Let's Talk AI

Let's Talk AI

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Let’s Talk AI is the podcast that makes you dive deeper into Artificial Intelligence. We talk with experts about topics, challenges, technologies related to AI with no fear to get into technical details. The goal is to learn from guests that are passionate about AI shares about real world cases, to take your business, career and projects to the next level! Hosted by Ausha. See ausha.co/privacy-policy for more information.

2 NGÀY TRƯỚC

#88 - Snipd and the Future of Podcasting: AI Meets Audio Content | Kevin Smith

Everyone says podcasting is already saturated, but Kevin Smith would disagree. While most platforms focus on distribution, he’s betting on AI as the core experience. As co-founder of Snipd, Kevin argues that the future of podcasting isn’t about more shows, but about smarter listening: capturing key ideas, surfacing highlights, and creating shareable knowledge from endless hours of audio. In this conversation, Thomas Bustos pushes on the big questions: is AI enhancing the podcast experience, or is it reshaping it entirely? What happens when AI curates your takeaways better than you can? For anyone who thinks AI is just a background tool, this episode is a wake-up call. The podcast player itself is becoming intelligent. Top Insights: Decide what to focus on and forget everything else. Podcasts are the largest knowledge library in the world. You have to be relentlessly resourceful as a founder. Talk to people to understand their problems before building. Give it to five people, and you'll see the problems immediately. Snipd is a fully fledged podcast player with unique features. Put small building blocks on top of each other for success. The world needs more entrepreneurial energy and spirit. AI is changing how we interact with audio content. Exclusive Listener Offer! One month free premium access on Snipd - https://link.snipd.com/Cx7S/thomas Connect with Kevin Smith Kevin Smith on LinkedIn - https://ch.linkedin.com/in/kevin-smith-673714b4 Snipd - https://www.snipd.com/ Hosted by Ausha. See ausha.co/privacy-policy for more information.

48 phút
24 THG 9

#87 - Why AI Engineers Must Think Like Problem-Solvers | Alessandro Romano

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 Romano Alessandro Romano’s Website - https://www.aromano.dev/ Connect with Thomas Bustos Thomas 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/6mVjFvdEkZDCTXpIuuSLAP Hosted by Ausha. See ausha.co/privacy-policy for more information.

50 phút
17 THG 9

#86 - Neural Maze: Guiding the Next Wave of AI Engineers | Miguel Otero Pedrido

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 Pedrido Miguel Otero Pedirdo on LinkedIn Miguel Otero Pedrido on Substack Miguel Otero Pedrido on Medium.com Miguel Otero Pedrido on GitHub Miguel Otero Pedrido on X The Neural Maze on Substack The Neural Maze on YouTube Connect with Thomas Bustos Thomas Bustos on LinkedIn Let’s Talk AI Let’s Talk AI on YouTube Let’s Talk AI on Spotify Hosted by Ausha. See ausha.co/privacy-policy for more information.

47 phút
10 THG 9

#85 - AI Is Moving Faster Than You Think: Here’s What to Know | Nathan Labenz

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 Labenz Nathan Labenz’ Website - https://www.nathanlabenz.com/ Nathan Labenz on LinkedIn - https://www.linkedin.com/in/nathanlabenz Nathan Labenz on X - https://x.com/labenz The Cognitive Revolution - https://www.cognitiverevolution.ai/ Connect with Thomas Bustos Thomas 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/6mVjFvdEkZDCTXpIuuSLAP Hosted by Ausha. See ausha.co/privacy-policy for more information.

1 giờ 2 phút
3 THG 9

#84 - Entrepreneurship Lessons You Won’t Learn in Business School | Pedro Goes

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 Goes Pedro Goes on LinkedIn - https://www.linkedin.com/in/pedrogoes/ InEvent - https://inevent.com/ Pedro Goes on X - https://x.com/goesinevent Connect with Thomas Bustos Thomas 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/6mVjFvdEkZDCTXpIuuSLAP Hosted by Ausha. See ausha.co/privacy-policy for more information.

44 phút
27 THG 8

#83 - The Truth About Freelancing in Data Science (And How to Succeed) | Jeremy Arancio

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 Arancio Jeremy Arancio on LinkedIn - https://cz.linkedin.com/in/jeremy-arancio Read his articles - https://medium.com/@jeremyarancio Jeremy Arancio on GitHub - https://github.com/JeremyArancio Email him - jeremyarancio.freelance@gmail.com Connect with Thomas Bustos Thomas 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/6mVjFvdEkZDCTXpIuuSLAP Hosted by Ausha. See ausha.co/privacy-policy for more information.

1 giờ 16 phút
20 THG 8

#81 - Is AI Outpacing Ethics? Machine Learning in the Real World | Marijn Markus

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 Markus Marijn Markus on LinkedIn - https://www.linkedin.com/in/marijnmarkus Capgemini - https://www.capgemini.com/ Connect with Thomas Bustos & Let's Talk AI Thomas 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/6mVjFvdEkZDCTXpIuuSLAP Hosted by Ausha. See ausha.co/privacy-policy for more information.

1 giờ 15 phút
20 THG 8

#82 - What Every Aspiring Data Engineer Needs to Know in 2025 | Ananth Packkildurai

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 Packkildurai Ananth Packkildurai on LinkedIn - https://www.linkedin.com/in/ananthdurai Data Engineering Weekly by Ananth Packkildurai - https://www.dataengineeringweekly.com/ Connect with Thomas Bustos Thomas 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/6mVjFvdEkZDCTXpIuuSLAP Hosted by Ausha. See ausha.co/privacy-policy for more information.

59 phút

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Let’s Talk AI is the podcast that makes you dive deeper into Artificial Intelligence. We talk with experts about topics, challenges, technologies related to AI with no fear to get into technical details. The goal is to learn from guests that are passionate about AI shares about real world cases, to take your business, career and projects to the next level! Hosted by Ausha. See ausha.co/privacy-policy for more information.

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2022 - 2025
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