By Peter Clarke

What’s at stake?
With the arrival of Generative AI in the mainstream, in platforms such as ChatGPT in Microsoft’s Bing and Bard within Google, and with billions of dollars of AI processor chip sales, AI was seen to have enjoyed a breakout year in 2023. Well, it’s going to be even bigger in 2024.

What has been a showcasing of Generative AI – as a somewhat whimsical extension of the tools at the disposal of artists and creative professionals – is going to become much more focused and about following the money saved and the profits generated.

By Bolaji Ojo

Taiwan Semiconductor Manufacturing Co. Ltd. has become too big to fail. And that is a problem for the entire electronics value chain.

It is the preferred foundry – and too often the only viable – partner for the world’s biggest fabless chipmakers; Intel Corp., the troubled MPU vendor that was once the global No. 1 semiconductor vendor by revenue and capitalization, found solace in TSMC’s arms while Nvidia, now the world’s most valuable chip vendor, credits the foundry with its survival.

That’s all good, justifiable and even admirable. But even TSMC has its Achilles heel. Except, unlike Hercules, TSMC has more than one major weakness. We have all just been too enamored of its ascent to realize the foundry may now represent the Weakest Link in the electronics supply chain. 

By Jon Peddie

Being in the right place at the right time is one way to success (assuming you’re smart enough to recognize the opportunity). Anticipating a market developing is another way, and creating a market is yet one more way to success. Nvidia has done all that and more with AI.

Before Large Language Models (LLMs), transformers, and generative AI exploded on the scene, Nvidia was already seeding what was called then “accelerated-compute,” or GPU-compute, and used its CUDA C++ like programming language as a catalyst and gateway to exploiting the power of parallel processing with a GPU. GPUs are complex devices and getting multiple threads of data to behave properly and in sync is a tricky process. CUDA took a lot of the drudgery out of that work and the payoff was so good that hundreds of developers in large organizations took advantage of it and built up a huge library of proprietary and open programs that ran on Nvidia GPUs.

By Junko Yoshida

With OpenAI CEO Sam Altman getting ousted by its board on Nov. 17, followed by the appointments of two short-lived interim CEOs and Altman getting reinstated on Nov. 21^st, it’s been a tumultuous week for Open AI employees and investors. Reporters on the technology beat have been working overtime. OpenAI’s upheaval has overshadowed other advancements in AI technology that continue to develop at breakneck speed.

While OpenAI staged its melodrama, the resignation of Cruise CEO Kyle Vogt on Nov. 19 largely escaped the media spotlight. Yet to come are media scrutiny on Cruise’s corporate governance and the company’s autonomous vehicle technology. Unfortunately, like most new wrinkles in AI, Cruise has kept its alleged advancements locked in a black box.

For those of us who are outside looking in, the CEOs at two different Silicon Valley companies seem irreconcilably disparate. But at a closer look, they are remarkably similar.