The conversation around AI engineering is shifting, and Alessandro Romano is at the center of it.In this episode of Let’s Talk AI, we explore why the future of AI is no longer just about tools. It’s now about people who can think critically, solve problems, and apply frameworks with purpose.Alessandro breaks down the evolution of roles in data science, the rise of hands-on workshops for real-world learning, and the practical use of frameworks like Crew AI and LangGraph.He also explains why observability isn’t a buzzword but a necessity for responsible AI development.If you’ve ever wondered how AI engineers can deliver business value without drowning in hype, this episode offers a grounded, professional perspective.Top Insights:A professional perspective in data science requires domain specificity.Experiences at conferences can lead to valuable networking opportunities.The role of a data scientist is evolving and often overlaps with AI engineering.AI engineering is about building solutions, not just maintaining infrastructure.Workshops can be effective for hands-on learning and engagement.Choosing the right framework depends on the specific problem being solved.Observability is crucial for understanding AI systems' decision-making processes.Problem-solving should be prioritized over tool selection in AI development.Experimentation with tools is essential for effective AI engineering.A strong foundation in software engineering enhances problem-solving capabilities.Connect with Alessandro RomanoAlessandro Romano’s Website - https://www.aromano.dev/Connect with Thomas BustosThomas Bustos on LinkedIn - https://www.linkedin.com/in/thomasbustos/ Let’s Talk AI - https://thomasbustos.substack.com/ Let’s Talk AI on YouTube - https://www.youtube.com/@lets-talk-ai Let’s Talk AI on Spotify - https://open.spotify.com/show/6mVjFvdEkZDCTXpIuuSLAPHosted by Ausha. See ausha.co/privacy-policy for more information.
The world of AI engineering is exploding. Every week, there’s a new framework, a new tool, a new breakthrough. For beginners and even mid-career engineers, it can feel overwhelming. Where do you even start?In this episode of Let’s Talk AI, Miguel explains why hands-on learning beats passive theory, why systems thinking is the real skill every AI engineer needs, and why observability—understanding what’s happening inside your models and systems—is non-negotiable if you want to build responsibly.For anyone looking to break into AI engineering, this episode offers a roadmap: stop chasing every trend, start focusing on systems, and above all…Build, learn, and grow.Top Insights:Neural Maze aims to help aspiring engineers navigate the overwhelming AI landscape.Building AI systems requires thinking in terms of systems, not just code.Observability is crucial for deploying AI systems in production.Learning by building projects is the most effective way to gain skills.Filo Agents project connects philosophy with gaming, showcasing innovative applications of AI.The value of code has shifted; engineers must adapt to new technologies.Miguel encourages staying out of the hype and focusing on building meaningful projects.He plans to expand Neural Maze into a community for self-contained courses.Connect with Miguel Otero PedridoMiguel Otero Pedirdo on LinkedInMiguel Otero Pedrido on SubstackMiguel Otero Pedrido on Medium.com Miguel Otero Pedrido on GitHubMiguel Otero Pedrido on XThe Neural Maze on SubstackThe Neural Maze on YouTubeConnect with Thomas BustosThomas Bustos on LinkedInLet’s Talk AILet’s Talk AI on YouTubeLet’s Talk AI on SpotifyHosted by Ausha. See ausha.co/privacy-policy for more information.
We’re standing at the edge of an AI-driven future, and most people don’t realize how fast we’re getting there.In this episode of Let’s Talk AI, Nathan Labenz joins us to share insights from years at the forefront of AI development. We cover everything from the disruptive potential of AI-powered content creation to the deep ethical debates around autonomy, alignment, and safety.This is an urgent conversation because the decisions we make now—about adoption, guardrails, and governance—will define the next decade.Top Insights:There is radical uncertainty about AI's future.Nathan Labenz's mission is to understand AI's current state.AI is transforming content creation and marketing.Hands-on experience with AI is crucial for understanding its capabilities.AI can provide services that were previously expensive and inaccessible.The ideal user experience is for AI to automate tasks seamlessly.AI's rapid adoption is unprecedented in history.Ethical considerations around AI consciousness are complex.AI can outperform humans in specific tasks, but has weaknesses.The future of AI holds both exciting opportunities and significant risks.Connect with Nathan LabenzNathan Labenz’ Website - https://www.nathanlabenz.com/Nathan Labenz on LinkedIn - https://www.linkedin.com/in/nathanlabenzNathan Labenz on X - https://x.com/labenzThe Cognitive Revolution - https://www.cognitiverevolution.ai/Connect with Thomas BustosThomas Bustos on LinkedIn - https://www.linkedin.com/in/thomasbustos/ Let’s Talk AI - https://thomasbustos.substack.com/ Let’s Talk AI on YouTube - https://www.youtube.com/@lets-talk-ai Let’s Talk AI on Spotify - https://open.spotify.com/show/6mVjFvdEkZDCTXpIuuSLAPHosted by Ausha. See ausha.co/privacy-policy for more information.
Most people think entrepreneurship is about having a groundbreaking idea. Pedro Goes disagrees.In this episode, the CEO of InEvent reveals why ideas are overrated, and why execution, adaptability, and timing matter far more. He shares unfiltered insights into securing funding, scaling globally, and leveraging AI-driven innovation to transform the events industry.We also dive into remote leadership, the brutal realities of startup life, and the surprising role luck plays in success. If you’ve been fed the “follow your passion” narrative, this episode will challenge everything you thought you knew about entrepreneurship.Top Insights:An idea's worth is tied to its revenue potential.AI can transform event technology in innovative ways.Starting a company often requires minimal initial investment.Persistence is key in securing funding and acceptance into accelerators.Founders must maintain a clear vision for their company.Effective decision-making involves prioritizing resources wisely.Market validation is crucial for product success.Iterative growth allows for focus and adaptation in business.Building an end-to-end platform enhances value propositions.Leadership in remote teams requires fairness and clear communication.Connect with Pedro GoesPedro Goes on LinkedIn - https://www.linkedin.com/in/pedrogoes/InEvent - https://inevent.com/Pedro Goes on X - https://x.com/goesineventConnect with Thomas BustosThomas Bustos on LinkedIn - https://www.linkedin.com/in/thomasbustos/ Let’s Talk AI - https://thomasbustos.substack.com/ Let’s Talk AI on YouTube - https://www.youtube.com/@lets-talk-ai Let’s Talk AI on Spotify - https://open.spotify.com/show/6mVjFvdEkZDCTXpIuuSLAPHosted by Ausha. See ausha.co/privacy-policy for more information.
Data science freelancing is a test of both technical skill and strategic adaptability. In our conversation with Jérémy Arancio, we dissect the frameworks he uses to thrive: relentless upskilling, leveraging platforms like LinkedIn for visibility, and distinguishing between hype and practical tools in AI. From the nuanced differences of GenAI vs. NLP to the tactical mindset shift freelancing requires, this episode breaks down what separates sustainable data science careers from those that fizzle out.Top Insights:Freelancing is a means to learn and grow.You will never feel fully prepared to start freelancing.The journey of freelancing can be both rewarding and challenging.AI should be used to solve specific business problems.Content creation can help build connections and opportunities.Choosing the right vehicle for your career is crucial.Growth often comes from discomfort and challenges.Networking on platforms like LinkedIn is valuable for career advancement.Understanding the difference between Gen.AI and NLP is important.Continuous learning is essential in the fast-paced tech industry.Connect with Jeremy ArancioJeremy Arancio on LinkedIn - https://cz.linkedin.com/in/jeremy-arancioRead his articles - https://medium.com/@jeremyarancioJeremy Arancio on GitHub - https://github.com/JeremyArancioEmail him - jeremyarancio.freelance@gmail.comConnect with Thomas BustosThomas Bustos on LinkedIn - https://www.linkedin.com/in/thomasbustos/ Let’s Talk AI - https://thomasbustos.substack.com/ Let’s Talk AI on YouTube - https://www.youtube.com/@lets-talk-ai Let’s Talk AI on Spotify - https://open.spotify.com/show/6mVjFvdEkZDCTXpIuuSLAPHosted by Ausha. See ausha.co/privacy-policy for more information.
AI is evolving fast, but are our systems, ethics, and infrastructure keeping up?In this episode, Thomas Bustos and Marijn Markus break down the complex interplay between innovation and responsibility in artificial intelligence and machine learning. They examine current limitations in explainability and bias, and unpack what it will take to build scalable, transparent, and human-centric systems.With examples from healthcare and finance, and a strong focus on aligning AI with social good, this episode offers both technical depth and strategic perspective. Whether you’re designing ML pipelines or debating LLM regulation, this conversation delivers insight you won’t want to miss.Top Insights:Ethical and Data Challenges: AI systems must navigate ethical considerations and data privacy concerns, ensuring transparency and accountability.Innovation and Impact: AI has the potential to revolutionize industries, from healthcare to finance, by driving advancements and creating new opportunities.Regulatory and Legacy Issues: Balancing innovation with necessary regulations and overcoming legacy systems are key challenges for AI adoption.Bias and Misinformation: Addressing bias in AI models and combating misinformation are critical for ensuring AI's positive impact on society.Job Market Evolution: While AI may automate some jobs, it also creates new opportunities, emphasizing the need for adaptability and skill diversification.Human Responsibility: The importance of human oversight in AI systems is crucial, as technology should serve humanity's best interests.Connect with Marijn MarkusMarijn Markus on LinkedIn - https://www.linkedin.com/in/marijnmarkusCapgemini - https://www.capgemini.com/ Connect with Thomas Bustos & Let's Talk AIThomas Bustos on LinkedIn - https://www.linkedin.com/in/thomasbustos/ Substack - https://thomasbustos.substack.com/ Let’s Talk AI on YouTube - https://www.youtube.com/@lets-talk-ai Let’s Talk AI on Spotify - https://open.spotify.com/show/6mVjFvdEkZDCTXpIuuSLAPHosted by Ausha. See ausha.co/privacy-policy for more information.
What do you really need to thrive as a data engineer today?Ananth Packkildurai joins us to cut through the noise. From his experience building systems at Slack to his current role in data engineering, Ananth reveals what skills truly stand the test of time, like SQL, data modeling, and a deep understanding of user needs. We also explore how the rise of Generative AI is changing the game, what observability means in practice, and why chasing the latest trend might not be your best move. Clear, practical, and refreshingly honest. This episode is for anyone who wants to grow with intention.Top Insights:Data engineering is at a pivotal moment, similar to the industrial revolution.The demand for data engineering skills is rapidly increasing.Understanding SQL is crucial as it constitutes the majority of data workloads.Feature prioritization should focus on high yield, low effort projects.Observability is essential for building reliable data systems.Scaling challenges often arise from unexpected user demand spikes.Product thinking is important in data engineering to meet user needs.GenAI has the potential to revolutionize data engineering practices.Exploring various aspects of data engineering is beneficial before specializing.Real-world observation can enhance understanding of data engineering concepts.Connect with Ananth PackkilduraiAnanth Packkildurai on LinkedIn - https://www.linkedin.com/in/ananthduraiData Engineering Weekly by Ananth Packkildurai - https://www.dataengineeringweekly.com/ Connect with Thomas BustosThomas Bustos on LinkedIn - https://www.linkedin.com/in/thomasbustos/ Let’s Talk AI - https://thomasbustos.substack.com/ Let’s Talk AI on YouTube - https://www.youtube.com/@lets-talk-aiLet’s Talk AI on Spotify - https://open.spotify.com/show/6mVjFvdEkZDCTXpIuuSLAPHosted by Ausha. See ausha.co/privacy-policy for more information.
🎙️ Who is Reuven Lerner?Reuven Lerner is a seasoned Python and Pandas instructor with over 30 years of experience in programming and teaching. He is dedicated to helping individuals enhance their careers through the Python language. With a background that includes an MIT education in computer science and a PhD in learning sciences, Reuven combines his industry experience with innovative teaching methods to empower learners.💡 In this episode...... Reuven shares insights from his extensive career, discussing his current projects that focus on improving online courses and engaging learners through newsletters. He emphasizes the importance of project-based learning and understanding deeper concepts in technology, rather than just syntax. Reuven reflects on the challenges of traditional education and the need for innovative teaching methods. He also addresses the impact of AI on learning and the significance of hands-on experience in skill development. Listeners will find encouragement to embrace programming as a journey and learn how acquiring these skills can lead to fulfilling career opportunities.Reuven Lerner: https://www.linkedin.com/in/reuven/Thomas Bustos: https://www.linkedin.com/in/thomasbustos/Follow Let's Talk AI:🎙️ Podcast 👉 http://smartlink.ausha.co/let-s-talk-ai/📹 Youtube 👉 https://www.youtube.com/@lets-talk-ai🎞️ TikTok 👉 https://www.tiktok.com/@letstalkai/Hosted by Ausha. See ausha.co/privacy-policy for more information.
🎙️ Who is Peter Gostev?Peter Gostev is the Head of AI at Moonpig, specializing in generative AI and its transformative applications in e-commerce. With a strong background in structured problem-solving and data analytics, Peter emphasizes the importance of collaboration and rapid prototyping to drive innovation in AI projects.💡 In this episode...... we explore Peter's journey in the AI landscape, discussing the balance between delivering immediate value and fostering innovative experimentation. He shares insights on the distinctions between classical and generative AI, highlighting their respective use cases in structured and unstructured data. Peter elaborates on how generative AI can enhance data quality and operational efficiency, particularly in customer service through automation and insights extraction.The conversation also addresses the challenges of integrating AI into software development, advocating for specialized teams to effectively manage new technologies. Peter encourages continuous learning and experimentation in AI, urging listeners to engage with emerging tools and models to drive innovation in their own practices.Peter Gostev: https://www.linkedin.com/in/peter-gostev/Follow Let's Talk AI:✉️ Newsletter 👉 http://eepurl.com/ijZ8qz🎙️ Podcast 👉 http://smartlink.ausha.co/let-s-talk-ai/📹 Youtube 👉 https://www.youtube.com/@lets-talk-ai📷 Instagram 👉 https://www.instagram.com/lets_talk_ai/🎞️ TikTok 👉 https://www.tiktok.com/@letstalkai/🌐 Website 👉 https://lets-talk-ai.com/Hosted by Ausha. See ausha.co/privacy-policy for more information.
🎙️ Who is Daniel Lenton?Daniel Lenton is the CEO of Unify, on a mission tounify and simplify the LLM landscape. He has a background in machine learning deployment, as well as in robotics and computer vision. Daniel is an intellectual and creative problem solver who values consistency, balance, and expectation management when building a startup.💡 In this episode...... we discuss Daniel's background in machine learning deployment and pursuit of interests in robotics and computer vision. He shares insights on effective communication, user discovery, and gaining insights from customer sales calls for building a successful start-up. He values consistency, balance, and expectation management and credits YC for giving him productivity tips to achieve this. He believes in prioritizing joy and ethics and acknowledges advancements and limitations in AI and AGI.Daniel Lenton: https://www.linkedin.com/in/daniellenton/Thomas Bustos: https://www.linkedin.com/in/thomasbustos/Artistic Direction & Video: Maxence KerhoasFollow Let's Talk AI:✉️ Newsletter 👉 http://eepurl.com/ijZ8qz🎙️ Podcast 👉 http://smartlink.ausha.co/let-s-talk-ai/📹 Youtube 👉 https://www.youtube.com/@lets-talk-ai📷 Instagram 👉 https://www.instagram.com/lets_talk_ai/🎞️ TikTok 👉 https://www.tiktok.com/@letstalkai/🌐 Website 👉 https://lets-talk-ai.com/Hosted by Ausha. See ausha.co/privacy-policy for more information.
🎙️ Who is Demetrios Brinkmann?Demetrios Brinkmann is the Founder and CEO of the MLOps Community, and also serves as a Conference Host. He is an expert in AI implementation for technical & non-technical professionals and has extensive knowledge of workflow optimization and AI automation. He has a passion for helping people find joy in AI implementation, and believes in augmenting expertise with AI instead of replacing it. Demetrios is also skilled in optimizing productivity through human-AI collaboration and effective decision-making.💡 In this episode...... we discuss AI incorporation and workflow optimization. Demetrios shares his expertise on improving efficiency and finding joy in AI implementation for professionals. Demetrios also emphasizes the importance of augmenting expertise with AI rather than replacing it, and optimizing productivity through human-AI collaboration. He provides insightful tips for improving case studies workflow, integrating AI in workflows, and optimizing web development processes. The episode also includes discussions on voice AI use cases, AI in customer service, and streamlining podcast production. Additionally, Demetrios shares his valuable insights on data engineering, financial operations, and MLOps in AI (and more!!).Demetrios Brinkmann: https://www.linkedin.com/in/nozurbina/MLOps Community: https://mlops.community/Deepgram: https://deepgram.com/Data Engineering for AI/ML Conference (12 september 2024): https://home.mlops.community/home/events/dataengforai?agenda_day=665ee46e12463aa4df4d48b2&agenda_track=665ee46f12463aa4df4d48c4&agenda_stage=665ee46e12463aa4df4d48b8&agenda_filter_view=stage&agenda_view=listThomas Bustos: https://www.linkedin.com/in/thomasbustos/Artistic Direction & Video: Maxence KerhoasFollow Let's Talk AI:✉️ Newsletter 👉 http://eepurl.com/ijZ8qz🎙️ Podcast 👉 http://smartlink.ausha.co/let-s-talk-ai/📹 Youtube 👉 https://www.youtube.com/@lets-talk-ai📷 Instagram 👉 https://www.instagram.com/lets_talk_ai/🎞️ TikTok 👉 https://www.tiktok.com/@letstalkai/🌐 Website 👉 https://lets-talk-ai.com/Hosted by Ausha. See ausha.co/privacy-policy for more information.
🎙️ Who is Noz Urbina?Noz Urbina is a content value designer, strategist, and podcaster who specializes in helping enterprises leverage AI and omnichannel for building brands that have relationships with their customers and to foster communities digitally. He has over 14 years of experience in content strategy and customer experience consultancy, where he is a pioneer in adaptive content modelling for delivering personalized, contextually relevant content experiences in an omnichannel environment. Noz has coached teams, developed processes, and spearheaded solutions for some of the world's largest organizations such as Eli Lilly Pharmaceuticals, Barclays Bank, Microsoft, and many more. He is also the founder of Urbina Consulting and OmnichannelX.digital, where he facilitates community learning and enables cross-industry collaboration. Noz is well-known for his work on customer journey mapping, structured content, project planning and scoping, and high-tech product evangelism.💡 In this episode...... we discuss how AI is enhancing content creation and the entire content life cycle, specifically in journey mapping, persona creation, and lead scoring. Noz also shares insights on building adaptable AI frameworks, optimizing customer engagement through omnichannel design, and measuring success in patient-centered content projects.Noz Urbina: https://www.linkedin.com/in/nozurbina/Urbina Consulting: https://urbinaconsulting.com/Omnichannel X: https://www.omnichannelx.digital/Thomas Bustos: https://www.linkedin.com/in/thomasbustos/Artistic Direction & Video: Maxence KerhoasFollow Let's Talk AI:✉️ Newsletter 👉 http://eepurl.com/ijZ8qz🎙️ Podcast 👉 http://smartlink.ausha.co/let-s-talk-ai/📹 Youtube 👉 https://www.youtube.com/@lets-talk-ai📷 Instagram 👉 https://www.instagram.com/lets_talk_ai/🎞️ TikTok 👉 https://www.tiktok.com/@letstalkai/🌐 Website 👉 https://lets-talk-ai.com/Hosted by Ausha. See ausha.co/privacy-policy for more information.
🎙️ Who is Markus Stoll?Markus Stoll is an expert AI guest who is well-versed in creating advanced software solutions for the efficient exploration of unstructured data. Markus is the Co-Founder and CTO of Renumics, a company that specializes in developing open-source tools for visualization in Data-Centric AI. Not only has Markus extensive experience in solving complex problems using workflow and visualization, but he also has a strong engineering background too. From Engineer to CTO, Markus has taken his passion for AI and founded Renumics, which has evolved over the years, and today, it's successfully developing machine learning and visualization solutions.💡 In this episode...... we discuss Markus's experience in creating advanced software solutions for exploring unstructured data. Markus discusses how feedback, domain understanding, and foundational models can be used to build scalable data evaluation projects and recommendation systems. He also highlights the challenges and opportunities of building RAG systems, the importance of glossaries and future fine-tuning, and introduces Spotlight, a powerful open-source tool for comprehensive data analysis. Finally, Markus introduces an open-source audio data segmentation and labeling tool that shifts from 3D visualization to audio data labeling based on user feedback.Markus Stoll: https://www.linkedin.com/in/markus-stoll-b39a42138/Markus's Medium: https://medium.com/@markus.stollGithub spotlight: https://github.com/Renumics/spotlightRenumics: https://renumics.com/Thomas Bustos: https://www.linkedin.com/in/thomasbustos/Artistic Direction & Video: Maxence KerhoasFollow Let's Talk AI:✉️ Newsletter 👉 http://eepurl.com/ijZ8qz🎙️ Podcast 👉 http://smartlink.ausha.co/let-s-talk-ai/📹 Youtube 👉 https://www.youtube.com/@lets-talk-ai📷 Instagram 👉 https://www.instagram.com/lets_talk_ai/🎞️ TikTok 👉 https://www.tiktok.com/@letstalkai/🌐 Website 👉 https://lets-talk-ai.com/Hosted by Ausha. See ausha.co/privacy-policy for more information.
🎙️ Who is Maxime Labonne?Maxime Labonne is a Staff Machine Learning Scientist at Liquid AI. Maxime received his PhD from the Polytechnic Institute of Paris and has been working with machine learning since 2019. He has applied his expertise in various contexts, including R&D, industry, finance, and academia. He is also an AI/ML Google Developer Expert. Maxime is widely known for creating popular LLMs on Hugging Face, like AlphaMonarch-7B, Beyonder-4x7B, Phixtral, and NeuralBeagle14. He also released LLM tools, such as LLM AutoEval, LazyMergekit, LazyAxolotl, and AutoGGUF. Maxime is the author of the technical book "Hands-On Graph Neural Networks using Python," published with Packt. He has written technical articles on his blog and Towards Data Science and created the popular LLM course on GitHub, which has over 27,000 stars.💡 In this episode...... we discuss Maxime's expertise in large language models (LLMs) and graph neural networks, as well as his journey from cybersecurity to machine learning. We also talk about insights on LLMS misconceptions, evaluation optimization techniques, and creating augmented datasets for fine-tuning. Maxime also talked about graph neural networks and non-transformer architectures and provided advice for leading language model research and mentoring language model research beginners. Finally, we discuss Maxime's passion for open source and knowledge sharing.Follow Let's Talk AI:✉️ Newsletter 👉 http://eepurl.com/ijZ8qz🎙️ Podcast 👉 http://smartlink.ausha.co/let-s-talk-ai/📹 Youtube 👉 https://www.youtube.com/@lets-talk-ai📷 Instagram 👉 https://www.instagram.com/lets_talk_ai/🎞️ TikTok 👉 https://www.tiktok.com/@letstalkai/🌐 Website 👉 https://lets-talk-ai.com/Hosted by Ausha. See ausha.co/privacy-policy for more information.
🎙️ Who is Jakub Czakon?Jakub Czakon is a senior data scientist turned CMO, currently working at neptune.ai. He has a strong background in AI and LLMs in marketing and has extensive knowledge on how to apply AI in marketing for practical implementation and trust navigation. Jakub draws inspiration from chess skill levels to teach us about data science and emphasizes the importance of learning by doing. He is also an expert in strategies for effective resource allocation and trust-building in marketing and Dev Rel, and he utilizes AI and data to inform decision-making and focuses on problem solving.💡 In this episode...... we discuss the application of AI in marketing for practical implementation and trust navigation. Jakub draws inspiration from chess skill levels to teach us about data science, emphasizes the importance of learning by doing, and shares strategies for effective resource allocation and trust-building in marketing and Dev Rel. Jakub also utilizes AI and data to inform decision-making and focuses on problem-solving.Jakub Czakon: https://www.linkedin.com/in/jakub-czakon/Thomas Bustos: https://www.linkedin.com/in/thomasbustos/Artistic Direction & Video: Maxence KerhoasFollow Let's Talk AI:✉️ Newsletter 👉 http://eepurl.com/ijZ8qz🎙️ Podcast 👉 http://smartlink.ausha.co/let-s-talk-ai/📹 Youtube 👉 https://www.youtube.com/@lets-talk-ai📷 Instagram 👉 https://www.instagram.com/lets_talk_ai/🎞️ TikTok 👉 https://www.tiktok.com/@letstalkai/🌐 Website 👉 https://lets-talk-ai.com/Hosted by Ausha. See ausha.co/privacy-policy for more information.
🎙️ Who is Andrew Jardine?Andrew Jardine is the Head of GTM at Adaptive ML and an advocate for open-source ML. He is also the leader of the MLOps community in Toronto. Andrew's AI journey began as an early employee at Kira Systems, a Doc AI and NLP startup, where he developed the GTM playbook for the corporate market. He has since held commercial roles at Hugging Face, and worked in data science and MLOps industries. Andrew has a diverse background, having worked as a management consultant in London, qualified as a chartered accountant, and obtained a master's degree in engineering.💡 In this episode...... we discuss Andrew's fascination with gen AI use cases and LLMS advancements, and the challenges and benefits of implementing open-source AI. We talk about overcoming the challenges of open-source language models through an innovative LLM platform, evaluating LLMs for specific use cases, ensuring safety and toxicity, and more. Andrew also explains how open-source models can help large enterprises control costs and extract data, and discusses the choice between open or closed source models.Andrew Jardine: https://www.linkedin.com/in/andrew-iain-jardine/Thomas Bustos: https://www.linkedin.com/in/thomasbustos/Artistic Direction & Video: Maxence KerhoasFollow Let's Talk AI:✉️ Newsletter 👉 http://eepurl.com/ijZ8qz🎙️ Podcast 👉 http://smartlink.ausha.co/let-s-talk-ai/📹 Youtube 👉 https://www.youtube.com/@lets-talk-ai📷 Instagram 👉 https://www.instagram.com/lets_talk_ai/🎞️ TikTok 👉 https://www.tiktok.com/@letstalkai/🌐 Website 👉 https://lets-talk-ai.com/Hosted by Ausha. See ausha.co/privacy-policy for more information.
🎙️ Who is Alex Merced?Alex Merced is a senior technical evangelist at Dremio and co-author of "Apache Iceberg: The Definitive Guide." With a diverse career path that spans from finance to developer advocacy, he is a seasoned expert in data engineering and open standards for unifying diverse data solutions. Alex is passionate about the open-source community and the excitement around data lake house technologies, which he specializes in.💡 In this episode...... we discuss data engineering and open-source technology as well as unified platforms, data lake houses, and how they can benefit AI and marketing analytics. Alex shares how Dremio's data lake house platform can optimize query performance, reduce costs, and increase scalability. He also gives advice on getting involved in the open-source community and creating value through curiosity and detours.Alex Merced: https://www.linkedin.com/in/alexmerced/Thomas Bustos: https://www.linkedin.com/in/thomasbustos/Artistic Direction & Video: Maxence KerhoasFollow Let's Talk AI:✉️ Newsletter 👉 http://eepurl.com/ijZ8qz🎙️ Podcast 👉 http://smartlink.ausha.co/let-s-talk-ai/📹 Youtube 👉 https://www.youtube.com/@lets-talk-ai📷 Instagram 👉 https://www.instagram.com/lets_talk_ai/🎞️ TikTok 👉 https://www.tiktok.com/@letstalkai/🌐 Website 👉 https://lets-talk-ai.com/Hosted by Ausha. See ausha.co/privacy-policy for more information.
🎙️ Who is Malcolm Hawker?Malcolm Hawker is the Head of Data Strategy at Profisee | Data Management. With over 25 years of experience in data and analytics, Malcolm is a recognized thought leader and advisor in the field of Master Data Management (MDM) and Data Governance. He has helped some of the world's largest businesses to improve their enterprise information management strategies and is passionate about sharing practical and actionable insights on how to leverage data as a strategic asset. Malcolm hosts the CDO Matters podcast where he interviews senior data leaders from various industries and domains and aims to raise the awareness and value of MDM and Data Governance globally, empowering companies with the best practices and solutions to overcome their data quality challenges and achieve their business goals.💡 In this episode...... we discuss the challenges and strategies for Chief Data Officers in building valuable data-driven products, quantifying the value of data and analytics, and improving data quality. We also explores the relationship between CIOs and CDOs, challenges in implementing Master Data Management (MDM), and the importance of data governance policies. Malcom emphasizes the role of governance in driving business success and measuring the effectiveness of data-driven decisions, as well as the limitations of marketing attribution models and effective use of MDM in AI implementation.Malcolm Hawker: https://www.linkedin.com/in/malhawker/Thomas Bustos: https://www.linkedin.com/in/thomasbustos/Artistic Direction & Video: Maxence KerhoasFollow Let's Talk AI:✉️ Newsletter 👉 http://eepurl.com/ijZ8qz🎙️ Podcast 👉 http://smartlink.ausha.co/let-s-talk-ai/📹 Youtube 👉 https://www.youtube.com/@lets-talk-ai📷 Instagram 👉 https://www.instagram.com/lets_talk_ai/🎞️ TikTok 👉 https://www.tiktok.com/@letstalkai/🌐 Website 👉 https://lets-talk-ai.com/Hosted by Ausha. See ausha.co/privacy-policy for more information.
🎙️ Who is Kyle Weller?Kyle is Head of Product at Onehouse.ai and ex-Azure Databricks. With over a decade of experience in managing teams of 2-60 people, Kyle is a proven product leader who specializes in data engineering and lake house architectures. He has scaled products for global enterprises to drive modernization of their data estates. Kyle also volunteered as an Entrepreneurship Coach and mentor for incarcerated and formerly incarcerated individuals. He has contributed to the open-source community by introducing the One Table project for interoperability and empowering positive change through collaboration.💡 In this episode...... we discuss Kyle's experience in data engineering and lake house architectures. He shares his insights on building data platforms and products, overcoming challenges and optimizing performance with One House, exploring diverse lake house table formats, empowering positive change through open source collaboration, scaling strategies, team alignment challenges at Databricks, and tips for beginners and advancing in the data engineering field.Kyle Weller: https://www.linkedin.com/in/lakehouse/Onehouse: https://www.onehouse.ai/Apache XTable™ (incubating): https://xtable.apache.org/Thomas Bustos: https://www.linkedin.com/in/thomasbustos/Artistic Direction & Video: Maxence KerhoasFollow Let's Talk AI:✉️ Newsletter 👉 http://eepurl.com/ijZ8qz🎙️ Podcast 👉 http://smartlink.ausha.co/let-s-talk-ai/📹 Youtube 👉 https://www.youtube.com/@lets-talk-ai📷 Instagram 👉 https://www.instagram.com/lets_talk_ai/🎞️ TikTok 👉 https://www.tiktok.com/@letstalkai/🌐 Website 👉 https://lets-talk-ai.com/Hosted by Ausha. See ausha.co/privacy-policy for more information.
🎙️ Who is James Serra?James Serra is a Technical Specialist at Microsoft with over 35 years of expertise in data warehousing and data management, making him a thought leader in the use and application of Big Data technologies. He is also well-versed in a number of data design concepts and methodologies, including normalized, relational, dimensional, and columnar approaches. Moreover, he has been a team leader and mentor for multiple large-scale, full life-cycle database implementations, from requirements and design through development, client acceptance and production. James is also a popular blogger, author, and speaker, having presented at PASS Summit, SQLBits, Enterprise Data World conference, Big Data Conference Europe, and dozens of SQL Saturdays. His specialties include business intelligence, data warehousing, big data, Hadoop, cloud, master data management, machine learning, solution architecture, ETL, data modeling, data migration, dashboarding, Kimball methodology, massively parallel processing, database architecture, data integration, and performance tuning among others.💡 In this episode...... we discuss his journey, the evolution of storing and reporting data, the use of AI technology for better business decisions and tips for staying up-to-date in the ever-changing world of technology and AI. We also delve into Microsoft's use of AI in providing insights on political advertisements.James Serra: https://www.linkedin.com/in/jamesserra/James's Book: https://www.amazon.com/Deciphering-Data-Architectures-Warehouse-Lakehouse/dp/1098150767Thomas Bustos: https://www.linkedin.com/in/thomasbustos/Artistic Direction & Video: Maxence KerhoasFollow Let's Talk AI:✉️ Newsletter 👉 http://eepurl.com/ijZ8qz🎙️ Podcast 👉 http://smartlink.ausha.co/let-s-talk-ai/📹 Youtube 👉 https://www.youtube.com/@lets-talk-ai📷 Instagram 👉 https://www.instagram.com/lets_talk_ai/🎞️ TikTok 👉 https://www.tiktok.com/@letstalkai/🌐 Website 👉 https://lets-talk-ai.com/Hosted by Ausha. See ausha.co/privacy-policy for more information.