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Generally, Artificial Intelligence (aka AI) leverages computers and machines to mimic the problem-solving and decision-making capabilities of the human mind. In terms of the human approach: this is where systems think like humans and act like humans. While in terms of the ideal approach: this is where systems think rationally and also act rationally.
Today, a lot of hype still surrounds AI development, which is expected of any new emerging technology in the market. As noted in Gartner’s hype cycle (link resides outside IBM), product innovations like self-driving cars and personal assistants, follow “a typical progression of innovation.
More so, from overenthusiasm through a period of disillusionment to an eventual understanding of the innovation’s relevance and role in a market or domain.” As Lex Fridman notes here (00:15) (link resides outside IBM) in his MIT lecture in 2019, we are at the peak of inflated expectations, approaching the trough of disillusionment.
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And as conversations emerge around the ethics of AI, we can begin to see the initial glimpses of the trough of disillusionment. Some of the activities computers with artificial intelligence are designed for a variety of reasons. Such as; Speech recognition, Learning, Planning, Perception, and Reasoning.
As well as Analysis, Cloud, Computing, Knowledgebase, Problem Solving, and the ability to manipulate and move objects. Especially, by processing large amounts of data and recognizing patterns in the data. In general, from chess-playing computers to self-driving cars, AI is just everywhere!
Surprisingly, they rely heavily on deep learning and natural language processing. In particular, using these technologies, computers can be trained to accomplish specific tasks.
What Is Artificial Intelligence?
Artificial Intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans. At its simplest form, Artificial Intelligence is a field, which combines computer science and robust datasets, to enable problem-solving.
In short, Artificial Intelligence (aka AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.
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As such, it also encompasses sub-fields of machine learning and deep learning, which are frequently mentioned in conjunction with artificial intelligence. These disciplines are comprised of AI algorithms that seek to create expert systems that make predictions or classifications based on input data.
It’s also important to realize, Artificial intelligence makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks. Whereby, most AI examples that you hear about today are generally around you. Digitally, it’s an interdisciplinary science concerned with building smart machines.
These smart machines are capable of performing tasks that typically require human thought. The implications will change virtually every aspect of our world. As of today, AI is rapidly spreading throughout civilization, where it has the promise of doing everything.
From enabling autonomous vehicles that navigate the streets, and also, to make more accurate weather predictions like hurricane forecasts. On an everyday level, AI figures out what ads to show you on the web too. Whereby, it powers those friendly Chatbots that pop up when you visit an e-commerce website.
Example of an Artificial Intelligence
As I mentioned, Chatbots are good examples of AI-driven tools. Their key role is to power those friendly pop up when you visit an e-commerce website. In order to answer your questions and provide more personalized customer service as well as.
Chatbots are computer programs that simulate human conversation through voice commands, text chats, or both. Basically, a Chatbot, short for Chatterbot, is an Artificial Intelligence (AI) feature that can be embedded and used through any major messaging application.
A Chatbot is also known as a Bot, Talkbot, Chatterbot, IM Bot, Interactive Agent, or Artificial Conversational Entity. The term “ChatterBot” was originally created by Michael Mauldin, the creator of the first Verbot, Julia in 1994. As for the term “Artificial Intelligence,” it was coined in 1955 by John McCarthy, a math professor at Dartmouth College.
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In addition, AI-powered personal assistants in voice-activated smart home devices perform myriad tasks too. From controlling our TVs and doorbells to answering trivia questions and helping us find our favorite songs. So, who uses Artificial Intelligence?
As an example, did you know, jmexclusives, Google, WordPress, Netflix, and many other web-based businesses all use Artificial Intelligence to help them exist? Not to mention, Google alone employs over 70,000 employees. Of course, this is one of the advantages of artificial intelligence.
Where over 70,000 people are able to have a job that doesn’t involve mindless tasks. And that’s just the success it has had with one company. Equally important, AI helps businesses grow, develop, and allocate new resources to hire more people.
In fact, right now there are many companies out there following Google’s example and using Artificial Intelligence Software in their business plans. If you wish to become more innovative and experience more benefits affiliated with the AI Cloud Computing Technology, please Plug us in.
When did Artificial Intelligence begin?
Artificial intelligence was founded as an academic discipline in 1956, and in the years since has experienced several waves of optimism. Followed by disappointment and the loss of funding (known as an “AI winter“). And also, followed by new approaches, success, and renewed funding.
For most of its history, AI research has been divided into subfields that often fail to communicate with each other.
These sub-fields are based on technical considerations, such as;
- particular goals (e.g. “robotics” or “machine learning”)
- the use of particular tools (“logic” or artificial neural networks)
- or deep philosophical differences
- Subfields have also been based on social factors (particular institutions or the work of particular researchers).
As a matter of fact, the traditional problems (or goals) of AI research include factors such as;
- reasoning,
- knowledge representation,
- planning,
- learning,
- natural language processing,
- perception
- and the ability to move and manipulate objects.
General intelligence is among the field’s long-term goals. Whereas, approaches include;
- statistical methods,
- computational intelligence,
- and traditional symbolic AI.
Many tools are used in AI, including versions such as;
- search and mathematical optimization,
- artificial neural networks,
- and methods based on statistics, probability, and economics.
Borrowing from the management literature, Kaplan and Haenlein classify artificial intelligence into three different types of AI systems. Including, analytical, human-inspired, and humanized artificial intelligence. Analytical AI has only characteristics consistent with cognitive intelligence.
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Especially, generating the cognitive representation of the world and using learning based on past experience to inform future decisions. Moreover, human-inspired AI has elements from cognitive, emotional intelligence, and understanding human emotions.
In addition to cognitive elements, and considering them in their decision making. And in general, humanized AI shows characteristics of all types of competencies. Such as cognitive, emotional, and social intelligence. In particular, it is able to be self-conscious and is self-aware in interactions with others.
The AI field draws upon elements such as;
- computer science,
- information engineering,
- mathematics,
- psychology,
- linguistics,
- philosophy,
- and many other fields.
Uses of Artificial Intelligence
A typical AI analyses its environment and takes actions that maximize its chance of success. In particular, an AI’s intended utility function (or goal) can be simple such as; if the AI wins a game of Go, or otherwise. And or even undertakes a complex task such as; doing mathematically similar actions to the ones that succeeded in the past.
Initiating common sense, reasoning, and problem-solving power in machines is a difficult and tedious task. If the AI is programmed for “reinforcement learning“, goals can be implicitly induced by rewarding some types of behavior or punishing others. Alternatively, an evolutionary system can induce goals by using a “fitness function.”
As a matter of fact, in order to mutate and preferentially replicate high-scoring AI systems. Similarly to how animals evolved to innately desire certain goals such as finding food.
Artificial Intelligence Evolution
AI often revolves around the use of algorithms. An algorithm is a set of unambiguous instructions that a mechanical computer can execute. A complex algorithm is often built on top of other, simpler, algorithms. Generally, a simple example of an algorithm is the following (optimal for the first player) recipe for play at tic-tac-toe. For instance, if;
- Someone has a “threat” (that is, two in a row), take the remaining square. Otherwise,
- a move “forks” to create two threats at once, play that move. Otherwise,
- take the center square if it is free. Otherwise,
- your opponent has played in a corner, take the opposite corner. Otherwise, take
- an empty corner if one exists. Otherwise, take
- any of the empty squares.
AI algorithms can enhance themselves by learning new heuristics, or can themselves write other algorithms. The overall research goal of artificial intelligence is to create technology that allows computers and machines to function in an intelligent manner.
The general problem of simulating (or creating) intelligence has been broken down into sub-problems. These consist of particular traits or capabilities that researchers expect an intelligent system to display. Such as;
- Reasoning and or Problem-solving
- Knowledge Representation
- Planning and Learning
- Natural Language Processing
- Perception, General and Social Intelligence
- Graphic Content Motion & Manipulation
Machine Intelligence
In computer science, artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines. In contrast to the natural intelligence displayed by humans and other animals.
Uniquely, computer science defines AI research as the study of “intelligent agents.” In regards to any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals.
More specifically, Kaplan and Haenlein define AI as “a system’s ability to correctly interpret external data and to learn from such data. In relation to using those achievable towards achieving specific goals and tasks. Especially through flexible adaptation.” Below are Factors for the Artificial Intelligence Demand;
Technology
As technology improves, we as a race are becoming increasingly impatient. While typing emails, we are used to getting name suggestions before typing the whole name.
When using our smartphones, we prefer talking instead of typing (Siri, Cortana, Google Assistant anyone?). These are just a few variations of how AI is being used in our daily lives.
Workforce
AI will be most useful in getting computers and robots to do stuff that’s possibly too dangerous for humans. Check out Boston Dynamics, a company owned by Google, that has used AI to make robots replicate animal movements and navigate weird terrains.
Think of a forest fire, and what we can potentially achieve by making a robot access areas that are not possible for humans (We’re still far away from that, but it’s still a great implication of AI)
Healthcare
This trillion-dollar industry continues to find applications in every new technology. There are so many rural areas with no access to doctors and basic diagnostic healthcare. Imagine what could potentially happen if we’re able to teach computers to diagnose simple ailments in humans.
Efficiency
The advantages of artificial intelligence don’t end there. Another benefit of it is that it’s convenient! One way AI makes life more convenient is through the elimination of repetitive tasks. A simple example of this is scheduling tasks and meetings.
Many staffers have noted that the incorporation of artificial intelligence in their office has allowed them to set aside extra time for tasks that they deemed more important. Artificial intelligence is a branch of computer science that aims to create intelligent machines.
It has become an essential part of the technology industry. Research associated with artificial intelligence is highly technical and specialized. The core problems of artificial intelligence include programming computers for certain traits such as:
- Knowledge
- Reasoning
- Problem-solving
- Perception
- Learning
- Planning
- Ability to manipulate and move objects
Machine Learning
Knowledge engineering is a core part of AI research. Machines can often act and react like humans only if they have abundant information relating to the world. Artificial intelligence must have access to objects, categories, properties, and relations between all of them to implement knowledge engineering.
Machine learning is also a core part of AI. Learning without any kind of supervision requires the ability to identify patterns in streams of inputs, whereas learning with adequate supervision involves classification and numerical regressions.
Classification determines the category an object belongs to. Whereas, regression deals with obtaining a set of numerical input or output examples. Thereby discovering functions enabling the generation of suitable outputs from respective inputs.
AI Perception
Machine perception deals with the capability to use sensory inputs to deduce the different aspects of the world, while computer vision is the power to analyze visual inputs with a few sub-problems such as facial, object, and gesture recognition.
Robotics is also a major field related to AI. Robots require intelligence to handle tasks such as object manipulation and navigation, along with sub-problems of localization, motion planning, and mapping.
Takeaway,
Eventually, the progressive advance of technology has seen an increase in businesses moving from traditional to digital platforms to transact with consumers. One AI technique that is growing in its application and use is Chatbots.
Some examples of chatbot technology are virtual assistants like Amazon’s Alexa and Google Assistant, and messaging apps, such as WeChat and Facebook messenger. Modern machine capabilities generally classified as AI include successfully understanding human speech.
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In addition to competing at the highest level in strategic game systems. Such as chess and Go, autonomously operating cars, and intelligent routing in content delivery networks and military simulations.
Finally, we are hopeful that this article has given you some ideas to help you narrow down your Artificial Intelligence understanding. But, if you’ll need more support, you can Contact Us and let us know how we can help you. You can also share your additional information, opinion thoughts, suggestions, or questions in our comments section below.
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Notice: All content on this website including text, graphics, images, and other material is intended for general information only. Thus, this content does not apply to any specific context or condition. It is not a substitute for any licensed professional work. Be that as it may, please feel free to collaborate with us through blog posting or link placement partnership to showcase brand, business, or product.