About this channel
NVIDIA presents AI through the infrastructure, products and companies involved in building and running it. The channel's topics reach from enterprise adoption and private data to networking…
NVIDIA presents AI through the infrastructure, products and companies involved in building and running it. The channel's topics reach from enterprise adoption and private data to networking, computing systems and the idea of an AI factory. Product and ecosystem coverage are central to the perspective, with technical demonstrations appearing alongside executive conversations, startup features and event material. It is a useful view into the questions NVIDIA chooses to emphasise around AI deployment.
One example examines using DOCA skills to build RDMA on BlueField-3 with fewer commands and less code, putting a specific development workflow in focus. At a broader level, AI Factory Insider considers the relationship between vertical integration and horizontal openness. Videos tracing the development of DGX systems connect an individual computing system with the larger infrastructure surrounding it. A separate discussion asks how businesses can use AI while keeping their data private, bringing organisational requirements into the technical picture.
The startup strand includes Simplismart's work on no-code enterprise AI and a feature on Probabl, identified in the title with the creators of Scikit-Learn. Jensen Huang appears in interview and summit material, while shorter items add glimpses of events and hardware reaching developers. Infrastructure teams, enterprise technology decision-makers and developers working around NVIDIA systems can use the channel to explore both specific tools and the broader product context. Viewers interested in AI beyond the model itself will find topics about the computing, networking and business arrangements that support it. The mix makes it possible to move from a narrowly defined technical task to the company's wider account of where AI infrastructure is heading.
Latest episode
Vertically Integrated, Horizontally Open | AI Factory Insider Ep 5
How can an AI platform be optimized from hardware to software while staying open to developers and partners at every layer?
In Episode 5 of AI Factory Insider, host Kaushik Shirhatti (VP, AI…
How can an AI platform be optimized from hardware to software while staying open to developers and partners at every layer?
In Episode 5 of AI Factory Insider, host Kaushik Shirhatti (VP, AI Factory, NVIDIA) is joined by Pradeep Gupta (VP, Industries Solutions Architecture, NVIDIA) and Stephen Jones (CUDA Architect, NVIDIA) to discuss how vertical integration works with an open ecosystem, how CUDA-X libraries serve specialized industry workloads, and how agent skills are changing software development.
What we cover:
0:00 — Introduction
1:08 — Meet Pradeep Gupta and Stephen Jones
1:28 — What does "vertically integrated, horizontally open" mean?
3:25 — One platform, many industries
4:30 — AI across healthcare, retail, and finance
6:35 — What stays common across industries
8:55 — CUDA: the link from apps to GPUs
10:29 — CUDA's early days and the first debugger
13:24 — The spreadsheet behind CUDA profiling
14:24 — CUDA vs. CUDA-X libraries
16:08 — Identifying the right CUDA-X library for your use case
17:42 — How is CUDA open if it runs on NVIDIA GPUs?
21:33 — CUDA-X in finance, biopharma, and smart cities
22:50 — How CUDA libraries build on each other
25:18 — CUDA and GPU hardware co-design
28:05 — Reuse the core; specialize when needed
29:15 — Agents need tools and skills
31:01 — CUDA-X libraries as agent skills
32:59 — How AI agents change the way developer work
37:15 — Wrap-up
Resources:
CUDA: New Features and Beyond 👉 https://nvda.ws/4hBmS5R
NVIDIA Enterprise AI Factory Design Guide White Paper 👉 https://nvda.ws/4xV5L5d
CUDA-X Libraries 👉 https://nvda.ws/4hqwP60
CUDA Toolkit 👉 https://nvda.ws/4yWzz22
NVIDIA AI Factories 👉 https://nvda.ws/4z8mdA5
YouTube Shorts
Deep Learning
Healthcare @ GTC
NVIDIA GeForce
NVIDIA Tegra
uploads
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