Artificial intelligence (AI) is the cat's meow right now. OpenAI's ChatGPT bot is the talk of the town as people from all walks of life are figuring out what this new tool can and can't do.
Crochet patterns for stuffed narwhals and guitar solos in E phrygian mode seem to be beyond ChatGPT's abilities so far, for example. But people have found the automated chatbot fun and useful enough to pose a threat to various long-established businesses. Above all, I keep hearing that AI services like ChatGPT could make web search obsolete. Microsoft (MSFT +2.20%) is already integrating this tool into its Bing search service in an attempt to challenge Alphabet 's (GOOG 0.48%) (GOOGL 0.31%) dominant Google platform.
Of course, it turned out that Google was working on something comparable to ChatGPT behind not-so-closed doors. We'll soon see how the Google Bard service compares to ChatGPT, In that announcement, Google CEO Sundar Pichai also claimed that many so-called generative AI applications are based on ideas from a research paper Google published in 2017.
Which servers run our AI systems? All of them! Image source: Getty Images.
So Microsoft and Google are facing off in the burgeoning AI industry, but that's far from the whole picture. Many other tech titans have AI systems of their own, including a few generative AI services in the style of ChatGPT and Bard. It's starting to feel like you can't call yourself a tech company unless you're doing something interesting with AI.
Here are a couple of tech giants with unique twists on the AI business. Their names might not immediately spring to mind when you're looking for AI investments, but maybe they should.
NYSE: IBM
Key Data Points
Elementary, my dear Watson
I'm sure you've heard of International Business Machines ' (IBM +2.42%) AI platform. It Deep Blue chess computer was the first machine to beat a human world champion on the classic 64 squares, way back in 1997. From there, Big Blue never abandoned its artificial intelligence pursuits.
Nowadays, artificial intelligence is a cornerstone of IBM's business model.
The company's financial filings are peppered with references to "IBM's hybrid cloud and AI strategy." IBM has provided AI solutions for large businesses for many years under the Watson brand. In particular, management is excited about the long-term prospects of large language models for AI -- exactly the type of artificial intelligence that ChatGPT uses.
"For businesses, deploying AI can be challenging because it takes time to train each model," CEO Arvind Krishna said in January's fourth-quarter earnings call. "But by using large language models, companies can now create multiple models using the same data set. This means businesses can deploy AI with a fraction of the time and resources. That is why we are investing in large language, our foundation models for our clients, and have infused these capabilities across our AI portfolio."
Later in the same call, Krishna noted that AI systems are expected to add $16 trillion of global economic value by 2030. His company will approach that gigantic revenue stream from the perspective of enterprise-class business tools. That being said, some of those tools might look and feel a lot like ChatGPT.
"If we can help retirees get their pensions through interacting with a Watson-powered AI chatbot, that is an enterprise use case where all of these technologies come into play," Krishna said.
So IBM might not launch a consumer-oriented service like ChatGPT, but is already integrating similar tools into its enterprise offerings. It's already the future for Big Blue.
NASDAQ: NVDA
Key Data Points
Nvidia's number-crunching AI muscle
Nvidia (NVDA 0.22%) graphics processing units (GPUs) were originally designed to run 3-D games and other graphically rich computer programs, but these processors have found new use cases in the processing of large data volumes. The math used for creating realistic computer graphics turns out to be great at many other types of intense number-crunching.
Artificial intelligence is one of these auxiliary opportunities to put Nvidia's GPU horsepower to work. For instance, the A100 GPU was made for hyperscale data analytics. This chip offers market-leading performance for training large language models and other machine-learning systems.
These chips were in high demand last fall, as cloud-scale computing platforms expanded their AI processing services.
"We are all hands on deck to help the cloud service providers stand up the supercomputers," CEO Jensen Huang said in November's third-quarter earnings call. "It's a miracle to ship one supercomputer every three years. it's unheard of to ship supercomputers to every cloud service provider in a quarter."
That was before the ChatGPT breakthrough started making waves. I can only imagine the demand for Nvidia's latest and greatest AI-processing GPUs in 2023.
IBM and Nvidia are deeply engaged in the red-hot AI trend. They've been there for years, actually -- just waiting for the rest of us to catch up. So if you want to invest in the next era of AI, inspired by the ChatGPT enthusiasm, you could start by giving these tech giants a closer look.
