This episode is sponsored by Oracle. AI is revolutionizing industries, but needs power without breaking the bank. Enter Oracle Cloud Infrastructure (OCI): the one-stop platform for all your AI needs, with 4-8x the bandwidth of other clouds. Train AI models faster and at half the cost. Be ahead like Uber and Cohere.

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In this episode of the Eye on AI podcast, Craig Smith sits down with Noa Srebrnik from Citrusx.ai to explore how AI is transforming risk management and compliance in high-risk industries like finance and insurance.

With a background spanning regulation, risk, and technology, Noa guides us through Citrusx.ai’s innovative approach to enabling organizations to leverage AI responsibly while adhering to complex regulatory environments.

We dive deep into Citrusx.ai’s AI platform, designed to validate, monitor, and explain AI models, ensuring transparency, fairness, and compliance. Noa explains how their proprietary synthetic data technology identifies hidden risks, allowing companies to confidently scale AI solutions across different use cases without compromising governance.

We also discuss the evolving regulatory landscape, including the challenges of navigating fragmented AI regulations in the U.S. and the EU AI Act’s influence on high-risk sectors.

Join us as we uncover how AI can drive innovation while maintaining regulatory accountability and why risk management is crucial for the future of AI in finance and beyond.

Don’t forget to like, subscribe, and hit the notification bell for more in-depth discussions on AI, regulation, and risk management!

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

NetSuite is offering a one-of-a-kind flexible financing program. Head to https://netsuite.com/EYEONAI to know more.

In this episode of the Eye on AI podcast, Craig Smith sits down with Krishna Rangasayee, CEO of SiMa.ai, to explore the innovations in AI at the edge and how embedded systems are transforming industries like robotics, automotive, and industrial automation.

Krishna brings over 30 years of experience in software and silicon design, leading us through SiMa.ai's vision of disrupting edge computing with their Machine Learning System on Chip (MLSoC).

We dive deep into how SiMa.ai’s chips are designed to accelerate AI workloads at the edge, providing unmatched performance and efficiency compared to cloud-based solutions.

We also discuss the future of AI hardware, including the role of open-source platforms, the challenges of scaling AI in embedded systems, and why the edge market is poised to outgrow the cloud in the coming years.

Krishna shares his insights on the importance of AI software architecture, how SiMa.ai’s platform simplifies integration for developers, and the emerging potential of neuromorphic and quantum computing.

Join us as we delve into the next big AI gold rush, the edge market, and learn why AI-powered edge devices will reshape the way industries operate.

Don’t forget to like, subscribe, and hit the notification bell for more exclusive insights into the future of AI and edge computing!

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

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

(00:00) Preview and Introduction

(02:13) SiMa.ai's Focus on Chip Design for the Edge

(05:38) How is SiMa.ai Different from NVIDIA’s CUDA?

(08:29) The Evolution of Chip Architecture

(11:50) AI’s Move to the Edge Market?

(19:19) Industries Driving Demand for SiMa.ai's Technology

(21:25) How Do Edge Applications Work?

(25:09) Chips Design for Edge Devices

(33:01) SiMa.ai Scaling Plans

(36:12) What is SiMa.ai Focusing On in the Future?

(40:30) SiMa.ai’s Fundraising Journey

(42:57) Hiring and Retaining Top Talent in the Industry

(46:01) The Future of Chip Technology

This episode is sponsored by Bloomreach.

Bloomreach is a cloud-based e-commerce experience platform and B2B service specializing in marketing automation, product discovery, and content management systems.

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In this episode of the Eye on AI podcast, we sit down with Randall Degges, Head of Developer Relations and Security at Snyk, to uncover the impact of AI on cybersecurity and software development.

Randall shares his 20+ years of experience as a software developer and security expert, leading us through Snyk's innovative approach to developer security. We dive into how Snyk is changing vulnerability detection and code generation by leveraging a hybrid AI model—combining symbolic AI for accurate detection and generative AI for smart fixes.

We explore the challenges and opportunities of using AI in code security, discussing whether AI-generated code can ever fully replace human coders or if it's best suited as a powerful tool in a developer's arsenal. Randall also addresses the risks of AI hallucinations in code generation and how Snyk mitigates these through rigorous testing and validation.

Join us as we discuss the future of coding, the role of AI in software development, and how developers can stay ahead in this rapidly evolving landscape.

Don’t forget to like, subscribe, and hit the notification bell for more expert insights into the latest AI and cybersecurity trends.

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

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

(00:00) Preview and Intro

(00:34) Randall Degges Background

(01:33) The Role of AI in Security at Snyk

(03:28) Symbolic vs. Generative AI in Code Security

(04:57) How Snyk Uses Rule-Based AI for Detection

(06:48) Challenges with AI-Generated Code Fixes

(09:08) The Future of AI in Code Generation

(11:56) Integrating AI with Developer Tools

(16:06) Risks of AI-Generated Code and Internet Saturation

(22:25) The Hybrid AI Approach for Code Security

(26:31) Future of AI and Its Impact on Developers

(30:02) Snyk's Integration with IDEs and Research Initiatives

(33:48) Autonomous Fixes and the Future of AI in Development

(41:04) DeepCode AI Fix Engine and Snyk’s ID Plugin

(46:38) Will AI Replace Developers?

(50:16) AI Readiness Report Insights

(52:59) Tech Layoffs and Opportunities in AI