Tech investors are eager to hear how much industry leaders are bolstering profitability now that they’re in cost-cutting mode.
But there’s one area where they also want to see hefty investments: artificial intelligence.
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Alphabet, Microsoft, Amazon and Meta all reported quarterly results this week, updating Wall Street on their efforts to improve efficiency as economic concerns mount. When it comes to AI and the latest boom in so-called large language models (LLMs) that power products like ChatGPT, the mega-cap tech companies can’t afford to get left behind.
Generative AI programs use increasing amounts of data and processing power to produce outputs that seem like they were made by a human — a block of text, a snippet of code, or a computer-generated image. They require specialized supercomputers that aren’t cheap.
On their earnings calls this week, tech CEOs talked at length about the potential for AI, whether they’re building their own models or rapidly integrating it into products. The common theme was their emphasis on the large sums of money they’ll be spending to build and run these applications.
Here’s what executives from Alphabet, Microsoft, Amazon and Meta told analysts:
Alphabet
Sundar Pichai, Alphabet’s CEO, is under intense pressure to deliver AI products due to the perceived threat that the company’s core Google search engine faces from the sophisticated chatbots hitting the market. The company recently declared an internal “code red.”
Pichai said on Tuesday’s earnings call that the company was making “good progress” towards its AI goals.
“We’ll continue to incorporate generative AI advances to make search better in a thoughtful and deliberate way,” Pichai said.
He said Google is using AI to improve the conversion rate of ads and reduce the amount of “toxic text” that goes into AI models. The company is also combining two primary AI teams, Brain and DeepMind.
Pichai said that in addition to using its own homegrown chips to power its models, it’s using processors from Nvidia, which makes the vast majority of graphics chips used to train and deploy cutting-edge AI.
Microsoft
Microsoft is using OpenAI’s GPT technology in its Bing search engine, Office, and Teams teleconferencing system.
CEO Satya Nadella says that AI will eventually drive revenue growth and is already sparking increased uptake in the company’s apps. Bing, for example, has seen downloads quadruple since Microsoft added a chatbot, he said. Microsoft has generated over 200 million images through its Bing integration.
Nadella warned that a significant amount of capital will be required to build out the massive datacenters needed to run AI applications.
“We will continue to invest in our cloud infrastructure, particularly AI-related spend, as we scale to the growing demand driven by customer transformation,” Nadella said. “And we expect the resulting revenue to grow over time.”
Amazon
Amazon CEO Andy Jassy gave an unusually lengthy response on Thursday to an analyst’s question about the company’s generative AI plans.
Jassy said Amazon is building its own LLMs, and designing data-center chips for machine learning, emphasizing that the market is massive.
“These large language models, generative AI capability, has been around for a while. But frankly, the models were not that compelling until about six to nine months ago,” Jassy said. “They have gotten so much bigger and so much better so much more quickly that it really presents a remarkable opportunity to transform virtually every customer experience that exists.”
Jassy also said Amazon’s size would allow it to become one of a handful of companies building LLMs, which can take hundreds of computers running for weeks, overseen by expensive machine learning engineers.
“There will be a small number of companies that want to invest that time and money and we will be one of them at Amazon,” Jassy said.
Unlike Microsoft and Google, Amazon’s focus is selling access to the technology through its Amazon Web Services division. However, Jassy said Amazon will work on some applications, such as programs to help engineers write code.
“Every single one of our businesses inside of Amazon are building on top of large language models to reinvent our customer experience,” Jassy said. That includes voice assistant Alexa, he said.
Meta
Meta CEO Mark Zuckerberg tried to dispel the notion that his company is no longer focused on the metaverse after turning his attention in that direction in late 2021.
But he wanted investors to know that Meta can invest in metaverse technologies while simultaneously putting tons of resources into AI, which he called a “key theme” for his company.
Zuckerberg said that while the company has used machine learning to deliver recommendations and power products like Facebook’s news feed or ad systems, a new main area of focus is generative foundation models.
“It’s been a pretty amazing year of progress on this front, and the work happening now is going to impact every single one of our apps and services,” Zuckerberg said.
He said the company would work on a variety of products using the technology, including chat experiences in WhatsApp and Facebook Messenger, tools for making images for posts on Facebook and Instagram, and eventually programs that could spit out entire videos from short descriptions.
A concept he’s particularly excited about is “AI agents,” which often refer to AI programs that can carry out goals.
“There’s an opportunity to introduce AI agents to billions of people in ways that will be useful and meaningful,” Zuckerberg said. One possibility for an AI agent would be to handle customer service for businesses, Meta has said.
Zuckerberg discussed the company’s big investments to build out its datacenters for AI applications. He said the technology was the “main driver” of Meta’s growth in capital expenditures over the past few years.
“At this point we are no longer behind in building out our AI infrastructure,” Zuckerberg said.
That doesn’t mean Meta is done buying graphics processors. Zuckerberg said the company would need to “continue investing,” but would do so after it launches its generative AI products and gets a better grasp on the resources required.
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