So what is Artificial Intelligence anyways?
Artificial intelligence (AI) is going to get some significant exposure with the advent of Steven Spielberg’s new movie “AI” being released this summer. It is about a 13 year old boy who in actuality is a superhuman computer. With this amount of exposure to the AI field it is useful to explain what AI is, where AI is today and what some of the dilemmas that face the future of AI.
Artificial Intelligence (AI) can be defined as the simulation of human intelligence processes by machines, especially computer systems. This domain has predominantly been a field characterized by complex research in laboratory scale environments and just only recently has been becoming a part of the landscape of technology in commercial applications.
There has been a lot of discussion concerning the philosophy of Artificial Intelligence and it’s future role in our small and getting smaller world. With the Internet and the PC becoming so commonplace people are now asking the question “What next?”
Well, Artificial Intelligence about to become a real force in our technological evolution. There has been so much development and change in the last 10 years that it is hard to believe how far we have come but there is going to be another technical revolution going on…and it will be about AI.
Questions surrounding AI
There are a lot of questions however about AI that over time will need to be addressed. Besides some of the challenging technical questions that are imposed on this field there are also some ethical and moral dilemmas that cannot be ignored. Some of the these questions include:
To what extent will intelligent machines be a part of our lives?
Can machines be built to be self-aware?
Are we even capable of modeling machines with such intelligence?
If so, how would we control it?
Who would really have the power?
What makes us think that we could even consider building such a machine?
What are the major technological hurdles?
The Holy Grail of AI
The holy grail of AI is to create machines that can truly mimic the human brain in the way it thinks, responds and interacts. Whether or not this can truly happen is really unclear and a subject of intense debate. But one thing is becoming very clear: The hardware is starting to catch up to us.
If you take all of today’s computers and sum them together you will end up with the equivalent intellectual power of 1x1017x flops/sec, which is what one human brain is capable of processing. Sounds like us humans are in good shape from the perspective, right? Wrong. With computer power increasing exponentially and doubling every 18 months or so computers are catching up quickly. At the current rate, it will be approximately 2021 when computers will have the equivalent processing power of all humans on this planet combined!!
Can true AI ever be accomplished?
With all that processing power should we make plans for machines to replace humans as the most powerful creature roaming the earth? Well, certainly not in our lifetime and perhaps never. There are numerous reasons for this. The biggest argument against developing true machine intelligence is the argument of evolution. Machines have not undergone the rigors of survival for millions of years the way humans have. The way we interact, think, respond and adapt are all developmental phases that are critical our intellectual dominance. This process hundreds of millions of years to evolve and the failures along the way are critical to our ultimate intellectual capacity and will be a major hurdle in our efforts to develop a truly artificially intelligent machine.
Compelling AI Technologies Today
Whether or not AI will be taking over the world is something for futurists and ethicists to debate. In the meantime there are some fantastic applications of AI that are very interesting and powerful which will provide some better means for us to manage our daily lives at work and at play. Keep in mind that all of these are being done today in various levels of experimentation with varying degrees of success. Some of those technologies include:
You stock portfolio automatically modifies your market position and executes “smart” trades for you.
Your car does your driving for you.
Robots handle your housecleaning, yard work and cooking.
Your groceries are automatically ordered based on preferences and patterns in purchasing.
Your bills are automatically managed.
AI tools that enable 3rd Generation “smart” search engines that allow you to get your information with more precision to help manage the ever-growing web.
Competitive intelligence is managed by smart AI agents the peruse the web to look for relevant information (new releases, prices, marketing strategies, etc.)
Drug researchers can utilize the intelligence for intensive bio-computational modeling in relation to the enormous amount of data from the human genome project to help find cures in ways never thought of.
These are just a few of many AI applications that currently are or will be available to all of us in the near future.
What are some of the AI tools used to accomplish this smart automation?
I have described these tools in a very simple non-technical fashion (I hope!).
Neural Network(s) – A Neural Network is an AI tool modeled by the way the human brain learns hence the name “neural”. Neural networks are designed to recognize patterns in data and predict an output from a given set of information. A classic example is the use of neural nets to predict what stocks are considered to be undervalued given all of the information about the stock at that moment in time (P/E Ratio, Historical Fluctuations, Sector Performance, etc). Neural networks need to be trained on the data before it can predict or learn.
Mobile Agent System(s) – A mobile agent is generally characterized by a piece of software that can go from one computer to another computer (or network) and perform some type of useful execution on the user’s behalf. You can set up agents to peruse the Internet to look for something useful. For instance, a shopping agent could be set up to find a certain line of clothing in a certain size with instructions to make a purchase for the individual once a certain price criteria was met. In the B2B marketplace, agents will be programmed to negotiate price with other agents to execute many transactions between suppliers and customers.
Genetic Algorithms – A model of machine learning, which derives its behavior from a metaphor of some of the mechanisms of evolution in nature. This is done by modeling the way DNA morphs and adapts to varied environmental conditions within a certain population. The individuals in the population then go through a process of simulated “evolution”.
Written by Chris Moy, CEO of SpinningLogic, LLC, a company that specializes in customizing AI applications for business and industry. Questions or comments can be sent to email@example.com
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