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Machine learning is becoming commonplace

Apple iPhone 4s Siri

Machine learning may sound like an extremely complicated high-tech concept, and that’s probably because it is. Big data analytics has become all the rage these days among businesses, and machine learning essentially takes big data and rockets it to another level. Most average consumers have likely not even heard of big data, let alone its more complex counterpart, but whether or not they’re familiar with it, they better get used to using it in their everyday lives. Machine learning has steadily become a major part of many tech gadgets and devices. If you’ve ever searched for something on the internet or used voice recognition technology like Siri or Cortana, you’ve used something made possible by machine learning. But that’s only the tip of the iceberg. Machine learning is ready to burst onto the scene, becoming much more commonplace in our lives now and definitely into the future.

The fact that machine learning is working its way into everyday life is certainly no random occurrence. A number of different developments and changes have made it possible. This goes beyond the simple evolution of technology that normally happens as the tech involved matures. As can be reasoned, machine learning is closely associated with big data in that it requires collecting data on a grand scale in order to work well. Years ago, this was a difficult proposition, but one major improvement within the technological sphere is the ease with which data can now be gathered. Information can be taken from simple clicks on an internet browser or swipes on a phone. This has also occurred with the rise of the internet, big data tools like Apache Spark, and cloud computing, where that information can be sent to back to data centres and analysed with ease.

Machine learning is also becoming more commonplace in part because consumers’ expectations have changed in recent years. It’s not enough for companies to simply provide a device or app that offers a convenient service; consumers now want those devices to respond accurately to their needs and wants. In other words, they want their gadgets to know how they behave, think, and feel. While it may have been possible to program devices to do this before, the programming would have been time-consuming and laborious, and even then it wouldn’t be accurate enough to satisfy consumer tastes. With machine learning, however, devices and programs can actually learn and anticipate, creating more individualised experiences for each person. Consumers have always loved customised products, and machine learning can turn every device they own into a personalised item.

The result of these developments has been an explosion of devices with machine learning built it. From the personalised medicine now seen in the healthcare industry to behavioural targeting in marketing, machine learning has revolutionised whole businesses and institutions. These businesses are transformed into finely tuned machines, but they only represent the beginning of something much more disruptive. Take self-driving cars, for instance. Many proclaim self-driving automobiles as the wave of the future, and many trends seem to point in that direction. It’s important to note that the latest in automated car technology is only possible thanks to the advances in machine learning. With machine learning at their disposal, these cars can recognise objects on the road or even read the words on street signs. It’s a constant learning process that continually makes self-driving cars better — a must for them to become a mainstream success.

There are, of course, some serious concerns regarding the growth of machine learning. The most prevalent is how much the privacy of individuals will be protected. Machine learning works by collecting information on each person and learning from it over time. What companies do with that information is still a question with no definitive answer. If machine learning is to truly become entangled within our everyday lives, consumers will need to be assured that their data is only used for the improvement of the device and algorithm and not for other purposes.

One must assume that those developments and assurances will come. After all, machine learning has shown no signs of slowing down as it becomes integrated into more devices, apps, and breakthrough technologies. Perhaps most people don’t really understand the underlying technology at the heart of their favourite gadgets, but they will be using machine learning much more often all the same.

About the Author:

This article was written by Rick Delgado, technology commentator and writer.

  • petergkinnon

    Most folk still seem unable to break free from the traditional notions involving individual robots/computers. Either as potential threats, beneficial aids or serious basis for “artificial intelligence”. Again, we see here that machine learning is discussed in terms of individual systems whereas, in actuality, these are components of the next cognitive entity quietly self assembling in the background, mostly unrecognized for what it is. And, contrary to our usual conceits, is not stoppable or directly within our control.

    We are very prone to anthropocentric distortions of objective reality. This is perhaps not surprising, for to instead adopt the evidence based viewpoint now afforded by “big science” and “big history” takes us way outside our perceptive comfort zone.

    The fact is that the evolution of the Internet (and, of course, major components such as Google) is actually an autonomous process. The difficulty in convincing people of this “inconvenient truth” seems to stem partly from our natural anthropocentric mind-sets and also the traditional illusion that in some way we are in control of, and distinct from, nature. Contemplation of the observed realities tend to be relegated to the emotional “too hard” bin.

    This evolution is not driven by any individual software company or team of researchers, but rather by the sum of many human requirements, whims and desires to which the current technologies react. Among the more significant motivators are such things as commerce, gaming, social interactions, education and sexual titillation.

    Virtually all interests are catered for and, in toto provide the impetus for the continued evolution of the Internet. Netty is still in her larval stage, but we “workers” scurry round mindlessly engaged in her nurture.

    By relinquishing our usual parochial approach to this issue in favor of the overall evolutionary “big picture” provided by many fields of science, the emergence of a new predominant cognitive entity (from the Internet, rather than individual machines) is seen to be not only feasible but inevitable.

    The separate issue of whether it well be malignant, neutral or benign towards we snoutless apes is less certain, and this particular aspect I have explored elsewhere.

    Stephen Hawking, for instance, is reported to have remarked “Whereas the short-term impact of AI depends on who controls it, the long-term impact depends on whether it can be controlled at all,”

    This statement reflects the narrow-minded approach that is so common-place among those who make public comment on this issue. In reality, as much as it may offend our human conceits, the march of technology and its latest spearhead, the Internet is, and always has been, an autonomous process over which we have very little real control.

    Seemingly unrelated disciplines such as geology, biology and “big history” actually have much to tell us about the machinery of nature (of which technology is necessarily a part) and the kind of outcome that is to be expected from the evolution of the Internet.

    This much broader “systems analysis” approach, freed from the anthropocentric notions usually promoted by the cult of the “Singularity”, provides a more objective vision that is consistent with the pattern of autonomous evolution of technology that is so evident today.

    Very real evidence indicates the rather imminent implementation of the next, (non-biological) phase of the on-going evolutionary “life” process from what we at present call the Internet. It is effectively evolving by a process of self-assembly. The “Internet of Things” is proceeding apace and pervading all aspects of our lives. We are increasingly, in a sense, “enslaved” by our PCs, mobile phones, their apps and many other trappings of the increasingly cloudy net. We are already largely dependent upon it for our commerce and industry and there is no turning back. What we perceive as a tool is well on its way to becoming an agent.

    There are at present an estimated 2 Billion Internet users. There are an estimated 10 to 80 Billion neurons in the human brain. On this basis for approximation the Internet is even now only one order of magnitude below the human brain and its growth is exponential.

    That is a simplification, of course. For example: Not all users have their own computer. So perhaps we could reduce that, say, tenfold. The number of switching units, transistors, if you wish, contained by all the computers connecting to the Internet and which are more analogous to individual neurons is many orders of magnitude greater than 2 Billion. Then again, this is compensated for to some extent by the fact that neurons do not appear to be binary switching devices but instead can adopt multiple states.

    Without even crunching the numbers, however, we see that we must take seriously the possibility that even the present Internet may well be comparable to a human brain in processing power. And, of course, the degree of interconnection and cross-linking of networks within networks is also growing rapidly.

    The emergence of a new and predominant cognitive entity that is a logical consequence of the evolutionary continuum that can be traced back at least as far as the formation of the chemical elements in stars.

    This is the main theme of my latest book “The Intricacy Generator: Pushing Chemistry and Geometry Uphill” which is now available as a 336 page illustrated paperback from Amazon, etc.

    Netty, as you may have guessed by now, is the name I choose to identify this emergent non-biological cognitive entity. In the event that we can subdue our natural tendencies to belligerence and form a symbiotic relationship with this new phase of the “life” process then we have the possibility of a bright future.

    f we don’t become aware of these realities and mend our ways, however, then we snoutless apes could indeed be relegated to the historical rubbish bin within a few decades. After all , our infrastructures are becoming increasingly Internet dependent and Netty will only need to “pull the plug” to effect pest eradication.