Schön, dass wir wieder mit dabei sind bei einer weiteren Folge von TJs Technology Tuesday. In dieser Episode einmal einen Vortragsausschnitt einer Kino, die ich vor kurzem gehalten habe, zum Thema künstliche Intelligenz. Ich wünsche Ihnen viel Spaß dabei.
Beginn der Keynote
McKinsey is publishing a state of AI every year. And these are the latest results where they are comparing top performing companies and less performing growing companies in terms of use AI. Both are adding up to 100%. And so when they look, the first thing you’re always doing is cutting costs. That’s not the focus of the top performers using AI. The focus is more on your business models. And talking about business models, I hear a lot that marketing agencies are dying. In the US, people are not waiting to die, so they are just rethinking their business model. And there’s a growing number of solo entrepreneurs coming out of the agency world. What are they offering? Their core offering is to say, you pay me $10,000 a month, and for $10,000 a month, you get every agency job within a business day. You need new business cards, you need new paperwork, you need a presentation, you need a poster, everything you need, you get it within one business day. AI generated, but of course, curated, communicated with a pro. Because give me the best artificial intelligence tools in terms of designing something, it would be a completely different result.
And these solopreneurs are working half a day and making a revenue of 1. 5 million a year. I don’t know how your business is structured. I still have some potential to reach that number. And yesterday in the bus, we had a nice discussion to say where I talked to one of you and we were talking about the Big Four to say they are competition, yes, What’s their big advantage? They have the resources and the processes and the standardization that you can even set an to the system, and they can do everything because they have all the systems in place. With artificial intelligence, you have all that also. You have the resources that only the big four had in the past. You have that with artificial intelligence in every of your companies. The challenge is not to wait until the Big Four have decided to do that, too. One of the main reasons why we are slow in adopting the technology is always that we say, Okay, I’m asking ChatGPT, and the results when I’m getting them are some like when we ask our colleague after the fifth beer to say, How is that with IDV as one?
How does that work? Probably even without any beer, you shouldn’t ask me on IDV, for example, because I have no clue on that. That’s a good idea to have an understanding to say, Which tool and which system are you’re using. Coming back to Amazon, the ugliest web page on the planet. So a nice thing where you can see how artificial intelligence is used because they use it since years. For example, when you order a TV, what you always get, you get a recommendation for a rack to mount it. Who has heard about the concept of temperature in the context of AI, artificial intelligence? So now you get a special super techy tip for the next cocktail party. Because very few people know the concept of temperature. You can explain it very easily with Amazon. When you order a TV and you get just one recommendation for rack, this is temperature zero. That gives you that one most probable answer. Temperature one would give you a cup or to put it out, a blanket for the sofa, a packet of crisps, for example, and probably even a pair of A pair of sneakers? We say, A pair of sneakers?
What does have a pair of sneakers to do with the TV? Probably you don’t dress up in sneakers when you watch TV, but probably you ordered at the same time because you said, okay, I need a new pair of sneakers. When I’m ordering at Amazon, okay, I don’t have to pick up things twice, so I order together. This is the reason why sometimes you’re getting some recommendations where you say, that doesn’t fit. Hopefully, that gives you an idea that it’s unrealistic to expect a perfect result of artificial intelligence because it’s statistics on steroids. Also important to understand the difference between automation and calculation and algorithms and artificial intelligence. A nice way to understand the difference is looking into a bad day that Garry Kaspara had in 1997 when he lost against Big Blue. A lot of people say this is artificial intelligence. No, that was pure computing power. Now you can play that on your watch. And talking about watches, probably some of you have realized it. I’m the crazy guy with the analog watch and the analog ring and the digital watch and the digital ring. So I love both worlds. And when I have a look at these smartwatches, the computing power you have in these smartwatches, it extends the computing power that the Americans had when they flew to the moon in 1969 by millions of factors.
What are we doing? The same what we did with this watch since we carried the first one, just reading the time. Most of us are using technology like driving a Porsche 911 with 60 miles an hour on the slow lane on the Autobahn. My mission is to gear that up. What is artificial intelligence now? Looking into Lisa Dole, who lost against AlphaGo in 2015. Alphago is a very simple game in terms of the rules, but it’s very complex in terms of all the probabilities. And even today, it’s not possible. You won’t have any Go apps where you can really play against PCs nowadays. That will change with quantum computing, but nowadays, it’s still not possible. What did they do? They just put in the rules of going to the system and let the system play 3 million times against each other. That was the idea. And the interesting thing is there was one move of the system where every go expert said, this is a complete stupid move of the system. Every expert said, Now, Lise Doell is going to win. Two moves later, he lost. Lise Doell was very contemplated and looked at that move and said, Respect.
This is a move no human being would have made. When you watched two keynotes of Sam Altman, he said, the next generation of artificial intelligence, now we are in the transformer ones that are combining no knowledge. We say the next step, which is already in the laboratories, are inventors. And inventor systems will be able to solve technological problems and human problems that humans were not able to solve yet. This is the bright side of technology. Looking into AI, most of people say, Yeah, it’s ChatGPT’s AI. This is like if you would have a toolbox with just a hammer. And of course, you can use a hammer to drill a screw into a wall, but it’s probably not the most elegant solution. It’s probably a good idea to have a well-assorted toolbox. Probably it’s also not a good idea to have an overwhelming toolbox where you don’t find anything. Probably it’s a good idea to have a curated set of toolbox.
Ende der Keynote
Fazit
Inspirierenden, einen bewegenden Redner suchen, der ihre Mannschaft, der ihre Vertriebspartner, ihre Servicepartner begeistert, inspiriert und vor allen Dingen in die Umsetzung bringt. Dann freue ich mich sehr, wenn Sie mich ansprechen. Dann spreche ich gerne auch als Kino-Speaker, als Workshop-Verantwortlicher oder in anderen Formaten für und mit Ihren Kunden.
Mit Ihren Kunden spreche ich natürlich dann auch nicht nur die eine Stunde, wo ich einen Vortrag halte, sondern ich bin bei der Veranstaltung schon den ganzen Tag mit dabei, sodass Ihre Teilnehmenden hinterher sagen: „Wow, das war aber ein toller Service. Genau das ist meine Idee, seit ich 1988 bei Nixdorff begonnen habe, das Thema Digitalisierung, Vertrieb und Produktivität zusammenzubekommen, aber das Ganze auch mit Spaß, mit Motivation, sodass neue Technik keine Angst erzeugt, sondern dass die Teilnehmenden Lust auf Digitalisierung, Lust auf KI haben. Ich freue mich sehr, wenn ich auch Ihre nächste Veranstaltung dementsprechend bereichern kann.
Ihr Thorsten Jekel.
