Hardware is difficult; it's painful; it's expensive. You have to get the timing, the form factor, and the user experience right, which is incredibly challenging.
Launching AI hardware too soon can lead to failure, as seen with products that aren't meeting user needs or expectations, emphasizing the need for market readiness.
The recent casualties in AI hardware highlight the risks involved, suggesting that while the potential is vast, the execution often proves challenging in practice.
Brunner emphasized the complexity of building AI hardware, requiring not just technical expertise but also understanding consumer desires and designing products that resonate with users.
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