This episode features a fascinating conversation with Sid Sheth, CEO and Co-Founder of d-Matrix. With a deep background in building advanced systems for high-performance workloads, Sid and his team are at the forefront of AI compute innovation—specifically focused on making AI inference more efficient, cost-effective, and scalable for enterprise use. Host Seth Earley dives into Sid’s journey, the architectural shifts in AI infrastructure, and what it means for organizations seeking to maximize their AI investments.

Key Takeaways:

• The Evolution of AI Infrastructure: Sid breaks down how the traditional tech stack is being rebuilt to support the unique demands of AI, particularly shifting from general-purpose CPUs to specialized accelerators for inference.
• Training vs. Inference: Using a human analogy, Sid explains the fundamental difference between model training (learning) and inference (applying knowledge), emphasizing why most enterprise value comes from efficient inference.
• Purpose-built Accelerators: d-Matrix’s approach to creating inference-only accelerators means dramatically reducing overhead, latency, energy consumption, and cost compared to traditional GPU solutions.
• Scalability & Efficiency: Learn how in-memory compute, chiplets, and innovative memory architectures enable d-Matrix to deliver up to 10x lower latency, and significant gains in energy and dollar efficiency for AI applications.
• Market Trends: Sid reveals how, although today’s focus is largely on training compute, the next five to ten years will see inference dominate as organizations seek ROI from deployed AI.
• Enterprise Strategy Advice: Sid urges tech leaders not to be conservative, but to embrace a heterogeneous and flexible infrastructure strategy to future-proof their AI investments.
• Real-World Use Cases: Hear about d-Matrix’s work enabling low-latency agentic/reasoning models, which are critical for real-time and interactive AI workloads.

Insightful Quote from Sid Sheth:

“Now is not the time to be conservative and get comfortable with choice. In the world of inference there isn’t going to be one size fits all... The world of the future is heterogeneous, where you’re going to have a compute fleet that is augmented with different types of compute to serve different needs.”

Tune in to discover how to rethink your AI infrastructure strategy and stay ahead in the rapidly evolving world of enterprise AI!

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• VKTR
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In this episode of the Earley AI Podcast, host Seth Earley sits down with Charles Migos, a veteran toolmaker whose career has spanned animation, post-production, visual effects, and large-scale media systems. Charles is recognized for his innovative approach to making emerging technologies—particularly generative AI—intuitive and accessible for creatives at every level, not just technical experts. Drawing on decades of experience, Charles shares what it means to design tools that empower storytellers and production teams, accelerate creativity, and address industry-specific needs.

Key Takeaways:

• The media and entertainment industry has been under stress due to macroeconomic changes and the disruptive impact of generative AI.
• Creative jobs and processes are being transformed as AI tools dramatically speed up and democratize production workflows, bridging the gap between concept and execution.
• Traditional creative roles are shifting: Directors, producers, and even clients can now participate directly in visual storytelling without years of technical training.
• Instead of relying solely on prompt-based AI systems, innovation lies in giving creatives precise, fine-grained control for rapid exploration and content iteration.
• Asset repurposability, modularity, and the ability to build on prior creative work are becoming crucial for agencies and studios to scale, reduce costs, and increase creative output.
• Protecting intellectual property and ensuring ethical AI use—particularly around deepfakes and content control—is fundamental as generative tools become more powerful.
• The foundation of successful creative AI lies in deeply understanding and honoring existing workflows, enabling faster collaboration, clearer communication, and greater creative trust.

Insightful Quote from Charles Migos:

"Your ability to create faster and better than you ever have before, your ability to collaborate with your team and your stakeholders in ways you never have before, and the ability to communicate around what you create as that team effort is what matters most."

Tune in to explore how AI is reshaping the creative landscape and to gain actionable insight on building truly human-centered design into emerging tech.

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• VKTR
• Earley Information Science
• AI Powered Enterprise Book

In this episode of the Earley AI Podcast, host Seth Earley sits down with Abhi Yadav, founder of iCustomer AI—a cutting-edge composable decision intelligence company. With a deep background in enterprise technology, Abhi pioneered the Customer Data Platform (CDP) category and is now leading innovation in advanced multigraph frameworks and customer intelligence. He is also an advisor to leading data management organizations and is passionate about helping brands reshape how they connect with customers by making data truly "AI-ready."

Together, Seth and Abhi explore the evolving landscape at the intersection of AI, data, and enterprise maturity. They dive deep into the challenges and opportunities organizations face as they strive for higher levels of decision intelligence, highlighting both the technical and strategic shifts driving the industry forward.

Key Takeaways:

• The evolution from traditional MDM (Master Data Management) and CDP platforms toward a “knowledge engineering era” powered by AI and multi-graph architectures.
• Why a single source of truth is more about a unified, reconcilable semantic layer than a single data repository.
• The importance of developing robust taxonomies, ontologies, and knowledge graphs to contextualize customer data and orchestrate intelligent decisioning at scale.
• Clear definitions and distinctions between zero-party, first-party, second-party, and third-party data—and why they matter for privacy, compliance, and effective marketing.
• Challenges enterprise leaders face in scaling decision intelligence, especially in determining the right balance of human and machine-led decisions.
• The emerging need for "decision lineage": tracking not only what data was used, but how and why decisions were made, for compliance and transparency.
• Advice for founders, technologists, and enterprise leaders: avoid the hype and focus on solving real, specific problems before building platforms or dreaming of category creation.

Insightful Quote from Abhi Yadav:

"Don't follow the hype, follow the real problem. There are still so many real problems—and the more specific that problem is, the more impact you can make. Platforms and categories come later; start with solving measurable problems today."

Tune in for a thoughtful, actionable conversation on unlocking the true potential of enterprise AI and creating data architectures that drive meaningful impact.

Thanks to our sponsors:

• VKTR
• Earley Information Science
• AI Powered Enterprise Book

In this episode of the Earley AI Podcast, host Seth Earley sits down with Yang Li, a leading figure in AI and software innovation. Yang is the Chief Operating Officer of Cosine, an advanced AI development firm, with deep experience driving startups, scaling organizations, and pioneering advancements in engineering and software development. Yang’s work focuses on leveraging AI to empower the next generation of developers, especially in navigating the increasingly complex landscape of modern and legacy codebases.

Yang and Seth dive into how AI is reshaping the role of software engineers, the evolving challenges of handling massive backlogs and legacy systems, and what creativity and efficiency really look like in an age of AI-powered software development.

Key Takeaways:

• AI’s Impact on Software Engineering: AI is shifting the developer’s role from hands-on coding to more creative, iterative, and strategic work.
• Tackling Legacy Code: Cosine is pioneering new ways for AI to handle outdated and complex codebases (like COBOL and Fortran) that most engineers—and AI models—struggle with.
• Augmenting, Not Replacing, Engineers: AI tools like Cosine’s Genie reduce ramp-up time for engineers, help address daunting backlogs, and act as creative partners rather than outright replacements.
• The Challenge of Benchmarks: Yang explains why public coding benchmarks can be misleading when bringing products to real-world enterprise environments, especially with diverse codebases.
• The Emergence of ‘Vibe Coding’: Idea-to-prototype time is shrinking, allowing non-technical team members to quickly bring their ideas to life using AI assistants.
• Risks & Limits: Over-reliance on AI, standardization versus differentiation, and the need for new evaluation criteria in engineering organizations.
• Future Skills: The importance of risk-taking, adaptability, and prompt engineering as software development evolves, plus insights into how organizations are rethinking career ladders and promotions in an AI-powered world.

Insightful Quote from Yang Li:

"Previously you had to use words and language to describe your idea, you can now show people your idea... The time between you having thought of an idea to actually be able to show people that idea has now reduced almost to zero because of vibe coding."

Tune in to discover what’s next for software engineering in the age of AI, and how to stay ahead in this rapidly changing landscape.

Thanks to our sponsors:

• VKTR
• Earley Information Science
• AI Powered Enterprise Book

In this episode of the Earley AI Podcast, host Seth Earley sits down with industry analyst and advisor Tony Baer, a seasoned expert in data, cloud, and analytics. With decades of experience guiding global tech leaders like AWS and Oracle, Tony brings a nuanced perspective on how knowledge engineering is evolving—and why context is the missing link in many enterprise AI initiatives.

Together, Seth and Tony explore the shift from static data models to dynamic knowledge frameworks, the renewed importance of governance, and how graph databases and generative AI are reshaping enterprise intelligence. This is a conversation packed with hard-earned lessons and actionable insight for data, IT, and transformation leaders aiming to make AI work in the real world.

Key Takeaways:

• Knowledge engineering today is about dynamic, adaptive structures—not static ontologies or rigid models.
• The role of the knowledge engineer is shifting: it’s less about technical mastery and more about bridging data, business, and domain expertise.
• Context is foundational. The five W’s—Who, What, When, Where, Why (and How)—unlock meaningful, actionable intelligence.
• Graph databases and AI are enabling real-time connections across data, turning static information into living knowledge.
• Generative AI delivers the most value when rooted in organizational context. RAG strategies demand clean data and strong information architecture.
• Successful AI initiatives are focused. Start with well-bounded, high-impact processes—avoid boiling the ocean.
• Core principles from previous data waves still apply. It’s about evolving governance, stewardship, and architecture for the AI era.
• Sustainable value comes from feedback loops, iteration, and alignment—not silver bullets.

Tune in to discover how to make AI practical, actionable, and intelligent for your organization.

Quote of the Show: "Just because something is old does not make it wrong. There are a lot of disciplines we've built up over the years—governance, data stewardship—that still matter. The principle was right. We just adapt it and use our learnings from each cycle to become more knowledgeable and proficient." Tony Baer

Links

LinkedIn: https://www.linkedin.com/in/dbinsight/

Website: https://www.dbinsight.io

Thanks to our sponsors:

• VKTR
• Earley Information Science
• AI Powered Enterprise Book

In this episode of the Earley AI Podcast, host Seth Earley welcomes two insightful guests from Anders, a top 100 CPA firm: David Hartley and Dave Blatt. David Hartley is a seasoned CPA with a profound understanding of the synergy between finance and technology. He advocates for how AI can enhance traditional accounting roles rather than replace them. Dave Blatt brings a wealth of knowledge in AI automation and analytics, focusing on empowering mid-sized companies to harness AI for competing with larger players.

Join us as we dive into the world of AI applications in the finance, accounting, and mid-market operations sectors. Our guests dispel common myths and fears surrounding AI, exploring how small and medium-sized enterprises can practically and effectively adopt AI technologies to drive transformation and growth.

Key Takeaways:

• Demystifying AI: Understanding AI in the context of mid-market companies and addressing misconceptions around AI replacing human jobs.
• AI for Mid-Sized Enterprises:** How AI is accessible and beneficial for mid-sized businesses, allowing them to compete with larger organizations.
• Impact on Accounting: Enhancing traditional accounting roles through AI and freeing up time for more value-added activities.
• Implementation Strategies: Best practices for implementing AI in mid-sized companies, focusing on education, small projects, and quick wins.
• Real-World Applications: Case studies in industries like construction and manufacturing, where AI has improved efficiency and productivity.
• Communication and Trust: The importance of communication and building trust among team members to ensure successful AI adoption.

Quote of the Show: "Start small and not make it so daunting... get some quick wins that will be a catalyst to doing more projects and bigger efforts." - Dave Blatt

Links:

LinkedIn: https://www.linkedin.com/in/davehartley/

LinkedIn: https://www.linkedin.com/in/daveblatt/

Website: https://anderscpa.com

Article: AI Adoption Is Not as Hard as You Think – Start Now or Fall Behind

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In this episode of the Earley AI Podcast, we welcome guest, Jack Lampka, an accomplished advisor and speaker with over 27 years of experience in corporate roles within the tech and pharma sectors. Now based in Munich, Germany, Jack specializes in enhancing data storytelling and cultivating a product mindset among technical employees. His extensive career journey includes living and working in countries like Poland and the United States.

Key Takeaways from this Episode:

• The importance of a product mindset for technical teams when developing AI solutions.
• Understanding the misconceptions and realistic expectations for AI and generative AI in businesses.
• How to successfully sell AI solutions internally by focusing on business needs and creating a comprehensive product marketing plan.
• The role of data storytelling in bridging the gap between technical and non-technical users.
• Insights into the hype surrounding Agentic AI and its relevance to current business applications.

Thanks to our sponsors:

• VKTR
• Earley Information Science
• AI Powered Enterprise Book

Join Seth Earley on Earley AI Podcasts as he welcomes Adam Honig, a pioneering force in the field of customer relationship management (CRM). As the founder of Spiro AI, Adam challenges the conventional need for CRM systems by offering an innovative AI-driven alternative. With a rich history of building one of the largest Salesforce consulting partners—eventually acquired by Accenture—Adam’s insights blend tradition with transformative technology, sparking discussions about the evolving landscape of CRM.

Key Takeaways:

• Revolutionizing CRM: Understand Adam's perspective on why traditional CRM systems are antiquated and how Spiro’s AI-driven approach offers a modern solution.
• Automated Data Capture: Learn how Spiro AI automates the tedious process of data entry and offers real-time insights for sales teams without manual input.
• Industry-Specific Challenges: Explore the unique hurdles faced by manufacturing and distribution sectors in adopting CRM and AI technologies.
• AI Implementation: Discover practical implementations of AI, including order entry automation, in revolutionizing traditional business models.
• Future of Work: Delve into a candid discussion on how AI could lead to significant job displacement, and the broader economic implications.
• Roadmap of Innovation: Get a sneak peek into future developments, including autonomous AI agents and enhanced integration with product data.

Quote from the show:

"Salespeople didn't go into sales to enter data. They want to meet with customers. They want to be where the action is, and they need the software to just get out of their way." – Adam Honig

Links:
LinkedIn: https://www.linkedin.com/in/adamhonig/

Website: https://spiro.ai

X: https://x.com/adamhonig

Thanks to our sponsors:

• VKTR
• Earley Information Science
• AI Powered Enterprise Book