contracts. He also explores the future directions of AI, and the impact of AI on user autonomy and privacy. Key Takeaways: Technological advancements shaping the future of secure and ethical AI applications The significance of open-endedness in AI How to build while balancing both innovation and privacy Why AI solutions are a good fit for winning RFPs GPT-5 and predictions for its future impact Guest Bio: Jimmy Secretan, CTO of JustWin, holds a Ph.D. from the Machine Learning Lab at the University of Central Florida, where he specialized in large-scale, privacy-safe neural networks. Having previously served as Chief Scientist at Korrelate, VP of Engineering of Sonobi, and CTO of Roadtrippers, Jimmy has architected privacy-safe AI/ML data pipelines, scaled infrastructure to hundreds of billions of requests per month to power predictive media planning, and led the creation of the AI-driven future of travel data. As VP of Ads and Premium Services at Brave, Jimmy helped launch Brave's global private ad network; led the development of premium functionality for the Brave browser; and managed initiatives like Brave News and Brave Talk. ---------------------------------------------------------------------------------------- About this Show: The Brave Technologist is here to shed light on the opportunities and challenges of emerging tech. To make it digestible, less scary, and more approachable for all! Join us as we embark on a mission to demystify artificial intelligence, challenge the status quo, and empower everyday people to embrace the digital revolution. Whether you're a tech enthusiast, a curious mind, or an industry professional, this podcast invites you to join the conversation and explore the future of AI together. The Brave Technologist Podcast is hosted by Luke Mulks, VP Business Operations at Brave Software—makers of the privacy-respecting Brave browser and Search engine, and now powering AI everywhere with the Brave Search API. Music by: Ari Dvorin Produced by: Sam Laliberte  

AI isn't just about writing emails faster; it's about capturing and scaling the expert knowledge that actually wins deals.  In this conversation, Vivun's Chief AI Officer Joseph Miller explains why most “just add a chatbot” projects stall, and how building a real-world model of your business (your terms, processes, and judgments) unlocks meaningful results. He breaks down the difference between low-stakes productivity and high-stakes outcomes—and what it takes to get from New York to San Francisco, not just Newark. You'll hear practical guidance for marketers, sales leaders, and operators: how to codify tribal knowledge, ground AI in your company's definitions, and design iterative experiments that deliver time-to-value. If you're tired of hype and want an honest blueprint for using AI to empower teams—not replace their judgment—this episode is for you. Leader Generation is hosted by Tessa Burg and brought to you by Mod Op.  About Joseph Miller: As the Chief AI Officer and co-founder of Vivun, Joseph Miller, PhD, leverages his expertise in AI/ML and causal inference to build complex agentic systems. He is nationally recognized for his work in AI labor disruption and algorithmic strategies, and has appeared on platforms such as Bloomberg and Nasdaq. Joseph also guest lectures on AI, entrepreneurship and quantitative finance. About Tessa Burg: Tessa is the Chief Technology Officer at Mod Op and Host of the Leader Generation podcast. She has led both technology and marketing teams for 15+ years. Tessa initiated and now leads Mod Op's AI/ML Pilot Team, AI Council and Innovation Pipeline. She started her career in IT and development before following her love for data and strategy into digital marketing. Tessa has held roles on both the consulting and client sides of the business for domestic and international brands, including American Greetings, Amazon, Nestlé, Anlene, Moen and many more. Tessa can be reached on LinkedIn or at Tessa.Burg@ModOp.com.

As agencies continue their digital transformation, cloud adoption is essential for mission agility, security and efficiency. This episode dives into how agencies are tackling cloud migration, operational continuity and regulatory compliance while ensuring their systems remain resilient and cost-effective.  ThunderCat Technology's Cloud CTO Nic Perez, Deon James, AI Lead at Google Public Sector and Jeff Marshall, Director of Hosting and Compute at DISA discuss best practices for securing workloads, leveraging AI/ML for performance optimization and navigating federal procurement challenges.

What if the biggest value of AI isn’t answers, but better questions? For Morgan Brown, Vice President of Product and Growth at Dropbox, that realisation has transformed everything from family dinners to global product strategy. In this episode, I chat with Morgan about how he uses AI as both a problem-solver and a sparring partner. Morgan leads Dropbox’s AI products, but he’s also built his own app from scratch - with no coding background - to help his six-year-old son manage type 1 diabetes. We dive into how Morgan uses AI to eliminate grunt work, create powerful prompts, and even stress test his own ideas. This conversation will show you practical ways to turn AI into a genuine partner for your work and life. We discuss: The story behind CARB Scan, the AI-powered app Morgan built to help his son manage diabetes How he uses AI to eliminate shallow work, like meeting recaps and email sorting Why designing prompts is a superpower—and Morgan’s framework for writing great ones The automation Morgan built to scan and summarise the entire AI/ML landscape every morning How to use AI as a true thought partner for brainstorming, strategy, and decision-making The risks of skipping human feedback and why real-world validation still matters Morgan’s advice for spotting your own hidden time sinks and turning them into AI experiments Key Quotes “LLMs aren’t the best search engine. They’re much better as a thought partner.” “The real leverage of AI isn’t the answers. It’s the better questions.” Connect with Morgan Brown on X (Twitter), LinkedIn, and his website https://www.morganbrown.co/ Check out Morgan’s book Hacking Growth. Get your hands on Morgan’s AI research prompt here. If you enjoyed this, listen to my episode with Bob Johansen - we talked about reframing AI as “augmented intelligence,” and it pairs beautifully with Morgan’s approach. My latest book The Health Habit is out now. You can order a copy here: https://www.amantha.com/the-health-habit/ Connect with me on the socials: Linkedin (https://www.linkedin.com/in/amanthaimber) Instagram (https://www.instagram.com/amanthai) If you are looking for more tips to improve the way you work and live, I write a weekly newsletter where I share practical and simple to apply tips to improve your life. You can sign up for that at https://amantha-imber.ck.page/subscribe Visit https://www.amantha.com/podcast for full show notes from all episodes. Get in touch at amantha@inventium.com.au Credits: Host: Amantha Imber Sound Engineer: The Podcast Butler See omnystudio.com/listener for privacy information.

In this episode, Lois Houston and Nikita Abraham are joined by Principal Instructor Yunus Mohammed to explore Oracle's approach to enterprise AI. The conversation covers the essential components of the Oracle AI stack and how each part, from the foundational infrastructure to business-specific applications, can be leveraged to support AI-driven initiatives.   They also delve into Oracle's suite of AI services, including generative AI, language processing, and image recognition.     AI for You: https://mylearn.oracle.com/ou/course/ai-for-you/152601/   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, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode.   -------------------------------------------------------------   Episode Transcript:  00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:25 Lois: Welcome to the Oracle University Podcast! I'm Lois Houston, Director of Innovation Programs with Oracle University, and with me is Nikita Abraham, Team Lead: Editorial Services. Nikita: Hey everyone! In our last episode, we discussed why the decision to buy or build matters in the world of AI deployment. Lois: That's right, Niki. Today is all about the Oracle AI stack and how it empowers not just developers and data scientists, but everyday business users as well. Then we'll spend some time exploring Oracle AI services in detail.  01:00 Nikita: Yunus Mohammed, our Principal Instructor, is back with us today. Hi Yunus! Can you talk about the different layers in Oracle's end-to-end AI approach? Yunus: The first base layer is the foundation of AI infrastructure, the powerful compute and storage layer that enables scalable model training and inferences. Sitting above the infrastructure, we have got the data platform. This is where data is stored, cleaned, and managed. Without a reliable data foundation, AI simply can't perform. So base of AI is the data, and the reliable data gives more support to the AI to perform its job. Then, we have AI and ML services. These provide ready-to-use tools for building, training, and deploying custom machine learning models. Next, to the AI/ML services, we have got generative AI services. This is where Oracle enables advanced language models and agentic AI tools that can generate content, summarize documents, or assist users through chat interfaces. Then, we have the top layer, which is called as the applications, things like Fusion applications or industry specific solutions where AI is embedded directly into business workflows for recommendations, forecasting or customer support. Finally, Oracle integrates with a growing ecosystem of AI partners, allowing organizations to extend and enhance their AI capabilities even further. In short, Oracle doesn't just offer AI as a feature. It delivers it as a full stack capability from infrastructure to the layer of applications. 02:59 Nikita: Ok, I want to get into the core AI services offered by Oracle Cloud Infrastructure. But before we get into the finer details, broadly speaking, how do these services help businesses? Yunus: These services make AI accessible, secure, and scalable, enabling businesses to embed intelligence into workflows, improve efficiency, and reduce human effort in repetitive or data-heavy tasks. And the best part is, Oracle makes it easy to consume these through application interfaces, APIs, software development kits like SDKs, and integration with Fusion Applications. So, you can add AI where it matters without needing a data scientist team to do that work.  03:52 Lois: So, let's get down to it. The first core service is Oracle's Generative AI service. What can you tell us about it?  Yunus: This is a fully managed service that allows businesses to tap into the power of large language models. You can actually work with these models from scratch to a well-defined develop model. You can use these models for a wide range of use cases like summarizing text, generating content, answering questions, or building AI-powered chat interfaces.  04:27 Lois: So, what will I find on the OCI Generative AI Console? Yunus: OCI Generative AI Console highlights three key components. The first one is the dedicated AI cluster. These are GPU powered environments used to fine tune and host your own custom models. It gives you control and performance at scale. Then, the second point is the custom models. You can take a base language model and fine tune it using your own data, for example, company manuals or HR policies or customer interactions, which are your own personal data. You can use this to create a model that speaks your business language. And last but not the least, the endpoints. These are the interfaces through which your application connect to the model. Once deployed, your app can query the model securely and at different scales, and you don't need to be a developer to get started. Oracle offers a playground, which is a non-core environment where you can try out models, craft parameters, and test responses interactively. So overall, the generative AI service is designed to make enterprise-grade AI accessible and customizable. So, fitting directly into business processes, whether you are building a smart assistant or you're automating the content generation process.  06:00 Lois: The next key service is OCI Generative AI Agents. Can you tell us more about it?  Yunus: OCI Generative AI agents combines a natural language interface with generative AI models and enterprise data stores to answer questions and take actions. The agent remembers the context, uses previous interactions, and retrieves deeper product speech details. They aren't just static chat bots. They are context aware, grounded in business data, and able to handle multi-turns, follow-up queries with relevant accurate responses, and driving productivity and decision-making across departments like sales, support, or operations. 06:54 Oracle University's Race to Certification 2025 is your ticket to free training and certification in today's hottest tech. Whether you're starting with Artificial Intelligence, Oracle Cloud Infrastructure, Multicloud, or Oracle Data Platform, this challenge covers it all! Learn more about your chance to win prizes and see your name on the Leaderboard by visiting education.oracle.com/race-to-certification-2025. That's education.oracle.com/race-to-certification-2025. 07:37 Nikita: Welcome back! Yunus, let's move on to the OCI Language service.  Yunus: OCI Language helps business understand and process natural language at scale. It uses pretrained models, which means they are already trained on large industry data sets and are ready to be used right away without requiring AI expertise. It detects over 100 languages, including English, Japanese, Spanish, and more. This is great for global business that receive multilingual inputs from customers. It works with identity sentiments. For different aspects of the sentence, for example, in a review like, “The food was great, but the service sucked,” OCI Language can tell that food has a positive sentiment while service has a negative one. This is called aspect-based sentiment analysis, and it is more insightful than just labeling the entire text as positive or negative. Then we have got to identify key phrases representing important ideas or subjects. So, it helps in extracting these key phrases, words, or terms that capture the core messages. They help automate tagging, summarizing, or even routing of content like support tickets or emails.  In real life, the businesses are using this for customer feedback analysis, support ticket routing, social media monitoring, and even regulatory compliances.  09:21 Nikita: That's fantastic. And what about the OCI Speech service?  Yunus: The OCI Speech is an AI service that transcribes speech to text. Think of it as an AI-powered transcription engine that listens to the spoken English, whether in audio or video files, and turns it into usable and searchable and readable text. It provides timestamps, so you know exactly when something was said. A valuable feature for reviewing legal discussions, media footages, or compliance audits. OCI Speech even understands different speakers. You don't need to train this from scratch. It is pre-trained model hosted on an API. Just send your audio to the service, and you get an accurate timestamp text back in return. 10:17 Lois: I know we also have a service for object detection… called OCI Vision?  Yunus: OCI Vision uses pretrained, deep learning models to understand and analyze visual content. Just like a human might, you can upload an image or videos, and the AI can tell you what is in it and where they might be useful. There are two primary use cases, which you can use this particular OCI Vision for. One is for object detection. You have got a red color car. So OCI Vision is not just identifying that's a car. It is detecting and labeling parts of the car too, like the bumper, the wheels, the design components. This is a critical in industries like manufacturing, retail, or logistics. For example, in quality control, OCI Vision can scan product images to detect missing or defective parts automatically.  Then we have got the image classification. This is useful in scenarios like automated tagging of photos, managing digital assets, classifying this particular scene or context of this particular scene. So basically, when we talk about OCI Vision, which is actually a fully managed, no complex model training is required for this particular service. It's available via API. It is also working with defining their own custom model for working with the environments. 11:51 Nikita: And the final service is related to text and called OCI Document Understanding, right? Yunus: So OCI Document Understanding allows businesses to automatically extract structured insights from unstructured documents like invoices, contracts, recipes, and also sometimes resumes, or even business documents. 12:13 Nikita: And how does it work? Yunus: OCI reads the content from the scanned document. The OCR is smarter. It recognizes both printed and handwritten text. Then determines what type of document it is. So document classification is done. Text recognition recognizes text, then classifies the document. For example, if this is a purchase order, or bank statement, or any medical report. If your business handles documents in multiple languages, then the AI can actually help in language detection also, which helps you in routing the language or translating that particular language. Many documents contain structured data in table format. Think pricing tables or line items. OCI will help you in extracting these with high accuracy for reporting on feeding into ERP systems. And finally, I would say the key value extraction. It puts our critical business values like invoice numbers, payment amounts, or customer names from fields that may not always allow a fixed format. So, this service reduces the need for manual review, cuts down processes time, and ensures high accuracy for your system. 13:36 Lois: What are the key takeaways our listeners should walk away with after this episode? Yunus: The first one, Oracle doesn't treat AI as just a standalone tool. Instead, AI is integrated from the ground up. Whether you're talking about infrastructure, data platforms, machine learning services, or applications like HCM, ERP, or CX. In real world, the Oracle AI Services prioritize data management, security, and governance, all essential for enterprise AI use cases. So, it is about trust. Can your AI handle sensitive data? Can it comply with regulations? Oracle builds its AI services with strong foundation in data governance, robust security measures, and tight control over data residency and access. So this makes Oracle AI especially well-suited for industries like health care, finance, logistics, and government, where compliance and control aren't optional. They are critical.   14:44 Nikita: Thank you for another great conversation, Yunus. If you're interested in learning more about the topics we discussed today, head on over to mylearn.oracle.com and search for the AI for You course.  Lois: In our next episode, we'll get into Predictive AI, Generative AI, Agentic AI, all with respect to Oracle Fusion Applications. Until then, this is Lois Houston… Nikita: And Nikita Abraham, signing off! 15:10 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.  

This episode dives into "Category-Theoretic Analysis of Inter-Agent Communication and Mutual Understanding Metric in Recursive Consciousness." The paper presents an extension of the Recursive Consciousness framework to analyze communication between agents and the inevitable loss of meaning in translation. We're thrilled to feature the paper's author, Stan Miasnikov, Distinguished Engineer, AI/ML Architecture, Consumer Experience at Verizon, to walk us through the research and its implications.Learn more about AI observability and evaluation, join the Arize AI Slack community or get the latest on LinkedIn and X.

Episode 815: Insurance companies rely on data to optimize performance, mitigate risk, and meet the rising expectations of consumers… but new questions are being raised about what happens when there's a lack of data or missing data?   On today's Unscripted… Neil Alldredge, president and CEO of NAMIC, sits down with Lindsey Klarkowski, policy vice president of data science, AI/ML, and cybersecurity at NAMIC, to better understand how insurers are tackling this emerging issue. Today's episode is sponsored by Holborn.

Medboard   EUROPE Guidance on the implementation of the Master UDI-DI - MDCG 2024-14 - rev.1 : https://health.ec.europa.eu/document/download/c8c6cca5-460e-410e-a325-be08bfc7dea6_en?filename=mdcg_2024-14_en.pdf Updated - Notified bodies survey on certificates under MDR and IVDR: https://health.ec.europa.eu/document/download/59b9d90e-be42-4895-9f6f-bec35138bb0a_en?filename=md_nb_survey_certifications_applications_en.pdf There's a significant backlog: far more applications submitted than certificates issued, especially for IVDs. Time for certification: between 13 to 18 months on average Delay due to application missing critical information and refusal due to submission outside NB scope No transparency on capacity Germany new radiation protection regulation - Start July 1st, 2025: https://www.bfarm.de/DE/Arzneimittel/Klinische-Pruefung/Strahlenschutz/_artikel.html?nn=986770If device emit radiation and need clinical investigation in germany: Include a radiation risk assessment in your clinical investigation dossier Coordinate with Radiation protection authorities Update investigator brochure and patient information Stricter Monitoring & Reporting Impact on Timelines So stricter documentation, more authorities involved and longer approval times   UK MHRA launches Route B notification pilot Clinical trials regulations rollout: https://www.gov.uk/government/news/mhra-launches-route-b-notification-pilot-as-part-of-clinical-trials-regulations-rollout  -  https://www.gov.uk/guidance/notify-mhra-about-a-clinical-investigation-for-a-medical-device   Switzerland New in Swissdamed - Medical Device registration with UDI Device Module: https://www.swissmedic.ch/swissmedic/en/home/medical-devices/medizinprodukte-datenbank/swissdamed-informationen/registrierung-mepprodukte-moeglich.html 1 july-2026   Magazine Easy Medical Device Mag - Your QA RA Magazine: https://mailchi.mp/easymedicaldevice/emdmag1   Podcast: Best 40 Medical Device Podcast - Thanks: https://www.millionpodcasts.com/Medical-Device-podcasts/   REST OF THE WORLD SaMD and/or Artificial Intelligence on the spotlight - All countries want their regulation on it:  USA: PCCP - https://www.fda.gov/regulatory-information/search-fda-guidance-documents/marketing-submission-recommendations-predetermined-change-control-plan-artificial-intelligence SFDA: Workshop September 9th: https://www.sfda.gov.sa/en/workshop/4387139 TGA: Understanding regulation of software-based medical devices: https://www.tga.gov.au/resources/guidance/understanding-regulation-software-based-medical-devices#samd-and-ai-medical-device-compliance SAHPRA: Regulatory Requirements of AI/ML: https://www.sahpra.org.za/document/regulatory-requirements-of-artificial-intelligence-and-machine-learning-ai-ml-enabled-medical-devices/ Medical Device or Wellness device - Choose your side: https://www.sfda.gov.sa/sites/default/files/2025-08/MDS-G027.pdf  

There are very few people like Stephen Brobst, a legendary tech CTO and "certified data geek," Stephen shares his incredible journey, from his early days in computational physics and building real-time trading systems on Wall Street to becoming the CTO for Teradata and now Ab Initio Software. Stephen provides a masterclass on the evolution of data architecture, tracing the macro trends from early decision support systems to "active data warehousing" and the rise of AI/ML (formerly known as data mining). He dives deep into why metadata-driven architecture is critical for the future and how AI, large language models, and real-time sensor technology will fundamentally reshape industries and eliminate the dashboard as we know it. We also chat about something way cooler, as Stephen discusses his three passions: travel, music, and teaching. He reveals his personal rule of never staying in the same city for more than five consecutive days since 1993 and how he manages a life of constant motion. From his early days DJing punk rock and seeing the Sex Pistols' last concert to his minimalist travel philosophy and ever-growing bucket list, Stephen offers a unique perspective on living a life rich with experience over material possessions. Finally, he offers invaluable advice for the next generation on navigating careers in an AI-driven world and living life to the fullest.

Meeting assets for The Space Show Present Mike Gold are ready! 8-29-25Hi David LivingstonThe following assets for the meeting - The Space Show Present Mike Gold are now available.Our program began with discussions about UAP research and national security concerns, including Michael Gold's involvement with NASA's UAP Independent Study Team and his testimony before Congress. The group explored space exploration initiatives, focusing on commercial space activities, human spaceflight capabilities, and international collaboration through the Artemis accords. The conversation concluded with discussions about budget and fiscal challenges, particularly regarding NASA's funding priorities and the need for strategic objectives in space exploration, while also addressing national debt concerns and immigration policies. He went on to discuss his new role at Redwire, focusing on international space business, particularly in Europe where he sees significant growth potential due to the continent's efforts to develop independent space capabilities. He expressed concern about national security threats related to drone technology, noting that if a conflict with China were to occur, they would likely employ similar tactics to Ukraine's against Russia. The discussion concluded with Gold revealing his involvement with NASA's UAP Independent Study Team and congressional testimony on the topic. Space Show participants including John Hunt, John Jossy, Dr. Ajay Kothari, Marshall Martin, guest Dr. Hank Alewine, Bill Gowan and Dr. Doug Plata.As for speaking on the UAP issue and concerns, our guest talked about the importance of addressing unidentified anomalous phenomena (UAP), particularly adversary drones, which he believes could pose a significant threat similar to what Ukraine did to Russia. He expressed concern about the stigma surrounding UAP and emphasized the need for enhanced anti-UAV capabilities to protect military bases, critical infrastructure, and nuclear facilities from potential drone attacks. Gold noted that while the current administration is more attentive to UAP issues, further acceleration in developing drone technology and defense strategies is necessary to prevent future conflicts.He brought up the NASA UAP Independent Study Team's findings and expressed disappointment with the treatment of academic members who faced ridicule and threats for their participation. He highlighted the need for a more objective scientific approach and emphasized the importance of analyzing data and witness testimony from pilots, such as those involved in the Tic Tac incident. Gold also suggested that NASA conduct an archival review and leverage AI/ML to search for UAP-related data, and proposed expanding the NASA ASRS system to include UAP reporting.The group discussed the potential for using the ASRS reporting system to transform pilots, crew members, and passengers into sensors for detecting unidentified aerial phenomena (UAP), which could provide valuable data for national security and scientific research. Marshall highlighted the growing global internet connectivity and increased bandwidth, enabling rapid deployment of cameras and sensors to capture anomalies. John Hunt shared insights on the historical context of UAP sightings, particularly around nuclear facilities, and expressed skepticism about some conspiracy theories. Michael emphasized the need for NASA to play a role in collecting and archiving UAP data, while also noting the challenges posed by the physics of UAP sightings. The discussion concluded with optimism about the future of UAP research, particularly under the leadership of NASA's interim administrator, Sean Duffy, and the potential for bipartisan support in Congress.We moved on with a discussion about the importance of human spaceflight and the potential for commercialization of the International Space Station (ISS). He highlighted Redwire's recent developments in bioprinting and pharmaceuticals, including the creation of a subsidiary called Space MD to commercialize space-grown crystals for drug development. Michael addressed concerns about the ISS's commercialization and its impact on funding for Moon and Mars initiatives, emphasizing that all three should be pursued simultaneously. He also touched on Redwire's global operations, including its presence in Europe and plans for expansion. The discussion concluded with questions about the timeline for bio printed medical implants and potential collaboration on artificial gravity technologies.The group talked about several space exploration initiatives, focusing on seed crystal development for drug creation and agricultural research in microgravity. Michael Gold highlighted Red Wire's collaboration with NASA and Vast for flying a pillbox in Haven One, emphasizing the importance of microgravity for various fields including agriculture and organ fabrication. Ajay raised concerns about the lack of focus on lunar infrastructure and cargo missions, suggesting the use of Falcon Heavy for cost-effective cargo transport to the moon. The discussion also touched on the need for human spaceflight capabilities to compete with China and the importance of cargo systems, with Michael noting that the administration plans to enhance the CLPS program with CLPS 2.0 for more robust lunar surface operations.Much was said about the Artemis Accords. The Artemis Accords and their success in bringing 56 countries together, with Doug proposing the need for a follow-on to coordinate international lunar exploration as Starship development progresses. Michael Gold emphasized the importance of leveraging the accords to optimize investments and collaborations among nations, while expressing caution regarding potential deals with China due to national security concerns and IP theft. The discussion also touched on Redwire's focus on innovation to address economic challenges and create new opportunities for America.The group discussed the potential of SpaceX's Starship for space manufacturing, with Michael highlighting its cost-effectiveness for launching large payloads like medical laboratories. They explored the economic and strategic importance of space exploration, with Gold emphasizing the need for continued investment in space capabilities to maintain American leadership and national security. The conversation also touched on the future of the International Space Station (ISS) and the importance of developing commercial space stations, with Gold advocating for maximizing ISS utilization while advancing plans for a Commercial LEO Destination (CLD).The group discussed the challenges of reducing the national debt, with Hank and David agreeing that current spending rates outpace revenue growth, making it difficult to balance the budget. They explored potential solutions, including selective increases in legal immigration and the role of automation and AI in the workforce, with Hank expressing concerns about AI's impact on education and cheating in online courses. The conversation concluded with a discussion of the demographic challenges facing many countries, including the United States, and the need to consider alternative approaches to immigration and education in response to these changes.As for the challenges of addressing the national debt and deficit, Hank noted that increased federal revenue through taxation has not led to reduced spending. David and Marshall highlighted how tax increases can reduce production and marketing, while John Hunt suggested that gradual inflation could help reduce the debt over time, though this approach faces political and economic challenges. The conversation also touched on the potential for state and local governments to handle certain services more efficiently, with Hank questioning the necessity of some federal rolesThe group discussed space policy and budget issues, with Hank expressing concerns about NASA's funding and the broader space sector's impact on national debt. Hank, who wrote the first paper on space accounting, emphasized the need for a complete rebranding of NASA's objectives in the new space economy and highlighted the lack of courage among academics and practitioners to discuss fiscal responsibility in space spending. The conversation also touched on the challenges of having open discussions about space funding priorities, with Hank noting that such conversations often become political and lead to excessive spending through Continuing Resolutions.As we were nearing the end of the program, we discussed NASA's priorities and budget, with Hank emphasizing the need to focus on strategic objectives and eliminate inefficiencies, particularly in activities that could be better handled by the private sector. They critically examined the cost and timeline issues of the SLS program, with Hank noting that NASA's infrastructure is often spread across congressional districts to secure funding. The conversation also touched on China's advanced space program and its potential to surpass the U.S. in lunar exploration, highlighting the need for the U.S. to accelerate its efforts. Mike offered his comments and thoughts on this issues as we closed our meeting.Be sure to watch the Zoom video of this program at doctorspace.substack.com. The audio will also be posted there as well as The Space Show website.Special thanks to our sponsors:Northrup Grumman, American Institute of Aeronautics and Astronautics, Helix Space in Luxembourg, Celestis Memorial Spaceflights, Astrox Corporation, Dr. Haym Benaroya of Rutgers University, The Space Settlement Progress Blog by John Jossy, The Atlantis Project, and Artless EntertainmentOur Toll Free Line for Live Broadcasts: 1-866-687-7223For real time program participation, email Dr. Space at: drspace@thespaceshow.comThe Space Show is a non-profit 501C3 through its parent, One Giant Leap Foundation, Inc. To donate via Pay Pal, use:To donate with Zelle, use the email address: david@onegiantleapfoundation.org.If you prefer donating with a check, please make the check payable to One Giant Leap Foundation and mail to:One Giant Leap Foundation, 11035 Lavender Hill Drive Ste. 160-306 Las Vegas, NV 89135Upcoming Programs:No program on Sunday August 31 due to Labor Day Holiday Weekend.Live Streaming is at https://www.thespaceshow.com/content/listen-live with the following live streaming sites:Stream Guys https://player.streamguys.com/thespaceshow/sgplayer3/player.php#FastServ https://ic2646c302.fastserv.com/stream Get full access to The Space Show-One Giant Leap Foundation at doctorspace.substack.com/subscribe

As India charts its trajectory to build in-house AI/ ML capabilities, data centres emerge, quite literally, as central to the ecosystem-building exercise. What role must industry play to bring capabilities home? How do challenges pertaining to power transmission and renewability affect data centre operations?Tune into this episode of 'All Things Policy', wherein Anushka Saxena quizzes Anwesha Sen on the nitty-gritty of India's AI Data Centre ecosystem, to know.Do not forget to participate in Takshashila's 2025 China Challenge Survey, which is your way to have a say in defining India's perception of Beijing. Link: bit.ly/ChinaSurvey2025.All Things Policy is a daily podcast on public policy brought to you by the Takshashila Institution, Bengaluru.⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Find out more on our research and other work here: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://takshashila.org.in/research-areas⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Check out our public policy courses here: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://school.takshashila.org.in⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Healthcare payments consume between $650 billion and $1 trillion annually in billing and insurance-related costs—an amount comparable to the entire U.S. Defense Department budget. At the heart of this staggering inefficiency lies a fundamental problem: when patients receive care, nobody actually knows in real-time whether the insurance will pay for it. Mike Desjadon, CEO of Anomaly, spent nearly two decades in healthcare payments before building a company to solve this core issue. In this episode, we explore how Anomaly is creating "payment assurance" for healthcare—bringing the same real-time payment certainty that exists everywhere else in commerce to an industry desperately in need of it. Topics Discussed: The massive scale of healthcare billing costs and why precision is impossible at this scale How the complex coding system (ICD, CPT, revenue codes) creates a "ridiculous Rubik's Cube" of payment determination Why healthcare lacks payment assurance while every other industry has real-time payment certainty The fundamental information asymmetry between providers and insurers that drives administrative waste Anomaly's approach to using AI and machine learning to predict payment outcomes early in the care process The strategic decision to focus exclusively on providers rather than serving both sides of the market   GTM Lessons For B2B Founders: Avoid "Annual Curiosity Revenue" in favor of deep customer relationships: Mike warns against chasing what he calls "ACR" - contracts driven by curiosity about new technology rather than real value. Instead of racing to accumulate surface-level customers, Anomaly focuses on 1-5 anchor customers where they forward-deploy engineers and dedicate leadership attention. As Mike explained, "I'd rather take a much smaller amount of those trusted pitches... find me 10 of the right conversations, don't find me a hundred surface level conversations." In healthcare's 14-month sales cycles, shallow relationships burn runway without building sustainable growth. Match your go-to-market strategy to industry realities, not investor expectations: Healthcare's long sales cycles and conservative nature require a fundamentally different approach than traditional SaaS growth models. Mike structured Anomaly's capital and hiring strategy around 14-month sales cycles rather than trying to compress them. "If you know that it's a 14 month sales cycle... being realistic about those timeframes and those capital structures, you just make sure your plan on burn matches your plan on strategy." This meant hiring customer success and engineering talent before traditional sales roles, aligning team composition with the actual customer adoption process. Segment ruthlessly based on transformation readiness: Not every healthcare organization is ready for transformative technology. Mike emphasizes the critical need to identify whether prospects are "looking for transformation" versus "looking to automate an isolated process." He shares that distinguishing between these segments determines the entire sales approach. Organizations seeking transformation are willing to work through implementation complexity for substantial outcomes, while those seeking automation want predictable, incremental improvements. Misreading this distinction leads to failed sales cycles and misaligned product development. Use forward-deployed engineering as a competitive advantage: Rather than traditional customer success managers, Anomaly deploys engineers directly to customers during implementation. This approach proves particularly valuable in AI/ML applications where the technology is rapidly evolving and customer needs aren't fully defined. Mike notes, "Having engineers in that has been hugely valuable for us because we're able to really quickly deliver value, very quickly deliver outsized value." This strategy enables rapid iteration, builds deeper technical trust, and often leads to expanded contracts through demonstrated capability rather than traditional sales pitches. Build category credibility through case studies, not connections: In healthcare, having impressive investors or warm introductions matters far less than demonstrating proven results with known organizations. Mike emphasizes, "What you need in healthcare is slapping six case studies down the desk... show me the six organizations that I know that you work with that are going to tell me I should work with you." This insight drives Anomaly's entire early-stage strategy—prioritizing customer success and measurable outcomes over rapid customer acquisition, building the credibility foundation needed for future sales acceleration.     //   Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe.  www.GlobalTalent.co   //   Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM 

Guests are Clayton Coleman and Rob Shaw. Clayton is a Core contributor to Kubernetes, the containerized cluster manager, and founding architect for OpenShift, the open source platform as a service. Clayton helped launch the shift to cloud native applications and the platforms that enable them. At Google my mission is to make Kubernetes and GKE the best place to run workloads, especially accelerated AI/ML workloads, and especially especially very large model inference at scale with the inference gateway and llm-d. Rob Shaw is an Engineering Director at Redhat and is a contributor to the vLLM project.   Do you have something cool to share? Some questions? Let us know: - web: kubernetespodcast.com - mail: kubernetespodcast@google.com - twitter: @kubernetespod - bluesky: @kubernetespodcast.com   News of the week Kubernetes 1.34 is expected to release end of August Kubecrash.io: A platform Eng conference with a purpose CNCF top 30 project of 2025 Links from the interview LLM-D KubeCon EU 25 Keynote: LLM-Aware Load Balancing in Kubernetes WG Serving vLLM Disaggregated Prefilling LWS: LeaderWorkerSet

Haseeb Budhani (@haseebbudhani, CEO @rafaysystemsinc) discusses the evolution from traditional DevOps to platform engineering and what "Enterprise Ready" Kubernetes looks like in 2025. We explore AI workloads running on Kubernetes and how modern orchestration solutions can transform teams from bottlenecks into enablers. We also cover the security considerations for GPU-enabled AI workloads and balancing developer self-service capabilities with proper governance and control.SHOW: 950SHOW TRANSCRIPT: The Cloudcast #950 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST: "CLOUDCAST BASICS"SPONSORS:[DoIT] Visit doit.com (that's d-o-i-t.com) to unlock intent-aware FinOps at scale with DoiT Cloud Intelligence.[VASION] Vasion Print eliminates the need for print servers by enabling secure, cloud-based printing from any device, anywhere. Get a custom demo to see the difference for yourself.SHOW NOTES:Rafay websiteTopic 1 - Welcome to the show, Haseeb. Give everyone a quick introduction.Topic 2 - Let's start by talking about the evolution of Kubernetes as a platform. You've said and we've talked about on this show for some time how Kubernetes is more of a platform to run platforms. We've also seen trends in the industry and shifts in what it means to be DevOps or Platform Engineering in recent years. You've positioned Rafay as a Kubernetes Operations Platform that's now evolved into a Cloud Automation Platform. How do you define the difference between Kubernetes management and true platform engineering?Topic 3 - What does “Enterprise Ready” Kubernetes look like in 2025?Topic 4 - Let's flip over to AI/ML and GPUs with Kubernetes for a bit. Many developers and data scientists aren't aware of the underlying platform they run on. I saw a stat recently that about 95% of AI runs on Kubernetes, either on-prem or in the cloud. Despite this, Platform teams are often stuck doing manual GPU provisioning, which doesn't scale with AI adoption. How do modern GPU orchestration solutions change the platform team's role?Topic 5 - With GPU workloads often handling sensitive data and AI models, security becomes even more critical. How should organizations approach security and compliance in their GPU-enabled Kubernetes operations?Topic 6 - "Most developers don't want to write YAML or manage clusters — they just want to ship software." How do you balance giving developers the self-service capabilities they want while maintaining the control and governance that platform teams need?FEEDBACK?Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod

Good morning from Pharma and Biotech Daily: the podcast that gives you only what's important to hear in Pharma and Biotech world.Eli Lilly has invested $1.3 billion in a partnership with Superluminal, an AI/ML startup focusing on endocrine and cardiometabolic diseases to develop new small molecule obesity medications. Schrodinger has discontinued the development of an early-stage blood cancer drug after two patient deaths. Trump has delayed pharma tariffs citing other priorities. RFK Jr. has been criticized for canceling Barda contracts related to mRNA vaccine research, leading to more vaccine misinformation. Genscript announces a new era of innovation and trust. Other news includes Vedanta downsizing, Abata shutting down.

August 12, 2025 | Diagonal Therapeutics founder and CEO Alexey Lugovskoy discusses the key lessons learned over his illustrious career, starting from his childhood in the Soviet Union to founding his own company, Diagonal Therapeutics. With host Tariq Ghayur, Lugovskoy shares insights gained from working with organizations of different sizes, taking on the obstacles of building a pipeline, and integrating AI/ML into discovery programs, as well as his most memorable achievement—and most memorable failure. He also offers advice to young scientists and entrepreneurs, emphasizing the importance of challenging problems and surrounding yourself with the right people. 

This week on DisrupTV, we interviewed: - Sanjib Sahoo, President, Global Platform Group at Ingram Micro - Tim Christophersen, Vice President, Climate Action at Salesforce, Author of Generation Restoration, & Board Member Ingram Micro is betting big on AI to power its next chapter. Sanjib revealed that the company's X Vantage platform weaves AI into every stage of the business, slashing operating costs and speeding up go-to-market strategies. With 400 AI/ML models trained on 4 petabytes of data, the shift is already driving major revenue gains. On a different front, Tim called for a generational reset in our relationship with nature, pointing to AI's potential to boost ecological literacy and accelerate large-scale restoration. DisrupTV is a weekly podcast with hosts R "Ray" Wang and Vala Afshar. The show airs live at 11 AM PT/ 2 PM ET every Friday. Brought to you by Constellation Executive Network: constellationr.com/CEN.

This episode is a crossover with our friends at the SRE Prodcast. Kaslin joined Ben Good and Steve McGhee to talk about Kubernetes for Platform Engineering.   Do you have something cool to share? Some questions? Let us know: - web: kubernetespodcast.com - mail: kubernetespodcast@google.com - twitter: @kubernetespod - bluesky: @kubernetespodcast.com   News of the week Kubernetes 1.34 Sneak Peak Upcoming changes to the Bitnami catalog (effective August 28th, 2025) Amazon EKS enables ultra scale AI/ML workloads with support for 100K nodes per cluster CNCF Cloud Native Glossary   Links from the interview Backstage DORA Metrics

In this episode, we're joined by Amber Knight from BookingsCloud to talk advertising, marketing teams, budget, AI/ML, targeting and a LOT more!Enjoy!⭐️ Links & Show NotesAdam NorkoConrad O'ConnellAmber KnightBookingsCloudEditor's note: we had some minor audio issues during recording. 

It was time to get Frank Denneman back on the show to discuss the enhancements introduced in VCF 9 and Private AI Foundation with NVIDIA. Frank goes over all new functionality and all the enhancements like Agent Builder etc. Frank also mentioned various must-attend sessions at Explore. Register now, as these will fill up fast:Chris Wolf, keynote and breakout!Shawn Kelly and Justin Murray: Accelerating AI WorkloadsFrank's AI/ML sessions!Disclaimer: The thoughts and opinions shared in this podcast are our own/guest(s), and not necessarily those of Broadcom, or Google.

Is your nonprofit still buried in paper forms and outdated systems? In this episode, I sit down with Patrick Waldo—AI and SaaS innovator and CEO of Unicorn Forms—to talk about the real risks and opportunities around e-signatures, data security, and going digital. From board agreements to grant paperwork and beyond, we explore how even small nonprofits can make a big leap into smarter, safer, and more accessible systems. If you're tired of chasing signatures and retyping forms, you need this conversation. Episode Highlights 05:20 - E-sign solutions and nonprofit needs 01:16 - Nonprofit Paperwork Challenges with Patrick Waldo 06:27 - E-signatures: Legal Basics & Security 13:14 - Digital Transformation & Real-World Examples 22:48 - Data, Analytics & The Future of Nonprofit Tech Meet the Guest My guest for this episode is Patrick Waldo. Patrick Waldo, CEO, is a seasoned technology leader with over 15 years of experience developing AI/ML and data analytics SaaS solutions adopted by the Fortune 500. As CEO of UnicornForms, Inc., he's on a mission to make paperwork frictionless through innovative form and document management. Previously, he served as VP of Product at Decernis, where he drove product development, led technical due diligence through two PE acquisitions, and secured two patents in AI/ML and NLP. At FoodChain ID, he led post-merger integration strategies, and at Redica Systems, he oversaw FDA analytics and monitoring for the pharmaceutical industry. Waldo holds master's degrees from Carnegie Mellon University and the University of Bologna, with expertise in IT, management, policy, and economics. He holds a Bachelor's degree from Grinnell College. Connect with Patrick: Web: https://www.unicornforms.com LinkedIn: https://www.linkedin.com/company/unicornforms Instagram: http://instagram.com/unicornforms Facebook: http://facebook.com/unicornforms Sponsored Resource Join the Inspired Nonprofit Leadership Newsletter for weekly tips and inspiration for leading your nonprofit! Access it here >> Be sure to subscribe to Inspired Nonprofit Leadership so that you don't miss a single episode, and while you're at it, won't you take a moment to write a short review and rate our show? It would be greatly appreciated! Let us know the topics or questions you would like to hear about in a future episode. You can do that and follow us on LinkedIn.

What happens after AI helps you write code faster? You create a bottleneck in testing, security, and operations. In part two of their conversation, SADA's Simon Margolis and Google Cloud's Ameer Abbas tackle this exact problem. They explore how Google's AI strategy extends beyond the developer's keyboard with Gemini Code Assist and Cloud Assist, creating a balanced and efficient software lifecycle from start to finish. We address the burning questions about AI's impact on the software development ecosystem: Is AI replacing developers? What does the future hold for aspiring software engineers? Gain insights on embracing AI as an augmentation tool, the concept of "intentional prompting" versus "vibe coding," and why skilled professionals are more crucial than ever in the enterprise. This episode offers practical advice for enterprises on adopting AI tools, measuring success through quantitative and qualitative metrics, and finding internal champions to drive adoption. We also peek into the near future, discussing the evolution towards AI agents capable of multi-step inferencing and full automation for specific use cases. Key Takeaways: Gemini Code Assist: AI for developer inner-loop productivity, supporting various IDEs and SCMs. Gemini Cloud Assist: AI for cloud operations, cost optimization, and incident resolution within GCP. AI's Role in Development: Augmentation, not replacement; the importance of human agency and prompting skills. Enterprise Adoption: Strategies for integrating AI tools, measuring ROI, and fostering a culture of innovation. The Future: Agents with multi-step inferencing, automation for routine tasks, and background AI processes. Relevant Links: Blog: A framework for adopting Gemini Code Assist and measuring its impact Gemini Code Assist product page Gemini Cloud Assist product page Listen now to understand how AI is shaping the future of software delivery! Join us for more content by liking, sharing, and subscribing!

As long-time listeners will know, I love the consumer lending space. So, I am delighted to welcome back to the podcast Matt Potere, the CEO of Happy Money, a position he has held since September 2024. Previously, Matt served as CEO of Sunlight Financial, which he took public via SPAC in 2021. With decades of experience in consumer finance across multiple asset classes, Matt brings deep expertise in credit cycles, risk management, and building successful lending platforms.In this episode, we discuss what differentiates Happy Money, their focus on credit unions, how they approach technology and underwriting, their big new forward flow agreement, the state of the consumer today, their use of AI, why culture is so important and much more.In this podcast you will learn:What attracted Matt to the opportunity at Happy Money.How he describes Happy Money today.What he learned leading Sunlight Financial that helps at Happy Money.Why they have focused on partnering with credit unions.Who is the typical customer coming to Happy Money.How their origination process works with their credit union partners.How they are using automation and AI/ML in their underwriting.Matt's perspective on the state of the US consumers.The primary use cases for a Happy Money loan.How they differentiate themselves from other fintech lenders.Matt's approach to scaling a lending business.How they are using AI tools in their operation.How the $500 million deal with Fortress and Edge Focus came together.What are his thoughts on an IPO.Matt thoughts about adding new products to personal loans.What they are focused on for the next 12 months.Connect with Fintech One-on-One: Tweet me @PeterRenton Connect with me on LinkedIn Find previous Fintech One-on-One episodes

As Black Hat USA 2025 approaches, the cybersecurity world is buzzing with innovation—and Dropzone AI is right at the center of it. With roots in Seattle and a mission to bring true intelligence into the security operations center (SOC), the Dropzone AI team is gearing up for a packed week in Las Vegas, from BSides to the AI Summit, and finally at Startup City (booth #6427).Founded by Edward Wu, former Head of AI/ML at ExtraHop Networks, Dropzone AI was built on a key realization: the last thing SOCs need is another flood of alerts. Instead, they need help processing and acting on them. That's where Dropzone comes in—offering an AI-powered security analyst that doesn't just detect threats, but investigates, correlates, and takes action.During a recent pre-event chat with ITSPmagazine's Sean Martin and Marco Ciappelli, Edward explained the core philosophy behind the platform. Unlike hype-driven claims of “fully autonomous SOCs,” Dropzone takes a practical, tiered approach to automation. Their agentic AI system performs full investigations, determines the nature of alerts (true vs. false positives), and recommends or executes containment actions depending on risk tolerance and policy.The tech has found particular traction with lean security teams, or those expanding toward 24/7 coverage without adding headcount. Rather than replacing humans, the platform augments them—freeing analysts from the drudgery of low-priority alert triage and giving them space to focus on strategic work. As Edward put it, “Nobody wants to be a tier-one analyst forever.” Dropzone helps make sure they don't have to be.The platform integrates across existing security stacks and data sources, drawing from threat intel, logs, and endpoint signals to build a full picture of every alert. Security teams retain full control, with human-in-the-loop decision-making remaining the standard in most use cases. However, for low-risk assets and off-hours scenarios, some customers are already authorizing autonomous action.With conversations at Black Hat expected to revolve around the reality of AI in production—not just the vision—Dropzone is entering the perfect arena. From demonstrating real-world impact to sharing insights on agentic design and trust boundaries, their presence will resonate with everyone from analysts to CISOs.Whether you're building out your SOC, questioning your MDR provider, or simply overwhelmed with alert fatigue, this may be your signal. Dropzone AI isn't selling buzzwords. They're delivering results. Visit them at Startup City, booth #6427, and see for yourself what the future of alert triage and SOC efficiency looks like—one investigation at a time. Note: This story contains promotional content. Learn more.Guests:Edward Wu, Founder/CEO at Dropzone AI On LinkedIn: https://www.linkedin.com/in/edwardxwu/DROPZONE AI: https://itspm.ag/dropzoneai-641Hosts:Sean Martin, Co-Founder at ITSPmagazine | Website: https://www.seanmartin.comMarco Ciappelli, Co-Founder at ITSPmagazine | Website: https://www.marcociappelli.com______________________ResourcesVisit the DROPZONE Website to learn more: https://itspm.ag/dropzoneai-641Learn more and catch more stories from Dropzone on ITSPmagazine: https://www.itspmagazine.com/directory/dropzoneaiLearn more about ITSPmagazine Brand Story Podcasts: https://www.itspmagazine.com/purchase-programsNewsletter Archive: https://www.linkedin.com/newsletters/tune-into-the-latest-podcasts-7109347022809309184/Business Newsletter Signup: https://www.itspmagazine.com/itspmagazine-business-updates-sign-upAre you interested in telling your story?https://www.itspmagazine.com/telling-your-story

Got ideas? Here's how to turn them into income—again and again.In this episode of 7-8 Figure Special Series I interviewed Jeremy Lessaris. Jeremy is an experienced global marketing and communicationsexecutive and entrepreneurial leader, with over two decades of experience in the industrial, energy, transportation, and technology sectors, establishing and investing in numerous ventures across several different industries.He previously served as Global Vice President of Marketing & Communications for Power Solutions International, owned by Weichai, a $28 billion Chinese industrial and marine conglomerate. Jeremy successfully managed global marketing efforts and secured over $30 million in capital and grants. During his tenure he rang the opening bell at NASDAQ and helped lead the company to become one of the fastest growing stocks in Illinois, up 364% in the first 6 months. Jeremy more recently founded, bootstrap funded and served as CEO of a leading US-based design agency Designed.co which was sold in late 2023. His leadership helped grow the agency nearly 3000% in the first 18 months of operation. His current role is Founder and CEO of Payment Brokers a fintech application that utilizes AI/ML to uncover proprietary pricing data used for negotiations with credit card processing companies. As an accomplished tech founder, with a proven track record, Jeremy has led 8 of his companies to successful exit. Want to build more than one business? Check this out!Show Links:Jeremy on LinkedIn: https://www.linkedin.com/in/jlessaris/Book a call with Michelle: https://go.appointmentcore.com/book/IcFD4cGJoin our Facebook group for business owners to get help or help other business owners!The Business Ownership Group - Secrets to Scaling: https://www.facebook.com/groups/businessownershipsecretstoscalingLooking to scale your business? Get free gifts here to help you on your way: https://www.awarenessstrategies.com/