There are several important questions that arise if we think about Artificial Intelligence (AI) today. What is Artificial Intelligence? Will AI replace humans on their jobs? Is it dangerous? What about killer robots, ethical issues, etc.? There is a lot of news about AI lately but the information is often misleading or even wrong. The aim of this article is to answer all of these questions based on the experience and future vision of the author.
Google, who is one of the leading technology giants in the fields of AI, explained recently that they are able to make the brain of a mouse today, but I think that even that is exaggerating. It will still take many years to build an AI which mimics well the human brain and body. You will understand why after reading this article.
But the answer to the question whether the current state of AI is useful is of course yes, very useful. We can use the results of many years of AI research in endless useful applications in all business sectors. The current state of AI helps humans to do their jobs better and makes things possible which otherwise would not be possible such as developing new vaccines for deadly diseases, improving business processes, helping humans with disabilities, discovering new things, gaining new insides from all kinds of data and in all business sectors, etc. Current AI algorithms can interpret all kinds of data such as numbers, text, images, video, audio, etc. A whole new range of applications are possible and only your imagination is the limit for finding useful applications in your business sector.
In the next sections I will explain in simple terms the current state and my vision about the most important building blocks of a real human like AI system: the Memory, CPU, Sensors, the whole interconnected System and also how it will Learn and use the learned information.
We will use the term AI throughout this article because the aim is to predict the future but if we speak about today’s capabilities then we use the term ‘machine learning’, since we do not have an AI yet, but several types of machine learning models, the building blocks of an AI. Read the article ‘Learn About Machine Learning and AI’ first if you are novice to the subject!
Memory
First of all, let me begin with a simplified explanation about how the human body and brain works and why it will be extremely difficult to make an AI (robot) in the future, which can replace a human even partly. One of the mistakes AI researchers make today is that they do not take into account the enormous amount of different types of interconnected memory (and stored information) a human body and brain has. Even brain research is still guessing about many things, but there are more and more signs (proven by experiments) that we store different types of things in our brain (memories). We store images, smells, sounds, etc. There is an enormous amount of information in a well developed human brain and body. Yes body, because our whole body has different types of interconnected memory, just think about, for example, what we call muscle memory. One of the reasons why we are unable to make even an attempt to replicate a human is because of the lack of flexible, very fast and huge amount of memory. We are not talking about megabytes or gigabytes of memory but terabytes of interconnected memory. The technology to be able to have this kind of memory is still very far away. It is very likely that this types of memory will not be like the memory modules we use in our computers today, but it will be some kind of chemical and biological substance (like the human body and brain has). There is an active research going on in this field also.
So how will an AI, similar to the human body and brain, function and work? I think, that there will be a very simple logic which connects the different types of memory and sensors (see later), and the complexity will not come from the basic building blocks (which will be very simple), but from the very cleverly interconnected and coordinated whole system. The AI will store all necessary information, like the human brain and body (and possibly even much more), and will be able to recall that information (even many of them in parallel) according to some kind of stimuli.
Sensors
The second reason why it is extremely difficult to replicate a human today with an AI is because of the many types of interconnected sensors the human body has. Just think about the eyes (vision), the ears (hearing), nose (smells), touch (all over the human body), temperature, etc.
We are at a very good level with the vision capabilities but even that is much more complex in reality, because a human eye (and connected brain) can sense in several dimensions. High resolution is again a very important element because only one 3D image a human eye sees consumes a huge amount of memory and there are endless numbers of images (as a kind of video). We can mimic the human eye 3D capabilities with two cameras today, but one human eye can see already in 3D (or more) and the image is used by our brain to estimate depth, distances, etc. Does one human eye contain several ‘camera’s’? Most probably yes! Most of today’s AI algorithms are limited to 2D grayscale images, because of the computing power and memory needed to analyze these images! E.g. most AI algorithms, which can detect an object in an image or video, first convert the images to grayscale before processing.
All sensors are active in a human body in parallel all the time, we see, we hear, we smell, etc., and they are interconnected with a very clever system containing the nerves in our body (yes the whole body and not only the brain). Just think about an object you are closing to and how you decide if you like that object. You will take several things into account at the same time, the visuals, the smells, the sounds, etc. and you decide automatically in an instant if you like that object or not.
The human body and brain also stores many of the information it receives, which takes up even more memory and logic. For example, how a smell is stored and recalled in your brain? I do not think that there is anybody who can answer this question yet. The human brain must have some kind of very efficient ‘internal language’ which is used to describe these things.
CPU & GPU
We have the capability today to use computers with several CPU’s containing separate computing units (cores). But how many and how fast ‘CPU units’ a human body and brain has, and how they work seamlessly in parallel? I think that you can imagine that this question is very similar to that of the memory issue above. The human body and brain process in parallel a huge amount of information (from many sensors in the human body, from memory, etc.) and all of this information is used instantly to make decisions. The information needs to be found in the different types of human memory, it needs to be processed and combined. We are very far away from the speed, storage capacity, parallel processing, logic, etc. to be able to replicate a human brain and body. The ‘wonders’ of nature and the human body have still a lot of secrets for us even after studying them for thousands of years!
One of the positive developments today is the recent appearance of extra computing power and extra AI capabilities in video cards led by NVIDIA Corporation. The special ‘cpu’ in a video card is called graphical processing unit (GPU). This is a completely logical evolution and I expect the appearance of the same capabilities e.g., in a separate audio processing unit (and other sensor systems). Computer systems will first grow in this way and just in the far future will they be integrated more closely and be much smaller in size. I also expect in the very far future that many things will be replaced by some kind of biological and chemical substances with human like capabilities.
But for the time being there is an urgent necessity for standardization of current and future developments in order to make these systems (CPU, GPU, memory, etc.) much better coordinated and easier to use (software development).
One last note about GPU’s. The introduction of GPU accelerated calculations (especially for image processing) is of course a very welcome and great evolution! I however think that in the far future CPU’s and GPU’s will evolve towards each other and finally they will become one unit which can handle all calculations. In the near future we may however still see the introduction of separate specialized processing units for different tasks.
The Whole System
A human body and brain contains an interconnected system which senses, processes, stores and recalls all of the information a human experiences. Many types of information is used at the same time to make decisions such as that a glass can be used to drink, that you can open a door, what to do if someone is calling you, what to say if someone is asking a question, etc. The basic building blocks of this interconnected system are very simple but the whole system together is extremely complex. Today AI systems do not take this into account because they are either over-complicating the basic building blocks, and/or they are incorrectly building the system as a whole e.g., not taking into account the distributed different types of memory and huge amount of stored information, stimuli and input from several sensors, etc.
This is of course also because we are not yet at the technological level and knowledge which is necessary for building a real AI system and that AI research is trying to simulate human like AI patterns.
So how will an AI similar to the human body and brain function and work? I think that there will be a very simple logic which connects the different types of memory, sensors, CPU, etc. and the complexity will not come from the basic building blocks (which will be very simple), but from the very cleverly interconnected and coordinated whole system. The AI will store all necessary information like the human brain and body (and possibly even much more) and will be able to recall that information (even many of them in parallel) according to some kind of stimuli.
There are a lot of AI algorithms out there and many people ask the question that which algorithms is the best, which should they use and which algorithm is the future. I have given the answer to this question already with the statement above that ‘there will be a very simple logic which connects the different types of memory, sensors, CPU, etc.’. Most of the complexity in current algorithms and the diversity of the algorithms are needed because of the limited memory, CPU and our limited knowledge about the whole system. The most efficient way to work today is to select the appropriate algorithm for a specific task. One of the often made mistakes by AI experts and researchers today is that they try to use complex neural networks based AI algorithms for every task despite the fact that for many tasks there are other much simpler and faster algorithms which may even give a better accuracy.
Learning and Ethics
We know already a lot of things about how learning happens. We can learn from existing knowledge, what we may call supervised learning (e.g. someone tells us or shows us that we can drink from a glass). We can learn unknown things which we may call unsupervised or reinforcement learning (we learn with trial and error). Both types of learning are very important and we can not have a real AI system which can not combine both of these learning strategies. An AI could of course learn with a trial and error strategy only, but that would be very inefficient and even dangerous because of the unknown direction the AI would evolve. Learning in reality is of course more complex than just these two learning strategies and it involves a range of strategies which are some kind of combination of these two.
A real human like AI must thus combine several learning strategies and choose and use the one automatically which is most appropriate in the given circumstances.
There were a lot of failures in automated learning/training of AI systems recently. Several AI giants announced, launched and then very soon recalled such AI systems. The reasons for this are very simple and twofold, the current AI algorithms are not intelligent enough and as a child can learn bad things an AI algorithm can also learn bad things. For example, put a child in a wrong environment and she/he will learn how and what they speak in that environment, put a natural language processing AI system on the internet where it can be acceded and influenced by anyone and it will learn unexpected things.
And with this last thought we have also arrived to the topic of Ethics. Ethics is of course something that is invented by humans and it must be learned! The good news is that good ethics can be learned, as we can learn any other thing, but the bad news is that like anything else in this world all good things can be used with bad intention. An AI system can be used to save or improve lives but it can also be used to destroy them. This is the same question as asking whether to sell guns or computers to bad people. Asking the question whether we will be able to prevent that bad people will access highly intelligent AI systems in the future is the same as asking if we can prevent bad people accessing guns or the internet. The balance of the world we are living in depends completely on us and this is as much important as evolution. There can not be an evolution without a good balance. If evolution would go much faster than we can keep up with holding the right balance, the world would be destroyed by the technology invented by humans.
Conclusion
The answer to the question whether the current AI algorithms are useful is of course yes, very useful, but we are very far from an all-in-one real AI system which can replace a human. We can of course use the results of several years of AI research in endless useful applications in all business sectors. The current state of AI helps humans to do their job better and makes things possible, which would not be possible otherwise such as developing new vaccines for deadly diseases, improving business processes, helping humans with disabilities, discovering new things, gaining new insides from all kinds of data and in all business sectors, etc. Current AI algorithms can interpret all kinds of data such as numbers, text, images, video, audio, etc. A whole new range of applications are possible and only your imagination is the limit for finding useful applications in your business sector. AI systems will start to speed up evolution very soon! It is already started!
Would you like to learn more about machine learning and AI? If you are interested in the subject then it is strongly recommended to read the book “The Application of Artificial Intelligence” which contains much more details and real world case studies for several sectors and disciplines! The book explains several examples by using the AI-TOOLKIT. The book is going through the publishing process at the time of writing this article. You may use the contact form for info about pre-ordering the book.
| Learn about the application of Artificial Intelligence and Machine Learning from the book "The Application of Artificial Intelligence | Step-by-Step Guide from Beginner to Expert", Springer 2020 (~400 pages) (ISBN 978-3-030-60031-0). Unique, understandable view of machine learning using many practical examples. Introduces AI-TOOLKIT, freely available software that allows the reader to test and study the examples in the book. No programming or scripting skills needed! Suitable for self-study by professionals, also useful as a supplementary resource for advanced undergraduate and graduate courses on AI. More information can be found at the Springer website: Springer book: The Application of Artificial Intelligence. |
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