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The jokes seemed to write themselves last week after the Biden administration announced Vice President Kamala Harris, known for her vapid word salad speeches and obvious gaslighting, would now run point on artificial intelligence. Even I jumped in on the action, noting on FOX Business that Harris was more associated with the word "artificial" than the word "intelligence." All joking aside, the future of AI technology is a serious issue. With her approval ratings in the toilet and President Biden showing obvious signs of age-related decline, Kamala Harris (and by that I mean the Democratic Party) urgently needs a way to rehabilitate her historically unpopular image ahead of the 2024 presidential race. This is not the way. On this issue, like so many before it, Harris is out of her depth.

In any emerging field, tech procurement is quite challenging as AI is particularly vulnerable. Businesses face a lot of problems to know how exactly they can use AI effectively as many non-AI companies engage in AI washing, some organizations overstate. It's true that AI technology is a luxurious retreat because you cannot oversee the radical changes it brings into the organization. However, to implement it an organization needs experts who are hard to find. For successful adoption, it needs a high-degree computation processing.

Artificial intelligence (AI) might be the way of the future in tech, gaming and smart-device industries. When applied effectively, AI can save on human employment costs and, in some cases, can accomplish tasks even better than humans can. It would make sense for other industries to try to capitalize on AI's efficiency, versatility and overall power, but for entrepreneurs, applying AI to human resources (HR) poses some challenges. HR professionals may want to put AI to use, at least partly because it can offer predictive analysis for recruiting. When a company is swamped with resumes, AI can scan resumes for those that best fit the skills and responsibilities required for that specific job.

Artificial Intelligence (AI) is one nowadays of the most trending IT topics, as it empowers novel applications that exhibit human-like capabilities. At the same time, there is a heated debate about the pros and cons of AI when compared to Human Intelligence (HI). AI is to date very efficient when dealing with domain specific problems like chess and GO, where no human can currently beat the top AI-based programs. However, AI performs poorly in problems where intelligence needs to be transferred and applied in different contexts. Humans are much more efficient than computers in generalizing their knowledge and applying it in different settings. AI and HI can both lead to erroneous decisions, especially when these decisions are biased.

A direct attempt to classify these and to describe machine methods of forming abstractions from sensory and other data would seem worthwhile.

In this article, I cover the 12 types of AI problems i.e. I address the question: in which scenarios should you use Artificial Intelligence (AI)? We cover this space in the Enterprise AI course. Recently, I conducted a strategy workshop for a group of senior executives running a large multinational corporation. In the workshop, one person asked the question: How many cats does it need to identify a Cat?