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"In the field of medical device development there are a number of factors generally recognised as being important for success. Among these are the biocompatibility, sterility, reliability and adaptability of materials to their surroundings. Without a suitable approach to these issues, the majority of medical devices will not be as successful as they could be. Biocompatibility of materials, in particular, is a critical factor in the development and application of permanent and temporary implants and other devices such as catheters and tubes that are to be used in and around the body. Coating technology is the obvious and ideal solution for separating the bulk properties of a material or device from direct interaction with its surroundings. The independent modification of surface and bulk properties widens the range of features that can be incorporated into products. Bulk properties are responsible for characteristics such as mechanical strength. A suitable coating will enhance the interaction of the device with its surroundings. For example, it will provide drug-elusion (stents), anti-fouling and antibacterial properties, and a hydrophobic self-cleaning surface, referred to as lotus coating.1 The lotus effect in material science is the observed self-cleaning property found with lotus plants. A coating with this effect will make surfaces self-cleaning and will decrease the need for active cleaning of the subsequent surface; it may even enhance the sterility of surfaces. Recently there have been some interesting developments in materials and coatings based on organic and inorganic components, which are responsible for current state-of-the-art devices. Examples include coatings for stents that provide multiple therapeutic effects in thinner layers and coatings with better adhesion to device surfaces. The future holds the promise of even greater functionality for medical coatings."

nanotechnology is an interesting concept. many world governments have invested billions in research for nanotechnology. "Nanotechnology (sometimes shortened to "nanotech") is the manipulation of matter on an atomic, molecular, and supramolecular scale. The earliest, widespread description of nanotechnology[1][2] referred to the particular technological goal of precisely manipulating atoms and molecules for fabrication of macroscale products, also now referred to as molecular nanotechnology. A more generalized description of nanotechnology was subsequently established by the National Nanotechnology Initiative, which defines nanotechnology as the manipulation of matter with at least one dimension sized from 1 to 100 nanometers. This definition reflects the fact that quantum mechanical effects are important at this quantum-realm scale, and so the definition shifted from a particular technological goal to a research category inclusive of all types of research and technologies that deal with the special properties of matter that occur below the given size threshold. It is therefore common to see the plural form "nanotechnologies" as well as "nanoscale technologies" to refer to the broad range of research and applications whose common trait is size. Because of the variety of potential applications (including industrial and military), governments have invested billions of dollars in nanotechnology research. Through its National Nanotechnology Initiative, the USA has invested 3.7 billion dollars. The European Union has invested 1.2 billion and Japan 750 million dollars."

"Nanotechnology (sometimes shortened to "nanotech") is the manipulation of matter on an atomic, molecular, and supramolecular scale" Nanotechnology is really a manipulation-nanotechnology doesn't happen naturally.

Pretty good facts on this, I just do not know how reliable this page is, given that it is off of wikipedia. It is interesting to find out just how much countries have invested in nanotechnology. Just may want to check credibility to this page.

This is someone else's outline of the book, which is important because it is showing the opinions of the book from someone else's perspective.

The review of "Physics of the Future" is very interesting to to take into account when about to read the book. Dwight Garner's review on this book gives another perspective to consider, not only about the ideas represented by Michio Kaku, but also about Kaku's writing ability.

New York Times article describing the book Physics of the Future

In any realistic learning application, the entire instance space will be so large that any learning algorithm can expect to see only a small fraction of it during training. From this small fraction, a hypothesis must be formed that classifies all the unseen instances. If the learning algorithm performs well then most of these unseen instances should be classified correctly. However, if no restric- tions are placed on the hypothesis space and no "preference criterion" 1124] is supplied for comparing competing hypotheses, then all possible classifications of the unseen instances are equally possible and no inductive method can do better on average than random guessing [261. Hence all learning algorithms employ some mechanism whereby the space of hypotheses is restricted or whereby some hypotheses are preferred a priori over others. This is known as inductive bias I hope to use this source to learn more about how artificial intelligence learns, as I have read in other places that the kind that learns from the "bottom up" learns by making mistakes and learning from them. AI, if to be truly intelligent, is probably going to have to learn the way we did; by experience and example. In Kaku's book, he mentions the differences between two artificially intelligent robots that he "met". One, STAIR, had a limited database and was programmed to do what it did. Another, LAGR, piloted itself through a park, bumping into miscellaneous objects and learning their locations so that on the next pass, it would not hit them. I hope to learn more about that kind of logic by reading this article, as I think it is important to have a better understanding of exactly how artificial intelligence learns.

"Our basic computational element (model neuron) is often called a node or unit. It receives input from some other units, or perhaps from an external source. Each input has an associated weight w, which can be modified so as to model synaptic learning." This is a simple and brief article, but I think that a better understanding of neuroscience and how neurons work will help us to better grasp what research is being done regarding AI. This is an important research category, because if we wish to recreate ourselves on a scale of intelligence, we will need to better analyze our neural relays and systems. Apparently, according to Kaku's book, it is a very complicated endeavor that has been met so far with limited success. Hopefully, we can better understand the basics of neuron structure and function with this article.

This website offers various information on TPF, or the Terrestrial Planet Finder. This website is especially useful, for it tells you not only how the machine works but why it still is not currently in space. You will learn why this machine is so important and how it could truly help humanity in finding other life in space. This website is reliable, for it is an edited newspaper taken from various reliable sources. You can understand how the machine works and how it plans on finding other life by reading this website.