Current Stages of Artificial Intelligence: Much has been said about building the infrastructure. This has clear advantages for chipmakers like Nvidia and hyperscalers like Amazon, Microsoft and Alphabet. Hyperscalers provide the massive cloud computing power needed for AI applications, and analysts predict a growing need for more data centers as they house the vast amount of computing power required for AI workloads. Is. But according to tech analysts, the next hurdle in AI infrastructure — and one to invest in — is networking. In general technical terms, networking refers to a network of devices that can transmit and share information over physical or wireless communication. However, in AI, the requirements are high due to large language models and other AI applications that require a lot of bandwidth and low latency. Morningstar analysts said in a June 2024 report, “While Nvidia and its graphics processing units get most of the headlines for creative artificial intelligence, we see networking as a critical partner in hardware that Underpins models and applications like ChatGPT.” “So far most of the attention has been on that. [graphics processing units], original AI chips. They are, of course, the most important piece of the puzzle. But networking is where we see the next bottleneck going,” Clare Pleydell-Bouverie, portfolio manager at Liontrust Asset Management, told CNBC Pro Talks in May. That's because “large-scale systems “Those coming to market, such as Nvidia's rack-scale systems, require infrastructure materials such as networking,” said Morningstar's equity analyst for technology, William D. Kerwin, and Technology Equity. Brian Colello, strategist, said he believes the need for faster networking in generative AI will translate to “strong, long-term growth for well-positioned networking vendors,” Morningstar analysts said said that translates to $34 billion in spending in 2028, up from Morningstar's estimate of $8 billion in 2023. He added that “networking firms are well-positioned to invest in generative AI A great second derivative is play.” “Most AI spending will go to GPUs, but networking is critical infrastructure to enable GPU performance.” Stock Marvel Technology Generative AI Networking Trends to Play Trend is Morningstar's top pick for the play, which the firm says is currently “attractively undervalued” and offers investors an “immediate opportunity” to tap into growing AI networking investments. Is. Other key winners in this networking trend are Arista Networks, Nvidia and Broadcom, Morningstar said. However, its analysts believe the creative AI opportunity is “overpriced” for all three stocks, as their share prices have already experienced “strong” appreciation. “However, patient investors can wait for returns, as the long-term underlying opportunity remains strong,” Morningstar said. It added that it is excited to adopt Ethernet in generative AI networks, citing a type of networking standard. According to Morningstar, Arista will be the primary beneficiary of the transition to Ethernet. The current technology commonly used is InfiniBand. “There are very few players who can really step up to deliver that infrastructure,” Pleydel-Bowry added, referring to networking infrastructure. He named Meta and Broadcom as stocks to play the trend. Broadcom is a “leader” in networking chips, he added, and will benefit as Ethernet emerges. “Ethernet networking is emerging as the de facto standard for reducing these AI workloads. And Broadcom has got the best-in-class chips that power this Ethernet network,” said Pleydell-Bouverie.
