AI's evolution will be shaped by conflicting bets on whether the technology's fate is to keep growing more gigantic.

Why it matters: "Big AI" and "small AI" chart two different futures for the tech that's likely to dominate business and society over the next decade.

• A big AI win could lock in the power of today's tech giants for decades to come, while a small AI victory could have more unpredictable and uncontrollable consequences.

Big AI means building ever-bigger digital brains, betting that if you just keep adding more synapse-like nodes, your model will keep getting better — and eventually, maybe, produce human-matching or -beating skills, known as artificial general intelligence (AGI).

• This is how ChatGPT and the generative AI wave began in 2022.
• OpenAI, allied with Microsoft, is big AI's standard-bearer, but you can be sure that every tech giant is also in this fantastically expensive game.

The small AI approach predicts we'll get better, faster and more efficient results by deploying a wider range and number of AI models fine-tuned for specific tasks or subject areas.

• Many small AI proponents believe that big AI will hit a wall before achieving its goal of AGI.
• Small AI efforts are also much more likely to be made available via open-source (or open-source-like) licensing, which allows for broad distribution and wider research. Big AI's price tag has already made developing its most advanced models too costly for academic institutions.
• Meta has been the highest-profile promoter of smaller and freely distributed models — but again, many of the giants are playing here, and lots of startups too.

The big picture: The tech industry is perpetually pulling in two directions.

• Its most powerful companies are always scaling up hardware and software, devices and services to do more and reach more people.
• But tech is also in the long-term game of miniaturization and personalization.
• That is how today's iPhone can fill your pocket with way more computing power than the room-sized supercomputers of yore.

The experts are divided over the big and small AI approaches.

• AI is still very much a work in progress, and the underlying science is still being discovered.

Be smart: Google's "transformers" paper, which kicked off the current era, was only published in 2017, and similarly disruptive breakthroughs could be happening right now.

• That means today's winners are always in danger of being displaced.

Yes, but: Small AI advocates argue that only the tech giants will be able to afford to develop big AI-style models and if Microsoft and Google dominate, Big Tech's power and profits will just keep growing.

• Big AI backers believe small AI opens the door to more dangerous AI outcomes, since smaller and open-source models could be easier to hijack for malicious purposes.

What we're watching: The outcome of this conflict will depend as much on regulation from Washington as on what comes out of the industry's labs.

• A looser regulatory environment would make it easier for small AI to flourish, while tighter rules and restraints from D.C. are more likely to benefit big AI, since only the largest firms will have the resources to run the bureaucratic gauntlet.

Go deeper: The push to make big AI small