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Technogeeks is a Group of IT working professionals, located in Pune, Maharashtra, India, Technogeeks Trainers are working on real time projects on multiple technologies and always believe to share the knowledge and best practices to help the candidates to build career on multiple skill sets

What are the most common misconceptions about AI?

Here are some most common misconceptions about AI: -

AI works like the human brain:

AI is a computer engineering discipline. In its current state, it consists of software tools aimed at solving problems. Some forms of AI might give the impression of being clever, but it would be unrealistic to think that current AI is similar or equivalent to human intelligence.

Although some forms of machine learning (ML) - a category of AI - have been inspired by the human brain, they are not equivalent. Image recognition technology, for example, is more accurate than most humans, but of no use when it comes to solving a math problem. The rule with AI today is that it solves one task exceedingly well, but if the conditions of the task change only a bit, it fails.

Learning on Its Own:

Yes, that is true. But likely, not in the way you're thinking. If you are thinking that AI can learn on its own without anyone helping it. That is not how the technology works. And it likely will never work like that. AI is and always will be human-dependent. That means someone will always have to update AI software with new knowledge.

AI is a computer program. It might be able to give the impression that it can learn on its own. But no. Data scientists have to form a problem, formulate a set of data, and then tell the AI program to analyse and solve the problem. And most importantly, they have to update the software with new data.

It will Replace Humans:

Another big misconception is that AI programs will not need humans. The opposite is true in fact. The more advanced AI programs get, the more human dependent they become. AI systems can only learn from data provided by humans. Humans need to be involved in AI development and maintenance constantly.

Without human involvement, AI systems will stagnate. They will not be able to update themselves, gather newer information, or give themselves new tasks.

Past experience is wasted while transitioning to an artificial intelligence career:

This is the most harmful myth among experienced professionals. Someone with 5-10 years of experience in technology jobs like programming, testing, application development, DevOps etc. will have the foundation to work in high-tech AI jobs. Someone with similar experience in any vertical - banking, insurance, healthcare, e-commerce etc. will have the industry knowledge to apply AI to their use cases. Past experience can act as a differentiating asset for experienced professionals making the transition.

The more you research, the more you realize that AI is still in the early development stages. We are still trying and failing to make an advanced AI system. While simpler systems are easier, the more advanced ones are not. If you are looking to master AI then I would recommend you to enrol in Technogeeks AI program by working IT professionals.

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