Artificial Intelligence or AI

Artificial Intelligence or AI: – It refers to the simulation of human intelligence in machines especially computer systems that are programmed to think like humans and mimic their actions. AI makes it possible for machine to learn from experience, adjust to new inputs and perform human-like tasks.

Specific applications of AI include expert systems, natural language processing (NLP), and speech recognition and machine vision.

• AI programming focuses on three cognitive skills

Learning processes This aspect of AI programming focuses on acquiring data and creating rules for how to turn the data into actionable information.

Reasoning processes This aspect of AI programming focuses on choosing the right algorithm to reach a desired outcome.

Self-correction processes This aspect of AI programming is designed to continually fine-tune algorithms and ensure they provide the most accurate results possible.

• Strong AI vs. weak AI

AI can be categorized as either weak or strong.

Weak AI, also known as narrow AI, is an AI system that is designed and trained to complete a specific task. Industrial robots and virtual personal assistants, such as Apple’s Siri, use weak AI.

Strong AI, also known as artificial general intelligence (AGI), describes programming that can replicate the cognitive abilities of the human brain. When presented with an unfamiliar task, a strong AI system can use fuzzy logic to apply knowledge from one domain to another and find a solution autonomously. In theory, a strong AI program should be able to pass both a Turing test and the Chinese room test.

• Applications of Artificial Intelligence (AI)

• Image recognition
• Speech recognition
• Chat-bots
• Natural language generation
• Sentiment analysis
• Healthcare
• Business
• Manufacturing
• Banking
• Finance
• Education
• Transportation

• Types of Models

Deep learning

Deep learning is an artificial intelligence function that imitates the workings of the human brain in processing data and creating patterns for use in decision making

Machine Learning

Machine learning focuses on the development of computer   programs that can access data and use it learn for themselves. The primary aim is to allow the computers learn automatically without human intervention or assistance and adjust actions accordingly.

Neural Networks

A neural network is either a system software or hardware that works similar to the tasks performed by neurons of human brain. Neural networks include various technologies like deep learning, and machine learning as a part of Artificial Intelligence (AI).

• Programming Languages for building models

• Python
• TensorFlow
• Java
• C

• AI as a service (AIaaS)

Because hardware, software and staffing costs for AI can be expensive, many vendors are including AI components in their standard offerings or providing access to artificial intelligence as a service (AIaaS) platforms. AIaaS allows individuals and companies to experiment with AI for various business purposes and sample multiple platforms before making a commitment.

Popular AI cloud offerings include the following:

• Amazon AI
• IBM Watson Assistant
• Microsoft Cognitive Services
• Google AI
• Types of AI
• Reactive machinesThese AI systems have no memory and are task specific. An example is Deep Blue, the IBM chess program that beat Garry Kasparov in the 1990s. Deep Blue can identify pieces on the chessboard and make predictions, but because it has no memory, it cannot use past experiences to inform future ones.
• Limited memory These AI systems have memory, so they can use past experiences to inform future decisions. Some of the decision-making functions in self-driving cars are designed this way.
• Theory of mindTheory of mind is a psychology term. When applied to AI, it means that the system would have the social intelligence to understand emotions. This type of AI will be able to infer human intentions and predict behavior, a necessary skill for AI systems to become integral members of human teams.
• Self-awareness In this category, AI systems have a sense of self, which gives them consciousness. Machines with self-awareness understand their own current state. This type of AI does not yet exist.

• HOW AI CAN BE DANGEROUS

1. The AI is programmed to do something devastating:Autonomous weapons are artificial intelligence systems that are programmed to kill. In the hands of the wrong person, these weapons could easily cause mass casualties. This risk is one that’s present even with narrow AI, but grows as levels of AI intelligence and autonomy increase.
2. The AI develops a destructive method for achieving its goal: If you ask an SMART car to take you to the airport as fast as possible, it might get you there chased by helicopters and covered in vomit, doing not what you wanted but literally what you asked for. If a super intelligent system is tasked with an ambitious geoengineering project, it might wreak havoc with our ecosystem as a side effect, and view human attempts to stop it as a threat to be met.

• FUTURE OF AI

We have already seen a self-driving car but with time they will become even more precise in their driving. And who knows, we may come to see a whole city only with self-driving public transport. This is the time that AI vision is getting stronger and stronger and we are the pilots of that growth. We construct how it will be used – for weapons or medicine, for our everyday routine or for space missions, it all depends on us.

With the evolution of technology, Artificial Intelligence is pushing against its peak again. Now we have more powerful hardware on which we can perform a more complex task and therefore we can create models for different tasks.

The next revolution in the field of AI would be when AI starts dreaming like as humans.

BY SAVIT PRIYA: