Podcasts about building ai products

Understand how to close the gap between AI experimentation and enterprise production. Shub Agarwal, Founder of the AI Trust Lab at USC and author of Successful AI Product Creation: A Nine-Step Framework, shares his AI product management framework for taking enterprise AI strategy from demo to production, drawing on two decades of product leadership at Amazon and Fortune 50 firms. He breaks down why experimentation must tie directly to business OKRs, the four mindset shifts leaders need to scale AI responsibly, and how the AI Trust Lab is building a benchmark evaluation framework for AI model trust and governance. Key Moments: Why 80% of AI Projects Never Reach Production (02:13): Shub traces the root cause of stalled AI programs to a missing system for moving from demo to deployment. Most teams have no repeatable path to production. Shub's Nine-Step Framework for Building AI Products (06:00): Most AI projects start with a cool model instead of a painful problem. Shub walks through the three phases of his framework: discovery, execution, and excellence. The Case Against "Fix Your Data First" (12:41): Conventional wisdom says clean your data before building AI. Shub challenges that, arguing modern LLMs offer far more flexibility with imperfect data. Four Mindset Shifts for Scaling Enterprise AI (16:35): Shub outlines the four shifts separating organizations that scale AI from those that stall, from measuring AI performance differently to embedding trust from day one. Inside Shub's AI Trust Lab at USC (23:54): Major foundation models are already being benchmarked on trust and safety. Shub explains the lab's mission to build a standardized evaluation framework for AI model governance. Why Enterprise AI Governance Needs Multiple Disciplines (28:36): AI models can be sycophantic, manipulative, or lack candor. Shub argues that building trustworthy AI demands an interdisciplinary approach. Key Quotes: “I think the fundamental problem that organizations are facing today… is not that they have a lack of experimentation in the demo aspect. The challenge is they don't know how to take those demos to production, and that is where I saw the gap.” - Shub Agarwal “I do think data is the fuel for AI… But I think today organizations are crippled by this ‘fix your data, and then we'll build AI', and they never build AI. They never build use cases that are adding value.” - Shub Agarwal “There's no FICO scores for models, so I decided to create one. I built this lab… bringing the computer scientists, the researchers, the applied AI researchers, the policy, and the communication people together to think of what is trust, define it, and ultimately measure and evaluate it.” - Shub Agarwal Mentions USC AI Trust Hub Successful AI Product Creation: A Nine-Step Framework by Shub Agarwal Four Steps to Epiphany: Successful Strategies for Products That Win by Steve Blank Masters of Scale podcast with Reid Hoffman Guest Bios  Shub Agarwal is an associate professor of professional practice at the University of Southern California, an industry executive, and an advisor to start-ups and academic institutions. He holds an MBA from the University of California, Los Angeles (UCLA), and an MS from Carnegie Mellon University (CMU). He is the author of two books: Solve Catch-22 of Product Management and Successful AI Product Creation: A 9-Step Framework. He has made significant contributions to the fields of artificial intelligence and machine learning, holding several U.S. and global patents for his work, and is also a published author of several technical research papers. With around two decades of extensive experience in product management and leadership, his journey has been marked by a relentless pursuit of leveraging AI technologies to create impactful products that redefine industry standards. His industry experience includes leadership roles at Amazon, Silicon Valley start-ups, and other Fortune 50 firms. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Send us Fan MailJoin Brandon Seigel on the Private Practice Survival Guide Podcast as he speaks with cybersecurity expert Yves Martin about the critical importance of cybersecurity for private practices. Discover how a single click can lead to devastating data breaches and ransomware attacks, and learn the essential strategies to protect your business. Yves Martin, president and founder of MQual, shares real-world insights and actionable advice on preventing, detecting, and responding to cyber threats in the healthcare industry. This episode is a must-listen for any private practice owner looking to fortify their digital defenses and ensure compliance. What You'll Learn:The prevalent dangers of phishing and social engineering in healthcare cybersecurity.The crucial difference between IT support and dedicated cyber protection.Why staff training is your most potent defense against cyberattacks.The benefits and ease of implementing multi-factor authentication across your systems.Urgent steps to take if you suspect your practice has been compromised.Don't let your practice become another statistic. Tune in to understand the cybersecurity landscape and empower your team.#Cybersecurity #PrivatePractice #DataProtection #HealthcareIT #RansomwareYves Martin has been programming since age twelve, starting with BASIC on a TRS-80. He studied Industrial Engineering at Lehigh University and holds a Professional Certificate in Artificial Intelligence from MIT, along with a certification in Designing and Building AI Products and Services. He also holds certificates in Statistics, Data Analysis, Data Science, and Analyzing and Visualizing Data. With over twenty years of experience designing and building data systems—including business intelligence platforms—he combines technical depth with practical insight. As an author, he writes about artificial intelligence and the use of technology to automate business processes.https://www.mqual.comhttps://www.facebook.com/mqualtech/Welcome to Private Practice Survival Guide Podcast hosted by Brandon Seigel! Brandon Seigel, President of Wellness Works Management Partners, is an internationally known private practice consultant with over fifteen years of executive leadership experience. Seigel's book "The Private Practice Survival Guide" takes private practice entrepreneurs on a journey to unlocking key strategies for surviving―and thriving―in today's business environment. Now Brandon Seigel goes beyond the book and brings the same great tips, tricks, and anecdotes to improve your private practice in this companion podcast. Get In Touch With MePodcast Website: https://www.privatepracticesurvivalguide.com/LinkedIn: https://www.linkedin.com/in/brandonseigel/Instagram: https://www.instagram.com/brandonseigel/https://wellnessworksmedicalbilling.com/Private Practice Survival Guide BookThis show is proudly produced at PS Studios — learn more https://www.psstudios.co

What does it take to build AI-powered products that customers actually trust? In this podcast hosted by EY Chief Platform Officer Justin Leibow, Unit21 Sr Product Leader Dhiraj Bhat will be speaking on how product leaders can design systems that leverage AI effectively. Drawing from his experience building fraud prevention products, Dhiraj explores the shift from feature-driven PM to systems thinking, and why implementation and trust will define the winners in AI.

January has a very particular energy. The holidays are behind us. The inbox is slowly filling up again. Calendars are waking up. And there's always this short window, just a few quiet days, where it feels like everything could still go in a different direction. I've been thinking a lot during this pause. Over the last couple of years, AI and large language models have gone from experiments to expectations. What used to feel optional is now part of daily work, whether someone asked for it or not. And the biggest shift I've personally noticed isn't technical. It's psychological. People aren't asking "What can AI do?" anymore. They're asking "What should we actually build?", "What do we trust?", and "What's worth shipping versus waiting?" That question shows up everywhere, especially in product teams. Because as exciting as LLMs are, shipping the wrong AI feature is worse than shipping none at all. And that's exactly why today's conversation matters. This episode is not about hype. It's about judgment, timing, and responsibility in product leadership. Chapters: 00:00 Introduction to Angshuman Rudra 01:06 The Impact of Large Language Models on Product Management 03:14 Balancing Innovation and User Needs 04:37 Navigating Generative AI in Product Development 06:46 Driving Adoption of New Features 09:34 Challenges and Lessons in Generative AI Products 11:15 Evolving Roles of Product Leaders with AI 12:39 The Future of Multi-Agent Systems 14:36 Translating User Requirements into Product Features 17:31 Finding the Next Big Feature 19:56 Adopting AI in Development Cycles 21:24 Tips for Job Seekers in Tech 23:10 Market Shifts in Marketing Technology 25:01 Exciting Use Cases in Marketing Technology 26:52 Concluding Thoughts and Future Outlook   Episode # 178 Today's Guest: Angshuman Rudra, AI Product Leader, building Martech platforms, AI Agents, and data workflows for 500+ agencies. Angshuman Rudra is a senior product executive at TapClicks, where he leads a portfolio of data, analytics, and AI products for a market-leading martech platform. Website: Angshuman Rudra What Listeners Will Learn: How to evaluate real user demand for AI features (not hype) When AI adds value and when it creates unnecessary complexity How product leaders should think about LLMs as tools, not magic Why many AI features fail after launch How to balance innovation with resource constraints What "AI adoption" actually looks like inside real companies Why multi-agent systems are promising but not ready to be fully autonomous How PMs can use AI for research, specs, and design without losing judgment What skills will matter most for product leaders over the next 3–5 years   Resources: Angshuman Rudra

By 2026, most leading newsrooms have moved past the question of whether AI belongs in their organization. Now the key question is: what does a sustainable AI product strategy look like when you're building for a subscription-based business and a high-trust brand?This week on Newsroom Robots, host, Nikita Roy sits down with Alessandro Alviani, Lead for Generative AI, and Fabian Heckenberger, Managing Editor for AI, at Germany's Süddeutsche Zeitung to discuss how they're using AI to build the next generation of news products.This conversation looks at what happens when AI becomes a permanent layer in a newsroom's product stack. Alessandro and Fabian walk through how they're designing AI experiences that fit naturally with reader behavior and how they're developing new distribution and accessibility formats that would have been impossible to sustain manually.This episode also goes deep on a topic that's becoming a defining competency which is operational trust. What do you monitor once an AI product is live? How do you categorize failures? And how do you respond quickly when something goes wrong, without panic and without eroding your brand?This episode, we cover:02:52 — How editorial and product roles complement each other in AI strategy13:13 — Addressing skepticism and fear around AI in the newsroom25:17 — Inside building the German election chatbot31:10 — The design framework that signals AI content without eroding trust35:30 — Real-time risk management and monitoring for live AI tools48:50 — The two questions every newsroom should ask before greenlighting an AI project54:55 — Closing reflections and personal AI useSign up for the Newsroom Robots newsletter for episode summaries and insights from host Nikita Roy. Hosted on Acast. See acast.com/privacy for more information.

How do you build an AI product that's powerful, reliable, and grounded in real user needs? In this podcast hosted by Qventus Product Director Mark Bailes, Google Product Lead Alankar Agnihotri discusses what it really takes to build impactful AI and LLM-driven products. He shares the hidden complexities behind model behavior, the shift from deterministic to probabilistic design, and what product managers must do to deliver AI experiences that scale. You'll hear firsthand insights from someone shaping Gemini in Android Automotive and building the future of in-car intelligence.

AI is fundamentally reshaping how digital products are conceived, built, and delivered—and the shift isn't just technical, it's cultural. Jyothi Nookula, a seasoned AI product leader with experience at companies like Netflix, Meta, Amazon AWS, and Etsy, joins Galen to unpack what makes AI-native products so different from conventional ones, why building them demands new evaluation frameworks, and how product teams can evolve their skills and mindset to keep pace.Whether you're dealing with unpredictable model outputs, shifting success metrics, or a team with uneven comfort levels around emerging tech, Jyothi offers grounded, real-world strategies for staying user-centered, experiment-driven, and confidently collaborative in the face of rapid change.Resources from this episode:Join DPM MembershipSubscribe to the newsletter to get our latest articles and podcastsConnect with Jyothi on LinkedInCheck out Next Gen Product Manager and Jyothi's website

In this episode of Open Tech Talks, host Kashif Manzoor speaks with Cristian Sibbles, founder of Autograph AI, a groundbreaking platform that transforms personal memories into digital legacies using Generative AI and Voice AI. Cristian shares how Autograph's virtual interviewer “Walter” calls users weekly to record their life stories, transforming them into searchable biographies and AI-powered avatars that preserve family wisdom for future generations. From his roots in Paraguay to studying Artificial Intelligence at Stanford and working at Google, Cristian's journey reveals how technology, storytelling, and emotion can converge to build products that outlive trends. The discussion invovlved into AI-driven memory preservation, the technical architecture of voice-based agents, and Cristian's rapid MVP-to-market strategy, which went viral across nine countries. Listeners will learn practical insights on building AI startups with emotional purpose, designing AI-first workflows, mastering iteration velocity, and leveraging Generative AI tools to solve real human problems. This episode is a must-listen for founders, engineers, and innovators exploring how AI can amplify human stories rather than replace them. Episode # 169 Today's Guest: Cristian Cibils Bernardes, Founder & CEO, Autograph Cristian Cibils Bernardes is the founder and CEO of Autograph, the company behind Walter, the world's first AI Historian. Walter functions as a journal, prompting users to document their life stories once a week. Cristian studied Symbolic Systems with a focus on Artificial Intelligence at Stanford, worked as a Software Engineer at Google, and was a Partner at Cibersons. Website: Autograph What Listeners Will Learn: Cristian's personal story of growing up in a tech-driven family, studying AI at Stanford, and transitioning from Google engineer to founder. How Autograph integrates telephony, scheduling, and generative models to facilitate lifelike conversations. Insights on MVP development speed from idea to working prototype in one week, and to live beta in under four months. The importance of iteration velocity, AI-first thinking, and design thinking in modern product building. The emerging market for AI-driven memory preservation addresses the issues of loneliness and social connection in an aging population. Key lessons for GenAI founders, identifying human-centric problems, staying ahead of AI commoditization, and building products that last beyond technological hype. Why unstructured, emotional data, not structured enterprise data, may define the next generation of AI experiences. Resources: Autograph

Welcome back to the Alt Goes Mainstream podcast.Today's episode provides a fascinating window into the world of private equity value creation and how AI can help transform both portfolio company and investment firm processes and operations to create value.We sat down in New York with Hg Partner and Head of Value Creation Chris Kindt to dive into how he spearheaded the growth of the firm's in-house value creation efforts and has built a high-performing team to meet the evolving needs of portfolio companies.Chris brings 15 years of experience in architecting and driving value creation to bear, with 11 years of experience at Hg and another 8 years as a consultant at BCG and Parthenon.Chris and his team are responsible for driving value across a portfolio of 55 companies that represents over $180B in enterprise value and would represent the second largest software company in Europe after SAP if it were a conglomerate.Chris and I had a thought-provoking discussion about value creation and the impact of AI on investing and operating companies. We discussed:How to build a high-performing value creation team.Where value creation has the biggest impact.How AI is transforming investment processes.How Hg has become an “AI-first” investment firm.Where AI will have the most impact in a company today and why agentic AI is transforming certain roles and processes within companies.How professionals can generate the most leverage from utilizing AI – without having cognitive decline.Why prompting and prompt engineering is so critical in the age of AI (and how you can use your weekends to perfect prompt engineering).How a management team can buy into AI and why the current time period represents an interesting opportunity for incumbents, particularly for those building mission-critical enterprise software.Thanks Chris for sharing your expertise and wisdom on company building and AI. We hope you enjoy.Note: this episode was filmed in August 2025.A word from AGM podcast sponsor, Ultimus Fund SolutionsThis episode of Alt Goes Mainstream is brought to you by Ultimus Fund Solutions, a leading full-service fund administrator for asset managers in private and public markets. As private markets continue to move into the mainstream, the industry requires infrastructure solutions that help funds and investors keep pace. In an increasingly sophisticated financial marketplace, investment managers must navigate a growing array of challenges: elaborate fund structures, specialized strategies, evolving compliance requirements, a growing need for sophisticated reporting, and intensifying demands for transparency.To assist with these challenging opportunities, more and more fund sponsors and asset managers are turning to Ultimus, a leading service provider that blends high tech and high touch in unique and customized fund administration and middle office solutions for a diverse and growing universe of over 450 clients and 1,800 funds, representing $500 billion assets under administration, all handled by a team of over 1,000 professionals. Ultimus offers a wide range of capabilities across registered funds, private funds and public plans, as well as outsourced middle office services. Delivering operational excellence, Ultimus helps firms manage the ever-changing regulatory environment while meeting the needs of their institutional and retail investors. Ultimus provides comprehensive operational support and fund governance services to help managers successfully launch retail alternative products.Visit www.ultimusfundsolutions.com to learn more about Ultimus' technology enhanced services and solutions or contact Ultimus Executive Vice President of Business Development Gary Harris on email at gharris@ultimusfundsolutions.com.We thank Ultimus for their support of alts going mainstream.Show Notes00:00 Message from our Sponsor, Ultimus01:18 Welcome to the Alt Goes Mainstream Podcast02:10 Guest Introduction: Chris Kindt03:58 Chris Kindt's Background and Journey05:43 Value Creation at Hg06:55 Pre-Investment and Diligence Process07:44 Management Team Dynamics08:40 Common Value Creation Interventions11:14 Building a Cross-Functional Team12:31 Scaling the Value Creation Team15:40 Measuring Value Creation Impact17:49 Investment Philosophy: Inch Wide, Mile Deep19:28 Partnerships with Management Teams20:03 Embedding AI in Value Creation20:24 Internal vs External AI Applications21:47 AI First Culture22:18 Effective AI Utilization24:04 Prompt Engineering and Whispering26:25 Choosing the Right AI Models26:50 AI Models: Strengths and Weaknesses27:42 Transformative Impact of AI28:21 Skills Needed in the AI Era28:26 AI's Role in Investment Firms28:55 Core Insights and Judgements29:04 The Core Skillset and Efficiency29:12 Philosophical Questions on AI and Talent Development30:18 Building Grit in the Age of AI31:12 Maintaining Discipline with AI32:08 AI as a Value Creation Lever32:35 Operational Efficiency and Copilots33:43 Emergence of Reasoning Models and Agentic Frameworks34:31 10x Efficiency in Engineering36:24 Challenges in Implementing AI37:16 AI Immersion Strategy Days39:52 Organizational Agility and AI42:15 AI's Impact on Investment Strategies43:26 AI in Mergers and Acquisitions45:29 The Importance of Proprietary Data47:12 AI Fatigue and Disillusionment48:07 Building AI Products and Agentic Products48:58 Hg's Internal AI Incubator49:59 The Next Wave of AI51:19 Voice and Multimodality in AI51:55 Globalization and Internationalization of AI53:35 Overestimating and Underestimating AI's Impact54:54 The Competitive Landscape of AI55:42 The Future of Value Creation with AI56:23 Conclusion and Final ThoughtsEditing and post-production work for this episode was provided by The Podcast Consultant.

In this episode of The Tech Trek, Amir speaks with Patrick Leung, CTO of Faro Health, about what it takes to lead an engineering organization through a transformation to become an AI-first company. From redefining the product roadmap to managing cultural and technical shifts, Patrick shares practical insights on team structure, skill development, and delivering AI-enabled features in a regulated domain like clinical trials. This is a must-listen for tech leaders navigating similar transitions.

This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.NetSuite is offering a one-of-a-kind flexible financing program.    Head to  https://netsuite.com/EYEONAI to know more. AWS partnered with Forrester Research to understand how software providers (ISVs), in particular, plan to drive profitable growth with generative AI, how they are uniquely approaching generative AI development, and the key challenges they're facing.   In this conversation with Jeffrey Hammond, Global ISV Product Strategist at AWS, he dives into the findings of the research and discusses how — particularly with AWS's help — ISVs can drive profitable growth and succeed in the gen AI gold rush.   Jeffrey helps software product management leaders leverage AWS cloud services to accelerate product delivery, create new revenue streams, reduce technical debt, and optimize operational costs.   You'll learn: Why “toil reduction” is the fastest path to GenAI ROI How AWS's GenAI Innovation Center helps companies cut costs and ship faster What most ISVs get wrong about trust, security, and customer communication The secret to scalable AI product pricing—and what Canva got right Why agentic workflows and federated models are the next frontier in software   Whether you're building on AWS or just exploring GenAI adoption, this conversation is packed with frameworks, examples, and strategy. Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI (00:00) The Future of Work with Generative AI   (03:20) Inside AWS: How Jeffrey Supports AI Innovation   (06:00) What the Forrester Survey Reveals About AI Adoption   (09:15) From Hype to Value: Building Real GenAI Use Cases   (13:45) How ISVs Are Reducing Toil and Driving Efficiency   (17:10) Balancing Innovation with Trust and Security   (22:00) AWS Programs That Help ISVs Win with AI   (28:00) GenAI Product Strategy: Accuracy, Cost & Pricing Models   (34:30) Overcoming Infrastructure Challenges in GenAI   (39:45) The Rise of Agentic Workflows and Interoperability   (46:00) The Biggest Tech Disruption in Decades?

Brought to you by:Gnist - Gnist is a leading boutique consulting company in Norway that helps companies reach their full digital potential. Whether you are a developer, product lead, tech lead, or business leader - Gnist can help you with the tools and practices you may need.UX Signals - Don't let your busy schedule stop you from talking to users.Automatically recruit interviews and user tests with people who are using your product. Talk to them while their user experience is still fresh in their mind. Used by big companies like DNB Bank, Vipps MobilePay, NAV, and many more.Tell them Afonso sent you, and get 50% off your trial.Know more here------------------My guest today is Morten Rand-Hendriksen, one of the clearest voices on tech ethics and AI in the world, author of multiple AI & Tech courses on Linkedin Learning - as a Principal Staff Instructor at LinkedIn.In this conversation, we unpack:* The hype and the harm behind AI agents* Why startups are building on dangerous ground* Why language models are being misused* The hidden risks of outsourcing decision-making to machines that don't understand context* The future of content creation: the ridiculous state of the current business models* And much moreWhether you're a founder, a business leader, a product mind, or just AI-curious - this one will make you pause and rethink.Enjoy!Check out Morten's courses on all things Tech & AI here: Linkedin Learning courses This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit afonsofranco.substack.com

As VP of Google Labs, Josh Woodward leads teams exploring the frontiers of AI applications. He shares insights on their rapid development process, why today's written prompts will become outdated and how AI is transforming everything from video generation to computer control. He reveals that 25% of Google's code is now written by AI and explains why coding could see major leaps forward this year. He emphasizes the importance of taste, design and human values in building AI tools that will shape how future generations work and create. Mentioned in this episode: Notebook LM: Personal research product based on Gemini 2 (previously discussed on Training Data.) Veo 2: Google DeepMind's new video generation model. Paul Graham on X replying to Aaron Levie's post that “One approach to take in building in AI is to do something that's too expensive to be reasonably practical right now, and just bet that the costs will drop by 10X or 100X over time. The cost curve is on your side.” Where Good Ideas Come From: Book on the history of innovation by Steven Johnson. Project Mariner: Google DeepMind's research prototype exploring human-agent interaction starting with browser use. Replit Agent: Josh's favorite new AI app The Lego Story: Book on the history of Lego. Hosted by: Ravi Gupta and Sonya Huang, Sequoia Capital 

In this episode, I had the pleasure of speaking with Wade Foster, the founder and CEO of Zapier. We discussed Zapier's journey with AI, from their early experiments to the company-wide AI hackathon they held in March. Wade shared insights on how they prioritize AI projects, the challenges they've faced, and the opportunities they see in the AI space. We also talked about the future of AI and how it might impact the way we work

In today's episode of the Retail Corner Podcast, we feature Stephen Kaufman, Chief Product Officer at Inriver, as he delves into the transformative impact of Generative AI in the retail sector. Kaufman discusses how this cutting-edge technology is revolutionizing product information management solutions, offering innovative ways to enhance and streamline retail operations. About our guest, Stephen Kaufman: As Chief Product Officer for Inriver, Stephen is responsible for driving product innovation, delivery, customer value, and strategic product road mapping. Prior to Inriver, he served as the Chief Product Officer at Esko where he led a global SaaS product team providing best-in-class tools for workflow, content management, digital asset management, and collaboration. Stephen has over 25 years of executive technology leadership experience in both CPO and CTO roles. Previously, Stephen was the founder, CTO, and CPO of Blue Software. He also served as CTO for Schawk Inc., where he led a team that was awarded the ComputerWorld Honor Laureate for Visionary Applications. In 2023, Stephen was also certified in the field of AI in “Designing and Building AI Products and Services” from MIT. Linkedin: https://www.linkedin.com/in/stephentkaufman/ Website: https://www.inriver.com About Retail Corner Podcast: Guest Host: Cole Koumalats Producer: Sachin Kumar Bhate Podcast Sponsor: Proxima360 Listen to other podcasts at: https://proxima360.com/retail-corner.podcast or https://retailcorner.live Subscribe our Podcast: Apple iTunes: https://apple.co/3eoeUdT Spotify: https://spoti.fi/3dvjpDJ Google Podcast: https://bit.ly/3DFHXHw Amazon Music: https://amzn.to/3tkbhk1 Interested in being on our podcast? Submit request at: retailcorner@proxima360.com  

In this episode, Logan and Nolan dive deep into building AI product's with Marily Nika, a lead product manager at Google. We explore how AI on its own is not a product. AI product managers act as a bridge between AI and user needs. The role of AI product managers is to solve the right problems for users by leveraging AI capabilities. The demand for AI product managers is increasing, with companies like Anthropic and OpenAI actively hiring for these roles. AI product managers need to be comfortable with technology and have a good understanding of AI concepts and options. They also need to collaborate with scientists and engineers to make informed decisions about technical approaches. And much more!

In the latest episode of the podcast, Lisa O'Malley — Sr. Director of Product Management at Cloud AI, Google — shares an executive's perspective on building AI products. Join us for an enlightening conversation on what it takes to thrive in AI and product management.

Rather than AI replacing journalists, Alessandro Alviani believes editorial teams can leverage AI to enhance and augment their work. Formerly as the Editorial Director at the Microsoft News Hub, Alessandro experienced firsthand the consequences that replacing human editors with automated systems caused. Drawing from his experience he says that the key is to empower journalists with AI tools rather than displace them. "It's our responsibility to help editors develop a more realistic approach to AI," he says.Now, as the Product Lead on AI at the German newsroom Ippen Digital, Alessandro has led the creation of a range of innovative AI products - from interview transcription tools to illustration generators - with transparency, responsibility, and human oversight as key principles. What I found particularly interesting was his three-pronged strategy towards an editorial-first approach to building AI products: internships with his product team, having two editors embedded within his 10-person team, and deep-dive discovery sessions across their newsrooms to understand editorial needs. This approach, which emphasizes collaboration and hands-on involvement, led to innovations such as an editorial assistant that was developed with input from human editors. With transparency and human oversight as guiding principles, Ippen's AI team built a self-evaluation system on top of their generative AI tools to automatically evaluate the quality of their output.Through their internal AI training programs, Ippen Digital strives to give every employee - not just technologists - a solid understanding of how AI models function, where they fall short, and why human judgment is irreplaceable.My biggest takeaway from Alessandro was this: by proactively shaping how AI gets built and deployed, journalists have an opportunity to set their direction. The future of news isn't human versus AI - it's human augmented by AI. And for the survival of quality journalism, getting that balance right is imperative.In the second part of our conversation out next week, Alessandro discusses how Ippen Digital is working on fine-tuning large language models for specific newsroom tasks. He also discusses his collaboration with colleagues at The Times of London as a 2022 JournalismAI fellow, where he developed a tool and methodology for journalists to track manipulated narratives, especially those from state-run media. Hosted on Acast. See acast.com/privacy for more information.

Madrona Investor Palak Goel talks with Arvind Jain, founder and CEO of Glean, which has raised about $155M since launching in 2019 and was named a 2023 IA40 winner. It should be no surprise that Glean is touted as the search engine for the enterprise because Arvind spent over a decade at Google as a distinguished engineer, where he led teams in Google Search. Palak and Arvind dive into Glean's vision to be the AI-powered personal assistants in the workplace, how AI should not be thought of as a product but rather as a building block to create a great product, the need for better AI models and tooling, and advice for founders in the AI space, including the importance of customer collaboration in product development, the need for entrepreneurs to be persistent – and so much more! Transcript: https://www.madrona.com/ia40-glean-arvind-jain-ai-in-the-enterprise/   (00:00) Introduction (01:32) The Challenges/Opportunities of Building AI Products (03:20) The Role of Glean in AI Applications (04:55) Impact of AI on Different Industries (06:17) From Prototype to Production (08:46) Importance of Persistence and Customer Centricity (10:32) Future of AI and Its Impact on Enterprises (13:07) AI is a Wave You Have to Ride (14:48) AI is Bigger than Cloud (16:35) Glean's Role in the Future of Work (17:52) Advice for Founders and Builders (20:44) The Impact of the Internet (23:07) Glean's Product Evolution (28:31) What Intelligent App Arvind's Excited About (28:50) AI Trends Arvind is Excited About

Google Group Product Manager, James Smith, is here with us to give us the low-down on what it takes to build AI products. Check out this episode if you want to learn more about all the incredible things we can learn from AI and how it can help us build better in the future.Get the FREE Product Book and check out our curated list of free Product Management resources here.Want to see how users experience your website or app? FullStory's award-winning platform gathers data on user experiences in real time, allowing product teams to better understand issues and successes in aggregate. Get started at fullstory.com.

How to Use machine learning and AI within Product Management. We discuss with Andrew Yu some very cool and interesting thoughts he has on Building AI products to Power Growth. In this interview, we cover three major parts: What is Growth PM, What is an ML/AI product, How do we use ML for product growth. The interviewee: Andrew Yu Growth Product Manager, LinkedIn The person behind the scenes, behind the My Network on LinkedIn. He is one of the key persons helping all of us building the right network, being productive and successful. The interviewer: Aggelos Mouzakitis is the founder of Growth Sandwich. He created Growth Sandwich, back in 2017 with a sole vision: to help promising early-stage teams get their products to market in a solid manner. He has worked or trained more than 500 marketers and founders on how to get to the market with the right mix of tactics and a product that drives engagement and happiness. About Growth Sandwich: Growth Sandwich is the first European Product-led Go-to-Market Strategy agency. We specialize in helping SaaS products and businesses that operate in the subscription economy. Our approach is 100% customer-centric and we help post-Product/Market fit companies establish a repeatable selling motion and recurring revenues.

Elaborates on a Framework to build AI products from ground up, what drives success of AI product from launch to adoption.

Today's guest is the great and brilliant Dr. Nick Pilkington, CTO and Founder of Drone Deploy. To date, DroneDeploy has raised 90+ million dollars for its cloud-based drone mapping and analytics platform, which enables capabilities such as automated flight safety checks, workflows, and real-time mapping and data processing. DroneDeploy is compatible with any drone, and industries adopting this technology include agriculture, real estate, mining, and construction. In this episode: Dr. Pilkington breaks down opportunities to enhance user experience and lower entry barriers for AI-driven technologies. Discover more opportunities, frameworks, and infographics for leveling up your AI capabilities with Emerj Plus: emerj.com/p1

Building AI products & teams - the art of combining human, machine and design. We discuss how the perception of AI products has shifted from core technology to holistic design, and map out changes in team structures. Human-machine interfacing is becoming a critical part of almost every digital process - find out what demands it sets for teams. Marc Dillon is a renowned technology entrepreneur and the active CTO of Basemark. Previously known for his work as the Co-founder and figurehead of Jolla, a telephone industry challenger platform, Marc has been a central part of building products and offerings utilising Machine Learning as the centre of core tech stack. Ville Hulkko is Co-Founder at Silo.AI, the largest private AI lab in the Nordics. Prior to Silo.AI he co-founded Valossa Labs, a computer vision startup. Ville lead the company to Silicon Valley, where he also founded Blackbear Startup Incubator.

In this episode, we speak to Saurabh Suri, CIO and managing partner at CerraCap Ventures, about building AI products for the enterprise. Saurabh discusses what he's seen work and not work across his portfolio of AI investments when it comes to their interface with the enterprise. We talk about the challenges that come with not only building a product but actually deploying it in the enterprise. If you want to learn more about how we discover which  you can do so at emerj.com/aiol

Ru is a graduate from the University of Cambridge, UK who has built six startups in four countries. His primary interest is to build products with social Value. He is also a mentor of Google Launchpad and a senior AI advisor of EFMA Banking group. Ru has been invited to speak at over 60 events from 21 countries. His talks are about sharing his experiences on growing various startups and building products in Artificial Intelligence and Machine Learning. Enjoy the show! We speak about: [01:45] How Ru started in the AI space [06:50] What surprised Ru about startups [10:15] Getting data first, then finding customers [15:00] Ru’s writing career [18:35] How to live a complete life [20:40] What success means to Ru [31:10] Bringing to life the machine learning models [35:00] Ru’s advisory roles [39:00] OpenAI [41:20] Overcoming challenges with data [44:00] Challenges with user adoption [50:00] What Ru is most proud of [51:40] Advice for the audience Resources: Ru’s LinkedIn: https://www.linkedin.com/in/mitrar Ru’s Website: https://www.mitrarudradeb.com Creating Value With Artificial Intelligence: Lessons Learned from 10 yrs of Building AI Products and Overcoming Data, Adoption, and Engineering Challenges Quotes: “I overcome challenges by learning from my failures.” “Two years ago I would have never thought I would be a good public speaker.” “Success cannot be defined by external factors.” “I haven’t been stressed for three years, maybe more.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show! --- Send in a voice message: https://anchor.fm/datafuturology/message

Summary: In this podcast Richard talks to Rudradeb about his new book. Creating Value With Artificial Intelligence: Lessons Learned from 10 yrs of Building AI Products and Overcoming Data, Adoption, and Engineering Challenges. It’s a good entry level introduction to the topic, and a great place to start if you know that AI is important … Continue reading Creating Value With Artificial Intelligence: an interview with Rudradeb Mitra (s5ep3) → The post Creating Value With Artificial Intelligence: an interview with Rudradeb Mitra (s5ep3) appeared first on Project Kazimierz.

This week on the podcast we’re featuring a series of conversations from the NIPs conference in Long Beach, California. I attended a bunch of talks and learned a ton, organized an impromptu roundtable on Building AI Products, and met a bunch of great people, including some former TWiML Talk guests. In this episode I speak with Yael Niv, professor of neuroscience and psychology at Princeton University. Yael joined me after her invited talk on “Learning State Representations.” In this interview Yael and I explore the relationship between neuroscience and machine learning. In particular, we discusses the importance of state representations in human learning, some of her experimental results in this area, and how a better understanding of representation learning can lead to insights into machine learning problems such as reinforcement and transfer learning. Did I mention this was a nerd alert show? I really enjoyed this interview and I know you will too. Be sure to send over any thoughts or feedback via the show notes page at twimlai.com/talk/92.

This week on the podcast we’re featuring a series of conversations from the NIPs conference in Long Beach, California. I attended a bunch of talks and learned a ton, organized an impromptu roundtable on Building AI Products, and met a bunch of great people, including some former TWiML Talk guests.This time around i'm joined by Matthew Crosby, a researcher at Imperial College London, working on the Kinds of Intelligence Project. Matthew joined me after the NIPS Symposium of the same name, an event that brought researchers from a variety of disciplines together towards three aims: a broader perspective of the possible types of intelligence beyond human intelligence, better measurements of intelligence, and a more purposeful analysis of where progress should be made in AI to best benefit society. Matthew’s research explores intelligence from a philosophical perspective, exploring ideas like predictive processing and controlled hallucination, and how these theories of intelligence impact the way we approach creating artificial intelligence. This was a very interesting conversation, i'm sure you’ll enjoy.

This week on the podcast we’re featuring a series of conversations from the NIPs conference in Long Beach, California. I attended a bunch of talks and learned a ton, organized an impromptu roundtable on Building AI Products, and met a bunch of great people, including some former TWiML Talk guests. This time around I'm joined by Joan Bruna, Assistant Professor at the Courant Institute of Mathematical Sciences and the Center for Data Science at NYU, and Michael Bronstein, associate professor at Università della Svizzera italiana (Switzerland) and Tel Aviv University. Joan and Michael join me after their tutorial on Geometric Deep Learning on Graphs and Manifolds. In our conversation we dig pretty deeply into the ideas behind geometric deep learning and how we can use it in applications like 3D vision, sensor networks, drug design, biomedicine, and recommendation systems. This is definitely a Nerd Alert show, and one that will get your multi-dimensional neurons firing. Enjoy!

This week on the podcast we’re featuring a series of conversations from the NIPs conference in Long Beach, California. I attended a bunch of talks and learned a ton, organized an impromptu roundtable on Building AI Products, and met a bunch of great people, including some former TWiML Talk guests. In this episode i'm joined by Sara Jennings, Timothy Seabrook and Andres Rodriguez to discuss NASA’s Frontier Development Lab or FDL. The FDL is an intense 8-week applied AI research accelerator, focused on tackling knowledge gaps useful to the space program. In our discussion, Sara, producer at the FDL, provides some insight into its goals and structure. Timothy, a researcher at FDL, describes his involvement with the program, including some of the projects he worked on while on-site. He also provides a look into some of this year’s FDL projects, including Planetary Defense, Solar Storm Prediction, and Lunar Water Location. Last but not least, Andres, Sr. Principal Engineer at Intel's AIPG, joins us to detail Intel’s support of the FDL, and how the various elements of the Intel AI stack supported the FDL research. This is a jam packed conversation, so be sure to check the show notes page at twimlai.com/talk/89 for all the links and tidbits from this episode.

This week on the podcast we’re featuring a series of conversations from the NIPs conference in Long Beach, California. I attended a bunch of talks and learned a ton, organized an impromptu roundtable on Building AI Products, and met a bunch of great people, including some former TWiML Talk guests. In this episode I sit down with Timnit Gebru, postdoctoral researcher at Microsoft Research in the Fairness, Accountability, Transparency and Ethics in AI, or FATE, group. Timnit is also one of the organizers behind the Black in AI group, which held a very interesting symposium and poster session at NIPS. I’ll link to the group’s page in the show notes. I’ve been following Timnit’s work for a while now and was really excited to get a chance to sit down with her and pick her brain. We packed a ton into this conversation, especially keying in on her recently released paper “Using Deep Learning and Google Street View to Estimate the Demographic Makeup of the US”. Timnit describes the pipeline she developed for this research, and some of the challenges she faced building and end-to-end model based on google street view images, census data and commercial car vendor data. We also discuss the role of social awareness in her work, including an explanation of how domain adaptation and fairness are related and her view of the major research directions in the domain of fairness. The notes for this show can be found at twimlai.com/talk/88 For series information, visit twimlai.com/nips2017

My guest this time is Hilary Mason. Hilary was one of the first “famous” data scientists. I remember hearing her speak back in 2011 at the Strange Loop conference in St. Louis. At the time she was Chief Scientist for bit.ly. Nowadays she’s running Fast Forward Labs, which helps organizations accelerate their data science and machine intelligence capabilities through a variety of research and consulting offerings. Hilary presented at the O'Reilly AI conference on “practical AI product development” and she shares a lot of wisdom on that topic in our discussion. The show notes can be found at twimlai.com/talk/11.