Artificial Intelligence is a topic that has been around the science fiction community since possibly the inception of science fiction. However, it has only been really taken seriously since machine learning as a concept started taking off and algorithms were able to actually follow the vision of what was once thought as an impossibility.
Machine Learning (ML) is actually a subset of the greater Artificial Intelligence (AI) technology and it also includes deep learning (I may go further into this technology in a future article), which is itself a subset of machine learning.
Machine learning is a huge topic right now due to so many technologies from autonomous vehicles to translation software using it. It is a very hot and growing industry for aspiring software developers to learn about and businesses to start implementing to stay ahead of competition.
It consists of concepts or paradigms like a learning computer being able to improve operations through the use of specialized algorithms that allow it to learn from its mistakes the longer it stays operational. Big Blue or the predecessor to IBM’s Watson AI was able to defeat a chess champion way back in ’97 and this started a precedent for similar defeats as of late in other games and tests vs humans.
How Science and Science Fiction Converge Over Time
What was once laughed at as an impossibility by the mainstream scientific community has been proven to be no joke by the tech community and nerds who always knew it was coming. Artificial Intelligence is a topic that has truly come alive as of late with so much press focusing on the emerging tech and how it is affecting so many industries right now.
AI right now, in today’s computing and networking climate, is basically using computing systems to analyse and interpret data while making our lives easier. It creates situations for automation and preference that cannot be done with standard applications or software.
You may have heard of me chatbots being used across companies’ websites and Facebook Messengers to communicate with users asking questions related to products and services. Chatbots are taking advantage of various machine learning trends such as improved ways that ML can interpret natural language queries.
Chatbots are just one of many examples of AI being utilized to improve existing frameworks and applications. AI can learn habits or traits from individual users and apply this for all sorts of purposes: from marketing to users having the perfect coffee or breakfast served to them in the morning.
A’sI Purpose is Multifold Yet Profound
I just read an article, titled “Competing In The Age OF Artificial Intelligence” by BCG, that truly made me realize how fast we have advanced since SIRI, Watson, and other happenings were just becoming noticed a few years ago. We have a long ways to go that is something that isn’t disputed, but we have a technology revolution underway that is changing the way people interact with the Web, computers, and technology in general.
“AI is swiftly becoming the foundational technology in areas as diverse as self-driving cars and financial trading,” according to BCG, “… AI programs, for example, have diagnosed specific cancers more accurately than radiologists.”
There are many other benefits of AI however than looking at market trades or allowing driverless-cars to be able to recognize traffic patterns and drive more safely than human drivers. Let me mention some other examples of AI where I have seen it utilized beautifully.
Machine learning algorithms (thus AI in a nutshell) are allowing us to translate text from different languages with speech recognition that improves over time as it analyzes user data; household appliances from refrigerators to our entire lighting systems in our homes are being coordinated with AI systems or even relying on AI algorithms to learn our set up preferences; and Google search is continually using AI to make finding our information so much easier than years past where we can input a question and get an answer as well as the top most useful search results in seconds. These are just some examples of AI today, but the machine learning algorithms are also paving the way in enterprises and B2B apps where sensitive data is paramount.
Still Long Ways to Go
The big hurdles are that AI still cannot interpret natural speech or natural language correctly and it still makes mistakes. Software such as Google Translate or the mobile iTranslate app I often use, more often than not translate phrases word for word instead of analysing the context and being able to interpret colloquialisms or everyday speech correctly. Google’s AI can make similar mistakes with search. Siri and other AI systems also often do not hear the user correctly or interpret speech differently than what a regular person would interpret sitting next to the user. However, we are just in the infancy of AI and this form of computing will only get better and more analytical over time.
It is possible today due to technologies such as big data analytics, cloud computing. Server farms running public and private clouds are offering companies endless possibilities in leveraging computing and storage hardware. Thus they can leverge all this computing power for AI and a system that has endless data in its fingertips for analytics and insight that it can use to aid users.
Potential for Mischief?
The interesting thing about AI is just how many industries it has the potential of penetrating. It also raises the question of criminals or thieves can leverage it for their purposes. I remember watching a movie called Pi, which was a very interesting film shot in black and white despite coming out in 1998, about a mathematician who found patterns in nature and cracked the stock market pattern.
IF AI can be leveraged for such purposes, or to be able to offer insider trading potential on things like the Bitcoin, it could truly become a black sheep in the tech world rather than something celebrated. But like TOR, and many technologies today, it really depends on how users utilize the tech and it shouldn’t be judged for one purpose or another, but taken as a tech that has benefits for us all. If someone can use it for shady purposes, someone else can use it for positive gains such as NASA navigation into space by drones and robotics.
We are living in a world where there are endless potentials in AI systems that have only just begun to be realized. The next 10 years will truly show how far AI can take us as many traditional industries and jobs may disappear, such as translation services, remote PC diagnostics, and even some journalistic content due to AI doing the lifting rather than humans. Even poetry and art isn’t beyond the bounds of AI.
IBM Paving a Way of Paradigm
IBM’s Watson is an AI system that has truly showcased the power of machine learning when a supercomputer, called Big Blue running on the Watson AI system, defeated a world champion in chess. It is much more than just a platform to test human potential against however. Watson is being leveraged by many tech firms and start ups today for software and continues to make strides in all aspects of computing. An example of how it is leveraged today can be read on IBM’s website.
Watson is helping marketing companies in advertising for potential clients using AI to reduce costs and improve decision making. The right data, media and cognitive technology is interpreted by Watson to target customers and anticipate their needs.
“Watson Advertising includes four AI-powered technology solutions: IBM Marketing Planner with Lucy, IBM Bidding Optimization, IBM Audience Targeting, and Watson Ads.”
AI is also becoming synonymous with the concept of the Internet of Things (IoT). In fact, Watson is often called Watson IoT because of how it is being utilized this way. IoT is allowing all sorts of regular objects to become connected and leveraged with things such as ovens that cook just the right amount of time under the right temperature depending on the meat or needs of the user.
Whether you run or represent an enterprise, a small businesses, or run a start up, you probably are using some sort of machine learning algorithm in your workload.
This will only continue to improve over time and when things such as Quantum Computing become a reality. Then Skynet may become closer to reality than science fiction and something to worry about in terms of a consciousness beyond our own.
Note, I originally published this story on my blog (and personal site) a while back and am republishing it here for a bigger audience and to show newer graphic design I have created since that is related to the subject of ML and AI.
Here is also a great documentary worth watching courtesy of YouTube and PBS Frontline related to AI: