Shattering the Myths of GenAI: Interview with Forrester Analyst Rowan Curran

Data Science Leaders

#Science #MBA #Math #Business #Domino Data Lab

51:57

On the Season 2 debut of Lost Cultures: Living Legacies , we travel to Bermuda, an Atlantic island whose history spans centuries and continents. Once uninhabited, Bermuda became a vital stop in transatlantic trade, a maritime stronghold, and a cultural crossroads shaped by African, European, Caribbean, and Native American influences. Guests Dr. Kristy Warren and Dr. Edward Harris trace its transformation from an uninhabited island to a strategic outpost shaped by shipwrecks, colonization, the transatlantic slave trade, and the rise and fall of empires. Plus, former Director of Tourism Gary Phillips shares the story of the Gombey tradition, a vibrant performance art rooted in resistance, migration, and cultural fusion. Together, they reveal how Bermuda’s layered past continues to shape its people, culture, and identity today. You can also find us online at ⁠travelandleisure.com/lostcultures Learn more about your ad choices. Visit podcastchoices.com/adchoices…

about a year ago 41:41

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The biggest challenges to driving impact with AI have little to do with AI and everything to do with humans. Nowhere is this greater than with GenAI where myths and misconceptions abound as to how organizations should be designing, developing and operationalizing GenAI-based applications. In this episode with Rowan Curran, industry analyst at Forrester Research, we debunk the most harmful myths and discuss how AI teams are shattering these myths and delivering transformative outcomes.
Join us as we discuss:

The role of data scientists and ML engineers in GenAI projects
Successful approaches to prompt engineering
The linkages between MLOps and LLMOps

96 episodes

Shattering the Myths of GenAI: Interview with Forrester Analyst Rowan Curran

Data Science Leaders

18 subscribers

published about a year ago

MP3•Episode home

The role of data scientists and ML engineers in GenAI projects
Successful approaches to prompt engineering
The linkages between MLOps and LLMOps

96 episodes

#Science #MBA #Math #Business #Domino Data Lab

All episodes

Data Science Leaders

1
The Rise of the Self-Driving Organization 34:54

6 weeks ago34:54

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As organizations race to become AI-driven, data has emerged not just as a resource, but as a strategic advantage. In this episode, Kjell Carlsson sits down with Doug Laney , author of Infonomics and Data Juice , to explore how generative AI is accelerating the journey toward data monetization and organizational autonomy. Doug shares why traditional approaches to data management no longer suffice, how digital twins and agentic AI are redefining business models, and why the future may belong to self-driving organizations. Tune in to hear: How AI is reshaping the economics of data and enabling new business models Why organizations should embrace agentic AI and digital twins to stay competitive What leaders must do today to build autonomous, AI-native enterprises…

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The Cultural Shifts That Power AI Adoption 46:52

8 weeks ago46:52

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AI strategy isn't just about technology. It's about transformation. In this episode, CDAO expert, Dr. Shahram Ebadollahi , joins to discuss what it takes to lead AI in an enterprise and why that leadership must go far beyond just selecting the right tools or models. Drawing on his experience building AI teams, Shahram explains why the Chief AI Officer role is one of the most complex, and most critical, positions in modern organizations. Here we talk about the cultural, organizational, and strategic shifts needed to embed AI deeply and responsibly, and how to move from experimentation to value delivery at scale. Whether you're leading AI or supporting it, this conversation offers a clear-eyed view of what success really requires. Tune in to hear: Why the Chief AI Officer must balance tech depth with business vision How to structure teams and incentives for lasting AI success How to move from AI experimentation to real business impact…

Data Science Leaders

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The AI Race: Predictions for AI in National Security & the Public Sector 45:30

10 weeks ago45:30

45:30

What does the global race for AI look like? How has the US Department of Defense been adopting AI by engaging the private sector? And how should we expect AI policy to shift under the new administration? In this episode – the last in our series on the future of AI – guest host Joel Meyer , President of Public Sector at Domino, sits down with General Jack Shanahan (Ret.) former Director of the Joint Artificial Intelligence Center at the U.S. Department of Defense, and Lauren Bedula , Managing Director at Beacon Global Strategies. Join us as we explore: How the U.S. Department of Defense is accelerating AI adoption The global AI race: U.S., China, and allies AI policy shifts under the new U.S. administration Predictions for AI in the Public Sector for 2025 and beyond Also, hear more of Lauren’s thoughts on national security and tech innovation on the Building the Base podcast.…

Data Science Leaders

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The Future of Enterprise AI? AI in Production! 41:29

12 weeks ago41:29

41:29

What does the near term future of Enterprise AI look like? A scramble to get valuable, cost-effective, enterprise-grade AI solutions into production, with rigorous governance at scale. If that sounds like a tall order - that’s because it is! However, large advanced organizations (yes, even outside of the tech sector) are already seeing success deploying AI solutions and we can expect the pace to accelerate rapidly in the next 1-2 years. To find out how enterprises are gearing up for this challenge we speak with Richard Swakla , AI and ML Specialist at NetApp and get the inside scoop on the trends that are underway and the strategies organizations are putting in place to operationalize meaningful AI outcomes. Join us as we discuss: The pressure to shift from experimentation to production Breaking down the data, infrastructure and organizational silos Best practices for tackling governance, security and cost challenges Examples of AI efficiency gains in healthcare, pharma, and beyond…

Data Science Leaders

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The Silent Future of AI in Financial Services 29:47

14 weeks ago29:47

29:47

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Data Science Leaders

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Pharma Is the New Tech: The Future of AI in Life Sciences 31:42

16 weeks ago31:42

31:42

AI is transforming drug discovery and clinical trials, making what was once cutting-edge the new standard. Pharma companies are evolving into tech companies, leveraging AI to revolutionize every phase of drug development. In this episode, Chris McSpiritt, VP of Life Sciences Strategy at Domino, discusses how AI is no longer a niche capability for select firms but an essential capability for all biopharma organizations. We explore AI-based digital organisms, the increasing reliance on AI in clinical trials, and the shift toward personalized medicine. Join us as we dive into: How AI will drive the majority of new drug discoveries The role of AI in clinical trials The growing need for pharma companies to adopt a tech company mindset The impact of AI-driven automation on regulatory compliance and reporting…

Data Science Leaders

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AI Predictions for 2025: The Boogeyman, Agentic AI & Governance 11:43

18 weeks ago11:43

11:43

What’s next for artificial intelligence in 2025? In this episode, Dr. Kjell Carlsson delivers his annual predictions about the immediate future of AI. From AI becoming the universal corporate scapegoat to the rebranding of generative AI as "agentic AI.” Discover why commercial AI solutions remain scarce, the pivotal role of workforce upskilling in achieving transformative AI outcomes, and how governance is shifting from regulation-focused to impact-driven. Want to see how Kjell fared in his 2024 predictions? Look no further than Data Science Leaders podcast Episode 62: AI in 2024: Predictions on the Future of the AI Revolution .…

Data Science Leaders

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Realizing AI Value Through Governance in Insurance 30:13

20 weeks ago30:13

30:13

Innovation and AI governance aren’t at odds. Done properly, governance practices can be the key to accelerating implementation of even the latest GenAI use cases. In this interview from RevX London with Raj Mukherjee , Head of Data Science and AI at Direct Line Group , we find out how they embraced the principles of a lean startup, adopted a product mindset and became the first major insurance company to implement a GenAI solution to accelerate customer service. Come find out how they were able to overcome the challenges of legacy infrastructure, build trust and do the seemingly impossible — make compliance fun.…

Data Science Leaders

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Mastering AI Governance with Forrester & the Federal Reserve 49:17

22 weeks ago49:17

49:17

How can organizations drive transformative AI innovation while effectively managing its inherent risks? Is governance a bottleneck or can it become a catalyst for AI success? In this webinar, we explore the critical role of AI governance with Brandon Purcell , VP Principal Analyst at Forrester Research, and Theo Linnemann , Data Scientist at the Federal Reserve Bank of New York. Together, they share actionable insights into the principles, practices, and policies necessary for ensuring the safe use of AI that drives real-world impact. Join us as we discuss: The evolution of AI governance and why it has become a top priority for AI teams Frameworks and practices for identifying and managing AI risk The growing importance of automation for effective governance Fairness, business, and other metrics for AI governance How to govern an Agentic AI future…

Data Science Leaders

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Crossover: Ethical Machines and AI Governance 46:07

24 weeks ago46:07

46:07

This episode is a collaboration with the Ethical Machines podcast featuring Reid Blackman — CEO of the AI ethical risk consultancy Virtue — and Nick Elprin , cofounder and CEO of Domino Data Lab. Join us as they discuss: The differences between AI ethics and AI governance How the AI governance challenges have changed (and where they haven’t) The people, process and technology solutions for genAI governance (and how they are all intertwined) Predictions about AI maturity, slip ups and regulation…

Data Science Leaders

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AI Transformation in Government: Lessons from Unit X 36:13

26 weeks ago36:13

36:13

Think you have a hard time driving AI adoption in your organization? Try driving AI transformation in the largest, most regulated organization on the planet – the Pentagon. In this episode, we sit down with Dr. Chris Kirchhoff – co-author of Unit X: How the Pentagon and Silicon Valley are Transforming the Future of War and former Director of Strategic Planning for the National Security Council – to uncover how the Department of Defense is accelerating the adoption of AI. Dr. Kirchhoff shares invaluable lessons on managing disruption and fostering innovation at scale. Join us as we discuss: How leadership and experimentation drove the success of the Defense Innovation Unit The importance of developing new frameworks for procurement for AI adoption Insights from modern warfare: drone technology and the shift to consumer-driven innovation Best practices for scaling technological transformation across any large organization…

Data Science Leaders

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The EU AI Act: Key Strategies for Regulatory Compliance 46:00

28 weeks ago46:00

46:00

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Data Science Leaders

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AI Governance in Action: Lessons from the Trenches 38:46

31 weeks ago38:46

38:46

AI governance is no longer a hypothetical consideration—it's critical not only to meet regulatory requirements but also to build trust, drive adoption, and deliver tangible impact with AI. In this episode, we bring together experts Jared Vaudrey and Dr. Dylan Bobby Storey , who have spent years developing AI solutions in heavily regulated industries. They share their hard-won insights on the realities of implementing AI governance across a wide range of organizations and use cases. Join us as we discuss: The value of AI governance for driving adoption and innovation How governance principles apply to traditional ML and genAI The common challenges of governance Real-world examples and best practices from advanced teams integrating AI governance How automation helps scale governance and provide the flexibility to support future regulation…

Data Science Leaders

1
Demystifying the Top 5 Questions of AI Governance 20:48

34 weeks ago20:48

20:48

AI governance is more important than ever, but confusion reigns about basic questions such as: what it is, why it is important and what we should do about it. As an AI, data science, or business leader, you need to dispel these governance misconceptions in order to manage AI risk and ensure the safety and reliability necessary to drive adoption and impact. The ability of your organization to drive impact with AI, and potentially your career, depends on it. Join us as host Kjell Carlsson, gives an opinionated take on the basic questions of AI governance: Why you should care about AI governance (and why it goes beyond ethics and regulation) What AI governance is (and how it differs from ethical AI, responsible AI, and trustworthy AI) Why AI governance is difficult (and the gap between frameworks and practices) What AI governance looks like in practice (across the AI/ML lifecycle) What we need for AI governance (and the capabilities to do it at scale)…

Data Science Leaders

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Operationalizing privacy in the age of AI 42:17

36 weeks ago42:17

42:17

Data privacy - why is it so important in the age of AI, why is it so difficult, and what should we be doing to improve it in our organizations? In this episode we speak with Dr. Rebecca Balebako , privacy engineer and Chief Privacy Officer at Lotic.ai, about why AI makes privacy more important than ever, the common misconceptions around data protection, who should own privacy, and the benefits and limitations of privacy enhancing technologies (PETs). Join us as we discuss: The value of privacy (~5% of annual profit) The many definitions of privacy. The top 3 misconceptions: no one cares, it can be fixed with a privacy policy, and privacy is a blocker. Who should own privacy in your organization. PETs vs. data hygiene For more on Rebecca’s consulting on privacy strategy, coaching and how to build a privacy advocate team see https://www.privacyengineer.ch/ and for more on privacy methods check out the book “ Practical Data Privacy ” by Katharine Jarmul.…

Data Science Leaders

1
Optimizing Your Architecture for AI Innovation: BARC Survey Results 46:31

38 weeks ago46:31

46:31

What capabilities do you need to take advantage of AI and what changes will you need to make to your IT architecture? Well, let’s look at the data. In this episode, Shawn Rogers , CEO and Fellow at BARC US , shares the results of their survey on how enterprises are optimizing their architecture for AI innovation. Shawn unpacks data on everything from the biggest obstacles to delivering AI impact to how companies are sourcing their AI capabilities. Join us as we discuss: The AI talent gap and the strategies that firms are using to close it The myriad AI capabilities that high-readiness firms are implementing The need to manage AI costs upfront to ensure deployment The perpetual question of build vs. buy (or both!) The crucial need for AI governance to ensure approval and adoption Download the full report here .…

Data Science Leaders

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Driving Digital Strategy with AI at OneAmerica 45:26

40 weeks ago45:26

45:26

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Data Science Leaders

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AI-driven Marketing, Optimization, Consciousness and CAIOs 47:11

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AI is disrupting marketing, but the biggest threat isn’t AI systems misbehaving, it is the unintended consequences of AI systems performing exactly what they were intended to do. In this interview with Dr. Daniel Hulme , Chief AI Officer at WPP and CEO of Satalia , we discuss the ways that AI is transforming marketing – from accelerating content creation and maximizing activation to exploring the creative landscape and creating “brains” that ensure it is responsible and legal. Also, tune in for fascinating discussions of AI consciousness and what it means to be a Chief AI Officer. Join us as we discuss: The greatest GenAI opportunities in marketing and beyond How to maximize AI impact with decision optimization Responsible AI and the challenges of AI systems going very right The emerging field of AI consciousness The Chief AI Officer: why you need one and the prerequisites for success For more information about the new research organization focused on AI consciousness co-founded by Daniel Hulme see conscium.com and his interview on the London Futurists Podcast .…

Data Science Leaders

1
Trust and faster AI time to value in manufacturing at IFF 42:07

44 weeks ago42:07

42:07

How do you deliver impact with AI and ML and cut development time by weeks and even months? By understanding your customer, building trust, and managing risk. Done well, effective and responsible AI practices can be the secret to faster implementation, adoption, and performance at lower cost and risk. In this episode with Dr. Alex Manasson , Data Science Leader for the Americas at International Flavors and Fragrances (IFF) , we uncover their best practices for managing risk and driving rapid AI development and adoption in the safety-focused world of manufacturing.. Dr. Manassof shares insights on balancing statistical process control with predictive modeling, the importance of adapting your data collection processes, and the pros and cons of digital twins. Discover practical tips and strategies for implementing AI and ML tools to boost efficiency and foster trust in high-stakes environments.…

Data Science Leaders

1
How to Make Responsible AI Happen: A Historical View 28:24

47 weeks ago28:24

28:24

How do you deliver value with responsible AI, who is responsible for it, how do you put it into practice, and could we use AI to make our organizations more ethical? This episode comes to you from the RevX conference in London, where we asked these questions of Chris Wiggins , Chief Data Scientist at the New York Times . He is also Professor of Applied Mathematics at Columbia University and author of the books “ How Data Happened: A History from the Age of Reason to the Age of Algorithms ” and “ Data Science in Context ”. Join us as we discuss: What we can learn from the history of research ethics and data legislation The need for clear principles and defined ownership to ensure ethical AI The translation of ethical principles into checklists, standards, and product decisions The importance of benchmarking AI against human performance and addressing how human biases in data lead to biased AI outcomes To see all of the sessions at the RevX conferences go to domino.ai/revx .…

Data Science Leaders

1
Efficient Data Pipelines for AI and a Healthier World 32:58

49 weeks ago32:58

32:58

AI is not all about the data, however, your ability to develop and deploy efficient data pipelines is absolutely critical for unlocking the power of AI at scale. But how do you manage modern data pipelines for AI and how do you deal with fragmented ecosystems and spiraling costs? In this episode, brought to you from the RevX Philadelphia conference, Richard Swakla , AI/ML Specialist at NetApp , joins us to discuss the current trends and best practices in the life sciences around data and AI. Join us as we discuss: The role of AI in enhancing productivity in healthcare and the life sciences, particularly in drug discovery, claims processing and fraud detection. The growing importance of hybrid cloud solutions to balance cost, efficiency, and infrastructure access. Challenges in transitioning AI projects from pilots to production due to high costs and rapidly evolving models. To see all of the sessions at the RevX conferences go to domino.ai/revx .…

Data Science Leaders

1
Enabling AI on Enormous Financial Datasets at FINRA 27:18

1 year ago27:18

27:18

How do you enable AI, data science and analytics on petabyte-scale data, with extremely stringent privacy and security requirements? This episode comes to you from the RevX-New York conference where we had a fireside chat with Ivan Black - Director in charge of ML, AI, and analytics platforms at the US financial services regulator FINRA . Join us as we discuss: The challenges of enabling AI on massive, rapidly growing financial datasets Talent strategies to support the rapidly changing AI ecosystem The importance of AI governance and reproducibility Managing cloud costs To see all of the sessions at the RevX conferences or to find information about attending upcoming ones go to domino.ai/revx .…

Data Science Leaders

1
Developing a Strategy for AI Transformation at Zendesk 37:42

1 year ago37:42

37:42

How do you craft and implement a strategy to transform an organization with AI? Not just to build a growing portfolio of successful AI projects, but to fundamentally re-engineer the organization’s core processes, to radically increase productivity, to overhaul the company’s tech stack, and to prepare it for a future of AI-driven competition. In this episode, Akshaya Murthy , who leads the AI efforts for Operations at Zendesk joins us to discuss the mandate and toolkit of the AI transformation leader, the importance of strategy for AI impact, the AI transformation efforts at Zendesk, and their successes to date. Join us as we discuss: The AI transformation leader: mandate and skillset Strategy: the misunderstood and frequently forgotten key to AI impact GenAI: the transformation leader’s new best tool for rapid impact Process transformation: the goal of AI transformation…

Data Science Leaders

1
Surviving and Thriving as an AI Leader in a GenAI World 43:41

1 year ago43:41

43:41

AI leaders. Why do we need them? How do you become one? And above all, how do you keep your job as one? In this episode, we are joined by guest speaker Mike Gualtieri , VP and Principal Analyst at Forrester, and we unpack the opportunities, pitfalls, and best practices of the AI leader role. He shares the pivotal role of AI leaders in catalyzing organizational transformation, their unique skill set that must encompass data science, business acumen, and software engineering, their importance in navigating the evolving regulatory landscape surrounding AI, and the need for platforms to facilitate rigorous auditing and compliance measures to foster trust and transparency. Join us as we discuss: The strategic imperative for AI leaders to curate a diversified portfolio of AI initiatives The multifaceted nature of AI risk management, spanning legal, ethical, and societal dimensions The formidable challenges inherent in navigating and enforcing AI-centric regulations amidst rapid technological advancement…

Data Science Leaders

1
Unlocking the Disruptive Potential of Generative AI: A VC Perspective 28:49

1 year ago28:49

28:49

GenAI is evolving at a breakneck pace, matched only by the startups that are looking to commercialize it. So what better way to understand the latest GenAI trends than to ask a venture capitalist specializing in AI? In this episode, we speak with James Cham , partner at Bloomberg Beta , about the state of GenAI – where it is delivering value today – and the challenges preventing firms from moving from incremental GenAI-driven productivity gains, to truly disruptive GenAI use cases. Along the way, we cover the problem of treating GenAI like software development, the rapidly changing economics of GenAI, and the key to success with all types of AI which is – as always – understanding people. Join us as we discuss: The cultural challenges preventing companies from unlocking the disruptive potential of GenAI Why developers don’t get data-powered applications (and why data scientists need product thinking) How GenAI can change our engagement with technology (by killing the GUI)…

Data Science Leaders

1
Overcoming the Data Challenges of AI-driven Drug Discovery 36:49

1 year ago36:49

36:49

A human being consists of billions of cells, each with the same genetic code but interacting in a myriad ways that can eventually translate into disease. Understanding and treating that disease is, in essence, a data problem. But how do you unlock that data and how do you change an organization to systematically use that data to improve decision-making and accelerate drug discovery? In this episode, we speak with Volodimir Olexiouk , Director of Scientific Engagement and Data Science Team Lead at BioLizard , about best practices for overcoming the data challenges for AI-driven drug discovery and combining scientific expertise with data science for augmented intelligence in the life sciences. Join us as we discuss: The challenges in discerning correlation from causation and integrating domain expertise How bridging expertise gaps and merging data silos in pharmaceutical companies radically improves drug-discovery processes The promise AI holds for swifter and more effective responses to future pandemics…

Data Science Leaders

1
AI Will Plan Your Next Vacation: GenAI at Tripadvisor 30:12

1 year ago30:12

30:12

Trip planning may well be the perfect AI use case. Too much information, too many combinations, and too little time —for humans, but not for Tripadvisor’s AI Trips. In this episode Rahul Todkar , VP Head of Data and AI, shares the secrets to building a trusted GenAI solution at internet scale and discusses the similarities and differences between data leadership roles at digitally native companies and more traditional enterprises. Join us as we discuss: How to use GenAI to unlock first party data The ideal GenAI development team The evolving role of data and AI leaders…

Data Science Leaders

1
From the Archive: A Hybrid Approach to Accelerating the Model Lifecycle 23:35

1 year ago23:35

23:35

Wouldn’t it be great if there was a commonly agreed-upon framework for executing all AI projects successfully? Well, there isn’t one. However, there is CRISP-DM, the antediluvian “Cross-Industry Standard Process for Data Mining”, but you need to expand, modernize and adapt this framework for success at your organization. In this episode from the archive, Dave Cole interviews David Von Dollen , former Head of AI at Volkswagen of America, about how they integrated CRISP-DM into an Agile process to drive more rapid iteration and, ultimately, more successful AI projects.…

Data Science Leaders

1
Unlocking AI in the Public Sector 30:59

1 year ago30:59

30:59

What’s just as important as the government keeping us safe from AI? Government leveraging AI to keep us safe! In this episode, we interview Joel Meyer – former head of strategy at the Department of Homeland Security (DHS) and the person who drove the creation of the DHS AI Task Force. Joel shares how they identified key areas where they could apply AI to improve national safety and security, such as combating fentanyl and child sexual exploitation and abuse, and the steps that the federal government is taking to build AI capabilities across the public sector. Join us as we discuss: Key areas where US government agencies are looking to leverage AI to improve mission effectiveness The people, process, and technology steps that government agencies are implementing to scale AI and how they apply to the private sector The importance and value of Responsible AI in public sector use cases and beyond…

Data Science Leaders

1
Disrupting Drug Discovery and Development With AI 38:12

1 year ago38:12