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Tech titans or tech fools?

This week we’re getting a closer look at many of our tech titans that have been committing billions of dollars to developing artificial intelligence, an area that most think will have a bigger impact than the Internet. They’re promising to spend more money than we spent during the space race to build the infrastructure for their new AI products, everything from more nuclear plants for the energy required to new more powerful microprocessors to process their large language models that digests the huge data loads into their systems. Companies, including Google, Meta, Microsoft, ChaptGPT, Amazon, and Anthropic, have been pledging to invest billions, each promising to outspend the others The numbers are so big it’s hard to comprehend. The one thing they all agree on is they can never invest too much into their AI.

But a funny thing happened this past weekend. A small investment company in China demonstrated their DeepSeek AI product that doesn’t require the energy, fast microprocessors or computer power to create and run it. They claimed it was done using slower, more readily available processors, and required only a small fraction of the energy. And it seems to work as well as many of the existing products from the larger companies.

If what they said is true, and many experts believe much of it is, then DeepSeek just proved that our tech billionaires are not as smart as they want us to believe. Imagine a small company in China comes along with a product that does much the same, but is much less expensive to use, and can easily be copied because it is open sourced.

The Verge writes, “DeepSeek’s successes call into question whether billions of dollars in compute are actually required to win the AI race. The conventional wisdom has been that big tech will dominate AI simply because it has the spare cash to chase advances. Now, it looks like big tech has simply been lighting money on fire.”

It’s hard to underestimate what just happened. The brightest minds in Silicon Valley’s tech and investment communities were all following a path in lockstep that was just overtaken by a small company in China without anywhere near the resources everyone assumed was needed, including the special Nvidea chips everyone thought were required.

This may actually be a watershed moment where Silicon Valley, for the first time, has been overshadowed and embarrassed. But, from what I know of Silicon Valley, few will be embarrassed.

From OpenAI’s GPT series to Google’s Gemini, Silicon Valley’s AI efforts have been marked by one-upmanship. Yet, these projects often prioritized scale over practicality, leading to bloated models with huge operational costs.

Unlike Silicon Valley’s profit-driven models, DeepSeek prioritized accessibility, outperforming Chat GPT-4 in some tasks while consuming 40% less computational resources. By focusing on modular AI architectures, DeepSeek avoided the “bigger is better” trap. In other words they thought small and focused instead of large and all encompassing, requiring billions and billions.

As DeepSeek expands further, the ball is in Silicon Valley’s court. Will they heed the wake-up call, or cede the future to a DeepSeek approach or continue to raise billions more? Only time will tell, but one truth is undeniable: the age of unassailable tech titans is over.