Tag: Artificial intelligence

Artificial intelligence and blockchain in tandem for success

Artificial intelligence (Of) and Blockchain intelligently combined, is a milestone towards the technological future.

Both technologies are becoming increasingly self-sufficient. Whether consciously or unconsciously, technology has arrived in our lives. We often don't notice this. Combinations are still the exception. Unfortunately!

The AI ​​in particular is making a quiet triumphal march in our homes, our everyday life is supported by artificial intelligence. Without this technical support, electricity providers would sleep much more restlessly – Power outages would be the order of the day. Conducting the enormous amounts of electricity over the European routes and their distribution cannot be handled without intelligent systems.
And, even if many people don't like it, the systems work autonomously to a certain extent. Everything has to happen at lightning speed. Otherwise the lights will literally go out very quickly.

Digital payment providers would also be lost without artificial intelligence and its techniques. Speed ​​and comfort must be reconciled. AI early fraud detection promises new opportunities through more expedient risk management in real time.

Blockchain provides security

Blockchain is on everyone's lips right now because of Bitcoin. Digital currencies are only a tiny area of ​​application for this decentralized and multiple existence of certain data sets. This makes the system secure!
It is currently impossible to change all data sets at once – to manipulate.

“Until now” is deliberately chosen. Even if the disciples of blockchain technology don't like to hear it or simply don't know it (want), the time will come, where quantum computing in the wrong hands will push technology to its limits. I will write a separate article on this topic in the near future.

With the best protection, if the swarm of blockchain servers is large and their locations are decentralized. In simple words: The more similar data sets there are, the harder it is, manipulate them all at once.

What has to happen?

Artificial intelligence has a problem! To work self-sufficiently, very large amounts of learning data are necessary. These are often recorded in a rudimentary manner, used and then flows into a system with real data. Here's the crux of the matter: Learning data can be easily manipulated!

Artificial intelligence and advertising have huge untapped potential

Even if it is suggested to you, that advertising is up to date, don't believe it! The potential is almost inexhaustible.
You can also compare it to a gold mine, where finished gold bars are lying around waiting to finally be lifted.

Artificial intelligence and advertising are made for each other! All the more regrettable, that until today there are almost no serious applications to be found, which serve to promote digital sales.

Despite all the technical innovations, advertisements are still mostly advertised with rigid posters, as they have been for decades. And, admitted, many a billboard has given way to a flat screen or a large screen, but the watering can principle has remained: Advertising for everyone – no trace of individualization. Injury!

Maybe you already have an idea of ​​what I'm getting at: persons- and situational advertising.
Almost every advertiser and every agency now has a chill running down their spines: Privacy Policy – it does not work!

Incorrect, totally wrong. In simple words, what you see, Artificial intelligence can also see it! As you decide, who you speak to or give a flyer to, Artificial intelligence can also decide, which advertisement should be shown on the flat screen in this and that second.

Sounds simple, it is. Already in the year 2019 an advertising medium was developed, which is equipped with a camera, has a mini PC integrated and can offer advertising to people, which the operator has defined in advance.


Example please? People with very bad sunburns walk along the beach promenade, What better way to do it than with a sidewalk display / Customer stoppers in front of the pharmacy to advertise sunscreen and after sun lotion. Completely automatic.

A dirty car on the road can also be recognized without any problems. On a big screen – near the next traffic light – a car wash “around the corner” to recommend, will be well received.
Which of course you are not allowed to do, is to show the dirty car on the big screen and thus annoy the driver. A really stupid idea, Because displaying it is against the law in many countries and can also have a huge backfire in terms of a marketing campaign.

These are two everyday examples, which can, however, be refined as desired, including company-specific applications.

Artificial intelligence in times of Corona

Artificial intelligence (Of) has long since arrived in our everyday life. Independently of the corona crisis and suggestive financial crisis, independently operating programs are normal.

Perhaps some of the processes are yours, which are related to artificial intelligence, not consciously or already so involved in everyday life, that you no longer attach any importance to them. You don't need either!

Anyway, that's what I'm saying, that artificial intelligence is so firmly anchored there, despite all the financial problems in industry and the service sector, that AI can no longer be dismantled.

Lots of people are coming right now – whether entrepreneurs or employees – up to me and ask, whether artificial intelligence still has a future.
The question is legitimate. After all, the artificial intelligence hype began in the year 2018-19 still (fast) Full employment and development budgets seemed infinite.

The foundations of modern developments can be explained by finance- and do not stop economic crises. It has been like that for the past few centuries, that great inventions emerged from major crises.

The crisis will give AI a new boost

The focus will change: the further Development of self-driving cars will surely take a back seat. More and more automobile manufacturers will enter into collaborations (must) and thus knowledge in the field of autonomous driving is also shared.

Of course, there will also be further groundbreaking advances in mobility, but not at the same pace as before the crisis year 2020.

Development costs are reduced across all industries. Naturally, the focus will initially be on returns – research does not have a good hand here.

As things stand at the moment, only a few companies will have money left over for developments, that do not bring huge amounts of money into the till in a very short time.

Rather, artificial intelligence sees a development spurt there, where technology helps and supports people in everyday life. Cheap labor is increasingly being replaced by machines. Intelligent machines will continue to change people's everyday lives.

Industrial robots are becoming even smarter and smartphones are even more merging virtual life with our reality. Direct applications are optimized, but completely new developments take longer.

Ultimately, artificial intelligence cannot be stopped! The current economic- and the financial crisis will give AI a new boost. No longer at the speed of sound, but in the steps, which increase the acceptance of artificial intelligence among citizens.

Artificial intelligence or artificial stupidity?

ob, ob (Of) ob.

ob, ob, ob.

ob. ob. ob, ob. ob!

ob, However, the software continues to develop with your own experiences. Comparable to a child: Nature and parents give the child knowledge, but the young person learns and draws conclusions himself.

AI decisions can only be interpreted

Transfer this to AI, is still one of the biggest challenges. Understanding and interpreting computer decisions, why he acted like that in the situation, is a separate branch of AI research. Development is certainly still in its early stages here.

The first legal cases arise in connection with artificial intelligence, then it will be more exciting than ever. Judges will ask, why the computer acted like that. Based on my current knowledge, you can only present answers with assumptions and probabilities. A challenge for every democratic legal system, where it just “and” oder “no” gives as an answer.

If we want to better understand these new technologies and their effects, then we should first look at the learning data. The foundation for interpretations or actions of artificial intelligence is usually hidden there.

There are cases, where AI is accused of racism. This is complete nonsense. Either the source code is written accordingly or the basic data was insufficient. Are dark-skinned people viewed as monkeys?, It's mostly because of that, that predominantly light-skinned people served as models during the learning phase. Zoo visits were also involved and monkeys were marked as such, then the result is not surprising.

As a conclusion one can say:: Artificial intelligence is only as smart as the data provided. The more learning data and experiences a system has, the more accurate the decisions become.

AI is always faced with challenges when it comes to evaluating images

What seems logical and clear to people in pictures, can be a huge challenge for artificial intelligence.

Image noise and knowledge logic require new solutions

Basically, two subject areas pose more or less major problems for artificial intelligence in image evaluation. This is the aleatory (random noise on objects) and the epistemic model.

Epistemic logic is one example, when Artificial Intelligence cannot distinguish a street from the sidewalk next to it, because both elements are made of asphalt.

In 3D recordings, this can perhaps be solved through the third dimension. However, such image sources are always available? Probably only in very few cases.

Live evaluation in autonomous driving is still not possible due to a lack of computing power and a certain level of uncertainty, the 3. dimension in this fineness.

In general, this problem can be solved in the learning phase, if you provide the system with further data and the algorithm approaches it with probabilities, that in our example there is a sidewalk next to the road.

When it ultimately comes down to human safety, objects and machines, Probabilities alone are a poor solution.
In such a sensitive environment, further safeguards must be installed. Whether it's radar electronics or distance sensors, must be tested in case of doubt.

For pure image recognition such as X-rays or similar, The algorithm can only be kept under control through an extended learning phase.

Aleatorics easier to solve

The random noise in images (Random) In many cases, this can be contained with higher resolutions. But there is also something to consider, that this can also trigger other sources of error. If the accuracy is too high, you can create new problem areas – depending on the available image material.

For explanation: In aleatorics, blur does not mean the entire image, but the demarcation of objects from one another. A traffic light or a tree trunk can be perceived by the software as jagged or stepped. No problem for a human, However, it is a disruptive factor that should not be underestimated for the program logic.

If there is enough computing power available, The most elegant solution is often to solve the aleatorics in software. With the help of artificial intelligence and an extensive learning phase, image noise can be minimized.

Instinctive actions only under laboratory conditions

Both subject areas are particularly important in the mobility industry. Heavy rain or even snowfall have so far been difficult problems for image recognition in the field of artificial intelligence. For humans it is instinctively clear, that a snowflake on the window or on a sensor does not pose a dilemma – What and how can you prevent artificial intelligence in an autonomous vehicle?, in this case, initiate emergency braking.

Based on my current knowledge, ultimately only a combination of several systems will ensure safe movement. Until artificial intelligence is ready and can reliably interpret human instincts in traffic, years will pass.

When aleatorics and the problems of the epistemic logic of knowledge are solved, is a huge step towards fully autonomous regional driving- and long-distance train done. In contrast to road traffic, the rules and sources of error in rail traffic are more manageable.

Complexity should not be underestimated

I am aware, that the topic is much more complex. To introduce laypeople to the topic, I allowed myself, only the most serious construction sites need to be mentioned.