WHAT IS ARTIFICIAL INTELLIGENCE (AI)?
It depends who you ask.
Minsky and McCarthy, described artificial intelligence as any task performed by a machine that would have previously been considered to require human intelligence. That’s obviously a fairly broad definition, which is why you will sometimes see arguments over whether something is truly AI or not. Intelligence is the efficiency with which you acquire new skills at tasks you didn’t previously prepare for. Intelligence is not skill itself, it’s not what you can do, it’s how well and how efficiently you can learn new things.
Typically, AI systems demonstrate at least some of the following behaviors associated with human intelligence like:
Planning, learning, reasoning, problem solving, knowledge representation, perception, motion, and manipulation and, to a lesser extent, social intelligence and creativity.
HOW AI AIDS PRODUCTIVITY
The use of artificial intelligence (AI) is already a reality in many industries, but the technology also has significantly more potential. An analysis from shows that labor productivity in developed countries increase by up to 40 percent due to the influence of AI. There is a 37% high increase in productivity in Sweden. The U.S. (35 percent) and Japan (34 percent) which will benefit greatly from the effects of AI. In Germany and Austria, AI can potentially maximize labor productivity by around 30 percent within the next 15 years.
The Big Picture
The AI revolution is already underway, and its effects will be far-reaching. If your company isn’t prepared, it will lag behind competitors that are implementing AI solutions. Here are a few tips to help you get started:
- Use Clean Data: The performance of any AI solution is contingent upon the quality of the data that’s used to train it. Use clean data that is accurate, complete, relevant and/or properly formatted — and be sure to have a clear business goal in mind so you’ll design a more effective model.
- Take A Proactive Approach To Model Maintenance: When you start building models, be sure to do so in ways that make retraining easier. No model you create and test should be considered disposable. Everything should be production-level quality.
- Replace Manual With Automated: Look across your organization, and identify any time-intensive manual process that’s a good candidate for automation. Then match that process with an AI solution that’s easy to implement and maintain.
Find interesting ways, like those above, to incorporate this disruptive technology into business practices, and you will enjoy the corresponding improvements to productivity and decision-making.
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