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In this episode of the Eye on AI podcast, Varun Mohan, Co-Founder and CEO of Codeium, shares the journey behind building one of the most innovative AI-powered coding tools available today.

Varun joins Craig Smith to explore the future of software development, the evolution of Codeium, and how generative AI is revolutionizing the way developers interact with codebases.

As a leader in AI and software engineering, Varun discusses how Codeium integrates advanced AI to enable real-time code completion, refactoring, and even end-to-end application building. From processing billions of lines of code to making complex legacy systems like COBOL more accessible, Codeium is empowering developers to work smarter and faster.

We delve into the challenges of managing massive codebases, the importance of maintaining security and self-hosted solutions, and how tools like Codeium stand apart from competitors like Copilot and CodeWhisperer. Varun also introduces **Cascade**, the AI assistant within Codeium’s custom IDE, Windsurf, which merges human ingenuity with AI's reasoning capabilities for a seamless coding experience.

Other fascinating topics include the role of AI in onboarding developers to complex systems, its ability to handle rare programming languages, and how Codeium is reshaping the software lifecycle from design to deployment.

Learn how Codeium is redefining the possibilities of software development with AI, and what the future holds as this technology continues to evolve.

Don’t miss this deep dive into AI-powered innovation with Varun Mohan. Like, subscribe, and hit the notification bell for more episodes exploring cutting-edge advancements in AI!

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Craig Smith Twitter: https://twitter.com/craigss

Eye on A.I. Twitter: https://twitter.com/EyeOn_AI

(00:00) Introduction to Varun Mohan and Codeium

(05:32) Introducing Codeium: AI-powered coding revolution

(08:42) Competing with Copilot and CodeWhisperer

(11:46) Using Codeium to streamline software development

(14:01) Features of Cascade: Refactoring and automation

(17:26) Building applications from scratch with Codeium

(22:00) Enterprise adoption and recognition by JPMorgan Chase

(23:14) The pivot to Codeium and lessons learned

(24:32) The vision for Codeium’s future

This episode of Eye on AI is sponsored by Citrusx.

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In this episode of the Eye on AI podcast, Terry Sejnowski, a pioneer in neural networks and computational neuroscience, joins Craig Smith to discuss the future of AI, the evolution of ChatGPT, and the challenges of understanding intelligence.

Terry, a key figure in the deep learning revolution, shares insights into how neural networks laid the foundation for modern AI, including ChatGPT’s groundbreaking generative capabilities. From its ability to mimic human-like creativity to its limitations in true understanding, we explore what makes ChatGPT remarkable and what it still lacks compared to human cognition.

We also dive into fascinating topics like the debate over AI sentience, the concept of "hallucinations" in AI models, and how language models like ChatGPT act as mirrors reflecting user input rather than possessing intrinsic intelligence. Terry explains how understanding language and meaning in AI remains one of the field’s greatest challenges.

Additionally, Terry shares his perspective on nature-inspired AI and what it will take to develop systems that go beyond prediction to exhibit true autonomy and decision-making.

Learn why AI models like ChatGPT are revolutionary yet incomplete, how generative AI might redefine creativity, and what the future holds for AI as we continue to push its boundaries.

Don’t miss this deep dive into the fascinating world of AI with Terry Sejnowski. Like, subscribe, and hit the notification bell for more cutting-edge AI insights!

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Craig Smith Twitter: https://twitter.com/craigss

Eye on A.I. Twitter: https://twitter.com/EyeOn_AI

(00:00) Introduction to Terry Sejnowski and His Work

(03:02) The Origins of Modern AI and Neural Networks

(05:29) The Deep Learning Revolution and ImageNet

(07:11) Understanding ChatGPT and Generative AI

(12:34) Exploring AI Creativity

(16:03) Lessons from Gaming AI: AlphaGo and Backgammon

(18:37) Early Insights into AI’s Affinity for Language

(24:48) Syntax vs. Semantics: The Purpose of Language

(30:00) How Written Language Transformed AI Training

(35:10) Can AI Become Sentient?

(41:37) AI Agents and the Next Frontier in Automation

(45:43) Nature-Inspired AI: Lessons from Biology

(50:02) Digital vs. Biological Computation: Key Differences

(54:29) Will AI Replace Jobs?

(57:07) The Future of AI

This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.

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In this episode of the Eye on AI podcast, Avthar Sewrathan, Lead Technical Product Marketing Manager at Timescale joins Craig Smith to explore how Postgres is transforming AI development with cutting-edge tools and open-source innovation.

With its robust, extensible framework, Postgres has become the go-to database for AI applications, from semantic search to retrieval-augmented generation (RAG). Avthar takes us through Timescale's journey from its IoT origins to disrupting the way developers handle vector search, embedding management, and high-performance AI workloads—all within Postgres.

We dive into Timescale's tools like PGVector, PGVector Scale, and PGAI Vectorizer, uncovering how they aid developers to build AI-powered systems without the complexity of managing multiple databases. Avthar explains how Postgres seamlessly handles structured and unstructured data, making it the perfect foundation for next-gen AI applications.

Learn how Postgres supports AI-driven use cases across industries like IoT, finance, and crypto, and why its open-source ecosystem is key to fostering collaboration and innovation.

Tune in to discover how Postgres is redefining AI databases, why Timescale’s tools are a game-changer for developers, and what the future holds for AI innovation in the database space.

Don’t forget to like, subscribe, and hit the notification bell for more AI insights!

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Craig Smith Twitter: https://twitter.com/craigss

Eye on A.I. Twitter: https://twitter.com/EyeOn_AI

(00:00) Introduction to Avthar and Timescale

(02:35) The origins of Timescale and TimescaleDB

(05:06) What makes Postgres unique and reliable

(07:17) Open-source philosophy at Timescale

(12:04) Timescale's early focus on IoT and time series data

(16:17) Applications in finance, crypto, and IoT

(19:03) Postgres in AI: From RAG to semantic search

(22:00) Overcoming scalability challenges with PGVector Scale

(24:33) PGAI Vectorizer: Managing embeddings seamlessly

(28:09) The PGAI suite: Tools for AI developers

(30:33) Vectorization explained: Foundations of AI search

(32:24) LLM integration within Postgres

(35:26) Natural language interfaces and database workflows

(38:11) Structured and unstructured data in Postgres

(41:17) Postgres for everything: Simplifying complexity

(44:52) Timescale’s accessibility for startups and enterprises

(47:46) The power of open source in AI