By Peter Clarke

What’s at stake:
The semiconductor and broader financial markets want to draw a line under a couple of years of lackluster performance, caused by political turmoil and economic recession. If successful, an IPO by Arm – one of very few in recent quarters – could signal that confidence is ready to return, helping unleash pent-up demand for deals and technology sales optimism. Wall Street and the markets could be “off to the races.”

Arm Ltd. is set to go public but the transaction is dogged by controversy – just like almost everything about the semiconductor IP vendor in recent years. A successful debut will be cheered by Wall Street, Arm’s customers and other chip enterprises. If the IPO has to be pulled or priced low to gain support, however, it could signal that caution will prevail in the markets generally. Worse, still, SoftBank Group and Arm may be perceived as yesterday’s heroes.

Read More »Is Arm’s IPO Destined to Disappoint?

By George Leopold

What’s at stake:
Cloud and telecommunications networks are groaning under the weight of ever larger data sets. Expanding optical networks are evolving to provide greater bandwidth and faster interconnects needed to move data from one facility to another. Optical chip makers and their networking equipment partners are leveraging emerging interoperability standards to help service providers super-charge their networks while avoiding vendor lock-in.

Cloud data center operators and stodgier but essential telecommunications carriers are beginning to see the light as they evolve their optical network architectures to address ever-growing bandwidth demands while extending the reach of those networks.

Read More »As Optical Networks Expand, Marvell Is In It For the Long Haul

By Junko Yoshida

What’s at stake:
Tech companies are promoting myriad claims that they have solutions to process transformer algorithms better than others. The benchmarking of transformer engines is not yet available.

The burgeoning trend toward generative AI has flipped the whole AI world on its head, or so it seems.

Large Language Models (LLMs), as seen in ChatGPT, are mostly limited to language modeling and text generation. But transformers – an overarching deep-learning architecture that underlines LLMs and other generative AI applications – offers a model useful in data streams ranging from text, speech and image to 3D and video, or any sensory data. 

Read More »Transformers in Auto: Who Does it, Who Needs it?

By Junko Yoshida

What’s at stake:
The conventional narrative is that artificial intelligence (AI) can transform safety, as a tool that can be used to detect anomalies and identify workplace hazards. Still unknown, however, is the functional safety of AI hardware and software. A group of engineers who delievered ISO 26262 is taking on the challenge.

AI is already being applied to safety-critical applications, such as autonomous vehicles or highly automated advanced driver assistance systems. So, how can designers of AI-driven E/E systems and developers of AI components validate their new designs as functionally safe – before AI-driven cars hit the road for millions, or billions, of test miles?

Read More »Is ISO’s New AI Functional Safety Standard Road-Ready? Hardly.

By Junko Yoshida

What’s at stake:
Except for Tesla, no automaker has contrived to roll out an automotive processor of its own. This vacuum, however, has not curbed car OEMs’ deep-seated desire to design chips for their vehicles. Can chip vendors still provide automakers what they want but aren’t doing for themselves, and at what cost? Or, are automakers’ wonderland agenda sending semiconductor companies down the rabbit hole?

Carmakers’ appetite to develop proprietary processors waned as OEMs got occupied in dealing with chip shortages. Their dream of automated consumer vehicles before 2027 is a memory.

Now, replacing the autonomous vehicles, the momentum among carmakers is an industry-wide push for software-defined vehicles. Automotive OEMs are now beginning to think that if the vehicle’s real value will be in software under the new era, they shouldn’t be in the business of just layering their software on top of hardware selected by tier ones.

Read More »Automakers’ Chip Agenda: RISC-V, AI, Chiplets

By Junko Yoshida

What’s at stake:
Except for a few recent funding announcements, all’s quiet on the Western front on AI. What must change to alter a market where Nvidia continues to be the sole winner? 

The time has come to reflect on the many AI hardware startups that have popped up in the last several years. Advancements in AI sent investors into a fever pitch, elevating AI processor startups into “unicorn” stardom.

As Keven Krewell, principal analyst at Tirias Research, recalls, “Intel really kicked off the explosion of AI startups when it bought Nervana in 2016. And it followed up by buying Habana.” He added, “I would argue that AMD’s acquisition of Xilinx was in large part because of Xilinx’s work in developing AI cores.”

Fast forward to 2023. 

More than a handful of notable AI hardware startups are gone. Layoffs abound. During this predictable process of elimination, did industry analysts anticipate so little churn among AI processor companies? Why no consolidations, mergers or acquisitions in recent years?

Read More »AI Hardware Startups Spoil for a Brawl

By Bolaji Ojo

OEM orders for semiconductors are still rising albeit at a slower pace. Inventories are increasing but some products remain on allocation although nobody quite knows which.

Meanwhile, inventories are creeping up at chipmakers even as they continue to ramp up production. The specter of double ordering is haunting suppliers but analysts say it is almost impossible to distinguish between actual orders and duplicates.

Inconsistencies like these hark back to a past the semiconductor industry was supposed to have jettisoned.

Read More »Automakers & Chipmakers March Towards a New Clash of Interests