Discover how AI is transforming healthcare and business models in this exclusive interview with Victor Pereboom, Co-Founder and CTO at UbiOps. Victor shares his insights on the potential impact of AI in diagnosis and personalized medicine, and emphasizes the importance of ethical practices in AI development. Learn about the future of AI and its role in our daily lives as Pereboom predicts a "cognitive revolution" in the next two decades.
Personally I think healthcare is one of the areas where AI can have a tremendous impact. Not only in diagnosis of diseases, but also in personalized medicine.
For many businesses, the most important thing at the moment to understand is how their business models will be impacted by the current rise in powerful AI tools like ChatGPT. As AI technology advances, having access to unique datasets will become a valuable asset. AI architectures and foundation models will slowly become commodities, making access to the data to fine tune them for specific use cases increasingly valuable.
Understanding how AI tools will impact the way we live and work, and especially how it will impact our current workforce.
Also, we need to understand the energy footprint of AI systems better and keep spending time on optimization.
Furthermore, we need to see and understand that AI is a tool that we should leverage and collaborate with instead of fear.
One important thing we have to deal with is that the ones who own and control the data will determine what an AI model like GPT-3 'learns' and therefore generates. Therefore, ethical practices around the development and training of AI are key to let society as a whole benefit from this technology.
In the next 5 years, we as a society will learn to adapt to collaborating with powerful AI systems that have human-like capabilities and understand how they will impact our society.
In 10 years, we hopefully also made a lot of progress in ethics and responsible use of AI and developed practices in how to validate fairness and limits of AI systems.
20 years from now is hard to predict, we might have made progress in other types of human-machine interfaces augmented by AI. We will see some kind of "cognitive revolution" as we'll rely more and more on AI systems to help and assist us in our everyday lives.
Assuming there is a business case where AI plays a central role. AI (cloud) infrastructure and even many foundation models will become a commodity at some point.
It's therefore not necessary anymore to build all capabilities for running AI systems in-house. Most important is to focus and invest in data and domain knowledge that is unique and needed to develop or tune an AI system for your specific case.
At the moment, all the hype is centered around large language models and foundation models. Progress will be made along the lines of creating systems and workflows for making more fine-tuned models for specific tasks.
One of the main drivers of AI capabilities will be the advancements in AI specific hardware development, which has also been a major driver so far. It will also help in reducing the energy footprint of AI systems and determine where they can run.
To share our learnings about deploying AI systems and how all recent developments in the AI space are changing the way we look at developing and running AI / ML systems.
Meeting like-minded people in the AI space
It's always great to meet with the whole AI community and get updated on what's going on in the field and any new developments.