An OpenAI social network: It's all about user attention and human-generated data

• OpenAI plans to launch a social network, according to a media report on Tuesday.
• A move like this would give OpenAI way more user attention and fresh data for AI model training.
• Elon Musk transformed X and xAI by protecting his social network's data and using it to create new AI services.

OpenAI is reportedly planning to launch its own social network. To understand why, consider what Elon Musk has done with X in recent years.

After overpaying for Twitter, one of the first things he did was shut off bot access to this social network. There were howls of protest. Most explanations focused on the assumption that Musk was gutting Twitter for some sort of evil fun.

What he was actually doing was protecting Twitter's valuable data from being pillaged by other tech companies that wanted to use this information for free to create generative AI models.

Instead, Musk's new AI startup, xAI, got exclusive access to this data. This was used to train new AI models. The result is Grok, a series of models and chatbot services that compete pretty well with OpenAI's ChatGPT — while also fueling new forms of content creation and sharing on what is now known as the X social network.

Now, Sam Altman is trying to replicate this magic. The Verge reported on Tuesday that OpenAI is developing a social media platform that could integrate ChatGPT outputs, such as image generation, with a social feed. It cited sources familiar with the matter. OpenAI didn't comment to the publication.

Bill Gross, the founder of tech incubator Idealab, told me there are two main reasons OpenAI would want its own social network. OK, well, three reasons.

First, Gross said that Altman doesn't like Musk, so why not start competing head-on with X?

OpenAI is looking for attention and data

The other two reasons are more interesting. They revolve around the two most important ingredients in today's AI-powered tech industry: attention and data.

"Altman needs to have more attention to justify OpenAI's valuation," Gross said. "He's already getting half a billion to a billion monthly unique visitors, which is incredible. He wants to get that higher so he can justify a trillion-dollar valuation."

Recall the title of Google's famous research paper that kicked off the generative AI boom: "Attention Is All You Need." To be a valuable tech giant, you need to control the online attention of billions of humans every day.

OpenAI was recently valued at about $300 billion. But Microsoft, Google, Amazon, and Meta are all in the trillion-dollar club. And these companies all have billions of regular users, Gross noted.

OpenAI needs the same reach, and a social network could do the trick, he said. "They just need more attention. So why not harvest the output of their models that users will share on a new social network, and this should attract even more users and even more attention," Gross said.

Human data is good. Labeled data is better. 

What do you do with all this user attention and related activity once you get it? A decade ago, the Big Tech business model was running targeted online ads to generate billions of dollars. Now, it's siphoning off user data to train and build powerful AI models and chatbots, then charging a subscription for access to these tools.

Like other AI companies, OpenAI has spent recent years collecting all the data from the internet and using that in clever ways to create AI models and chatbots, including ChatGPT, GPT-4, and the new 4o image-generation tool.

The appetite for more, high-quality human-generated data is insatiable. But the supply can't keep up, so AI companies often have to pay in various ways to generate new data.

What if, instead, you could just collect mountains of free human data from your very own social network?

"If users start typing words into this new OpenAI social network, the company can use that for all kinds of AI model training," Gross said.

The company would have this new source of human vocabulary, but users would also share images and videos and add commentary. This is essentially humans identifying and labeling content on a massive scale, Gross explained.

This is crucial for successful AI model development. Raw data is good, but when humans take the time to annotate and label the information, that's way more valuable.

"How else can OpenAI acquire new training data at scale going forward?" Gross said.

I asked OpenAI all about this on Tuesday and didn't get a response.