Recent advances in AI for IT have shown the huge potential for changing the way that we do work. However, AI can’t replace everyone in the workforce. In this episode, Tom Hollingsworth is joined by Rita Younger, Josh Warcop, and Rob Coote as they look at how the hype surrounding AI must inevitably be reconciled with the reality of real people doing work.

Cyber Resiliency is a term that encompasses much more than simply protecting data. This episode features Tom Hollingsworth joined by Krista Macomber and Max Mortillaro discussing the additional features in a cyber resiliency solution and the need to understand how data needs to be safeguarded from destruction or exploitation.

Join Tech Field Day on April 10-11, 2024 for Security Field Day 11. This exciting event will feature presentations from Aryaka, Zerto, Palo Alto Networks, and Index Engines. Read on for more details about the presenting companies and schedule as well as the delegates in attendance.

The US and the UK have allied to make sure AI is developed safely. A new memorandum of understanding has laid out proposals for testing and information sharing to ensure that AI is being safely written and maintained to prevent harm to anyone using it. The ultimate goal, as stated by representatives from both governments, is harnessing the potential of AI while ensuring the risks are understood and mitigated.

In this Networking Field Day article presented by Forward Networks, Tom Hollingsworth explains how the company is using AI to enhance their NQE.

NVIDIA GTC event was the big story last week, both on the Rundown and in the tech industry generally. NVIDIA is clearly the company to beat in AI and HPC and this has the entire industry on its toes. Every company in tech is emphasizing their partnership and joint offerings with NVIDIA. But there’s a reaction from their competitors, too, with Google, Qualcomm, and Intel announcing their intent to undermine NVIDIA’s dominance.

The Tech Field Day Podcast returns! The name may change but the content and format are still the same. Read on to learn more about the history of the podcast and focus going forward with our new episodes.

This week is NVIDIA GTC, or as Futurum Group CEO Daniel Newman called it “the Woodstock of AI”. There’s been a lot of discussion about the ascendant NVIDIA and how they plan on capitalizing on a hot market.

NVIDIA unveiled Blackwell, their newest architecture. The chip was named after American mathematician David Blackwell and math is most definitely the strong suit of this product line. It has 208 billion transistors to power a second-generation transformer engine for accelerating inferencing. There is also support for fifth-generation NVLink and NVLink Switch connectivity for GPU clusters with speeds of up to 1.8 terabytes per second of bidirectional throughput, which means Blackwell could process the entire bandwidth of the Internet in just 11 units. Blackwell is being integrated into The GB100 and GB200 superchip systems which focus on Tensor core performance and can be combined into new clusters of water-cooled units of up to 72 Blackwell GPUs.

Multicloud networking is hard enough. Why not let AI help you understand the challenges and reduce some of the stress? In this article, Tom Hollingsworth looks at Prosimo Nebula, the latest solution to help operations teams deal with the complexity of the modern cloud network.

Yesterday VAST Data announced what they are calling the AI Factory, and we got a detailed look at this during a Tech Field Day Showcase. VAST is collaborating with NVIDIA, Supermicro, and Run:ai to demonstrate their ability to operationalize AI at scale. Highlighting their rapid growth and partnerships, VAST Data’s architecture supports new capabilities like VAST DataBase and VAST DataEngine. Discussions cover integrating VAST Data with NVIDIA BlueField-3 DPUs, optimizing for Supermicro hyperscale servers, and running full-stack AI operations with Run:ai. The showcase emphasized the benefits of DPUs, power savings, and strategic partnerships. It also explored the complexities of deploying AI at scale, emphasizing the integration of data processes and the role of Run:ai in managing GPU resources.