Barry Hutt co-founder Viviota
Attending the recent NVIDIA show was nothing short of a technological spectacle. The event was packed, with thousands of attendees flocking to keynotes, floor demos, and sessions. NVIDIA’s vision of becoming a trillion-dollar company felt within reach as it outpaced competitors like Intel, AMD, and other silicon manufacturers. Their commitment to Artificial Intelligence (AI) and Machine Learning (ML) was evident throughout the venue. The show even earned the nickname “Woodstock of AI” from Jim Cramer of Mad Money, who hosted a segment and interviewed NVIDIA’s rockstar CEO, Jensen Huang.
Personal Encounters
My brief encounter with NVIDIA CEO Jensen Huang was memorable. Surrounded by crowds akin to a rockstar, his reception was reminiscent of the adoration Steve Jobs once commanded. This fanfare reflects the excitement and momentum NVIDIA has cultivated within the AI and ML ecosystem.
General Impressions
The sheer effort and focus on AI and ML from various industries was breathtaking. From deep GPU utilization to developing AI agents, the NVIDIA show felt reminiscent of the early internet boom of the late 1990s and early 2000s. However, this AI-driven wave appears more sustainable and deeply rooted.
A central theme of the show was data quality. The lack of efficient data preparation, metadata enhancement, and calculation tools was often discussed. This gap aligns perfectly with the capabilities we have built into our Time-to-Insight platform, particularly in engineering data.
Vendor Interactions & Key Takeaways
Throughout the event, I engaged with various vendors and companies, both large and small. Here are some notable highlights:
- Databricks: Their booth showcased impressive AI capabilities, particularly in translating metadata, generating summary reports, and crafting queries from that metadata. While the demo didn’t present groundbreaking features, it was a polished display of well-developed tools. Conversations with their partner management team underscored potential collaboration opportunities where our Viviota technology could integrate with the Databricks ecosystem to create value.
1. HPE (Hewlett-Packard Enterprise): 
HPE's high-performance computing (HPC) systems, featuring water-cooled NVIDIA GPUs, were astonishing. These systems handle vast amounts of data and transactions at a scale reminiscent of Cray systems. The product manager I spoke with expressed significant interest in our use cases, which differ from their standard applications. Follow-up discussions are planned.
2. Dell: I attended a presentation detailing their data architecture, which covers database connections, data ingestion, metadata creation, and output generation. They expressed enthusiasm about potential collaborations with our Time-to-Insight platform3
3. Startups & Emerging Tech: A dedicated aisle showcased startups focused on various use cases, including computer-aided design (CAD), computer-aided engineering (CAE), factory automation, and digital twins. While intriguing, none of these companies seemed to be directly competing with our approach.
5. VAST Data is a rapidly growing storage virtualization company partnered with HPE. Its solutions focus on computing and storage systems, and it has boasted tremendous growth and investment within a few years.
6. Crusoe: An AI SaaS company specializing in setting up AI instances, offering potential avenues for future collaboration.
Sessions Worth Noting
- GM & NVIDIA Collaboration: A highlight of the event was a session led by GM and NVIDIA executives, David Richardson and Norm Marks during which they discussed their partnership on AI, autonomous driving, simulation, and digital twins. While the vision is grand, I suspect the practical implementation may not fully align with the polished presentation. It’s worth noting David’s hesitation to predict when the world will achieve full autonomy.
2. Accenture’s Data Governance Panel was the most insightful session of the show. This panel featured representatives from Bank of America, Jabil (a prominent EMS company), and Amgen (a bioscience leader). Their discussions of data analytics, ML, and AI demonstrated varied approaches to these technologies.
The NVIDIA show was a whirlwind of technology, innovation, and AI-focused ambition. While many companies are making strides, there remains a considerable gap in the market for effective data preparation and metadata creation tools. The event provided me with invaluable insights and promising leads to pursue, giving me a clearer picture of where the AI and ML landscape is headed.