In recent years, the growing need for materials that have high thermal resistance, non-flammability, high radioactive resistance and durability is the reason for the development of new technologies for electroless metallisation of glasses. The most important operation is surface roughening, which is usually carried out in etching solutions containing HF acid, which is harmful to the environment and to health and safety at work. In this regard, the aim of the present research is the creation of an environmentally friendly technology for electroless metallisation of glasses. & Tcy;he samples were pre-treated in two ways: one group was covered with a thin polymer film (Plastik 70 special glue or epoxy resin, thinned with dimethylformamide), and the other was degreased and treated with a solution of (3 aminopropyl) trimethoxysilane (APTS) at different concentrations and under different conditions. All samples were activated with a colloidal activator, after which copper or nickel-phosphorus coatings were deposited by electroless plating.

We will reduce the task of creating AI to the task of finding an appropriate language for description of the world. This will not be a programing language because programing languages describe only computable functions, while our language will describe a somewhat broader class of functions. Another specificity of this language will be that the description will consist of separate modules. This will enable us look for the description of the world automatically such that we discover it module after module. Our approach to the creation of this new language will be to start with a particular world and write the description of that particular world. The point is that the language which can describe this particular world will be appropriate for describing any world. This is the first part of the paper. In this part we will define the basic theoretical concepts which will we will need when creating the language we are looking for.

This is the second part of the paper. In this part we will use the world of the chess game in order to create the language we are looking for. We will show how a complex world can be described in a simple and understandable way. Before describing the movement of chess pieces, we will need to extend the concept of algorithm. The new concept describes the algorithm as a sequence of actions performed in an arbitrary world. In the meaning of the new concept, a cooking recipe is also an algorithm. If we look at a world in which there is an infinite tape and a head which travels over the tape, then the algorithm of that world will be a Turing machine. This means that the new concept of algorithm is a generalization of the old one. Computer programs are algorithms both in the new concept and in the old one, however, there are many other sequences of actions which extend the concept.

We will consider all policies of the agent and will prove that one of them is the best performing policy. While that policy is not computable, computable policies do exist in its proximity. We will define AI as a computable policy which is sufficiently proximal to the best performing policy. Before we can define the agent's best performing policy, we need a language for description of the world. We will also use this language to develop a program which satisfies the AI definition. The program will first understand the world by describing it in the selected language. The program will then use the description in order to predict the future and select the best possible move. While this program is extremely inefficient and practically unusable, it can be improved by refining both the language for description of the world and the algorithm used to predict the future. This can yield a program which is both efficient and consistent with the AI definition.

In recent years, significant changes have occurred in the field of three-dimensional printing (3D-printing) and it has been applied both in the production of prototypes and in regular production in the following sectors: architecture, construction, automotive, aircraft, biotechnology, fashion, etc. Different technologies for 3D-printing are proposed. Between them, the technology FDM (Fused Deposition Modelling) has the greatest application in the industry due to the low cost and simplified operations. This technology is suitable for 3D-printing of various polymers (PET, ABS, PLA, PETG, etc.), which after preliminary treatment can be metallised by electroless deposition in order to obtain an even metal coating. The present paper describes investigations of some properties of nickel or copper coatings, electroless deposited from two kinds of solutions on 3D-printed and on cast under pressure ABS samples. For deposition of electroless nickel or copper coatings with good adhesion, the influence of the pre-treatment operations was also evaluated in both cases upon deposition on 3D-printed ABS samples with different resolutions (0.8 or 0.25 mm,) and on cast under pressure ABS samples. The thickness of the deposited layers was determined gravimetrically; the morphology and the elemental composition of the layers were examined by SEM or EDS, respectively; the surface roughness of the ABS samples was measured by AFM, and the adhesion of the metal layers was evaluated by a standard test with an adhesive tape (type Test-Method ASTM D 3359-83).

We will reduce the task of creating AI to the task of finding an appropriate language for description of the world. This will not be a programing language because programing languages describe only computable functions, while our language will describe a somewhat broader class of functions. Another specificity of this language will be that the description will consist of separate modules. This will enable us look for the description of the world automatically such that we discover it module after module. Our approach to the creation of this new language will be to start with a particular world and write the description of that particular world. The point is that the language which can describe this particular world will be appropriate for describing any world.

In the metallisation of dielectrics, this process and the deposited metal layer quality is influenced by the dielectric pre-treatment, and the solution compositions for both pre-treatment and metallisation are vital for establishing the optimum operating conditions for metal layer deposition. The investigations in this study were carried out on samples of acrylonitrile-butadiene-styrene (ABS - Novodur PM/2C Type, Bayer) with a working surface of 0.1 dm(2). The investigated operations of the technological scheme for pre-treatment are as follows: degreasing, etching, reduction, pre-activation, activation. After passing through these operations, the ABS samples were subjected to chemical deposition of copper layers from a recently-developed solution. The copper layers were characterised by AFM, SEM, EDX, XRD and XPS analyses.

With Reinforcement Learning we assume that a model of the world does exist. We assume furthermore that the model in question is perfect (i.e. it describes the world completely and unambiguously). This article will demonstrate that it does not make sense to search for the perfect model because this model is too complicated and practically impossible to find. We will show that we should abandon the pursuit of perfection and pursue Event-Driven (ED) models instead. These models are generalization of Markov Decision Process (MDP) models. This generalization is essential because nothing can be found without it. Rather than a single MDP, we will aim to find a raft of neat simple ED models each one describing a simple dependency or property. In other words, we will replace the search for a singular and complex perfect model with a search for a large number of simple models.

In Reinforcement Learning we look for meaning in the flow of input/output information. If we do not find meaning, the information flow is not more than noise to us. Before we are able to find meaning, we should first learn how to discover and identify objects. What is an object? In this article we will demonstrate that an object is an event-driven model. These models are a generalization of action-driven models. In Markov Decision Process we have an action-driven model which changes its state at each step. The advantage of event-driven models is their greater sustainability as they change their states only upon the occurrence of particular events. These events may occur very rarely, therefore the state of the event-driven model is much more predictable.

There is no need for the health insurance fund to collect health contributions and then to pay for the activities carried out with that money. It is better if the National health insurance fund collects the money and keeps it and the health fund only manages it without actually passing the money through it. This eliminates the risk of bankruptcy of the fund and the need to create a guarantee fund. So changing the fund will be very easy, because no real money will be moved, but only the subject that manages it will change.

Who should own the Artificial Intelligence technology? It should belong to everyone, properly said not the technology per se, but the fruits that can be reaped from it. Obviously, we should not let AI end up in the hands of irresponsible persons. Likewise, nuclear technology should benefit all, however it should be kept secret and inaccessible by the public at large.

Most researchers regard AI as a static function without memory. This is one of the few articles where AI is seen as a device with memory. When we have memory, we can ask ourselves: Where am I?, and What is going on? When we have no memory, we have to assume that we are always in the same place and that the world is always in the same state.

Each test gives us one property which we will denote as test result. The extension of that property we will denote as the test property. This raises the question about the nature of that property. Can it be a property of the state of the world? The answer is both yes and no. For a random model of the world the answer is negative, but if we look at the maximal model of the world the answer would flip to positive. There can be various models of the world. The minimal model knows about the past and the future the indispensable minimum. Conversely, in the maximal model the world knows everything about the past and the future. If you threw a dice the maximal model would know which side will fall up and would even know what you will do. For example, it would know whether you will throw the dice at all.

All it takes to identify the computer programs which are Artificial Intelligence is to give them a test and award AI to those that pass the test. Let us say that the scores they earn at the test will be called IQ. We cannot pinpoint a minimum IQ threshold that a program has to cover in order to be AI, however, we will choose a certain value. Thus, our definition for AI will be any program the IQ of which is above the chosen value. While this idea has already been implemented in [3], here we will revisit this construct in order to introduce certain improvements.

Data are reported on the successful metallisation of cubic boron nitride by chemical reduction of solutions containing nickel and cobalt ions. The processes of growth of these two types of films differ substantially from each other. While in cobalt plating no screw-like dislocation mechanism film growth is observed, in nickel plating growth is by a screw-like dislocation mechanism. The titanium film deposited as a pretreatment on grains of cubic boron nitride does not influence the rate and structure of subsequent cobalt and nickel deposition. Thus, the metallised super-hard material obtained is useful for embedding into composite materials for the production of abrasive materials.

Artificial Intelligence - what is this? That is the question! In earlier papers we already gave a formal definition for AI, but if one desires to build an actual AI implementation, the following issues require attention and are treated here: the data format to be used, the idea of Undef and Nothing symbols, various ways for defining the meaning of life, and finally, a new notion of incorrect move. These questions are of minor importance in the theoretical discussion, but we already know the answer of the question Does AI exist? Now we want to make the next step and to create this program.

Two different definitions of the Artificial Intelligence concept have been proposed in papers [1] and [2]. The first definition is informal. It says that any program that is cleverer than a human being, is acknowledged as Artificial Intelligence. The second definition is formal because it avoids reference to the concept of human being. The readers of papers [1] and [2] might be left with the impression that both definitions are equivalent and the definition in [2] is simply a formal version of that in [1]. This paper will compare both definitions of Artificial Intelligence and, hopefully, will bring a better understanding of the concept.

Chemical metallisation of cubic boron nitride (cBN) in solutions containing copper ions has been achieved in order to use the metallised hard material for its inclusion in composite materials. It was found to be appropriate to work with smaller fractions of cBN grains, in order to avoid an uneconomically long period of electroless copper plating. The possibility of obtaining composite materials by copper chemical plating with included dispersed particles of cubic beta- and alpha hexagonal boron nitride with a grain size range of 50-80 mu m for cBN and 1-5 mu m respectively for hexagonal boron nitride on flexible materials of the pressed polyethylene terephthalate textile was shown.

In this paper we offer a formal definition of Artificial Intelligence and this directly gives us an algorithm for construction of this object. Really, this algorithm is useless due to the combinatory explosion. The main innovation in our definition is that it does not include the knowledge as a part of the intelligence. So according to our definition a newly born baby also is an Intellect. Here we differs with Turing's definition which suggests that an Intellect is a person with knowledge gained through the years.

In order to build AI we have to create a program which copes well in an arbitrary world. In this paper we will restrict our attention on one concrete world, which represents the game Tick-Tack-Toe. This world is a very simple one but it is sufficiently complicated for our task because most people cannot manage with it. The main difficulty in this world is that the player cannot see the entire internal state of the world so he has to build a model in order to understand the world. The model which we will offer will consist of final automata and first order formulas.