How Meta wins even if its new AI assistant fails

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At its annual developer conference this week, Meta announced a slew of new AI-related products, including Meta AI, a conversational AI assistant that will be available on WhatsApp, Messenger, and Instagram in the US. The chatbot will also be incorporated into Ray-Ban smart glasses and its virtual reality headset Quest 3.

Along with the general assistant, Meta is launching more than two dozen AI assistants that have their own distinct interests and personalities and are inspired by real people including Kendall Jenner, Naomi Osaka, and Snoop Dogg. Kendall Jenner is described as “Bille, No-BS, ride-or-die companion; Naomi Osaka is “Tamika, Anime-obsessed Sailor Senshi in training; Snoop Dogg is characterized as “Dungeon Master, Choose your own adventure with the Dungeon Master. Meta paid them for the AI characters but did not disclose details on compensation.

The idea is that users will be able to engage with these characters for specific purposes, like learning a new skill or exploring a certain interest. The company is also rolling out AI-powered stickers, which will be available on WhatsApp, Messenger, Instagram, and Facebook stories starting next month. Users will be able to generate unique stickers via text prompts on the different platforms.

Meta is just the latest company to reveal its own version of an AI assistant, entering a crowded market that includes OpenAI’s ChatGPT and Google’s Bard. One of Meta’s competitors, Character.AI, a startup that is valued at $1 billion and is in a similar business of building customized AI bots, called out the likeness on Twitter, highlighting how competitive the AI chatbot race has become. How well users will adopt any of the new and more developed AI assistants is anybody’s guess. Regardless, Meta will collect a whole host of user data that will help inform the company on how to improve the product, or scrap it and build something new.

Not all AI bets will pan out

It’s not just Meta, either. Big Tech can afford to make a lot of bets—remember Microsoft’s Clippy?—and not all of them will scale. These companies want to be seen as relevant. They want to put out generative AI tools and pick pet projects from within the company and launch them all off, said Ashwini Asokan, founder and CEO of Mad Street Den, a San Francisco-based AI company that focuses on retail automation.

What matters is the data the companies collect on users engaging with the new generative AI assistants. For example, when Google launched a new virtual try-on clothing shopping feature, powered by generative AI, earlier this year—it wasn’t necessarily just to provide users with a helpful new tool. Google’s biggest revenue source is search, and the data collected from how people use the new shopping feature will help refine Google’s search targeting. “This is a concerted effort to get data and that’s all it is,” Asokan said. Similarly, Meta can gain insights into how people interact with its new chatbots and use that data to better target users with relevant content.

When it comes to Big Tech and its projects, “there’s a clear history of lots of trial and error versus scaled applications like these that genuinely add to revenue,” Asokan said. “There is a lot of data collection, however.” Surely, something will stick.

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