The Software You’ve Never Heard of That IBM Predicts Will Have A Billion Users By The End of Next Year

IBM’s ‘Watson’ artificial intelligence software is currently at the forefront of cognitive computing. It was first thrown into the spotlight of the public eye when it beat a human being in a jeopardy episode in 2011 but it has come a long way since then. Up until now, most artificial intelligence software systems have been primarily based on mathematical equations, rules, and logic; often following a very rigid decision making system. However, with the amount of information for these softwares to sift through constantly expanding, these systems are becoming more and more obsolete. Rather than this approach, Watson is dependent upon natural language which is governed by things like rules of grammar, context, and culture.

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Watson reads and understands the information the same way that people do. It breaks down the sentences via grammar, relations, and structure which makes it able to actually understand context unlike simple speech recognition software like a google search engine that simply looks for key word matches and synonyms.

Due to this, unlike conventional computing systems which can only comprehend information if it’s neatly organized and well-structured, Watson can assess unstructured information the same way that humans do. Some examples of unstructured data are literature, articles, research reports, blogs, posts, tweets and pretty much any other types of data that is created by humans for other humans to consume.  When humans want to understand something, there are four steps to which they attempt to do so:

  • Observation of information and evidence
  • Interpretation of what has been presented to them in order to form hypotheses
  • Evaluation of which hypotheses are right or wrong
  • Deciding which option seems best

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Because Watson mirrors a lot of these same cognitive abilities that human beings possess, it approaches problems the same way that humans do but at a much faster speed and can assess information on a much larger scale.

In the initial stages of preparing Watson to become literate in a field, experts manually select the relevant information that is uploaded into the corpus of information. As time progresses, Watson’s corpus is constantly updated and improved in order to make sure that Watson’s information continues to be accurate. Once Watson begins operating in a particular field, it learns the language, dialect, jargon, and thought process of the field. This is done by giving it Question & Answer pairs that teach it how to find patterns of linguistics within the information in order to find the answers to questions on it’s own as well as identify new insights or patterns in the available information. Once identifying certain parts of speech within a sentence, Watson generates hypotheses which are then compared with the data within the corpus to either support or refute the hypotheses. Watson can handle even the most complex of fields such as law, medicine, or culinary arts. Currently, Watson is discovering patterns and offering answers to questions we never even knew existed faster than any person or group of people ever could.

Watson constantly adapts and changes the same way that human beings do. It gets smarter with age as well, just like human beings. It learns from interactions with human beings and from it’s own successes and failures just like us.

In a recent study at the University of North Carolina School of Medicine, Watson was given the task of analyzing the cases of 1,000 cancer diagnoses. In 99% of the cases, Watson recommended the treatment plans that matched the actual suggestions from real oncologists. Watson also found treatment options that the human doctors missed in 30% of the cases. Due to the fact that it can analyze thousands of documents in mere minutes, it allows the software to read all of the clinical trials or research papers that a human may not have the time to read.

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Although about 2/3 of Watson’s sales are coming from the medical field, this technology has shown to be extremely flexible with a multitude of uses. Grammy-award winning producer “Alex da Kid” recently used Watson’s “Beat” algorithm to create his first solo EP. It has also created movie trailers all on it’s own. General Motors will be implementing the software for their newest OnStar system, OnStar Go. IBM is currently in the process of developing the software to analyze, identify, and hopefully prevent cybersecurity threats. Beginning next year, IBM will release a version of Watson that will assist teachers in creating lesson plans. It can also assist traders with “up to the minute” financial, economic, product, and client data for more personalized recommendations. These are just a few of the many ways this technology has been used.

 

A few years ago, I would have said that technology like this was not going to be accessible to the general public in my lifetime but I was wrong. It’s official, the intellectual capability of technology has now exceeded that of mankind. The future possibilities of this technology are endless.

8 comments

  1. emmaharney21 · ·

    Great post! I am interested in how this software is going to manifest or look in the next year. Are we going to simply have a Watson at our disposal as software, or is it going to be embedded into other kinds of apps and such? I looked into their website http://www.ibm.com/watson/ and noticed that they are primarily advertising this idea to facilitate business growth. Do you think that is limiting for them or just a smart starting place? Do you think this software actually has the potential to be part of our daily lives as consumers not just business people. I personally think that it does have this potential. We talk a lot in class about the ethics around AI. This is a great example of how this question is going to continue to be important. While Watson may help us make more effective decisions faster, can we promise that they will also be moral decisions. If so, who determines how to program morality into AI? This generated a lot of questions for me, great job!

    1. I think that as of now, it will only be embedded in technologies for consumer/research purposes. I think eventually it’s going to make things like Siri and Alexa fully capable of replacing things like personal assistants. This technology gives suggestions, not commands. I think it’s up to the people using this technology to use their own moral compass in their decision making process.

  2. rohansuwarna · ·

    Great job! I really enjoyed reading about how Watson compares to the thinking of actual humans. However, I was looking at Watson’s AR abilities from a different viewpoint. I feel like AR will take away the natural thinking that comes with cognitive research. I personally am a fan of natural human innovation. Yet, the ability that Watson’s AR abilities include the skills to learn a new language in a new industry provide us with many more benefits than with natural human progression. I just hope with Watson’s growth comes the growth and not loss of technology jobs.

    1. A lot of companies are now offering artificial intelligence training courses online due to the rapid growth of this so hopefully this will ease your concerns

  3. adawsisys · ·

    Very interesting post. I enjoyed learning about the four step process. I didn’t realize all that was involved in programming something as complex as Watson. I wonder how long it will take before Watson replaces some human jobs, and if there will be backlash from the public. The success rates in medical diagnoses shows that Watson is well on its way to becoming a trusted technology. I am curious to see what fields IBM will program Watson for next, and I wonder if Watson will have consumer capabilities down the road.

  4. Cool article on the power of IBM Watson. I have read a lot about IBM Watson in the past and think it’s potential is limitless. I am extremely excited for the ways in which IBM plans to deploy it in the near future. I think at this point as they pitch it to businesses IBM is initially trying to start sales for their Watson project, and to slowly roll it out. But, I think Watson has far more potential then to facilitate business growth. I believe Watson can help create the next big advances in science, medicine, and more, and it’s only a matter of time before IBM monopolizes on these advantages.

  5. Really interesting post! I read a lot about IBM and Watson last spring in my Technology and Culture class. We specifically talked about why Watson failed on Jeopardy. It (he? weird…) was really skilled at the strictly factual questions about etymology, history, geography, etc, but failed in categories related to puns, emotions, or complicated phrase deconstruction. I’m a super geek and actually love watching Jeopardy (7:30pm weeknights on CBS!) and I’ve paid much closer attention to the categories since reading that case. Take for example the “onomatopoetic words” category: “Proverbially, “All” this, “no steak” means something didn’t live up to expectations.” Answer: “What is, all sizzle, no steak.” Since this is a slang phrase, it seems like a question Watson would have difficulty answering.

  6. IBM is betting big on Watson. The tech seems to be well in place and the platform can be applied to numerous problems/industries.

    The interesting thing is that this type of AI with machine learning just gets better the more it is used and the more exposure it has to data. Little known fact is that IBM acquired the Weather Channel a little while ago. May seem odd, but the primary driver behind the deal was the massive data sets used to predict whether and the future predictive power of Watson once it can leverage that data long with current information.

    Watch out weatherman. Watson is coming :o)

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