In the mid-20th century, the world entered the Information Age—a transformation of industrial sectors driven by information technology. This era began with the miniaturization of computers and culminated in the invention of the World Wide Web, which made information accessible to nearly everyone at their fingertips.

PayPal Vice President: The AI Revolution Is Propelling Humanity Toward the "Intelligent Age"

Today, with the rise of artificial intelligence, some tech leaders believe this era has come to an end, and a brand-new technological age has begun.

"We have moved from the Information Age to the Intelligent Age," Prakhar Mehrotra, Senior Vice President of Artificial Intelligence at PayPal, stated at an AI summit earlier this month.

Mehrotra explained that the hallmark of this "Intelligent Age" is that industries are moving away from traditional models of data storage and retrieval. Leveraging AI capabilities, data can be generated more autonomously, with the ultimate goal of automating certain aspects of the workplace.

Currently, enterprises worldwide are racing to implement AI in their workplaces—anticipating improvements in productivity and output, but with mixed results. A study by the Massachusetts Institute of Technology in August found that 95% of enterprise AI workplace initiatives failed to achieve rapid revenue growth.

"This is a journey... It must go through the stages of 'crawling, walking, running,'" Mehrotra noted. "This maxim held true a decade ago, and it still applies in this era."

Marc Hamilton, Vice President of Solution Architecture and Engineering at NVIDIA, who was interviewed alongside Mehrotra, pointed out that the key for enterprises to build AI systems in the future lies in investing in "AI factories," whether deployed on-premises or in the cloud. This is because the data required to run companies will no longer be primarily retrieved by humans or computers, but generated by AI.

"When you ask to 'create a PowerPoint slide with specific content' or 'I'm working on this coding feature—can you generate the code?'—this is not retrieving information from a database; it's calling a model to generate data," Hamilton explained.

Tokens Determine Success

Mehrotra emphasized that for enterprises to effectively build the computing power needed to generate such data, they must prioritize a new type of building block: Tokens. As the fundamental units through which text-based AI understands and processes language, Tokens are both fragments of information in training data and the output generated by models in response to instructions.

"Every company must think about their data in terms of Tokens, because that's how they can derive intelligence from it," Mehrotra stressed.

As a metric for measuring input and output, token generation volume has become a key indicator for tech enterprises. In May this year, NVIDIA announced that its chip customer Microsoft generated over 100 trillion tokens in the first quarter, a fivefold year-on-year increase. These output metrics help AI companies market themselves to investors and drive up valuations, although data suggests that the correlation between tokens and demand or profits is weaker than tech companies imply.

Both Mehrotra and Hamilton agree that many enterprises today recognize the value of tokens in enhancing AI capabilities but are still weighing how best to integrate them into their needs—every company now operates some form of AI factory that both consumes tokens and produces valuable tokens.

"I see this as a form of 'muscle building,'" Mehrotra said. "If all employees start thinking in terms of tokens, in terms of the generation process, then yes, this becomes an entirely different company."

In the mid-20th century, the world entered the Information Age—a transformation of industrial sectors driven by information technology. This era began with the miniaturization of computers and culminated in the invention of the World Wide Web, which made information accessible to nearly everyone at their fingertips.

PayPal Vice President: The AI Revolution Is Propelling Humanity Toward the "Intelligent Age"

Today, with the rise of artificial intelligence, some tech leaders believe this era has come to an end, and a brand-new technological age has begun.

"We have moved from the Information Age to the Intelligent Age," Prakhar Mehrotra, Senior Vice President of Artificial Intelligence at PayPal, stated at an AI summit earlier this month.

Mehrotra explained that the hallmark of this "Intelligent Age" is that industries are moving away from traditional models of data storage and retrieval. Leveraging AI capabilities, data can be generated more autonomously, with the ultimate goal of automating certain aspects of the workplace.

Currently, enterprises worldwide are racing to implement AI in their workplaces—anticipating improvements in productivity and output, but with mixed results. A study by the Massachusetts Institute of Technology in August found that 95% of enterprise AI workplace initiatives failed to achieve rapid revenue growth.

"This is a journey... It must go through the stages of 'crawling, walking, running,'" Mehrotra noted. "This maxim held true a decade ago, and it still applies in this era."

Marc Hamilton, Vice President of Solution Architecture and Engineering at NVIDIA, who was interviewed alongside Mehrotra, pointed out that the key for enterprises to build AI systems in the future lies in investing in "AI factories," whether deployed on-premises or in the cloud. This is because the data required to run companies will no longer be primarily retrieved by humans or computers, but generated by AI.

"When you ask to 'create a PowerPoint slide with specific content' or 'I'm working on this coding feature—can you generate the code?'—this is not retrieving information from a database; it's calling a model to generate data," Hamilton explained.

Tokens Determine Success

Mehrotra emphasized that for enterprises to effectively build the computing power needed to generate such data, they must prioritize a new type of building block: Tokens. As the fundamental units through which text-based AI understands and processes language, Tokens are both fragments of information in training data and the output generated by models in response to instructions.

"Every company must think about their data in terms of Tokens, because that's how they can derive intelligence from it," Mehrotra stressed.

As a metric for measuring input and output, token generation volume has become a key indicator for tech enterprises. In May this year, NVIDIA announced that its chip customer Microsoft generated over 100 trillion tokens in the first quarter, a fivefold year-on-year increase. These output metrics help AI companies market themselves to investors and drive up valuations, although data suggests that the correlation between tokens and demand or profits is weaker than tech companies imply.

Both Mehrotra and Hamilton agree that many enterprises today recognize the value of tokens in enhancing AI capabilities but are still weighing how best to integrate them into their needs—every company now operates some form of AI factory that both consumes tokens and produces valuable tokens.

"I see this as a form of 'muscle building,'" Mehrotra said. "If all employees start thinking in terms of tokens, in terms of the generation process, then yes, this becomes an entirely different company."