Let’s find out how do AI Developers cognize and employ the solutions and benefits of AI in their applications!Artificial intelligence handles data-intensive workloads from data preparation to refined training models. It requires purpose-built servers, simple classification, and pattern recognition tasks and systems capable of using historical data to make predictions. Machine learning advanced in the 21st century bringing many relevant breakthroughs like self-driving cars, virtual assistants like Alexa and Siri. Narrow or weak AI with savant-like skills to demonstrate human-level intelligence and consciousness is still a work in progress.
The emergence of artificial super-intelligence will change humanity, but it’s not happening soon. Here are the types of AI leading up to that new reality.
Such algorithms lack memory and are reactive. These offer the same output even after being given a specific input. Machine learning models that use this type of AI – are effective for pattern recognition tasks. But they are incapable of analyzing scenarios that include imperfect information or historical understanding.
Algorithms in limited memory machines work in proportion to the human brain. These are capable of handling complex classification tasks and use historical data to make predictions. Example: Autonomous driving. Limited machines come with narrow intelligence as they lag behind human intelligence in many respects. They require training data to learn and behave.
Theory of Mind
This type of AI is capable of understanding human motives and delivers personalized results based on individual needs. Theory of mind is also known as artificial general intelligence (AGI). It can contextualize information and generalize knowledge to resolve varied problems. It also incubates the ability to detect human emotions and empathize with people (a part of sentiment analysis)
This type of artificial intelligence considers the mental state of other entities, as well itself. It is capable of surpassing human cognition by creating more intelligent versions of itself.
|Applications||Types of Models||Software/Hardware for Training and Running Models||Programming Languages for Building Models|
|Image Recognition||Deep Learning||GPU’s||Python|
|Speech Recognition||Machine Learning||Parallel Processing Tools (Like Spark)||TensorFlow|
|Chatbots||Neural Networks||Cloud Data Storage and Computing Platforms||Java|
|Natural Language Generation||C|
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