Silicon and networking insights from MWC Barcelona

It was a special episode of theCUBE Podcast for theCUBE Research industry analysts Dave Vellante and John Furrier, as they recorded live from MWC Barcelona. The show was all about networking and silicon and involved exclusive coverage on theCUBE, including conversations from Antonio Neri, Michael Dell, Charlie Kawwas and Rami Rahim, amongst others.

Covering silicon chips has been an element of coverage at theCUBE for greater than a decade. The importance of silicon has at all times been well understood, and this week saw several intriguing conversations happen.

“It was interesting to listen to Charlie Kawwas discuss CMOS, and what a game changer it was,” said Vellante (pictured, left). I remember when IBM mainframes were running ECL — emitter-coupled logic — they usually transferred into CMOS, which was much low power. They’d to pay a performance penalty, but they knew they were on a brand new curve. They dominated that business. After all, we all know what happened with the PC revolution and Intel.”

Future data centers: On-premise, edge and power

Charlie Kawwas, as a part of his interview, mentioned a pivotal a part of Broadcom’s philosophy revolving around three core principles: openness, scale and low power. That results in what has been an ongoing conversation around clustered systems, in accordance with Furrier (right).

“The info center of the long run is on-premise and edge. Smaller, faster, cheaper — Moore’s law,” he said. “It’s a cloud operation. Public cloud, on-premise and edge is distributed computing, operating as a cloud operation, meaning microservices, APIs and, now, AI, generative AI stack. OK, in order that’s going to occur.”

Power is the brand new constraint, with no motherboard anymore, Furrier added. The query is, how much power and cooling can one generate in the info center?

“Then on the device, what’s the facility consumption relative to generating that AI or application? The sport remains to be the identical; it’s just shifting distributedly,” he said. “We talked about it with Charlie. The metaphor you used, I brought in highly available versus high availability. That’s a storage concept.”

Highly available and high availability sound the identical, but they’re different. Highly available means one has data right there, able to go, while high availability means one goes and gets it, in accordance with Furrier.

“High availability means I can get data. High availability means I’ve got an application that needs data,” he explained. “It’s available, meaning it’s on a server elsewhere — you get to go fetch it. Across the network, highly available means it’s on the device itself, low latency.”

When one talks about strategic warfare, any sort of drone activity has “the tactical edge,” in accordance with Furrier. With consumers, it’s called edge.

“If you happen to need data immediately, it’s got to be on the device,” Furrier said.

Broadcom’s AI position and Tesla’s silicon situation

The talk of the tech stock world continues to be Nvidia Corp., which surged last week. On last week’s episode of theCUBE podcast, Vellante suggested Nvidia had been constructing a moat for well over a decade.

“We debated, the industry is debating about, and I feel there’s a consensus. There’s going to be all these alternatives that come out,” he said. “AMD, Intel, things like LPU, very specialized processors. I even have said, ‘Yeah, but none of them are going to have a monopoly like Nvidia.’”

But where Vellante said he could have been asleep on the wheel involves Broadcom Inc., which essentially has a monopoly-like business. The corporate has very, very high gross margins at almost 70%.

“Not likely serious about, and I missed it because I used to be pondering narrowly about Nvidia’s GPU competitors,” he said. “I feel I might put Broadcom in the combo. They’re the number two AI company by valuation. They’re an AI company because AI is all the pieces now.”

Broadcom is perfectly situated for AI, though Charlie Kawwas would say the corporate wasn’t attempting to go after the AI curve and was as an alternative just going after 10-year durable businesses, in accordance with Vellante. The opposite point Vellante said he desired to mention needed to do with low latency edge and real-time data.

“Within the moment, from a silicon standpoint, Tesla is the perfect example. It is a company that said, ‘We’re not going to make use of Mobileye,’ Intel’s chipset silicon. ‘We’re going to develop our own custom silicon using Arm,’” Vellante said. “Why did they do this? Because they desired to eliminate LiDAR.”

Whether or not eliminating LiDAR is the best thing or the safest thing is up for debate. But the corporate did lower your expenses.

“They saved roughly $2,000 a vehicle by utilizing low-cost cameras and developing their very own custom chipsets with highly customizable NPU code — that they develop themselves — in order that they could interpret what was happening and use low-cost cameras,” Vellante said.

Watch the complete podcast below to search out out why these industry pros were mentioned:

Rami Rahim, CEO of Juniper Networks
Charlie Kawwas, president at Broadcom
David Floyer, analyst emeritus at theCUBE Research
Andy Jassy, president and CEO of Amazon
Jensen Huang, founder and CEO of Nvidia
Steve Ballmer, former CEO and president of Microsoft
Frank Slootman, chairman of the board of directors at Snowflake
Sridhar Ramaswamy, CEO of Snowflake
Michael Scarpelli, CFO of Snowflake
Jim Cramer, investment pro and media personality
John Donahoe, president and CEO at Nike, former CEO at ServiceNow
Joe Tucci, chairman and co-founder at Big Growth Partners

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Photo: SiliconANGLE