Five Companies That Came To Win This Week

For the week ending March 22, CRN takes a look at the companies that brought their ‘A’ game to the channel including Cisco Systems, Nvidia, Intel, Databricks and Nile.

The Week Ending March 22

Topping this week’s Came to Win list is Cisco Systems for completing its blockbuster $28 billion acquisition of Splunk, a move expected to strengthen Cisco’s competitive stance in cybersecurity and observability.

Also making this week’s list is Nvidia, which sought to extend its lead in the AI computing space with the launch of its new Blackwell GPU architecture. Intel is on this week’s list for a potential windfall of federal funding from the U.S. CHIPs and Science Act for semiconductor research and manufacturing.

Data lake giant Databricks is here for a savvy acquisition in the AI data management space. And next-generation networking startup Nile rounds out the list for the launch of its new AI services networking platform.

Cisco Completes $28 Billion Splunk Acquisition

Cisco Systems this week completed its $28 billion blockbuster acquisition of Splunk in a move to combine the two companies’ cybersecurity and observability strengths and create what company executives have described as a distinctive, AI-powered data platform.

The completion of the acquisition, the biggest in the IT industry so far this year, came six months after Cisco and Splunk first announced the deal on Sept. 21.

“I think at the end of the day, customers care about high performance, secure network infrastructure. That's what they care about. And we're applying AI to networking data as well,” Cisco CEO Chuck Robbins told CRN in an interview. “With the Splunk acquisition, we just improved our position in the security world, so for customers who want to run platform-based secure networking infrastructure, we're going to have the right answer.”

The two companies said in a statement that “over the next several months customers can expect a number of new product innovations across the portfolio with the integration of Splunk.” Robbins hinted at announcements to come at the RSA security conference in May and Cisco’s Live 2024 and Splunk’s .conf24 conferences in June.

Robbins said the Splunk acquisition is a key element of Cisco’s AI strategy. “It's hugely critical because we needed a large data platform. AI is going to benefit the incumbents with the data sets. In the past, sometimes new technologies would enable startups to compete more effectively, and they'll be some of that, particularly in the AI space. But from an industry perspective, if you're in healthcare, financial services or you're in manufacturing, the companies that have the biggest data sets and apply AI effectively are going to be the ones who create a competitive moat, so having Splunk and giving us that data platform for our customers is hugely important.”

Robbins also addressed the importance of the Splunk acquisition to Cisco’s huge base of channel partners.

“If partners want to be deploying solutions that have AI built into them so they're introducing that in their customer base, we have it across full stack observability,” Robbins said. “I think the partner community needs to really pay attention to the security portfolio, particularly with Splunk coming, I think that's going to move very fast and I think that the capabilities that we, with our partners, should be able to take to our customers in this world of fear and a rapidly evolving threat landscape.”

Nvidia Continues Its GenAI Offensive With Next-Gen Blackwell GPUs

Perhaps no IT company has ridden the GenAI wave more than chip designer Nvidia – just look at its nearly $2.3 trillion market cap. This week Nvidia, which held its GTC 24 event in San Jose, took some major technology steps that will maintain the company’s momentum.

Topping the list was the unveiling of the company’s next-generation Blackwell GPU architecture, the much-touted successor to the AI chip giant’s Hopper platform. Nvidia says Blackwell will enable up to 30 times greater inference performance and provide 25 times less energy consumption and lower costs for large-scale AI processing tasks.

Nvidia also debuted the first GPU designs, the B100 and B200, to use the Blackwell architecture. The new GPUs, due to arrive later this year, are expected to power cloud platforms operated by Amazon Web Services, Microsoft Azure, Google Cloud and Oracle Cloud Infrastructure, as well as servers from Cisco Systems, Dell Technologies, Hewlett Packard Enterprise, Lenovo and Supermicro.

Nvidia also used its GTC 2024 event as the launchpad for Nvidia NIM, a new software platform and set of generative AI microservices that the company said is designed to streamline the development and deployment of generative AI copilots on the Nvidia CUDA platform.

Intel Eyes Up To $8.5B In Federal Funds For Chip Making

Nvidia rival Intel was making some news of its own this week when the company said it would be eligible for up to $8.5 billion in federal funds for semiconductor design and manufacturing.

The funding from the U.S. Department of Commerce, under the U.S. CHIPS and Science Act of 2022, would apply to Intel commercial semiconductor manufacturing and R&D projects in Arizona, New Mexico, Ohio and Oregon.

This week Intel said it had signed a non-binding, preliminary memorandum of terms for direct semiconductor project funding under the U.S. CHIPS and Science Act.

Intel said it also expects a U.S. Treasury Department Investment Tax Credit (ITC) of up to 25 percent on Intel’s previously announced $100 billion in qualified investments over five years. The company should also be eligible for federal loans up to $11 billion.

Databricks Expands GenAI Capabilities With Latest Acquisition

Fast-growing data and AI platform developer Databricks this week acquired Lilac, a Boston-based startup that provides data science tools for improving the quality of data for generative AI applications and the large language models (LLMs) that power them.

The integration of Lilac's tooling into Databricks “will help customers accelerate the development of production-quality generative AI applications using their own enterprise data,” said a company blog post written by Matei Zaharia, Databricks co-founder and CTO, Naveen Rao, Databricks vice president of Generative AI, and other executives.

The acquisition is the latest by data lakehouse powerhouse Databricks to extend its capabilities within the AI space. Databricks bought generative AI startup MosaicML for $1.3 billion in June of last year, acquiring technology that developers use to build and train models using their own data.

Other Databricks acquisitions over the last year include natural language processing pioneer Einblick in February, data replication startup Arcion in October, and data governance tech provider Okera in May.

Databricks described Lilac’s software as a “scalable, user-friendly tool for data scientists to search, cluster, and analyze any kind of dataset with a focus on generative AI.” The Lilac technology can be used for a range of uses cases, Databricks said, from evaluating the output of LLMs to understanding and preparing unstructured datasets for model training. Databricks said its own MosaicML team is among Lilac’s users.

Legacy Networking Throwdown: Nile Launches AI Networking Services Platform

Nile, the next-generation networking services platform provider backed by former Cisco CEO John Chambers, is getting attention for launching a full-fledged AI services platform with AI applications aimed at automating network design, configuration and management.

The Nile AI architecture, unveiled this week, includes the Nile Services Cloud, which includes AI-based network design; the Nile Service Blocks, which automates network deployment including access point configuration; and Nile Copilot and Nile Autopilot applications for AI-based network monitoring and operations.

Nile vice president of worldwide channels Vivek Khemani said the networking services disruptor was built from the ground up with AI and machine learning and is now putting its AI capabilities front and center with the new service offerings.

“We are using AI in more creative ways to solve real problems that the industry is facing like doing site surveys in a more automated fashion and zero-touch configurations, which prevents many network outages” Khemani said.

The net result is a reduction in total cost of enterprise network ownership for customers amounting to as much as 60 percent, according to Khemani. That translates into a customer payback on the next-gen Nile networking services investment in less than three years.

In a prepared statement, Chambers, a Nile co-founder and board member, said that what Nile “understands that the rest of the industry has missed is that AI cannot be an incremental addition” to an existing architecture. “In order to truly reap the benefits of the biggest technology shift we have ever seen – bigger than the Internet and cloud combined – companies need a new architecture, one built from the ground up to fully leverage AI,” Chambers said.