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Tech on the Rocks

Latest episodes

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Feb 20, 2025 • 59min

Semantic Layers: The Missing Link Between AI and Data with David Jayatillake from Cube

David Jayatillake, VP of AI at Cube, shares his expertise on the critical role of semantic layers in bridging raw data and actionable insights. He reveals how Cube achieved 100% accuracy in natural language data queries using semantic layers, vastly outperforming traditional methods. The conversation dives into the challenges of building these layers, emphasizing the significance of clear naming and documentation. Jayatillake also discusses future trends, including AI-powered features set to launch in 2025, and the potential of LLMs as intelligent agents.
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Feb 4, 2025 • 59min

From black holes to AI in mathematics: AI Innovation in Mathematics and Health with Yaron Hadad

In this episode, we chat with Yaron Hadad, a fascinating individual who transitioned from theoretical physics to entrepreneurship. We explore his groundbreaking work on black holes and gravitational waves, and learn about the Ramanujan Machine - an algorithmic system he helped develop that discovers new mathematical formulas and democratizes mathematical research. We'll hear about the scientific community's mixed reactions to this innovative approach. The conversation then shifts to his work with Neutrino, a company he founded that uses AI and continuous monitoring devices to understand how food affects individual health. We delve into the complexities of nutrition science, the challenges of processing multiple data streams, and the future of personalized health monitoring. Throughout the episode, Yaron shares insights on bridging theoretical research with practical applications, and the role of AI in advancing both pure mathematics and healthcare.00:00 Yaron Hadad's Journey: From Physics to AI in Healthcare04:50 The Complexity of Einstein's Equations and Their Solutions10:12 AI in Mathematics: The Ramanujan Machine and Conjectures15:41 Navigating Criticism: The Scientific Community's Response to Innovation29:24 The Impact of Algorithms in Mathematics35:30 The Planck Machine: A New Approach41:15 Neutrino: A Personal Journey in Nutrition50:11 Connecting Food Complexity to Health Metrics
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Jan 16, 2025 • 1h

Building a Native Search Engine in PostgreSQL: ParadeDB's Journey to Replace Elasticsearch with Philippe Noël

In this episode, we chat with Philippe Noël, founder of ParadeDB, about building an Elasticsearch alternative natively on PostgreSQL. We explore the challenges and benefits of extending PostgreSQL versus building a separate system, diving into topics like full-text search, faceted analytics, and why organizations need these capabilities. We discuss the emerging bring-your-own-cloud deployment model, the state of the PostgreSQL extension ecosystem, and what makes a truly production-ready database extension. Philippe shares insights on the future of search technology and how recent AI developments are actually increasing the demand for traditional search capabilities. The conversation also covers the misconceptions around PostgreSQL's scalability and the trade-offs between multi-tenant and single-tenant architectures in modern data infrastructure.Chapters00:00 Introduction to ParadeDB and Its Mission06:35 User-Facing Search and Analytics11:45 The Role of Postgres in Modern Data Solutions17:30 Future of Multimodal Databases31:04 The Rise of Fintech and Data Integrity36:36 Deployment Models: BYOC and Control Plane43:41 The Evolution of Cloud Infrastructure and Serverless Databases49:38 The Future of Search and Community EngagementClick here to view the episode transcript.
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Jan 3, 2025 • 1h 6min

Optimizing SQL with LLMs: Building Verified AI Systems at Espresso AI with Ben Lerner

In this episode, we chat with Ben, founder of Espresso AI, about his journey from building Excel Python integrations to optimizing data warehouse compute costs. We explore his experience at companies like Uber and Google, where he worked on everything from distributed systems to ML and storage infrastructure. We learn about the evolution of his latest venture, which started as a C++ compiler optimization project and transformed into a system for optimizing Snowflake workloads using ML. Ben shares insights about applying LLMs to SQL optimization, the challenges of verified code transformation, and the importance of formal verification in ML systems. Finally, we discuss his practical approach to choosing ML models and the critical lesson he learned about talking to users before building products.Chapters00:00 Ben's Journey: From Startups to Big Tech13:00 The Importance of Timing in Entrepreneurship19:22 Consulting Insights: Learning from Clients23:32 Transitioning to Big Tech: Experiences at Uber and Google30:58 The Future of AI: End-to-End Systems and Data Utilization35:53 Transitioning Between Domains: From ML to Distributed Systems44:24 Espresso's Mission: Optimizing SQL with ML51:26 The Future of Code Optimization and AIClick here to view the episode transcript.
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Dec 19, 2024 • 1h 4min

Security as Code: Building Developer-First Security Tools with David Mytton

David Mytton, founder and CEO of Arcjet, shares his journey from cloud monitoring to creating developer-first security tools. He dives into the challenges of bot detection and the failures of traditional security methods. Mytton discusses using WebAssembly for rapid security checks and highlights the balance between security and latency. He also touches on the importance of documentation in developer tools and his work on sustainability in cloud computing, revealing how environmental impacts shape modern tech solutions.
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Dec 4, 2024 • 1h 9min

Dev Environments in the AI Era: Standardizing Development Infrastructure with Daytona's Ivan

Delve into the evolution of developer environments with insights from a pioneer in browser-based IDEs. Discover the challenges of integrating complex systems and the distinction between user needs and buyer demands. Explore the impact of AI on coding practices and the unique approach of standardization and automation. Ivan shares his experience transitioning to open source and the future of integrated development environments. Plus, hear about the dynamics of organizing tech conferences and the importance of adapting to emerging trends.
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Nov 21, 2024 • 1h 3min

Evolving Data Infrastructure for the AI Era: AWS, Meta, and Beyond with Roy Ben-Alta

In this episode, we chat with Roy Ben-Alta, co-founder of Oakminer AI and former director at Meta AI Research, about his fascinating journey through the evolution of data infrastructure and AI. We explore his early days at AWS when cloud adoption was still controversial, his experience building large language models at Meta, and the challenges of training and deploying AI systems at scale. Roy shares valuable insights about the future of data warehouses, the emergence of knowledge-centric systems, and the critical role of data engineering in AI. We'll also hear his practical advice on building AI companies today, including thoughts on model evaluation frameworks, vendor lock-in, and the eternal "build vs. buy" decision. Drawing from his extensive experience across Amazon, Meta, and now as a founder, Roy offers a unique perspective on how AI is transforming traditional data infrastructure and what it means for the future of enterprise software.Chapters00:00 Introduction to Roy Benalta and AI Background04:07 Warren Buffett Experience and MBA Insights06:45 Lessons from Amazon and Meta Leadership09:15 Early Days of AWS and Cloud Adoption12:12 Redshift vs. Snowflake: A Data Warehouse Perspective14:49 Navigating Complex Data Systems in Organizations31:21 The Future of Personalized Software Solutions32:19 Building Large Language Models at Meta39:27 Evolution of Data Platforms and Infrastructure50:50 Engineering Knowledge and LLMs58:27 Build vs. Buy: Strategic Decisions for Startups
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Nov 6, 2024 • 58min

From Functions to Full Applications: How Serverless Evolved Beyond AWS Lambda with Nitzan Shapira

In this episode, we chat with Nitzan Shapira, co-founder and former CEO of Epsagon, which was acquired by Cisco in 2021. We explore Nitzan's journey from working in cybersecurity to building an observability platform for cloud applications, particularly focused on serverless architectures. We learn about the early days of serverless adoption, the challenges in making observability tools developer-friendly, and why distributed tracing was a key differentiator for Epsagon. We discuss the evolution of observability tools, the future impact of AI on both observability and software development, and the changing landscape of serverless computing. Finally, we hear Nitzan's current perspective on enterprise AI adoption from his role at Cisco, where he helps evaluate and build new AI-focused business lines.03:17 Transition from Security to Observability09:52 Exploring Ideas and Choosing Serverless16:43 Adoption of Distributed Tracing20:54 The Future of Observability25:26 Building a Product that Developers Love31:03 Challenges in Observability and Data Costs32:47 The Excitement and Evolution of Serverless35:44 Serverless as a Horizontal Platform37:15 The Future of Serverless and No-Code/Low-Code Tools38:15 Technical Limits and the Future of Serverless40:38 Navigating Near-Death Moments and Go-to-Market Challenges48:36 Cisco's Gen .AI Ecosystem and New Business Lines50:25 The State of the AI Ecosystem and Enterprise Adoption53:54 Using AI to Enhance Engineering and Product Development55:02 Using AI in Go-to-Market Strategies
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Oct 22, 2024 • 1h 2min

From GPU Compilers to architecting Kubernetes: A Conversation with Brian Grant

Brian Grant, the original lead architect of Kubernetes and a pioneer in GPU compiler technology, shares insights from his distinguished career in systems engineering. He recalls the unique challenges in early GPU computing and the transformative innovations in compiler architecture. The conversation delves into the architectural decisions of Kubernetes and Google's Borg, highlighting the importance of a rich abstraction model and the need for standardization in cloud infrastructure. Grant also envisions a future beyond mere infrastructure as code.
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Oct 8, 2024 • 1h 1min

Proving Code Correctness: FizzBee and the Future of Formal Methods in Software Design with FizzBee's creator JP

In this episode, we chat with JP, creator of FizzBee, about formal methods and their application in software engineering. We explore the differences between coding and engineering, discussing how formal methods can improve system design and reliability. JP shares insights from his time at Google and explains why tools like FizzBee are crucial for distributed systems. We delve into the challenges of adopting formal methods in industry, the potential of FizzBee to make these techniques more accessible, and how it compares to other tools like TLA+. Finally, we discuss the future of software development, including the role of LLMs in code generation and the ongoing importance of human engineers in system design.LinksFizzBeeFizzBee Github RepoFizzBee BlogChapters00:00 Introduction and Overview02:42 JP's Experience at Google and the Growth of the Company04:51 The Difference Between Engineers and Coders06:41 The Importance of Rigor and Quality in Engineering10:08 The Limitations of QA and the Need for Formal Methods14:00 The Role of Best Practices in Software Engineering14:56 Design Specification Languages for System Correctness21:43 The Applicability of Formal Methods in Distributed Systems31:20 Getting Started with FizzBee: A Practical Example36:06 Common Assumptions and Misconceptions in Distributed Systems43:23 The Role of FizzBee in the Design Phase48:04 The Future of FizzBee: LLMs and Code Generation58:20 Getting Started with FizzBee: Tutorials and Online PlaygroundClick here to view the episode transcript.

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