Artificial Intelligence: Teaching Machines to Think Like People

Dharmendra Modha: Brain-Inspired Chips for Better AI, What Comes After Von Neumann, and the Need for Fault Tolerance

What it takes to make silicon chips more like our own brain: An interview with IBM fellow Dharmendra Modha.

Dharmendra Modha is an IBM fellow and chief scientist for the company’s brain-inspired computing efforts. Since 2004, he’s been on a quest to create a chip that has the power, speed, and capability of the human brain. Now, he’s closer than ever to realizing this dream, and hundreds of scientists beyond IBM are testing their ideas on these chips.

Key Takeaways

• The Von Neumann architecture won’t be able to give us the massively parallel, fault-tolerant, power-efficient systems that we’ll need to create to embed intelligence into silicon. Instead, we need to rethink processor design.

• You can’t throw out the baby with the bathwater: even if you rethink underlying hardware design, you need to implement sufficiently abstracted software libraries to reduce the pain of the software developer so that he can program your chip.

• You can achieve power efficiency by changing the way you build software and hardware to become active only when an event occurs; rather than tying computation to a series of sequential operations, you make it into a massively parallel job that runs only when the underlying system changes.

Jack: Tell us about what you’re building and trying to achieve with the neuromorphic computing project.

Dharmendra: If you look at the computation ...