As robots become more capable, the most important questions may no longer be technological. This article explores how societies can balance automation, human responsibility and meaning in a future increasingly shaped by intelligent machines and autonomous systems.
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Artificial intelligence may appear weightless and digital, but robotics ultimately depends on energy, materials and physics. This article explores how batteries, compute efficiency, photonics and infrastructure could determine the future limits of autonomous machines.
Why do humans keep building machines in their own image? This article explores the cultural and psychological fascination with humanoid AI, the difference between simulation and experience, and why machine intelligence may become complementary rather than human-like.
Artificial intelligence may be advancing rapidly, but robotics is revealing a deeper reality: intelligence becomes far more complicated once it enters the physical world. The Limits of Machine Intelligence explores why machines still struggle with embodiment, energy, uncertainty and the messy complexity of reality itself.
Nvidia’s investments in photonics highlight a growing shift within AI infrastructure. The question is no longer simply how to build faster processors, but how to connect, package and integrate increasingly complex systems. The next bottleneck may emerge not inside the chip, but in everything surrounding it.
Nvidia is pouring billions into photonics as the future of artificial intelligence shifts beyond the GPU. Yet a growing debate suggests the next bottleneck may not lie in silicon photonics itself, but in the packaging, assembly and integration systems needed to connect AI infrastructure at unprecedented scale.
