When you mention robotics and artificial intelligence (AI) in conversation, images from blockbuster Hollywood movies often spring to mind, usually including the Terminator, Transformer, or Iron Man franchises.
Let’s face it: androids like Data in Star Trek’s Next Generation series are firmly entrenched in the realms of science fiction and our technology is in no way prepared to even start developing products of this nature. If the build was possible, battery life is sure to be an issue when you consider the hours currently available on laptops, tablets and smartphones. Our Data would definitely need a ‘hibernate’ function and a battery the size of a small sedan.
In most cases, robots are designed to perform precise yet repetitive tasks, acting as replacements for human counterparts in a production line or similar environment. While jobs are lost due to the introduction of robots that do not care about the approaching weekend or suffer from its after effects, robot adoption creates other jobs (in design, support, machine learning, robotics, data analytics and swarm intelligence), improves product quality, and increases productivity.
Robots are used in many industries, including but not limited to manufacturing, educational, industrial and last but not least, entertainment. Welding and painting are just some of the areas robotics are used in the auto industry.
Neutral Net and Mainstream AI
The Holy Grail of the AI world is, and will be for the foreseeable future, the creation of a neural net (using a combination of hardware and software) that will compare favorably with the human brain. While it may not seem like it at times, the human brain has far more storage and processing power than even the fastest gaming computers. It is this fact more than any other that limits AI development. Endowing robots with “intelligence” is a complex task and the reason data scientists, who are specialists in machine learning and advanced mathematics, employ adaptive and predictive algorithms that allow “learning” to take place. By analyzing what has already happened, the program (which in turn can link with a robot) can learn and make decisions.
Technology limits notwithstanding, today’s applications of AI are making a tangible difference to our lives. Improvements in speech and image recognition are only possible through machine learning. Other examples include Facebook’s AI, which generates verbal descriptions of images for blind users, and Amazon’s Alexa, part of its vision for voice controlled smart homes.
High Demand for AI Tech Skills
In the non-consumer market, AI is driving big business, whether in data analytics or in predictions of shopping habits based on browsing history and more. It is also used to gather vast amounts of data (in the form of satellite imagery), analyze it and predict the weather, crop yields and effects of climate change.
Robots, with or without AI, are programmed and employment prospects for those with skills in machine learning, data analytics, high performance computing (HPC), sensors and related application software and many other areas are in high demand.
AI is the future and as long as Asimov’s three laws of Robotics hold up, advances in technology will ensure that the human race can enjoy a an AI supported existence. Robots, delivery drones, smart cities and speech recognition will combine to meet our every need.
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