From the course: Generative AI for Business Leaders

How generative AI is likely to evolve

From the course: Generative AI for Business Leaders

How generative AI is likely to evolve

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- Futurists often talk about how the difference between science fiction and non-fiction is just a matter of time. I agree. In my previous course about developing an AI-first mindset, I discussed the incredible potential of artificial general intelligence and how that future is very near. The velocity of AI has exceeded my expectation since then. We are living in an era of unprecedented innovation, and that's not about to slow down. I believe it will accelerate. As we discussed in this course, it's clear that AI will continue to play an increasingly important role in every industry. As the technology becomes more accessible, accurate, and cost effective, we can expect this trend to continue with more and more companies adopting advanced AI applications in their day-to-day operations. It will no doubt have a lasting impact on society. Instead of trying to predict the exact future, I'd like to share with you a mental framing of what changes we should expect. Here are a few dimensions to consider. Number one, investment in algorithms. Generative algorithms are continuously evolving, and there are still limitations in terms of accuracy, speed, and generalization. I expect these algorithms to evolve and become more and more sophisticated over time. Number two, reduce demand for computing power. Without GPU constraints, AI systems can handle larger data sets, perform computations faster, and deliver results in near real time. And number three, allowance of more tokens. Without token constraints, AI could be used to address the wider variety of tasks as they'll be able to better equipped to handle longer and more complex inputs. And lastly, computational resources. GPU and token constraints are some of the most common bottlenecks. But AI systems can also be limited by other computational resources, such as CPU power, memory, or storage. As these constraints are lifted over time, performance will continue to improve. This would mean more accurate predictions, greater efficiency, increased capabilities, faster iteration times, and more creative outputs. Imagine a continuously evolving better brain. These advancements will compound over time, as each cycle will pave the way for the next one. While generative AI models will be used primarily in a few use cases, at first, they will likely expand, increase prevalence, and become broadly used over the next few years, transforming industries and creating new opportunities for businesses.

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