Artificial Intelligence is one of the emerging technologies that try to simulate human reasoning in AI systems. Researchers have made significant strides in weak AI systems, while they have only made a marginal mark in strong AI systems.
Most of us have used Siri, Google Assistant, Cortana, or even Bixby at some point in our lives. What are they? They are our digital personal assistants. They help us find useful information when we ask for it using our voice. We can say, ‘Hey Siri, show me the closest fast-food restaurant’ or ‘Who is the 21st President of the United States?’, and the assistant will respond with the relevant information by either going through your phone or searching it on the web. This is a simple example of Artificial Intelligence! Let’s read more about it!
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Instead of automating manual tasks, AI performs frequent, high-volume, computerized tasks. And it does so reliably and without fatigue. Of course, humans are still essential to set up the system and ask the right questions.
AI adds intelligence to existing products. Many products you already use will be improved with AI capabilities, much like Siri was added as a feature to a new generation of Apple products. Automation, conversational platforms, bots and smart machines can be combined with large amounts of data to improve many technologies. Upgrades at home and in the workplace, range from security intelligence and smart cams to investment analysis.
AI adapts through progressive learning algorithms to let the data do the programming. AI finds structure and regularities in data so that algorithms can acquire skills. Just as an algorithm can teach itself to play chess, it can teach itself what product to recommend next online. And the models adapt when given new data.
AI analyzes more and deeper data using neural networks that have many hidden layers. Building a fraud detection system with five hidden layers used to be impossible. All that has changed with incredible computer power and big data. You need lots of data to train deep learning models because they learn directly from the data.
AI achieves incredible accuracy through deep neural networks. For example, your interactions with Alexa and Google are all based on deep learning. And these products keep getting more accurate the more you use them. In the medical field, AI techniques from deep learning and object recognition can now be used to pinpoint cancer on medical images with improved accuracy.
When algorithms are self-learning, the data itself is an asset. The answers are in the data. You just have to apply AI to find them. Since the role of the data is now more important than ever, it
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