Cisco Systems today announced its new Wi-Fi 7 access points. During the main keynote at Cisco Live APJC in Melbourne, Tom Gillis, senior vice president and general manager of the Cisco Security Business Group, introduced the products and mentioned that Cisco’s goal with the new APs is to give its customers the ability to “solve for their connectivity, security and assurance challenges while also providing a flexible foundation to future-proof their workplaces.”
Juniper Networks Inc. is focusing on helping customers move artificial intelligence in their networks from vision to reality, and today it laid out its plans at its AI-Native NOW customer event at the New York Stock Exchange. Over the last several years, Juniper has developed strong AI networking products, and interest in AI for networking is extremely high, as engineers need help keeping up with modern networks’ complexity.
There hasn’t been a tech tailwind as strong as artificial intelligence since the early days of the internet. Many companies are vying to be the kingpin in the AI battleground, with Nvidia Corp. taking the early lead. The company has kept that position by taking a systems approach to AI. One of the key differentiators for Nvidia has been NVLink and NVSwitch, which enabled better and faster connectivity between graphic processing units to help with inferencing.
Cisco Systems Inc. provided positive numbers in its fiscal fourth-quarter results Wednesday, and there’s a story behind those numbers. The networking giant posted a modest revenue beat of $13.64 billion, $100 million more than consensus estimates. Gross margin, boosted by the acquisition of Splunk Inc., came in at a whopping 67.5%, the highest number for Cisco in 20 years. Product order growth rose 14% year over year, 6% excluding Splunk.
There has been plenty of hype and ballyhoo around artificial intelligence and networking, but much of the vendor focus has been AI for networking, where AI is used to improve network operations. The other side of the AI coin is networking for AI, where a network must be designed and provisioned to support an AI implementation. Though many businesses will likely deploy AI in the cloud, making the supporting network the problem of the hyperscaler, 58% of respondents to a recent ZK Research/theCube Research study stated they have deployed or will be deploying AI in their own private data center.