The oldest architecture in computing
The author reflects on the impact of AI on the workforce, arguing that adaptability is key to remaining relevant in an era of automation. The piece contrasts the energy efficiency of the human brain with the high power consumption of modern GPUs, suggesting a future where biological and silicon computing might converge.
Why it matters
It provides a philosophical perspective on the future of work and the potential evolution of computing architectures.
When I talk to customers about AI, there's one question that always seems to come up: "Will AI take my job?" My answer, "Maybe." It's an honest response that often catches people off-guard, but the answer is grounded in every technology shift since the Industrial Revolution. Some work will be automated, some job families will disappear, some industries will consolidate, some of the skills we have today will be commodities tomorrow.
If I reframe the question to "Will AI make me obsolete?", my answer is, "No. Not if you evolve." While we're seeing incredible results from AI, it's still just a tool. And as we’ve seen throughout history, staying relevant is tied to our ability to adapt, to use the tools at our disposal to build better and faster, and to solve harder problems.
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