And so I think the -- by putting NVIDIA's DGX supercomputers into the cloud with NVIDIA DGX cloud, we're going to democratize the access of this infrastructure, and with accelerated training capabilities, really make this technology and this capability quite accessible.Source

By coming up with new processors, new systems, new interconnects, new frameworks and algorithms and working with data scientists, AI researchers on new models, across that entire span, we've made large language model processing a million times faster, a million times faster.Source

Enterprises in just about every industry are activating to apply generative AI to reimagine their products and businesses.Source

The accumulation of breakthroughs from transformers, large language model and generative AI has elevated the capability and versatility of AI to a remarkable level.Source

We are at the beginning of Act One and we find ourselves already reaping tangible results, a surge in productivity that has in some cases doubled our previous benchmarks.

AI is a transformative technology and also the gateway to a new disruption in the corporate world, the one we call Hyper Digital.

However, there is hype surrounding artificial intelligence leading to inflated expectations and misconceptions.

However, I must start by saying, we are still decades behind achieving sci-fi-like artificial general intelligence. But no, AI is not just a hype. It's a transformative technology with real-world applications and rapid advancements.

To date, we're doing $250,000 a month in revenue from our GPUs doing HPC and AI compute.

So our GPUs are being used for some very, very cool large language model operations and even fine-tuning.

So to shake up things and make the AI chips aplenty and affordable is going to take a lot more money than most people think.

what's really significant is the AI world. And the world doesn't have enough AI chips to keep up with the booming demand.

AI-based predictive maintenance is the largest segment today. How will this evolve? I mean, it's clear we will be applying AI to all business processes...

I mean, it's clear we will be applying AI to all business processes, production optimization, demand forecasting, supply chain risk okay, stochastic optimization, the supply chain CRM, either.

Industry analysts estimate that organizations will invest almost $800 billion annually in AI software by 2026. According to a leading consulting firm, companies will generate $15 trillion annually in added value by 2030 from the use of these new technologies.Source

The C3 AI Platform has been refined, tested, and proven in some of the most demanding industries and production environments—electric utilities, manufacturing, oil and gas, and defense—comprising petabyte-scale datasets from thousands of vastly disparate source systems, massive volumes of high-frequency time series data from millions of devices, and hundreds of thousands of ML models.Source

We believe we're now just at the early stages of exploiting these market opportunities and we believe that these market opportunities are themselves at their early stages.

We're super excited about that. We're expecting these companies to spend billions of dollars over the next several years for training and fine-tuning generative AI models.

According to Bloomberg also, AI focused IT services are actually among the four hottest market opportunities in generative AI, all with 10 year CAGRs of 100% or more.

Bloomberg released a report stating, and I'll now quote from the report, 'generative AI market is poised to explode'.

To give you an example, I don't believe that in 10 years there will be a lot of lawyers reading documents that that is going to be obsoleted using AI.

I think AI is clearly an opportunity, and I can tell you it's not just the product things, but it's I'm not sure if I put this in my prepared remarks, but for me, I have not been as excited about any fundamental technology advances since the mid 90s web which is, I was in school at the time, that's what convinced me to study computer science.

We're seeing customers who have used AIP in one context, going to new companies, adopting it at new companies and converting quickly.

AI forces an alignment with your enterprise. And so you begin to ask really business relevant questions.

The pace of innovation around AI and LLMs presents a unique opportunity for leveraging our Apollo and FedStart infrastructure.

The speed of iteration on these models biasing to a goldilocks size of power iteration pace ratio will dominate.