Recently, Elizabeth Weil, founder and partner at Scribble Ventures, shared her point of view on consumer AI applications. She elaborated further on how they’ve ended up in what she referred to as an “awkward teenage middle ground.” At a panel discussion, Weil highlighted the limitations of smartphones in reimagining consumer AI products, asserting that these devices may be too restrictive for the expansive potential of AI technologies.
Weil predicts, and is hopeful about, a future where we see more personalized AI applications. Now, picture that same “always-on” tutor making their way into everyday life! Get ready for this highly customized learning experience to come to you right on your smartphone. It will be responsive to your personal preferences and foster relationship-building between you and your AI friends.
Throughout the conversation, Weil shared a healthy dose of skepticism about the potential for a few stealthy, AI-powered social network startups to save the day. She further emphasized the struggles that these platforms experience, meaning that they often are not able to connect users in effective, impactful ways.
Chi-Hua Chien, a leading light of the venture capital world, ignited the debate. He proposed strangely nerdy ways these personal AI applications could be integrated into consumers’ everyday lives. He pitched the idea of a personal AI financial adviser, a system designed to serve unique user needs. Chien expanded on how different companies are creating networks in which thousands of AI bots engage with user-created content.
“I think we’re right on the cusp of the equivalent to mobile of the 2009 -2010 era.” – Chi-Hua Chien
Chien made comparisons between the current prominent wave of AI and the initial wave of mobile applications. He pointed to how long it took for the smartphone platform to crystalize before revolutionary consumer applications like Uber came to fruition. Along the same line, he championed the notion of a “stabilization” period for AI platforms to allow long-lasting consumer products.
Despite the ongoing interest in consumer AI, Chien pointed out that most AI startups continue to generate revenue by selling to businesses rather than individual consumers. He remarked, “It’s unlikely that a device that you pick up 500 times a day but only sees 3% to 5% of what you see is going to be what ultimately introduces the use cases that take full advantage of AI’s capabilities.” Similarly, the current generation of consumer-facing devices seems not quite ready to take advantage of the truly transformative potential AI technologies can provide.
Weil and Chien’s fog of new consumer AI insights just underscore how fast applications have been changing. Both realized that proving AI first early on, particularly in video, audio, and photo, was revolutionary. They were very aware that such innovations often failed to develop into viable consumer products.
It made for a riveting exchange, as the conversations shed light on some big picture changes in today’s tech landscape. From the launch of fun new applications such as Sora and Nano Banana, to developments in Chinese open-sourced video models. These innovations are a testament to the real interest in AI being used for more practical, positive applications and the promise of future breakthroughs.