The Circuit Ben Bajarin and Jay Goldberg

Episode Summary
The recent downturn in semiconductor and AI-related stocks has sparked concerns about a bubble. The volatility in these stocks can be attributed to the unpredictability of retail investors and traders. The market is experiencing a correction, but it does not indicate a slowdown in AI. The hype around AI has been tempered by the realization that progress is slower than expected. The energy constraint is a topic of discussion, but improvements in hardware and software will continue to address this issue. The future of AI depends on the balance between compute power and energy efficiency.

This episode of The Circuit discusses the recent trend of companies developing their own custom CPUs and accelerators for AI workloads. Google, Amazon, and Microsoft have all announced their own custom chips, while Facebook and Marvell are also entering the custom chip market. The conversation also touches on the challenges and trade-offs of custom silicon, the impact on NVIDIA, and the difficulty of accurately sizing the AI market. The hosts highlight the uncertainty surrounding the future of AI outsourcing and the potential shift in the fortunes of the semiconductor and cloud industries.

Summary
In this conversation, Ben Bajarin and Jay Goldberg discuss the recent Intel webinar on the foundry business and the financial breakout for Intel Foundry Services (IFS). They analyze the financial details, including the higher costs and lower margins than expected, and the potential for improvement in the future. They also discuss the impact of the CHIPS Act and the subsidies received by TSMC for their Arizona foundries. The conversation concludes with a discussion on Intel's progress under CEO Pat Gelsinger and the opportunities and challenges they face in the data center and AI markets.

In this episode, Ben Bajarin and Jay Goldberg discuss the competition faced by Nvidia in the semiconductor industry. They explore various competitors, including AMD, Intel, and startups like Grok, Etched, and Cerebras. They also delve into the threat posed by custom silicon and the strategies of hyperscalers like Google, Microsoft, Facebook, and Amazon. Overall, the conversation highlights the challenges and opportunities for Nvidia in maintaining its position as a leader in the market. In this conversation, Jay Goldberg and Ben Bajarin discuss various themes related to Nvidia and the AI market. They explore the growing moat of Nvidia and the dominance of CUDA as a software platform. They also discuss the ease of use and stickiness of CUDA, as well as the uncertainty of Nvidia's software adoption. The conversation delves into the market potential and consumer applications of AI, as well as the slow progression of the AI market. They also touch on the risks of AI factories and inventory cycles, the potential slowdown of performance gains, and the regulatory concerns for Nvidia. The conversation concludes with a discussion on the impact of China's market and US sanctions.

Nvidia's recent keynote highlighted their dominance in the data center and their position as a platform company. They offer a full stack solution and are recognized for their sum of the parts story. While some customers may be concerned about getting locked into Nvidia's ecosystem, many appreciate the simplicity and turnkey nature of their offerings. The importance of inference and the transition to generative AI was also discussed, highlighting the complexity of scaling and the need for compute power. However, there may be room for competition in the inference market, particularly in relation to Nvidia's NVLink technology. The conversation covers various topics related to NVIDIA's keynote, including the need for more compute power, the potential of robotics and 6G, the challenges of implementing 6G, the future of software at NVIDIA, and the uncertainty of NVIDIA's software revenue. The conversation also touches on the future of AI software, the computing S-curve, and the longevity of performance gains. Overall, the conversation highlights the excitement and optimism surrounding NVIDIA's advancements in AI and computing.

In this conversation, Ben Bajarin, Jay Goldberg, and Austin Lyons discuss the semiconductor industry and the role of AI accelerators. They cover topics such as the future of Intel, the spectrum of AI accelerators, the dominance of Nvidia in training, the failure of accelerator startups, and the debate between general-purpose and specialized accelerators. They also explore the issue of GPU bloat and the need for alternative solutions in the accelerated computing space. The conversation explores the challenges of porting software to new architectures, the reluctance to switch from Nvidia, the potential for startups to disrupt the AI hardware market, Grok's approach to inference as a service, the need for purpose-built AI architectures, the struggle of custom chip design, and the sustainability of custom chip efforts.