This episode is sponsored by Babbel. Babbel is conversation-based learning built with science-backed cognitive tools like spaced repetition and interactive lessons created by real language teachers and voiced by real native speakers.

Get 55% off your Babbel subscription 👉 https://babbel.com/eyeonai

Unveil the transformative power of AI in business and society.

Join us on #165 of the Eye on AI podcast as we sit down with Andy Hock, VP of Product at Cerebras Systems, an AI hardware startup out to accelerate deep learning and change computing forever.

Focusing on the intersection of AI and business, Andy discusses how advanced technologies are reshaping corporate strategies and operations. He offers insights into integrating AI into traditional business models, emphasizing the transformative role of technology in innovation and growth.

We also explore the societal implications of AI. Andy delves into the ethical considerations and challenges posed by AI, including privacy and responsible deployment. He sheds light on the latest trends in AI research, particularly in areas like natural language processing and machine learning, and their diverse applications across industries.

Andy concludes with advice for businesses and individuals navigating the AI landscape, underscoring the importance of adaptability and continuous learning in this rapidly evolving field. Make sure you watch till the end!

Stay Updated:

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

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

(00:00) Preview and Introduction

(01:09) Decoding Cerebras Systems' Technology.

(03:25) The Power of the Wafer Scale Engine

(05:24) Training and Inference Capabilities

(10:44) Accessibility for Students and Researchers

(12:08) GPU Equivalents and Wafer Scale Engine's Efficiency

(13:53) Utilization and Power of the Chip

(19:02) Understanding Wafer and Circuitry

(23:27) Computing Power of the Wafer Scale Engine

(28:59) Challenges in Cooling the Wafer Scale Engine

(32:31) Utilization of Silicon Waste

(36:21) Cost Comparison with Other Technologies

(40:01) Customer Usage Patterns – Cloud vs On-Premise

(45:22) Training Models for Edge Devices

(47:30) Collaborations with OpenAI

(49:26) Addressing GPU Shortages and Enterprise Needs

(51:01) Inference Capabilities and Future Developments

(57:46) AI as a National Compute Resource

(01:03:41) Closing Remarks