The big US technology companies are investing heavily in artificial intelligence (AI), one of the key technologies of the 21st century. National states such as Russia and China have made AI a central goal of their innovation efforts. China is already so successful that it is outperforming American companies in some areas. And Russian President Putin even states that the one who dominates the world takes over leadership at AI.
Perhaps he is right, because the applications already implemented today give an idea that practically all areas of life and industry can be supported and fundamentally changed by AI.
But what does that mean for “normal” companies? And how could Blockchain help them to play in the concert of the greats? To answer these questions, we first need to look at what role AI plays today and how it works.
KI has long arrived in the advertising and creative industries
AI is already widespread in media, agencies, arts and entertainment.
The German start-up Deepl.com translates texts between several languages in previously unknown quality. Often, only a few follow-up translations are necessary. Significant cost savings can be achieved for multilingual agencies and editors.
KI recognizes and tags millions of pictures at breakneck speed. Which photo agency should still use people?
And who does not know the many functions that cell phones offer to optimize our photos? All this is AI in daily use. Which amateur was able to shoot portrait photos with a blurred background with almost 100% certainty? Thanks to AI, today every child can use the camera apps of the latest smartphones.
Of course, Spotify also uses AI to create personalized playlists that are popular with millions of people. How big would a team of people have to do this work? Totally priceless.
But when putting together already produced songs to playlists it does not stay. KI has long been used to support composers in their creative process or even to create music completely independently.
In these examples, until recently, we thought they were so special that they could only be done by humans. In fact, the bulk of ‘creative’ activities are likely to be AI-based. What’s next?
Is it unthinkable that an agency uses an AI to develop not three, but three hundred design lines for a new corporate design? The creative director then only has to select the ten best ones and present them to the customer. Human work is otherwise no longer necessary.
As in all industries, in advertising and media companies will also have a cost and probably creative edge, which will be involved early in integrating AI tools as core elements in their processes and products.
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AI needs Big Data
Commonly referred to as ‘KI’ today is almost always the sub-discipline of ‘machine learning’. In this form of AI, statistical models with large amounts of data are trained to make decisions.
For example, they should learn to correctly assess what can be seen on a picture. Or they should make the right decisions when driving a vehicle, even in complicated traffic situations.
Although you have to use the right algorithms and fast processors for successful machine learning (ML). The deciding factor for the quality of an AI system, however, is the amount of training data. The more data, the better the decisions. That’s why ‘big data’ is on everyone’s lips.
Enterprises that engage in AI enter into a self-reinforcing system: those with more data can better train their AI. If you have better AI, you can offer better products. If you have better products, you will get more customers. If you have more customers, you can collect more data. And the circle starts from the beginning.
That’s why major platforms such as Google, Facebook and Amazon are in an excellent position to consolidate and expand their supremacy over the next few years. Today, they already have huge amounts of data that they use to develop better and better AI-based products.
Also interesting: Blockchain replaces Google & Facebook – what does that mean for advertising?
The data is trapped in silos
How can companies now enter this cycle of data, AI, better products and more customers?
As a small to medium-sized company, you have a limited amount of data in your own data silo and virtually no chance to catch up with the big ones.
AI-based innovation could move much faster if companies could pool their data and share it.
Until recently, however, that was virtually impossible. On the one hand, the technical systems and data models are usually incompatible with each other. On the other hand, the organizational hurdles are even more serious. For how do you organize a consortium that manages data from different parties? Who pays for it? And who operates the database in which all data is finally stored? Mutual mistrust of the actors often causes such projects to fail before they even start.
Blockchain frees the data and makes it usable for AI
Blockchain technology provides solutions to both the technical and organizational issues that arise when organizations share data.
First, in blockchain networks, the data is typically isolated from the applications. That is, each user can create their own programs to work with the data, for example, to use it for AI training purposes.
In Blockchain-based open Bitcoin network, each participant has full access to all (pseudonymized) transactions. It is open to anyone to analyze the data or to program their own Bitcoin banking software. The previous centralized banking system gives banks an advantage, because only they have an overview of all transactions.
As a second major innovation, the Blockchain uses cryptocurrencies and Smart Contracts to provide useful concepts for organizing marketplaces for data.
With Smart Contracts, data between vendors and users can be traded fully automatically and settled using crypto currencies. So if you have valuable data as input for machine-learning algorithms, you can earn money even if you do not use the data yourself. A possible basic infrastructure for such data marketplaces is currently being developed in Berlin. It’s called ‘Ocean Protocol’.
And thirdly, the blockchain scene is working on cryptographic methods that allow encrypted data to be traded and used. The idea behind it: The AI algorithms ‘travel’ to the data, are trained there, pay a data usage fee and come back to their ‘owner’ better.
The records themselves stay where they are and do not need to be sent through the open internet to a possibly untrustworthy site. This allows highly sensitive data to be used, and even direct competitors can collaborate without having to disclose the exact content of the data.
The necessary procedures are quite complicated and beyond the scope of this article. If you want to go deeper, I can recommend this post at Medium.
If you want to stay competitive, you have to use AI now
Concepts such as machine learning and blockchain are referred to as ‘exponential technologies’ because their advancement is accelerated by the general advances in computer technology.
In addition, these technologies are mutually reinforcing: the Internet of Things (IoT), billions of Internet-connected sensors, vehicles and buildings, generates huge amounts of data. Blockchain now makes it possible to exchange and use this data more economically and securely. This benefits the development of artificial intelligence. And that in turn will make the devices more useful in the IoT.
The examples show that this revolution has long been part of our everyday lives. Even companies in the media and advertising industries now have to work hard to stay competitive.
Also interesting: the winners of the Blockchain era
About the author: For more than twenty years, Collin Müller has been helping companies achieve growth and efficiency through digital transformation. On Blockruption.com he blogs about Bitcoin and the Blockchain and how the great opportunities of this revolutionary technology can be meaningfully used. He is also the “founder” of the Blockchain Bar, where the blockchain is explained to the layman with a wink.
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