Artificial Intelligence Shift
Last year I was wondering about how AI has developed. Between 2016 and 2019 there was a lot of movement. People were talking about General Artificial Intelligence and Artificial Super Intelligence where robots and AI supersedes humanity and possibly take over. In the past 3 years that has changed. It was more silent around AI and some people talked asked each other if there is another “AI-Winter” where there is far less progress.
A few days ago we started our Job search for AI Architects and developers. We knew that it may be difficult because of the complex problem we are trying to solve. In addition, it may not be perfect timing to look for top talents moving into a young company. But we were overwhelmed in many ways. With over 100 applicants within just 72 hours, we were super excited, but also worrying about the quality of applicants. When looking through the resumes and backgrounds there were two stunning discoveries that I’m just sharing here:
1) Education Level
When looking through resumes you find lists of tags or buzzwords that don’t really say anything about the quality. It looks like they touched everything and anything. We asked for videos with a short explanation of what challenges they had to solve and things they are proud of. Watching the videos we got more and more excited about the depth and the width we saw. Also the ambition and motivation this new generation of talents develop. When interviewing candidates it was simply amazing what has been done by the candidates. Some jobs were more exploratory than others and some were AI at work at its best. The talent level has skyrocketed over the past years. Being located in Switzerland — we knew we had an advantage. We saw candidates from Spain, Italy, France, Germany, UK, and a few other countries and were impressed about the educational development in particular in the southern countries. But the knowledge transfer, exchange, and practical experience students from ETH or EPFL seem to overshadow every other nation. No wonder the biggest tech companies build massive European technology centers in Zürich. In other words, the education level of the next-generation AI architects and engineers is stunningly high.
2) What the industry is doing
Another interesting insight was the background of candidates who are having AI-related positions in the industry. Without exposing any details, it becomes clear that the competition for AI experts is high and the projects the industry is working on are everything from extremely complex to amazingly simple and from breakthrough thinking to solving age-old problems. We noticed that AI seems to be everywhere. Not only in top tech companies but in almost every research organization, in trading businesses, in heavy-duty industry companies, retailers, and even in services organizations. But make no mistake, we only saw through the window in industry segments where AI experts work. We did not see the many companies that just do business as usual. But the shift towards AI-based business applications is rather apparent. Unlike typical new technologies or products that find their way into the market, AI-based solutions take far more effort. When you have a new tool that seems to can do almost anything, the question is, how should we use it. And when the leadership bench does not know what they don’t know, that would only engage when their competition is passing by.
What about the risks and potential of AI
This is a very personal opinion, not research. And my perception of AI has profoundly shifted. My first encounter with a quasi AU was a program called Eliza in the early 1980’s. I was a believer that one day we can build machines smarter than humans. Today I’m very influenced by our work in the neuroscience space. The more I understand how the brain works the more I realize that we still don’t understand the brain at all. Comparing the power of our brain with an AI today I realize that we compare a quantum computer with an abacus. Our brain does not work based on algorithms, its neural network is self-learning and self-adapting. The brain’s long-term memory is a biologic content-sensitive and autonomous network of storage. The brain is controlled by what we call purpose. There may be the day that an AI system can get close to a human brain capacity but that is when the AI system is replaced by a biological system that can work on extremely complex projects and only consumes the energy of bred with butter an apple and a bottle of water — not a fully loaded power station :).
The potential of serving the human brain like all other tools we built so far from hammer to power drills to cars, the Internet, and space ships, is enormous. Just imagine you get a tool that helps you and your brain and an entire team to think through the most complex challenges and the AI guides you through such a process so you can think rather than manage all the parameters, dependencies, and variations that could happen. Imagine that you have an AI that gives you one of a billion options at every step of the way and calculates the next best option based on your thoughts from the previous step. Managed Complexity is what we need in our highly interwoven world. Solving the dilemma of business processes transformation, without ripping the current business apart, or genuine next-generation digitization without putting the company on hold. The most massive problems on earth are of overwhelming complexity and never be understood in a linear way. Solving highly complex problems in a step-by-step model would take longer than the lifetime of engineers building it or customers benefiting from it. But even the computer software that is supposed to support us, is written in a linear manner. This is one of the next big frontiers of AI: Managed Complexity.
Hey AI enthusiasts
What shift do you see?