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.
Over the past two decades, the contact center industry has promised capabilities that will significantly improve customer experience. This is important because CX is now the top brand differentiator, with many consumers switching loyalties because of a single bad experience. Though it’s true that the contact center providers have delivered new capabilities such as omnichannel communications, self-service tools and more, consumer satisfaction with contact centers remains low.
The network continues to grow in importance as a strategic business asset. A recent joint study between ZK Research and The Cube Research found that 93% of organizations felt the network was more critical to business operations than two years ago. At the same time, 80% of respondents believe the network has grown in complexity in that same time frame. The continuation of these two trends will lead to an untenable situation.
Accenture Plc Tuesday announced the launch of the Accenture AI Refinery framework, developed on Nvidia Corp.’s new AI Foundry service. The offering, designed to enable clients to build custom large language models using Llama 3.1 models, enables enterprises to refine and personalize these models with their own data and processes to create domain-specific generative AI solutions.