Investing in ChatGPT’s AI Revolution: Where to Start

AI Basics

Artificial intelligence (AI) is now the meow of a cat. His ChatGPT bot from OpenAI is making headlines because people from all walks of life understand what this new tool can and cannot do.

For example, the stuffed narwhal in Ephrygian mode and the guitar solo crochet pattern seem to exceed ChatGPT’s capabilities so far. But people have found automated chatbots to be fun and useful, to the point that they pose a threat to a variety of well-established businesses, and above all, AI services like ChatGPT could render his web searches obsolete. I often hear that there is microsoft (MSFT 2.55%) I’m up for the challenge and have already integrated this tool into my Bing search service. alphabet of (GOOG 3.76%) (Google 3.78%) Dominant Google platform.

Of course, it turns out that Google isn’t working on something comparable to ChatGPT behind closed doors. It’s easy to see how the Google Bard service compares to ChatGPT. In that announcement, Google CEO Sundar Pichai claimed that many so-called generative AI applications are based on ideas from his 2017 research paper that Google published.

Two technicians discussing something in data center server room.

Which servers run AI systems? All of them! Image Source: Getty Images.

Microsoft and Google are going head-to-head in the burgeoning AI industry, but it’s far from the big picture. Many other tech giants have their own AI systems, including ChatGPT and several generative AI services in the style of Bard. I’m starting to feel like you can’t call yourself a tech company unless you do something interesting with AI.

Here are some tech giants with their own twist on the AI ​​business. Their names may not immediately come to mind when looking for AI investments, but maybe they should.

Elementary, Watson

i think i’ve heard International office equipment(IBM -1.24%) AI platform. Deep Blue’s chess computer was the first machine to beat a human world champion in 1997 in the classic 64 squares. Since then, Big Blue has never abandoned its pursuit of artificial intelligence.

Today, artificial intelligence is the cornerstone of IBM’s business model.

The company’s financial documents are sprinkled with references to “IBM’s hybrid cloud and AI strategy.” IBM has a long history of providing AI solutions for large enterprises under the Watson brand. In particular, management is excited about the long-term prospects of his AI large-scale language models. This is exactly the type of artificial intelligence he ChatGPT uses.

“Adopting AI can be difficult for companies because it takes time to train each model,” CEO Arvind Krishna said during the company’s fourth-quarter earnings call in January. “However, using language models at scale has enabled companies to create multiple models using the same dataset. That’s why we’re investing in languages ​​at scale, and we’ve been injecting these capabilities across our AI portfolio.”

Later in the same conference call, Krishna said AI systems are expected to add $16 trillion to the global economy by 2030. His company approaches its huge revenue stream in terms of enterprise-class business tools. Having said that, some of these tools may look a lot like ChatGPT.

“Helping retirees receive their pensions by interacting with Watson-powered AI chatbots is an enterprise use case for all of these technologies,” said Krishna.

So while IBM may not launch a consumer-facing service like ChatGPT, it’s already integrating similar tools into its enterprise offerings. It’s already the future of Big Blue.

Numerical AI Muscle from Nvidia

NVIDIA (NVDA 0.58%) Graphics processing units (GPUs) were originally designed to run 3D games and other graphical computer programs, but these processors have found new use cases in processing massive data volumes. The mathematics used to create realistic computer graphics turned out to be superior to many other kinds of intense number calculations.

Artificial Intelligence is one of the ancillary opportunities to harness the processing power of Nvidia’s GPUs. For example, the A100 GPU was made for hyperscale data analytics. This chip offers market-leading performance for training large-scale language models and other machine learning systems.

These chips were in high demand last fall as cloud-scale computing platforms expanded AI processing services.

CEO Jensen Huang said on the company’s third quarter earnings call in November: “It’s a miracle that he ships one supercomputer every three years. It’s unprecedented to have a supercomputer shipped to every cloud service his provider in one quarter.”

That was before the ChatGPT breakthrough started making waves. We can only imagine the demand for Nvidia’s latest and greatest AI processing GPUs in 2023.

IBM and Nvidia are deeply involved in the ferocious AI trend. They’ve actually been there for years, waiting for the rest of us to catch up. You can start by taking a closer look.

Alphabet executive Suzanne Frey is a member of The Motley Fool’s board of directors. Anders Bylund has held positions at Alphabet, International Business Machines, and his Nvidia. The Motley Fool has positions in and recommends Alphabet, Microsoft and NVIDIA. The Motley Fool’s U.S. headquarters has a disclosure policy.

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