Podcasts about ai ml

 ABOUT PRASHANT RAMARAOPrashant is a hands-on technology executive with extensive experience in software engineering, leading large organizations, specializing in AI / ML, and large-scale systems architecture. With advanced degrees in computer science and engineering leadership, he excels at defining technical strategies that align with business goals, delivering results, and fostering high-performing, cross-functional teams. He cares about engineering excellence, leveraging cutting-edge technology to solve complex problems and scale operations for long-term growth. He has a lifelong passion for learning and looks for opportunities to challenge the status quo to drive change. He loves the outdoors and is a self-proclaimed podaholic - going on long hikes in Bay Area while listening to his podcasts is one of his favorite activities.This episode is brought to you by Side – delivering award-winning QA, localization, player support, and tech services for the world's leading games and technology brands.For over 30 years, Side has helped create unforgettable user experiences—from indies to AAA blockbusters like Silent Hill 2 and Baldur's Gate 3.Learn more about Side's global solutions at side.inc. SHOW NOTES:Behind Prashant's rapid leadership evolution (3:26)Transitioning from IC to management: early steps and surprises (5:51)Navigating the mindset shifts from tech expert to people leader (7:31)Friction points in moving from informal to formal leadership (11:00)Skills for communicating with less technical audiences (13:46)Learning to talk with GMs & other non-technical leaders (16:32)Frameworks for effective meeting planning (19:03)Examples of communicating technical work to execs (20:08)Learning the impact of the “observer effect” (21:59)Incorporating feedback gathered by observing (27:03)Strategies for maintaining technical credibility as a senior leader (29:29)Why personal projects and experimentation matter for leadership growth (32:21)How Prashant's personal projects enhance technical credibility & leadership skills (36:59)Rapid fire questions (37:57)This episode wouldn't have been possible without the help of our incredible production team:Patrick Gallagher - Producer & Co-HostJerry Li - Co-HostNoah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/

Demetrios and Mohan Atreya break down the GPU madness behind AI — from supply headaches and sky-high prices to the rise of nimble GPU clouds trying to outsmart the giants. They cover power-hungry hardware, failed experiments, and how new cloud models are shaking things up with smarter provisioning, tokenized access, and a whole lotta hustle. It's a wild ride through the guts of AI infrastructure — fun, fast, and full of sparks!Big thanks to the folks at Rafay for backing this episode — appreciate the support in making these conversations happen!// BioMohan is a seasoned and innovative product leader currently serving as the Chief Product Officer at Rafay Systems. He has led multi-site teams and driven product strategy at companies like Okta, Neustar, and McAfee. // Related LinksWebsites: https://rafay.co/~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreMLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Mohan on LinkedIn: /mohanatreyaTimestamps:[00:00] AI/ML Customer Challenges[04:21] Dependency on Microsoft for Revenue[09:08] Challenges of Hypothesis in AI/ML[12:17] Neo Cloud Onboarding Challenges[15:02] Elastic GPU Cloud Automation[19:11] Dynamic GPU Inventory Management[20:25] Terraform Lacks Inventory Awareness[26:42] Onboarding and End-User Experience Strategies[29:30] Optimizing Storage for Data Efficiency[33:38] Pizza Analogy: User Preferences[35:18] Token-Based GPU Cloud Monetization[39:01] Empowering Citizen Scientists with AI[42:31] Innovative CFO Chatbot Solutions[47:09] Cloud Services Need Spectrum

I recently read a blog post on AI/ML performance on top of VCF, and figured it was time to invite Frank Denneman back to the podcast. During the episode we discuss VMware Private AI Foundation with NVIDIA, and Frank also mention Ollama as a great starting point.Disclaimer: The thoughts and opinions shared in this podcast are our own/guest(s), and not necessarily those of Broadcom, VMware by Broadcom, or SAP.

Ian Failes from befores & afters chats to Version Zero AI co-founders Chad Wanstreet and Allan McKay about their new platform and tool that utilizes machine leaning for roto, matting, clean painting and paint.

In this episode of Add To Cart, we chat to Luke Matthews, Head of IT at Camilla, the iconic Australian fashion brand known for its vibrant prints, celebrity fans, and big name collaborations with the likes of Disney and White Lotus. Luke shares how he's building the tech foundations that are powering Camilla's global expansion, from Australia to the US and beyond. He lifts the lid on the hidden challenges of running a best-of-breed tech stack with NetSuite, Shopify and CDP and explains why data discipline, system resilience and seamless customer experience are critical to scaling a creative brand. This episode was brought to you by: Shopify PlusKlaviyoAbout your guest:Luke Matthews is an experienced technology executive with over a decade leading digital transformation and innovation in retail. As Head of IT at Camilla Australia, he drives technology initiatives that enhance customer experience, streamline operations and support growth across physical and online stores. A former CTO at Kitchen Warehouse Australia, Luke championed digital advancements, including website optimisation, data-driven marketing, and click-and-collect solutions. He has also led major projects at Retail Directions, delivering software development and system localisation for global retailers. Luke's expertise spans cybersecurity, AI/ML in retail, data analytics, cloud architecture and business process re-engineering. With a results-driven mindset, he consistently delivers solutions that boost profitability, efficiency and customer engagement.About your host:Nathan Bush is the host of the Add To Cart podcast and a leading ecommerce transformation consultant. He has led eCommerce for businesses with revenue $100m+ and has been recognised as one of Australia's Top 50 People in eCommerce four years in a row. You can contact Nathan on LinkedIn, Twitter or via email.Email hello@addtocart.com.au We look forward to hearing from you! Hosted on Acast. See acast.com/privacy for more information.

Welcome to the CanadianSME Small Business Podcast, hosted by Maheen, where we explore the strategies and innovations that empower businesses to succeed in today's ever-evolving digital landscape.In this episode, we delve into the intersection of cybersecurity, AI, and digital transformation with Deepak Kumar, Director at SSB Technologies Inc. With the rise in cybercrime incidents, businesses need robust strategies to secure their digital assets and drive innovation. Join us as Deepak discusses responsible AI, brand protection, and how businesses can effectively navigate the complexities of digital transformation and cybersecurity. Key Highlights:Responsible Gen AI: Deepak explains the concept of responsible and enterprise Gen AI and how businesses can use it to drive innovation while managing risks.Cybersecurity Challenges: Key challenges businesses face in cybersecurity today and strategies to protect brand data, especially through cyber insurance.Balancing Security and Innovation: How businesses can successfully implement digital transformation without compromising security.Real-World Cybersecurity Success: A success story about improving security and efficiency through data loss prevention strategies.Cloud Security and AI/ML: Deepak shares insights on deploying cloud security strategies and optimizing security with AI/ML-powered solutions.Special Thanks to Our Partners:RBC: https://www.rbcroyalbank.com/dms/business/accounts/beyond-banking/index.htmlUPS: https://solutions.ups.com/ca-beunstoppable.html?WT.mc_id=BUSMEWAGoogle: https://www.google.ca/For more expert insights, visit www.canadiansme.ca and subscribe to the CanadianSME Small Business Magazine. Stay innovative, stay informed, and thrive in the digital age!Disclaimer: The information shared in this podcast is for general informational purposes only and should not be considered as direct financial or business advice. Always consult with a qualified professional for advice specific to your situation.

In this episode of Coach to Scale, we sit down with Tony Burnside, SVP of APJ at Netskope, to dismantle the outdated playbook on sales leadership. Tony challenges the myth that effective managers need to lead through pressure, fear, or control. Instead, he shares his approach to building high-performing, culturally aligned teams, starting with hiring good humans, creating space for accountability, and making coaching a non-negotiable part of the manager's role. With over 200 reps across 15 countries under his leadership, Tony's insights are battle-tested and globally relevant.We dig into what it takes to scale culture across borders, what most leaders miss in their 1:1s, and why every resignation is, as Tony puts it, “a performance review for leadership.” Whether you're a CRO trying to stabilize performance or a frontline leader drowning in deals and check-the-box coaching, this episode delivers practical frameworks and hard-earned lessons for leveling up your org without burning out your team.Key Takeaways:1. Culture drives performance, not charisma or controlBurnside argues that strong sales cultures don't emerge from aggressive personalities but from clarity, consistency, and mutual respect across the organization.2. Good human first" is a hiring filter, not a luxuryHe prioritizes character over credentials, explaining that people who want to win as a team outperform lone wolves in the long run.3. Every resignation is a leadership review.Attrition isn't just HR's concern; Tony reframes it as direct feedback on your leadership brand and your managers' effectiveness.4. Yes, you can be friends with your reps  if you're still willing to hold them accountableBurnside pushes back on the false tradeoff between camaraderie and performance, noting that trust and accountability aren't mutually exclusive.5. Global coaching cultures require local empathy.Leading in APJ taught him that you can't copy-paste U.S. management styles into Japan or India; success comes from adjusting expectations and coaching cadence to cultural norms.6. Managers need a litmus test for connection and respectHe shares a personal test: if you wouldn't grab a drink with a rep while traveling, they may not be the right cultural fit for your team.7. Most managers don't know how to coach because they were never taughtTony calls out the common pattern of promoting star reps without equipping them to lead, which leads to tactical, deal-centric 1:1s instead of skill development.8. He invests personally in his own growth and expects others to do the sameFrom Dale Carnegie to Sandler, Tony's career changed after he paid out of pocket for training; he sees self-investment as a signal of leadership potential.10. Coaching must be operationalized, not left to chance or personalityInformal, unstructured coaching creates inconsistency and lost opportunities; managers need frameworks and tools to coach effectively at scale.Ways to Tune In:Spotify: https://open.spotify.com/show/0Yb1wPzUxyrfR0Dx35ym1A Apple Podcasts: https://podcasts.apple.com/us/podcast/coach2scale-how-modern-leaders-build-a-coaching-culture/id1699901434 Google Podcasts: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy50cmFuc2lzdG9yLmZtL2NvYWNoMnNjYWxlLWhvdy1tb2Rlcm4tbGVhZGVycy1idWlsZC1hLWNvYWNoaW5nLWN1bHR1cmU Amazon Music: https://music.amazon.com/podcasts/fd188af6-7c17-4b2e-a0b2-196ecd6fdf77 Podchaser: https://www.podchaser.com/podcasts/coach2scale-how-modern-leaders-5419703 YouTube: https://www.youtube.com/@Coach2Scale CoachEm™ is the first Coaching Execution Platform that integrates deep learning technology to proactively analyze patterns, highlight the "why" behind the data with root causes, and identify the actions that will ultimately improve business results going forward.  These practical coaching recommendations for managers will help their teams drive more deals, bigger deals, faster deals, and loyal customers. Built with decades of go-to-market experience, world-renowned data scientists, and advanced causal AI/ML technology, CoachEm™ leverages your existing tech stack to increase rep productivity, increase retention, and replicate best practices across your team.Learn more at coachem.io

Jason Brink is the CEO and co-founder of Datagram, a decentralized real-time communication (RTC) infrastructure platform that leverages underutilized network resources to provide secure, scalable, and cost-effective communication solutions.  Why you should listen Datagram is a decentralized real-time communication (RTC) infrastructure platform that leverages underutilized resources to provide scalable and cost-effective connectivity solutions. It operates as a DePIN (Decentralized Physical Infrastructure Network) baselayer, utilizing an AI-driven, Hyper-Fabric Network to enable fast and scalable connectivity across various applications, including gaming, AI, and telecom. By unifying idle hardware bandwidth into a global decentralized network, Datagram delivers fast, secure, and scalable connectivity for modern internet applications. ​ One of the key features of Datagram is its AI-driven coordination, which dynamically optimizes traffic, congestion control, and scalability while predicting traffic patterns to balance network loads for peak efficiency. This ensures that the network can adapt to varying demands and maintain optimal performance. Additionally, Datagram offers cross-network interoperability through standardized DePIN cross-network communication, ensuring seamless interoperability, improved efficiency, and optimal resource utilization while scaling effortlessly.  Datagram's decentralized architecture eliminates the need for central servers, reducing the risk of single points of failure and enhancing privacy and security. It provides a multifunctional platform with RTC, CDN, GPU compute, and storage functionalities, supporting mission-critical connectivity across the next generation of digital applications. Use cases include distributing AI/ML workloads, enabling seamless real-time audio and video communication, powering multiplayer gaming with ultra-low latency, and accelerating content delivery through a global node network. Supporting links Stabull Finance Datagram Andy on Twitter  Brave New Coin on Twitter Brave New Coin If you enjoyed the show please subscribe to the Crypto Conversation and give us a 5-star rating and a positive review in whatever podcast app you are using.  

In this episode, Carlos Gonzalez de Villaumbrosia interviews Nicholas Daniel, Chief Product Officer at Etsy — the world's largest marketplace for unique and handmade items. Founded in 2005, Etsy has grown into a global platform connecting over 6 million sellers with 90 million buyers worldwide, featuring more than 130 million unique items.Nicholas leads Etsy's product organization, overseeing 30+ product squads that drive innovation across the marketplace. His 11-year tenure at Etsy has been instrumental in transforming the platform from a web-centric marketplace to a multi-platform powerhouse while staying true to its core mission of "keeping commerce human."We explore how Etsy manages its massive scale of unique inventory, leverages AI for better discovery, and maintains the delicate balance between growth and marketplace identity. Nicholas shares insights on structuring product teams around business challenges, measuring seller success, and fostering innovation through features like "Spaces" that enhance browsing experiences.What you'll learn:How Etsy structures its product organization to tackle marketplace challengesStrategies for managing and categorizing millions of unique itemsKey metrics for measuring seller success and platform healthApproaches to balancing automation with maintaining human connectionsThe role of AI in understanding and surfacing unique inventoryKey Takeaways

Tom Young, VP of Sales at BMC Software, joins Matt Benelli to challenge outdated assumptions about how enterprise sales should work. Drawing on decades of experience and a recent moment on the other side of a buying decision, Tom reveals how sellers often leave buyers to navigate complex purchasing decisions alone, leading to stalled deals, weak adoption, and low rep confidence. The problem isn't buyer intent. It's a lack of structure, coaching, and guidance.This conversation gets tactical and strategic. Tom breaks down the myth that buyers know how to buy, why seller-led engagement models outperform passive following, and how high-performing FLMs simplify complexity through coaching, not control. CROs and sales leaders will appreciate the clear through line: when managers teach reps how to lead a buying journey, not just chase a number, sales cycles shorten, win rates improve, and performance becomes repeatable. If you're building a scalable sales org, this is a must-listen.Top TakeawaysEnterprise buyers often don't know how to buy software Despite assumptions, many buyers lack a defined decision process, which means sellers must guide, not follow, their journey.The best salespeople act as guides, not followers When sellers proactively lead buyers through a structured engagement model, the experience improves and adoption increases.Mutual Action Plans need to go beyond the PO date Ending your plan at "PO received" signals self-interest; the real impact comes from aligning with the customer's go-live and success milestones.Effective FLMs sell the engagement model, not the product first Top-performing managers train reps to win by selling how the decision will be made, not just what to buy.Sellers must ask the questions buyers should be asking themselves High-quality discovery isn't just fact-finding; it helps buyers clarify their own thinking, build confidence, and reduce internal friction.Sales cycles fail when reps abdicate process control Letting the buyer “drive” often results in delays, missed stakeholders, and no decision; a structured engagement keeps momentum.Managers must balance pressure with coaching Pushing deals without guiding reps through skills and behavior leads to burnout and underperformance.You can't outsource coaching and rep development Even strong enablement and RevOps support can't replace the day-to-day behavioral coaching frontline managers must deliver.One-on-ones are not for pipeline inspection—they're for skill development Coaching isn't about the forecast; it's about improving rep effectiveness so the forecast becomes more predictable.Every manager needs a consistent, inspectable operating rhythm Without structured 1:1s and repeatable frameworks, rep development becomes ad hoc, and performance becomes unpredictable.Ways to Tune In:Spotify: https://open.spotify.com/show/0Yb1wPzUxyrfR0Dx35ym1A Apple Podcasts: https://podcasts.apple.com/us/podcast/coach2scale-how-modern-leaders-build-a-coaching-culture/id1699901434 Google Podcasts: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy50cmFuc2lzdG9yLmZtL2NvYWNoMnNjYWxlLWhvdy1tb2Rlcm4tbGVhZGVycy1idWlsZC1hLWNvYWNoaW5nLWN1bHR1cmU Amazon Music: https://music.amazon.com/podcasts/fd188af6-7c17-4b2e-a0b2-196ecd6fdf77 Podchaser: https://www.podchaser.com/podcasts/coach2scale-how-modern-leaders-5419703 YouTube: https://www.youtube.com/@Coach2Scale CoachEm™ is the first Coaching Execution Platform that integrates deep learning technology to proactively analyze patterns, highlight the "why" behind the data with root causes, and identify the actions that will ultimately improve business results going forward.  These practical coaching recommendations for managers will help their teams drive more deals, bigger deals, faster deals, and loyal customers. Built with decades of go-to-market experience, world-renowned data scientists, and advanced causal AI/ML technology, CoachEm™ leverages your existing tech stack to increase rep productivity, increase retention, and replicate best practices across your team.Learn more at coachem.io

In this episode of The New Stack Makers, recorded at KubeCon + CloudNativeCon Europe, Alex Williams speaks with Ville Aikas, Chainguard founder and early Kubernetes contributor. They reflect on the evolution of container security, particularly how early assumptions—like trusting that users would validate container images—proved problematic. Aikas recalls the lack of secure defaults, such as allowing containers to run as root, stemming from the team's internal Google perspective, which led to unrealistic expectations about external security practices.The Kubernetes community has since made strides with governance policies, secure defaults, and standard practices like avoiding long-lived credentials and supporting federated authentication. Aikas founded Chainguard to address the need for trusted, minimal, and verifiable container images—offering zero-CVE images, transparent toolchains, and full SBOMs. This security-first philosophy now extends to virtual machines and Java dependencies via Chainguard Libraries.The discussion also highlights the rising concerns around AI/ML security in Kubernetes, including complex model dependencies, GPU integrations, and potential attack vectors—prompting Chainguard's move toward locked-down AI images.Learn more from The New Stack about Container Security and AIChainguard Takes Aim At Vulnerable Java LibrariesClean Container Images: A Supply Chain Security RevolutionRevolutionizing Offensive Security: A New Era With Agentic AI Join our community of newsletter subscribers to stay on top of the news and at the top of your game. 

Your favorite podcast about nothing continues to find things to talk about. Whatever you do, DO NOT e-mail me at podcast@searls.co or else I will read it on air and tell everyone how smart you sound and how good you look. Video of this edition of the show is up on YouTube. Links to follow: Loving my Tariffmas gifts: external SSD array and pool skimmer, especially My first taste of GitHub Copilot's Agent mode Me putting Agent mode to the test in a fun little screencast Aaron's puns, ranked Videogame consoles like the Switch 2 are NOT exempt from tariffs Digital Foundry's technical analysis of Mario Kart World The stunning Marathon cinematic trailer Star Wars Zero Company is the X-Com game I want Almost 19% of Japanese people in their 20s have spent so much money on gacha they struggled with covering living expenses, survey reveals A bunch of Vision hardware leaks and rumors: 1, 2, 3, 4 People at Apple were calling the AI/ML group AIMLess, lol React Native might not be as popular as you think Boarding passes and check-in could be scrapped in air travel shake-up Incredible plot to print every single possible ticket to win the Texas lotto A Lack of Intelligence, Not Training, May Be Why People Struggle With Computers AI models still struggle to debug software, Microsoft study shows LLM bots + Next.js bankrupting people who design their sites badly Apps are being paid to install frameworks that sell users' bandwidth to proxy providers for AI scrapers OpenAI o3 and o4-mini announced (they also hallucinate more) GPT 4.1 is better at coding Codex CLI is OpenAI's answer to Claude Code Extremely long read: OpenAI is a Systemic Risk to the Tech Industry GPS magnetic quantum is 50x more accurate and unjammable The Gorge is good but takes a sharp left turn into horror town I went to Epic Universe and have opinions

In today's episode, Chandra Kapireddy, head of generative AI, machine learning, and analytics at Truist, delves into the evolving landscape of AI with a particular focus on how GenAI tools reshape the way Truist and similar organizations must navigate model risk management and regulations. GenAI is more versatile than traditional AI, he notes, yet its flexibility introduces new challenges around ensuring model reliability, validating outputs, and making sure that AI-driven decisions don't lead to unfair or opaque outcomes. Chandra's responsible AI approach at Truist is focused on risk mitigation while emphasizing the importance of human oversight in high-stakes decision-making. He points out that while GenAI can vastly improve productivity by handling repetitive or analysis-heavy tasks, it's essential to properly train employees in order to use the tools effectively and not over-rely on their outputs, especially given their tendency to hallucinate or produce inaccurate results. Read the episode transcript here. Guest bio Chandra Kapireddy is head of generative AI, machine learning, and analytics, at Truist. He brings over 27 years of experience building and leading world-class data, analytics, and artificial intelligence teams to the financial services firm. Kapireddy has held key leadership positions at some of the industry's leading companies, including Capital One, Wells Fargo, Bank of America, Oracle, and Amazon Web Services. Most recently, he served as managing director and head of AI/ML products for JPMorgan Chase, where he served on the firm's AI Executive Council, which influences its strategy, products, controls, and governance. Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the executive producer is Allison Ryder. Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.

Today, I'm talking with Natalia Andreyeva from Infor about AI / ML product management and its application to supply chain software. Natalia is a Senior Director of Product Management for the Nexus AI / ML Solution Portfolio, and she walks us through what is new, and what is not, about designing AI capabilities in B2B software. We also got into why user experience is so critical in data-driven products, and the role of design in ensuring AI produces value. During our chat, Natalia hit on the importance of really nailing down customer needs through solid discovery and the role of product leaders in this non-technical work. We also tackled some of the trickier aspects of designing for GenAI, digital assistants, the need to keep efforts strongly grounded in value creation for customers, and how even the best ML-based predictive analytics need to consider UX and the amount of evidence that customers need to believe the recommendations. During this episode, Natalia emphasizes a huge key to her work's success: keeping customers and users in the loop throughout the product development lifecycle.   Highlights/ Skip to What Natalia does as a Senior Director of Product Management for Infor Nexus (1:13) Who are the people using Infor Nexus Products and what do they accomplish when using them (3:01) Breaking down who makes up Natalia's team (4:15) What role does AI play in Natalia's work? (5:42) How do designers work with Natalia's team? (7:27) The problem that had Natalia rethink the discovery process when working with AI and machine learning applications (10:38) Why Natalia isn't worried about competitors catching up to her team's design work (14:34) How Natalia works with Infor Nexus customers to help them understand the solutions her team is building (23:17) The biggest challenges Natalia faces with building GenAI and machine learning products (27:35) Natalia's four steps to success in building AI products and capabilities (35:03) Where you can find more from Natalia (36:59)   Quotes from Today's Episode “I always launch discovery with customers, in the presence of the UX specialist [our designer]. We do the interviews together, and [regardless of who is facilitating] the goal is to understand the pain points of our customers by listening to how they do their jobs today. We do a series of these interviews and we distill them into the customer needs; the problems we need to really address for the customers. And then we start thinking about how to [address these needs]. Data products are a particular challenge because it's not always that you can easily create a UX that would allow users to realize the value they're searching for from the solution. And even if we can deliver it, consuming that is typically a challenge, too. So, this is where [design becomes really important]. [...] What I found through the years of experience is that it's very difficult to explain to people around you what it is that you're building when you're dealing with a data-driven product. Is it a dashboard? Is it a workboard? They understand the word data, but that's not what we are creating. We are creating the actual experience for the outcome that data will deliver to them indirectly, right? So, that's typically how we work.” - Natalia Andreyeva (7:57) “[When doing discovery for products without AI], we already have ideas for what we want to get out. We know that there is a space in the market for those solutions to come to life. We just have to understand where. For AI-driven products, it's not only about [the user's] understanding of the problem or the design, it is also about understanding if the data exists and if it's feasible to build the solution to address [the user's] problem. [Data] feasibility is an extremely important piece because it will drive the UX as well.” - Natalia Andreyeva (11:00) “When [the team] discussed the problem, it sounded like a simple calculation that needed to be created [for users]. In reality, it was an entire process of thinking of multiple people in the chain [of command] to understand whether or not a medical product was safe to be consumed. That's the outcome we needed to produce, and when we finally did, we actually celebrated with our customers and with our designers. It was one of the most difficult things that we had to design. So why did this problem actually get solved, and why we were the ones who solved it? It's because we took the time to understand the current user experience through [our customer] interviews. We connected the dots and translated it all into a visual solution. We would never be able to do that without the proper UX and design in that place for the data.” - Natalia Andreyeva (13:26) “Everybody is pressured to come up with a strategy [for AI] or explain how AI is being incorporated into their solutions and platform, but it is still essential for all of my peers in product management to focus on the value [we're] creating for customers. You cannot bypass discovery. Discovery is the essential portion where you have to spend time with your customers, champions, advisors, and their leads, but especially users who are doing this [supply chain] job every single day—so we understand where the pain point really is for them, we solve that pain, and we solve it with our design team as a partner, so that solution can surface value. ” - Natalia Andreyeva (22:18) “GenAI is a new field and new technology. It's evolving quickly, and nobody really knows how to properly adapt or drive the adoption of AI solutions. The speed of innovation [in the AI field] is a challenge for everybody. People who work on the frontlines (i.e. product, engineering teams), have to stay way ahead of the market. Meanwhile, customers who are going to be using these [AI] solutions are not going to trust the [initial] outcomes. It's going to take some time for people to become comfortable with them. But it doesn't mean that your solution is bad or didn't find the market fit. It's just not time for your [solution] yet. Educating our users on the value of the solution is also part of that challenge, and [designers] have to be very careful that solutions are accessible. Users do not adopt intimidating solutions.” - Natalia Andreyeva (27:51) “First, discovery—where we search for the problems. From my experience, [discovery] works better if you're very structured. I always provide [a customer] with an outline of what needs to happen so it's not a secret. Then, do the prototyping phase and keep the customer engaged so they can see the quick outcomes of those prototypes. This is where you also have to really include the feasibility of the data if you're building an AI solution, right? [Prototyping] can be short or long, but you need to keep the customer engaged throughout that phase so they see quick outcomes. Keep on validating this conceptually, you know, on the napkin, in Figma, it doesn't really matter; you have to keep on keeping them engaged. Then, once you validate it works and the customer likes it, then build. Don't really go into the deep development work until you know [all of this!] When you do build, create a beta solution. It only has to work so much to prove the value. Then, run the pilot, and if it's successful, build the MVP, then launch. It's simple, but it is a lot of work, and you have to keep your customers really engaged through all of those phases. If something doesn't work [along the way], try to pivot early enough so you still have a viable product at the end.” - Natalia Andreyeva (35:03)   Links Natalia's LinkedIn

In this conversation of Coach the Scale, host Matt Benelli sits down with Michael Janes, CRO, investor, and co-founder of Rapid Commercialization Partners, to explore why top sales leaders are shifting their focus upstream. Janes unpacks his core philosophy: Sell to the strategy behind the capital, revealing how understanding a company's ownership structure, whether private equity, venture-backed, or founder-led, can dramatically reshape how reps position value, influence internal champions, and align with executive priorities.From myth-busting the idea that activity volume alone drives results to challenging how most one-on-ones miss the mark, Janes offers a grounded yet forward-looking perspective on what it takes to lead high-performance sales organizations. Listeners will walk away with practical insights on coaching beyond the forecast, the dangers of “super rep” management, and why the real leverage often starts at the board level, not the buying committee. If you're a CRO or sales leader aiming to uplevel your team and shorten the path to influence, this conversation is required listening.Key Takeaways:1. Sell to the strategy behind the capitalDon't just “follow the money”—understand the investor's goals and align your sales motion to how capital is deployed, managed, and expected to grow.2. Coaching needs to shift from deal review to skill developmentMost one-on-ones are ineffective because they focus on forecasting instead of developing the behaviors that lead to consistent performance.3. One-on-ones are broken when they lack preparation and structureGreat coaching starts with preparation; otherwise, reps get a therapy session or a pipeline interrogation, not actual development.4. Sales managers are overwhelmed and under-equippedFLMs are juggling too many priorities with little training on how to coach or drive rep performance—this gap undermines quota attainment.5. Activity without purpose is a myth that needs killingThe old-school mindset of “just make more calls” misses the point; consistency only matters if it's paired with relevance and precision.6. Start high and cascade down—not the other way aroundThe most strategic salespeople begin with senior-level conversations, understanding investor priorities, then work downward to shape the internal sale.7. Internal champions are built through strategic guidance, not feature pitching.Could you make sure to provide your buyers with the narrative they need to sell internally by aligning your message with capital goals and business outcomes?8. Overlay roles only work when they add real valueJanes proved that overlays focused on investor relations can be a force multiplier—but only if they help reps access decision-makers and frame deals through a capital lens.9. Respect the chain of command—but don't ask permissionWhen engaging PE or VC boards, it's critical to keep execs in the loop without letting them gatekeep the conversation.10. Managers need enablement, too—not just repsThe assumption that great reps make great managers is flawed; without systems, training, and coaching support, FLMs can't scale performance across the team.Ways to Tune In:Spotify: https://open.spotify.com/show/0Yb1wPzUxyrfR0Dx35ym1A Apple Podcasts: https://podcasts.apple.com/us/podcast/coach2scale-how-modern-leaders-build-a-coaching-culture/id1699901434 Google Podcasts: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy50cmFuc2lzdG9yLmZtL2NvYWNoMnNjYWxlLWhvdy1tb2Rlcm4tbGVhZGVycy1idWlsZC1hLWNvYWNoaW5nLWN1bHR1cmU Amazon Music: https://music.amazon.com/podcasts/fd188af6-7c17-4b2e-a0b2-196ecd6fdf77 Podchaser: https://www.podchaser.com/podcasts/coach2scale-how-modern-leaders-5419703 YouTube: https://www.youtube.com/@Coach2Scale CoachEm™ is the first Coaching Execution Platform that integrates deep learning technology to proactively analyze patterns, highlight the "why" behind the data with root causes, and identify the actions that will ultimately improve business results going forward.  These practical coaching recommendations for managers will help their teams drive more deals, bigger deals, faster deals, and loyal customers. Built with decades of go-to-market experience, world-renowned data scientists, and advanced causal AI/ML technology, CoachEm™ leverages your existing tech stack to increase rep productivity, increase retention, and replicate best practices across your team.Learn more at coachem.io

Industrial Talk is onsite at PowerGen 2025 and talking to Buddy Lee, Artificial Intelligence SME at Mesa Associates about "AI and Asset Management". Scott MacKenzie hosts an industrial podcast from Power Gen in Dallas, Texas, celebrating industry professionals and discussing innovations. Buddy Lee from Mesa Associates, an AI subject matter expert, shares his background in electrical engineering and reliability engineering. Buddy discusses the application of AI in asset management, particularly in detecting anomalies and predicting failures in industrial machinery. He highlights the importance of having a good data set for AI models, emphasizing the need for accurate and reliable data. Buddy also touches on the cultural challenges of implementing AI in industrial settings and the potential for AI to improve operational efficiency and reduce maintenance costs. Action Items [ ] Reach out to Buddy Lee to discuss further details on Mesa's AI-powered asset management solutions. [ ] Explore opportunities to instrument industrial equipment and collect relevant sensor data for AI/ML model development. [ ] Assess current maintenance practices and failure modes to determine if an FMEA-based AI approach could provide value. Outline Introduction and Welcome to Industrial Talk Podcast Scott MacKenzie introduces the Industrial Talk Podcast, emphasizing its focus on industry professionals and their innovations. Scott welcomes listeners to the platform, highlighting the importance of industry professionals in solving global problems. The podcast is broadcasting from Power Gen in Dallas, Texas, showcasing the latest innovations in the power generation industry. Scott mentions the excitement of the event and the opportunities to explore new technologies on the show floor. Introduction of Buddy Lee and His Background Scott introduces Buddy Lee from Mesa Associates, who has previously been a guest on the show. Buddy shares his background, mentioning his education at the University of Tennessee and Carson Newman College. Buddy discusses his degrees in church music, electrical engineering, MBA, and Masters of Engineering in reliability engineering. Scott notes Buddy's enthusiasm for Tennessee and his support for the University of Tennessee's football team. Discussion on Power Generation and AI in the Industry Buddy talks about his positive experience at the Power Gen conference, highlighting the technical information and new equipment available. They discuss the advancements in small modular reactors and AI in the hydro industry. Scott and Buddy touch on the role of AI in driving power demand, particularly in data centers. Buddy explains his role as the AI subject matter expert at Mesa Associates, focusing on industrial applications. Buddy's Thesis on AI Models and Data Sets Buddy shares his thesis on using AI models with limited data sets, specifically vibration analysis from a paper machine. He explains the process of comparing AI models to human analysts using a seven-year database of vibration data. Buddy highlights the accuracy of five AI models in predicting bearing failures, achieving 95% accuracy. Scott and Buddy discuss the differences between large language models and small data sets in AI applications. AI Applications in Industrial Asset Management ...

Send us a textToday's guest is someone who needs no introduction in the world of innovation, data science, and education—but still, let's give him the one he deserves! Meet Dr. Noble Arya – a man who has turned curiosity into a mission and learning into a global movement.From working with giants like GE and Wipro to founding his own global learning platform, from earning over 200+ certifications in AI/ML to winning 300+ awards in innovation and project management—he's done it all. He's not just a Data Scientist, he's a full-stack educator, an innovation mentor, and a modern-day monk practicing Vipassana meditation with the same dedication he gives to algorithms.Connect With Kapeel Guptaor Click on the link: http://bit.ly/4jlql8sWhat You May Learn0:00 Introduction3:15 Q16:42 Q213:35 Q316:03 Q420:10 Q523:45 Q633:16 Q741:10 Q843:24 Q948:10 Q1050:43 Q1154:34 Q!21:04:04 Call to ActionSupport the show

This blog defines the governance requirements that streaming data pipelines must meet to make artificial intelligence/machine learning (AI/ML) initiatives successful. Published at: https://www.eckerson.com/articles/streaming-data-governance-three-must-have-requirements-to-support-ai-ml-innovation

Hello Las Vegas — we've arrived for Google Cloud Next 2025!Arthur C. Clarke's third law, "Any sufficiently advanced technology is indistinguishable from magic"Hot drop coming through! The Cloud Realities podcast team has landed in electric Las Vegas—and you know what they say: what happens in Vegas normally stays in Vegas... but in this case, we're bringing 8 incredible conversations in the coming days with inspiring Google guests who are shaping the future of cloud, data, and AI.On the first day, we have 3 separate episodes lined up to discuss Google AI strategy & vision, practical implementations, and exciting use cases.In the second conversation, Dave, Esmee, and Rob, talk with Charlotte Gistelinck, Machine Learning / AI Partner Engineer at Google, on how strategic thinking and visioning in AI/ML are key to driving innovation and long-term success.TLDR00:24 Introduction of Charlotte Gistelinck 04:12 Key announcements from the Google Cloud Next Keynote 07:17 Main conversation with Charlotte about Strategic Thinking and Visioning in AI  37:14 Who's your favorite magician?GuestCharlotte Gistelinck: https://www.linkedin.com/in/charlottegistelinck/HostsDave Chapman: https://www.linkedin.com/in/chapmandr/Rob Kernahan: https://www.linkedin.com/in/rob-kernahan/ProductionMarcel van der Burg: https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman: https://www.linkedin.com/in/chapmandr/SoundBen Corbett: https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:  https://www.linkedin.com/in/louis-corbett-087250264/'Cloud Realities' is an original podcast from Capgemini

Hello Las Vegas — we've arrived for Google Cloud Next 2025!Arthur C. Clarke's third law, "Any sufficiently advanced technology is indistinguishable from magic"Hot drop coming through! The #CloudRealities podcast team has landed in electric Las Vegas—and you know what they say: what happens in Vegas normally stays in Vegas... but in this case, we're bringing 8 incredible conversations in the coming days with inspiring guests who are shaping the future of cloud, data, and AI.On the first day, we have 3 separate episodes lined up to discuss Google AI strategy & vision, practical implementations, and exciting use cases.In the third conversation, Dave, Esmee, and Rob talk with Jim Anderson, VP, NA Partner Ecosystem & Channels at Google, on how customers are using Cloud, AI/ML, and Data Analytics to power digital transformation. From real-world success stories to the trends shaping the year ahead—this one's packed with actionable insights.TLDR00:23 Introduction of Jim Anderson04:17 Key announcements from the Google Cloud Next Keynote06:44 Main conversation with Jim Anderson about Driving Digital Transformation with Customers 24:50 Who's your favorite magician?GuestJim Anderson: https://www.linkedin.com/in/jimmya/HostsDave Chapman: https://www.linkedin.com/in/chapmandr/Rob Kernahan: https://www.linkedin.com/in/rob-kernahan/ProductionMarcel van der Burg: https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman: https://www.linkedin.com/in/chapmandr/SoundBen Corbett: https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:  https://www.linkedin.com/in/louis-corbett-087250264/'Cloud Realities' is an original podcast from Capgemini

Discusses the importance of fostering AI literacy in research and higher education. Our guest today is Sarah Florini who is an Associate Director and Associate Professor in the Lincoln Center for Applied Ethics at Arizona State University. Sarah's work focuses on technology, social media, technology ethics, digital ethnography, and Black digital culture. Among other things, Sarah is dedicated to fostering critical AI literacy and ethical engagement with AI/ML technologies. She founded the AI and Ethics Workgroup to serve as a catalyst for critical conversations about the role of AI models in higher education.  Additional resources: Distributed AI Research Institute: https://www.dair-institute.org/ Mystery AI Hype Theater 3000: https://www.dair-institute.org/maiht3k/ Tech Won't Save Us: https://techwontsave.us/ CITI Program's Essentials of Responsible AI course: https://about.citiprogram.org/course/essentials-of-responsible-ai/ 

In this episode, bestselling author and CEO of Blind Spots, Kevin McCarthy, shares a deeply personal story of how unchecked blind spots, not bad intent, can quietly derail careers, culture, and company performance. After spending 33 months in federal prison for a white-collar crime he didn't knowingly commit, Kevin emerged with a mission: help leaders see what they're not seeing before it costs them everything.When top performers become first-line managers, most are handed the title without the tools. We explore why so many sales managers default to deal reviews instead of skill development, how perception gaps fracture team trust, and why most coaching is misnamed and misdirected. Kevin breaks down the cognitive science behind decision-making under pressure and explains how poor coaching hygiene is driving regrettable attrition. This conversation hits directly at the heart of today's frontline execution crisis and offers a clear path forward for CROs who want to scale with integrity.Top Takeaways: Blind spots—not bad intentions—derail leaders. Kevin's story underscores that well-meaning leaders can still make costly mistakes if they lack self-awareness and critical thinking under pressure.Perception gaps destroy trust and performance. The difference between how a manager intends to communicate and how it's received can lead to misalignment, demotivation, and attrition.Sales managers are promoted, not prepared. High-performing reps are often elevated into management without training in people leadership, coaching skills, or emotional intelligence.Most sales coaching isn't actually coaching. Managers default to forecasting and deal reviews, missing the opportunity to develop reps' skills in a systematic and personalized way.One-size-fits-all management breaks teams. Kevin explains how failing to adapt your coaching style to each rep's communication style and mindset leads to disengagement.The hardest job in the company is being ignored. First-line managers juggle execution, admin, and development but rarely get the support, tools, or training to coach effectively.Reps leave when they don't feel developed. Talent walks when managers only talk numbers. Real coaching connects with reps' goals, strengths, and growth trajectory.Self-awareness is the most underdeveloped leadership skill. Kevin makes the case that improving self-awareness and emotional intelligence in managers is the single best lever for improving sales culture.Frontline execution problems are strategic risks. What looks like a rep issue is often a management system failure—CROs must prioritize manager enablement if they want predictable performance.Ways to Tune In:Spotify: https://open.spotify.com/show/0Yb1wPzUxyrfR0Dx35ym1A Apple Podcasts: https://podcasts.apple.com/us/podcast/coach2scale-how-modern-leaders-build-a-coaching-culture/id1699901434 Google Podcasts: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy50cmFuc2lzdG9yLmZtL2NvYWNoMnNjYWxlLWhvdy1tb2Rlcm4tbGVhZGVycy1idWlsZC1hLWNvYWNoaW5nLWN1bHR1cmU Amazon Music: https://music.amazon.com/podcasts/fd188af6-7c17-4b2e-a0b2-196ecd6fdf77 Podchaser: https://www.podchaser.com/podcasts/coach2scale-how-modern-leaders-5419703 YouTube: https://www.youtube.com/@Coach2Scale CoachEm™ is the first Coaching Execution Platform that integrates deep learning technology to proactively analyze patterns, highlight the "why" behind the data with root causes, and identify the actions that will ultimately improve business results going forward.  These practical coaching recommendations for managers will help their teams drive more deals, bigger deals, faster deals, and loyal customers. Built with decades of go-to-market experience, world-renowned data scientists, and advanced causal AI/ML technology, CoachEm™ leverages your existing tech stack to increase rep productivity, increase retention, and replicate best practices across your team.Learn more at coachem.io

Join us on "Beyond the Numbers: Leadership, Diversity, and Data with Natalie Cramp, Partner at JMAN Group," where we dive deep into the intersections of data science, leadership, and advocacy for diversity. Each episode, hosted by Natalie Cramp, offers an exploration of how data-driven strategies can reshape industries and enhance decision-making processes. Natalie brings nearly two decades of experience across private, public, and third sectors, providing unique insights into mobilizing technology and people to address complex challenges. In this series, we'll uncover the transformative power of data in driving business success and societal change. Natalie will share her expertise in scaling organizations, entering new markets, and leading significant transformations. Additionally, we focus on her passionate work in promoting gender equality in healthcare through data, offering listeners actionable insights and inspiration to leverage data for impactful change. Whether you're a CEO looking to harness the potential of AI, a data professional aiming to advance in the tech field, or someone interested in the crucial role of data ethics and education, this podcast will equip you with the knowledge and perspectives needed to lead effectively in today's data-centric world. Tune in to gain leadership insights from one of the data industry's most influential figures and learn how you can contribute to a more diverse and inclusive data science landscape. Learn more about Leadership in AI/ML at DSS SEA on April 16 https://www.datascience.salon/seattle/

Welcome to the TestGuild Automation Podcast! In this episode, host Joe Colantonio sits down with Gaurav Mittal, a cybersecurity, data science, and IT expert with over two decades of experience. Gaurav, recognized for his thought leadership in AI and automation with multiple industry awards, shares his insights on making How To Optimize your Automation CI/CD Pipelines in DevOps more cost-effective. Whether you're a test automation engineer or security professional or work with AI/ML, you'll want to hear Gaurav's take on implementing DevOps pipelines that reduce licensing costs and enhance flexibility without sacrificing your team's productivity. Learn about his experiences with GitHub Actions, Jenkins, and the innovative ways he's optimized CI/CD pipelines to save resources and automate extensive testing processes, all while incorporating strong security measures. Join us as we delve into the innovative strategies and practical advice that can help transform your DevOps practices.

Matt Benelli sits down with Mike Montague, sales and marketing expert at Avenue9 and host of the Human-First AI Marketing podcast, for a candid conversation about what sales managers are still getting wrong about coaching. From the myth that leaders need to have all the answers to the burnout caused by "super reps" turned managers, Mike breaks down why most 1:1s fail and how asking better questions can flip the script on team performance. If you're still equating pipeline reviews with coaching, this one's for you.They also unpack the critical gap between coaching and execution and why online learning and conversation intelligence tools fall short without behavior change. Mike shares his "Iron Man vs. Terminator" analogy to help sales leaders reframe their use of AI and makes the case for exposure therapy and tough love as the missing ingredients in most sales organizations. Whether you're trying to scale performance or stop regrettable attrition, this episode gives frontline and senior leaders a roadmap for more effective, accountable teams.Top Takeaways:Coaching is about asking questions, not giving answers. Managers who try to “know it all” become bottlenecks; real coaching empowers reps to think for themselves.The best leaders make themselves irrelevant. Like elite sports coaches, great sales leaders build systems and skills so teams can operate independently.AI won't replace salespeople, but it will replace those who don't use it. Sales leaders need to think like Ironman, using AI as an enhancement tool to increase awareness and execution, not as a replacement for human strategy.The frontline sales manager (FLM) role is the hardest in the company. FLMs are overwhelmed by tasks, undertrained in coaching, and lack the time or tools to develop their teams effectively.Selling someone what they need and can afford isn't cheating—it's your job. Sales should focus on qualified buyers with budget, authority, and urgency, not on convincing disinterested prospects.Coaching fails when it focuses only on deals, not skills. Most coaching sessions are just pipeline reviews; they don't address the behaviors that improve performance in the long term.Exposure therapy is essential for growth. Managers need more reps, not more theory, to improve at hard conversations or high-stakes moments.Online learning is helpful but only if it's paired with feedback and behavior change. Asynchronous learning tools often reinforce what reps already know; without coaching moments, they don't close performance gaps.Managers who need approval frequently avoid necessary conversations. Leadership requires discomfort, and effective managers must overcome the urge to be liked to hold reps accountable.Coaching is different from managing—and most people don't know how to do it. There's a widespread misunderstanding of coaching; most FLMs were never taught how to develop others, and it shows.Ways to Tune In:Spotify: https://open.spotify.com/show/0Yb1wPzUxyrfR0Dx35ym1A Apple Podcasts: https://podcasts.apple.com/us/podcast/coach2scale-how-modern-leaders-build-a-coaching-culture/id1699901434 Google Podcasts: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy50cmFuc2lzdG9yLmZtL2NvYWNoMnNjYWxlLWhvdy1tb2Rlcm4tbGVhZGVycy1idWlsZC1hLWNvYWNoaW5nLWN1bHR1cmU Amazon Music: https://music.amazon.com/podcasts/fd188af6-7c17-4b2e-a0b2-196ecd6fdf77 Podchaser: https://www.podchaser.com/podcasts/coach2scale-how-modern-leaders-5419703 YouTube: https://www.youtube.com/@Coach2Scale CoachEm™ is the first Coaching Execution Platform that integrates deep learning technology to proactively analyze patterns, highlight the "why" behind the data with root causes, and identify the actions that will ultimately improve business results going forward.  These practical coaching recommendations for managers will help their teams drive more deals, bigger deals, faster deals, and loyal customers. Built with decades of go-to-market experience, world-renowned data scientists, and advanced causal AI/ML technology, CoachEm™ leverages your existing tech stack to increase rep productivity, increase retention, and replicate best practices across your team.Learn more at coachem.io

Ever wondered how companies like Amazon or Pinterest deliver lightning-fast image search? Dive into this episode of MongoDB Podcast Live with Shane McAllister and Nenad, a MongoDB Champion, as they unravel the magic of semantic image search powered by MongoDB Atlas Vector Search!

In this Light Reading Extra podcast, SES' Nadine Allen explains how the satellite operator is applying AI, ML and SDN to improve application and network performance, and how the company is providing connectivity to underserved areas. Hosted on Acast. See acast.com/privacy for more information.

Every sales leader has heard the mantra: “Pipeline cures all.” But what if that's only half the truth? In this episode, Matt Carey, SVP of Global Sales at FIS, breaks down why more pipeline isn't always the answer—the right pipeline is. He shares hard-earned lessons from leading sales teams at Oracle, SAP, and FIS, explaining how top-performing organizations prioritize quality over quantity, measure pipeline health beyond raw coverage, and avoid common forecasting pitfalls.Matt also explores the real role of frontline managers, not as super reps, but as force multipliers who elevate their teams. He discusses hiring strategies that separate true performers from resume fluff, the importance of post-mortem loss reviews, and why most companies still get coaching wrong. Whether you're a CRO, VP of Sales, or a frontline manager looking to level up, this conversation is packed with insights that will change the way you build and manage your pipeline.Top Takeaways:Pipeline Quantity vs. Quality – More pipeline doesn't guarantee success; leaders must focus on the right pipeline by assessing deal quality, aging, and true viability.The Problem with "Just Add More Pipeline" Thinking – Sales teams often flood CRMs with unqualified deals to meet coverage targets, leading to bloated and misleading forecasts.Why Frontline Managers Must Stop Being Super Reps – The best managers don't just close deals for their teams; they enable reps to develop the skills to win consistently.Hiring Based on Past Performance, Not Promises – Great sales hires have a history of winning, regardless of industry or background; track record matters more than potential.Loss Reviews Are More Valuable Than Win Reviews – Studying why deals were lost provides deeper insights into messaging gaps, pricing misalignment, and product fit issues.How Sales Leaders Sell Internally – At higher levels, sales leaders spend as much time selling internally for budget, resources, and strategy alignment as they do selling to customers.Coaching Needs a System, Not Just Good Intentions – Too many one-on-ones are either deal reviews or therapy sessions; real coaching needs structure, accountability, and a focus on skill development.Managing a Global Sales Team Requires Cultural Awareness – Sales leaders must adapt their messaging and approach across markets, respecting regional differences in business etiquette and buying behavior.The Shift from Tactical to Strategic Leadership – Senior sales leaders must move beyond the day-to-day deal cycle and focus on long-term market positioning, competitive threats, and team scalability.Why Sales Leaders Must Track Trends, Not Just Deals – The best leaders analyze broader win-loss data, competitive shifts, and industry changes to refine strategy, not just react to individual deal outcomes.Ways to Tune In:Spotify: https://open.spotify.com/show/0Yb1wPzUxyrfR0Dx35ym1A Apple Podcasts: https://podcasts.apple.com/us/podcast/coach2scale-how-modern-leaders-build-a-coaching-culture/id1699901434 Google Podcasts: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy50cmFuc2lzdG9yLmZtL2NvYWNoMnNjYWxlLWhvdy1tb2Rlcm4tbGVhZGVycy1idWlsZC1hLWNvYWNoaW5nLWN1bHR1cmU Amazon Music: https://music.amazon.com/podcasts/fd188af6-7c17-4b2e-a0b2-196ecd6fdf77 Podchaser: https://www.podchaser.com/podcasts/coach2scale-how-modern-leaders-5419703 YouTube: https://www.youtube.com/@Coach2Scale CoachEm™ is the first Coaching Execution Platform that integrates deep learning technology to proactively analyze patterns, highlight the "why" behind the data with root causes, and identify the actions that will ultimately improve business results going forward.  These practical coaching recommendations for managers will help their teams drive more deals, bigger deals, faster deals, and loyal customers. Built with decades of go-to-market experience, world-renowned data scientists, and advanced causal AI/ML technology, CoachEm™ leverages your existing tech stack to increase rep productivity, increase retention, and replicate best practices across your team.Learn more at coachem.io

Rooshana Purnyn, Director of Data Architecture and Platform Engineering at Hyatt, discusses the potential of Generative AI in the hospitality sector, and how Hyatt is integrating AI to enhance guest experiences in their 1300 properties worldwide. She also emphasizes the need for balancing technology with human interaction, and fostering a culture of continuous learning within her team. Key Takeaways: How AI is used to understand, anticipate, and enhance the unique needs and travel habits of each guest. How Hyatt leverages AI to deliver seamless, highly personalized guest experiences across its 1,300 worldwide properties. The critical role of robust data architecture and pipeline design in supporting hospitality analytics. How a culture of innovation and a growth mindset drive the recruitment and development of Hyatt's teams. Guest Bio: Rooshana Purnyn is an innovative and strategic technology leader with extensive experience across the hospitality, healthcare, retail, finance, and marketing sectors. With over a decade of expertise in data and analytics, Rooshana serves as the Director of Data Architecture and Platform Engineering at Hyatt, where she is celebrated for designing, building, and managing large-scale, cutting-edge technology platforms that support data-driven decision making. A visionary in leveraging technology for business growth, Rooshana led the development of an advanced analytics platform optimized for AI/ML and generative AI workloads, enabling real-time data processing and supporting algorithmic product development to drive revenue and customer engagement. In her role, Rooshana has overseen the deployment of secure, globally accessible analytics applications, including the implementation of an AI-powered self-service analytics tool that empowers stakeholders with data insights. Her work in the AI/ML and generative AI space includes establishing scalable infrastructure and pipelines for machine learning operations (MLOps), allowing for seamless deployment of personalized customer experiences. Rooshana's commitment to innovation keeps her at the forefront of industry trends, while her customer-focused and data-centric approach consistently drives value and growth. ---------------------------------------------------------------------------------------- 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  

In this episode, we sit with security leader and venture investor Sergej Epp to discuss the Cloud-native Security Landscape. Sergej currently serves as the Global CISO and Executive at Cloud Security leader Sysdig and is a Venture Partner at Picus Capital. We will dive into some insights from Sysdig's recent "2025 Cloud-native Security and Usage Report."Big shout out to our episode sponsor, Yubico!Passwords aren't enough. Cyber threats are evolving, and attackers bypass weak authentication every day. YubiKeys provides phishing-resistant security for individuals and businesses—fast, frictionless, and passwordless.Upgrade your security:https://yubico.comSergj and I dove into a lot of great topics related to Cloud-native Security, including:Some of the key trends in the latest Sysdig 2025 Cloud-native Security Report and trends that have stayed consistent YoY. Sergj points out that while attackers have stayed consistent, organizations have and continue to make improvements to their securitySergj elaborated on his current role as Sysdig's internal CISO and his prior role as a field CISO and the differences between the two roles in terms of how you interact with your organization, customers, and the community.We unpacked the need for automated Incident Response, touching on how modern cloud-native attacks can happen in as little as 10 minutes and how organizations can and do struggle without sufficient visibility and the ability to automate their incident response.The report points out that machine identities, or Non-Human Identities (NHI), are 7.5 times riskier than human identities and that there are 40,000 times more of them to manage. This is a massive problem and gap for the industry, and Sergj and I walked through why this is a challenge and its potential risks.Vulnerability prioritization continues to be crucial, with the latest Sysdig report showing that just 6% of vulnerabilities are “in-use”, or reachable. Still, container bloat has ballooned, quintupling in the last year alone. This presents real problems as organizations continue to expand their attack surface with expanded open-source usage but struggle to determine what vulnerabilities truly present risks and need to be addressed.We covered the challenges with compliance, as organizations wrestle with multiple disparate compliance frameworks, and how compliance can drive better security but also can have inverse impacts when written poorly or not keeping pace with technologies and threats.We rounded out the conversation with discussing AI/ML packages and the fact they have grown by 500% when it comes to usage, but organizations have decreased public exposure of AI/ML workloads by 38% since the year prior, showing some improvements are being made to safeguarding AI workloads from risks as well.

Performance improvement plans (PIPs) are meant to help struggling reps, but more often than not, they're just a step toward the exit. So why do they fail? And what should CROs and frontline sales managers do instead to truly develop their teams? Why does urgency hurt your coaching?In this episode of Coach2Scale, host Matt Benelli sits down with Eric Hachmer and Steve Frappier of High Five Advisory to uncover the biggest mistakes sales leaders make when it comes to coaching and accountability. They break down why rigid sales policies backfire, how “one-size-fits-all” coaching kills performance, and the key to turning struggling reps into consistent performers. Whether you're leading a team or coaching the coaches, this episode is packed with real-world insights on what actually drives long-term sales success.Top Takeaways:Performance Improvement Plans (PIPs Often Fail) – PIPs are typically used as a last resort before termination rather than as a true coaching tool; leaders should focus on proactive development instead of reactive intervention.One-Size-Fits-All Coaching Doesn't Work – Every rep has different learning styles, motivations, and challenges, so great leaders tailor their coaching approach to individual needs instead of using a rigid playbook.Sales Policies Can Hurt More Than Help – Relying too much on black-and-white sales policies can create roadblocks for both customers and reps, whereas flexibility and good judgment lead to better outcomes.Good Leaders Focus on Behaviors, Not Just Results – The best sales managers don't just chase numbers; they work to change the behaviors that drive performance, ensuring long-term success.Listening Is a Leader's Superpower - Effective coaching starts with understanding. Great leaders take the time to listen before jumping to solutions, which builds trust and improves team engagement.Accountability Goes Both Ways – Reps should be held accountable for performance, but managers also need to take ownership of removing roadblocks, providing support, and developing their people.Urgency Can Get in the Way of Coaching – Sales leaders often move fast and focus on immediate results, but taking the time to coach properly leads to sustainable, long-term performance improvements.Trust and Authenticity Are Non-Negotiable – The best sales leaders show up as their true selves, follow through on their commitments, and create environments where reps feel supported, not micromanaged.Ways to Tune In:Spotify: https://open.spotify.com/show/0Yb1wPzUxyrfR0Dx35ym1A Apple Podcasts: https://podcasts.apple.com/us/podcast/coach2scale-how-modern-leaders-build-a-coaching-culture/id1699901434 Google Podcasts: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy50cmFuc2lzdG9yLmZtL2NvYWNoMnNjYWxlLWhvdy1tb2Rlcm4tbGVhZGVycy1idWlsZC1hLWNvYWNoaW5nLWN1bHR1cmU Amazon Music: https://music.amazon.com/podcasts/fd188af6-7c17-4b2e-a0b2-196ecd6fdf77 Podchaser: https://www.podchaser.com/podcasts/coach2scale-how-modern-leaders-5419703 YouTube: https://www.youtube.com/@Coach2Scale CoachEm™ is the first Coaching Execution Platform that integrates deep learning technology to proactively analyze patterns, highlight the "why" behind the data with root causes, and identify the actions that will ultimately improve business results going forward.  These practical coaching recommendations for managers will help their teams drive more deals, bigger deals, faster deals, and loyal customers. Built with decades of go-to-market experience, world-renowned data scientists, and advanced causal AI/ML technology, CoachEm™ leverages your existing tech stack to increase rep productivity, increase retention, and replicate best practices across your team.Learn more at coachem.io

In this episode of the TestGuild Automation Podcast, host Joe Colantonio chats with machine learning engineer Lakshmithejaswi Narasannagari, who boasts over fourteen years of experience working with tech giants like Intuit, Incom, and Poshmark. Check out App Automate: https://testguild.me/appautomate2 Lakshmi delves into her fascinating career journey from Oracle developer to transitioning into machine learning operations and test automation. The conversation covers best practices for ML pipelines, testing at scale, and how to integrate testing effectively in the AI ML space. Lakshmi shares insights on understanding machine learning models, navigating various roles within AI and machine learning, and setting up guardrails to ensure model performance and accuracy. Please tune in to gain valuable knowledge from Lakshmi's expertise and learn how to approach testing in our AI-driven world.

In this episode, we dive into the evolving landscape of logistics missions and the need for innovation in navigating disruption. Drawing insights shared by industry leaders at GDIT, we explore how organizations can leverage technology, data, and agile strategies in an increasingly complex environment. Tune in for expert perspectives on overcoming challenges and driving operational excellence in modern logistics missions.In Voices of Innovation—a podcast by GDIT—we bring you into conversations with the thinkers, innovators, and mission experts who are shaping some of the most complex government, defense, and intelligence projects across the country. We explore cutting-edge technologies, from artificial intelligence to quantum computing, that are crucial for leading and accelerating government missions.   Each episode features insights and stories from GDIT, government, and industry technologists. They are at the helm, leveraging groundbreaking technology to drive missions that matter most. Join us as we  dive into a world where technological innovation meets strategic execution. Subscribe now to never miss an episode.   GDIT is a global technology and professional services company that delivers technology and mission services to every major agency across the U.S. government, defense and intelligence community. Our 30,000 experts extract the power of technology to create immediate value and deliver solutions at the edge of innovation. We operate across 30 countries worldwide, offering leading capabilities in digital modernization, AI/ML, Cloud, Cyber and application development.     

March 11, 2025 | In this episode of The Chain, host Andrew Buchanan, principal scientist at AstraZeneca, and Andreas Plückthun, professor and head of biochemistry at the University of Zurich, discuss AI/ML technologies in the antibody and protein engineering space. Plückthun shares his perspectives on what technologies show promise and success, why the definition of epitope is important when developing a drug, and what aspects he expects to improve in the ML field in the future.  

How is AI changing the game for creative teams? Find out in this episode of Cloud and Clear! Simon Margolis, Associate CTO, AI/ML at SADA and Amy Clark, Director of Content and Product Ops at The Sherlock Company dive into how AI streamlines content creation, saves resources, and empowers brands to manage global content at scale. Discover the innovative software and AI solutions that are transforming creative workflows. Join us for more content by liking, sharing, and subscribing!

This article breaks down the evolving landscape of AI/ML platforms, from AutoML to full-stack AI workbenches, and provides a structured tool evaluation framework to cut through vendor ambiguity. Published at: https://www.eckerson.com/articles/the-ai-ml-tool-evaluation-template-a-guide-to-smarter-selection

Too many sales teams operate on instinct, hoping charisma and hustle will carry them to quota. However, Paul Fannon, Global CRO at Bottom Line, views sales as a science. In this Coach to Scale episode, Paul explains why a structured, data-driven approach is the key to predictable success. He shares how top reps aren't necessarily the most talented—they're the most disciplined. You'll hear why work ethic can't be taught but can be uncovered, how sales leaders should adapt their coaching style to each individual, and why frontline managers need continuous development to succeed.We also explore Paul's philosophy on “no wasted sales calls” and how technology should serve sales teams, not distract them. Learn why getting a clear yes or no is better than living in the limbo of “maybe,” how to avoid the biggest coaching mistakes, and what separates high-performing sales organizations from those that struggle. If you're a CRO or sales leader looking for practical insights on driving efficiency and effectiveness, this conversation is a must-listen.Top Takeaways:Sales is a Science, Not an Art – Success in sales isn't about charisma; it's about following a structured process, leveraging data, and executing consistently.No Wasted Sales Calls – Every call should be targeted and strategic, ensuring reps engage with the right prospects at the right time to drive meaningful outcomes.Work Ethic Can't Be Taught, But It Can Be Uncovered – Some reps have the drive but don't realize it; great leaders help bring it out through the right environment and expectations.Frontline Managers Are the Key to Sales Success – Strong sales organizations don't just develop reps; they invest in managers who can coach, hold teams accountable, and drive performance.One Process, Many Coaching Styles – While sales organizations need a standardized process, managers must adapt their coaching approach to each individual's motivations and learning style.Consistency Beats Talent – The most successful sellers aren't always the most naturally gifted; they're the ones who show up every day, follow the process, and put in the work.Data-Driven Selling Reduces Risk – Reps and managers who rely on gut instinct often struggle with inconsistency; using data ensures repeatable success and predictable pipeline growth.Decisiveness Matters More Than "Maybe" – The worst outcome isn't hearing “no,” it's being stuck in limbo; great salespeople know how to get clear answers and move deals forward.Technology Should Serve Sales, Not Distract From It – Sales tech should help reps focus on high-quality calls and pipeline movement, not overwhelm them with unnecessary complexity.Coaching Should Go Beyond Deals – Many managers only focus on pipeline and forecasting, but real sales growth comes from coaching skills, behaviors, and long-term development.Ways to Tune In:Spotify: https://open.spotify.com/show/0Yb1wPzUxyrfR0Dx35ym1A Apple Podcasts: https://podcasts.apple.com/us/podcast/coach2scale-how-modern-leaders-build-a-coaching-culture/id1699901434 Google Podcasts: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy50cmFuc2lzdG9yLmZtL2NvYWNoMnNjYWxlLWhvdy1tb2Rlcm4tbGVhZGVycy1idWlsZC1hLWNvYWNoaW5nLWN1bHR1cmU Amazon Music: https://music.amazon.com/podcasts/fd188af6-7c17-4b2e-a0b2-196ecd6fdf77 Podchaser: https://www.podchaser.com/podcasts/coach2scale-how-modern-leaders-5419703 YouTube: https://www.youtube.com/@Coach2Scale CoachEm™ is the first Coaching Execution Platform that integrates deep learning technology to proactively analyze patterns, highlight the "why" behind the data with root causes, and identify the actions that will ultimately improve business results going forward.  These practical coaching recommendations for managers will help their teams drive more deals, bigger deals, faster deals, and loyal customers. Built with decades of go-to-market experience, world-renowned data scientists, and advanced causal AI/ML technology, CoachEm™ leverages your existing tech stack to increase rep productivity, increase retention, and replicate best practices across your team.Learn more at coachem.io

In this episode, Craig Jeffery shares insights from his experience with driverless cars and connects it to the use of AI/ML in treasury. He highlights three key essentials for implementing AI/ML tools in financial decision-making. How can these new technologies boost efficiency, accuracy, and decision-making in treasury operations, and why is it crucial to understand and guide these tools? Listen in to learn more.

Sales leadership is full of hidden pitfalls that can derail even the most experienced managers. In this episode, Kevin Gaither—former ZipRecruiter sales leader, CRO of Inside Sales Expert, and author of It Happened on the Sales Floor—pulls back the curtain on the most common mistakes sales managers make. He challenges the myth that you can be friends with your reps, shares the six must-have traits for every sales hire, and explains why most coaching efforts fall flat. If you're a CRO or frontline sales leader, this conversation will change how you think about hiring, coaching, and managing your team.Kevin's straight-shooting approach delivers hard-earned lessons from building and scaling high-growth sales teams. We cover why many first-time managers fail, how to identify coachable reps, and the key to developing a sales culture that breeds success. Whether you're struggling with underperforming reps, overwhelmed managers, or a lack of accountability, this episode offers actionable strategies to avoid costly leadership missteps and build a team that consistently wins.Top Takeaways:You Can't Be Friends with Your Sales Reps – Building personal friendships with your team creates favoritism risks, weakens accountability, and can backfire when tough decisions need to be made.Hire for Six Non-Negotiable Traits – Every great sales hire must have need for achievement, competitiveness, optimism, coachability, continual learning, and organizational skills—if they're missing even one, don't hire them.Coaching Is More Than Just Deal Reviews – Most managers only coach around pipeline and forecasting, but real coaching focuses on skill development and long-term rep growth.First-Time Managers Fail Without Proper Training – Many sales leaders assume they can manage just because they were top reps, but without structured training, they struggle to develop their teams effectively.A Strong Hiring Process Is the #1 Predictor of Sales Success – The best sales strategy in the world won't work if you put the wrong people in the seats—hiring is the most critical leadership skill.Reps Don't Change Just Because You Want Them To – Without consistent coaching, accountability, and reinforcement, reps will default to old habits, no matter how much you tell them to improve.Perception Is Reality in Sales Leadership – Even if you treat your team fairly, if others perceive favoritism or inconsistency, it will erode trust and team cohesion.Managers Need a Playbook, Not Just Experience – Experienced managers still need structure and frameworks to be effective; winging it leads to inconsistent coaching and missed opportunities for rep development.Ways to Tune In:Spotify: https://open.spotify.com/show/0Yb1wPzUxyrfR0Dx35ym1A Apple Podcasts: https://podcasts.apple.com/us/podcast/coach2scale-how-modern-leaders-build-a-coaching-culture/id1699901434 Google Podcasts: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy50cmFuc2lzdG9yLmZtL2NvYWNoMnNjYWxlLWhvdy1tb2Rlcm4tbGVhZGVycy1idWlsZC1hLWNvYWNoaW5nLWN1bHR1cmU Amazon Music: https://music.amazon.com/podcasts/fd188af6-7c17-4b2e-a0b2-196ecd6fdf77 Podchaser: https://www.podchaser.com/podcasts/coach2scale-how-modern-leaders-5419703 YouTube: https://www.youtube.com/@Coach2Scale CoachEm™ is the first Coaching Execution Platform that integrates deep learning technology to proactively analyze patterns, highlight the "why" behind the data with root causes, and identify the actions that will ultimately improve business results going forward.  These practical coaching recommendations for managers will help their teams drive more deals, bigger deals, faster deals, and loyal customers. Built with decades of go-to-market experience, world-renowned data scientists, and advanced causal AI/ML technology, CoachEm™ leverages your existing tech stack to increase rep productivity, increase retention, and replicate best practices across your team.Learn more at coachem.io

In this podcast episode, MRS Bulletin's Sophia Chen interviews Bowen Deng, a graduate student in Gerbrand Ceder's group at the University of California, Berkeley, about their work on increasing the accuracy of artificial intelligence/machine learning materials prediction models. The use of computer simulations to predict the interaction between atoms in a given molecule is being replaced by machine learning. Researchers describe the atoms' collective interactions as a quantity of energy, where higher energies correspond to stronger forces holding the molecule together. Now, Deng's research group studied three machine learning models and found that they tend to predict lower energies than what is accurate by about 20 percent. The researchers have determined that these underpredictions were caused by biased training data and they found a way to remedy the situation. This work was published in a recent issue of NPJ Computational Materials.

An airhacks.fm conversation with Francesco Nigro (@forked_franz) about: Netty committer and performance engineer at Red Hat, discussion of Netty's history, focus on low-level core components like buffers and allocators in Netty, relationship between Vert.x and Netty where Vert.x provides a more opinionated and user-friendly abstraction over Netty, explanation of reactive back pressure implementation in Vert.x, performance advantages of Vert.x over Netty due to batching and reactive design, detailed explanation of IO_uring as a Linux-specific asynchronous I/O mechanism, comparison between event loop architecture and Project Loom for scalability, limitations of Loom when working with IO_uring due to design incompatibilities, discovery of a major Java type system scalability issue related to instance-of checks against interfaces, explanation of how this issue affected Hibernate performance, deep investigation using assembly-level analysis to identify the root cause, collaboration with Andrew Haley to fix the 20-year-old JDK issue, performance improvements of 2-3x after fixing the issue, discussion of CPU cache coherency problems in NUMA architectures, explanation of how container environments like kubernetes can worsen performance issues due to CPU scheduling, insights into how modern CPUs handle branch prediction and speculation, impact of branch misprediction on performance especially with memory access patterns, discussion of memory bandwidth limitations in AI/ML workloads, advantages of unified memory architectures like Apple M-series chips for AI inference Francesco Nigro on twitter: @forked_franz

Aaron Hunter, AWS principal developer advocate, joins the vBrownBag crew to discuss general tips on preparing for certifications, the AWS AI/ML certification catalog, and great tools YOU can use to help pass an AWS AI/ML certification. Chapters: 00:00 Sean, the prodigal son, returns! There is much rejoicing across the lands!

In this episode, Craig Jeffery hosts Ed Barrie and Randy DeVita from Treasury4 to discuss the importance of architecting a strong data ecosystem for the Office of the CFO and the treasurer. They explore challenges with data management, the need for accurate and detailed data, and how AI/ML can support decision-making. Key topics include structuring data solutions, maintaining a single source of truth, and using transaction mapping and anomaly detection for better forecasting and insights. Listen in to learn more. Find more information at https://www.treasury4.com/

In this episode of the DevOps Toolchain Podcast, host Joe Colantonio sits down with Richmond Alake, a developer advocate at MongoDB and an AI/ML practitioner with a strong background in computer vision, robotics, and machine learning. With years of experience in software development, Richmond has authored over 200 technical articles and taught numerous AI/ML courses. Together, they dive into the evolving landscape of AI, machine learning, and multimodal AI, discussing how MongoDB shapes the future of AI-powered applications. Richmond shares insights on how vector embeddings, Retrieval-Augmented Generation (RAG), and agentic systems transform data storage and retrieval for AI-driven development. They also explore the impact of generative AI, the rise of multimodal AI, and how MongoDB serves as the memory provider for intelligent systems. If you're a developer looking to build AI-powered applications efficiently, streamline your data management, or understand where AI is headed next, this is an episode you don't want to miss!

In this episode, we dive into how AI is transforming video editing with Gaurav Misra, the CEO of Captions. Launched in New York in 2021, Captions already empowers over 10 million creators worldwide, leveraging AI to make video production as simple as clicking a button.Discover the strategic framework that led to the inception of Captions, and learn how the founders identified societal changes and technological advancements to build a groundbreaking company. We explore the challenges and opportunities of building an AI product for video editing, including how Captions is outpacing traditional content production workflows.Gaurav shares insights into the future of video editing, the role of AI in democratizing video production, and the unique approach Captions takes to differentiate itself from industry giants like Adobe and Capcut. CaptionsWebsite - https://www.captions.aiX/Twitter - https://x.com/getcaptionsappGaurav MisraLinkedIn - https://www.linkedin.com/in/gamisra1X/Twitter - https://x.com/gmharharFIRSTMARKWebsite - https://firstmark.comX/Twitter - https://twitter.com/FirstMarkCapMatt Turck (Managing Director)LinkedIn - https://www.linkedin.com/in/turck/X/Twitter - https://twitter.com/mattturck(00:00) Intro(01:30) What is Captions?(03:43) How did Captions start?(08:25) The strategy behind launching Captions(12:32) How is Captions different from other editing tools?(14:13) How does it compare to CapCut?(18:22) Who is the typical Captions user?(20:13) Why ‘Captions'?(23:47) Captions' product suite for production and editing(26:37) AI models powering Captions(36:22) AI lipsync(38:49) Personalized fine-tuned models for creators?(39:38) Building models vs. building wrappers(43:09) Cloud AI vs. Local AI(45:19) Optimizing for low latency(48:07) AI/ML stack at Captions(51:10) “Hallucinations are a feature, not a bug”(53:19) Prompt engineering(54:12) Have we passed the uncanny valley for AI avatars?(01:01:47) The impact of deepfakes(01:04:33) CapCut ban and its effects(01:05:05) Evolving from paid to freemium(01:07:42) Building a company on foundation models(01:09:01) Running an AI company in New York

Today I'm speaking with @HarperCarrollAI  an AI and ML software engineer, on the Longevity Optimization Podcast. In this episode, we explore the fascinating intersection of artificial intelligence and health optimization. Harper shares insights into the concept of AI as the ultimate polymath, detailing her journey into the field and the transformative potential of AI in revolutionizing health diagnostics and treatments, particularly in cancer care. The conversation delves into the implications of AI in personalized medicine and how technology can shape the future of health optimization.Harper Carroll is an AI/ML engineer, advisor and educator focused on making AI concepts accessible. With almost a decade of formal experience in AI, she holds two Computer Science degrees from Stanford University specializing in AI, worked at Facebook/Meta on News Feed Ranking, Integrity Intelligence, and AR, and then was Founding Engineer and then Head of AI/ML at a startup acquired by NVIDIA. Her background combines technical expertise with teaching experience, including as a TA for advanced CS and AI courses at Stanford, including a PhD-level core AI course. Her model fine-tuning guides became the most popular fine-tuning guides on Google. In just one (1) year of teaching AI online, she has garnered 0.5M followers.Polymath book Harper references: Genesis: Artificial Intelligence, Hope, and the Human Spirit: https://www.amazon.com/Genesis-Artificial-Intelligence-Human-Spirit/dp/0316581291Follow Harper on IG: https://www.instagram.com/harpercarrollai/Follow Her on YouTube: https://www.youtube.com/@HarperCarrollAIFollow Her on X: https://x.com/HarperSCarrollVisit Her Website: https://www.harpercarrollai.comTimestamps00:00 Introduction to AI and Longevity05:08 The Polymath Concept in AI09:58 Harper's Journey into AI14:47 Understanding AI: Definitions and Applications19:56 AI in Health: Opportunities and Concerns25:00 AI's Role in Cancer Treatment and Diagnostics30:10 Future of AI in Personalized Medicine32:23 Innovative Approaches to Women's Health35:11 The Role of AI in Health Optimization36:51 Empathy and Virtual Reality Experiences41:05 AI's Impact on Creativity and Accessibility43:59 AI as a Personal Assistant in Daily Life48:54 Understanding AI Hallucinations and Their Implications53:28 The Environmental Impact of AI and Future Solutions

Can a misconfigured prompt spark a massive data breach?On this episode of Your AI Injection, host Deep Dhillon and Keith Hoodlet, Director of AI/ML and Application Security from Trail of Bits reveal the critical vulnerabilities hiding in your AI chat systems. Keith explains how RAG systems and other API endpoints, if not rigorously secured, can create unintended data portals, allowing hackers to extract everything from HR records to confidential strategic documents. The two navigate the complexities of prompt injection vulnerabilities, dynamic adversarial testing, and the balancing act between rapid innovation and robust security. As they discuss the human and technical factors that contribute to these risks, Deep and Keith challenge the industry to view security not as an afterthought, but as an integral feature of every AI-driven product. Tune in for a deep dive into safeguarding your digital future!Learn more about Keith here: https://www.linkedin.com/in/securingdev/and Trail of Bits here: https://www.trailofbits.com/Check out some of our related podcast episodes: Your Code Base Is Already Gen AI—Now What? with Matt Van Itallie of SemaWhy Generative AI Could Make Programming Languages Obsolete with Austin Vance of FocusedExploring Artificial General Intelligence: Intent, Intellect, and Innovation with Lucas Hendrich of the Forte Group

This episode is sponsored by https://WE-PN.com Become your own VPN provider.To get 50% off enter promo code: kingraam50-------------------------This episode is sponsored by BetterHelp. Give online therapy a try at https://betterhelp.com/MASTYORASTY and get on your way to being your best self.-------------------------Farshad is senior director of AI/ML at Betterhelp. In this episode he talks to Raam about his journey to the United States, the different companies he has worked at, and the development of artificial intelligence and machine learning.-------------------------To learn more about psychedelic therapy go to my brother Mehran's page at: https://www.mindbodyintegration.ca/ or to https://www.legacyjourneys.ca/ for his next retreat.***Masty o Rasty is not responsible for, or condone, the views and opinions expressed by our guests ******مستی و راستی هیچگونه مسولیتی در برابر نظرها و عقاید مهمان‌های برنامه ندارد.***--------Support the showhttps://paypal.me/raamemamiVenmo + Revolut: @KingRaam Hosted on Acast. See acast.com/privacy for more information.