The AI Hardware Dilemma

🌈 Abstract

The article discusses the challenges faced by new AI-powered hardware devices in the market, and explores potential paths for these companies to succeed in competing with the dominance of the iPhone.

🙋 Q&A

[01] Why is this hardware's moment?

1. What are the key reasons behind the rapid launch of new AI-powered hardware devices and the investor interest in this category?

• The reasoning is that AI is seen as a technological paradigm shift, similar to the transition from personal computers to mobile computing. There is a belief that a new "Apple" could be built on the back of AI.
• AI allows using the sensors, silicon, and interfaces developed for smartphones in novel ways. It can take in large amounts of ambient data and provide unique, personalized insights and actions.
• This evolution of our relationship with devices, moving away from the distraction of smartphone screens, is seen as a net positive for humanity.

2. What are the three key components of a hardware device that the article discusses?

• Silicon: The chips running the computation for the device
• Interface: How the user interacts with the device
• Sensors: The instruments providing data to the software, such as cameras, accelerometers, GPS, etc.

[02] Why is the category so challenging?

1. What is the main reason why new AI-powered hardware devices are struggling to succeed? The iPhone is too dominant and capable, making it very difficult for new devices to compete. The iPhone has:

• Powerful sensors, silicon, and a flexible multi-touch interface that can do "a good enough job at essentially everything a consumer needs".
• Apple has spent years and billions of dollars perfecting the smartphone, giving it a supply chain and manufacturing capabilities that startups cannot match.

2. What are the key challenges faced by AI hardware companies trying to compete with the iPhone?

• They have inferior sensors, generic silicon chips, and a lack of a developer ecosystem compared to the iPhone.
• They are forced to try to innovate on the interface, but the best bet is to differentiate on the software, not the hardware.
• The AI capabilities in their products are often not ready, leading to disappointing reviews.
• It is incredibly expensive and challenging to differentiate on the basis of AI models, as open-source models are becoming increasingly capable.

[03] What happens next with AI hardware?

1. What are the three paths the article suggests for AI hardware companies to compete with the iPhone?

1. Get weird with it: Explore use cases fundamentally different from smartphones, such as healthcare or manufacturing, and experiment with unconventional interfaces.
2. Go screen-free: Develop AI-powered devices that primarily rely on voice interactions.
3. Rely on the phone: Use the smartphone's silicon and interface, with a hardware component acting as a supplemental sensor.

2. What is the overall perspective on the future of AI hardware startups?

• Venture-backed startups have a high failure rate, but this is a feature, not a bug. We should be cheering for every founder trying something new, as there is a viable path, but it requires something wholly new and different.
• Startups doing the "same-old" end up with the "same-old" result - failure. To succeed, they need to find a truly unique approach, not just try to compete directly with the iPhone.