Existing Systems and Future of Artificial Intelligence

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Existing Systems and Future of Artificial Intelligence

Introduction

Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans. Generation AI will rely on artificial intelligence to assist them through all the milestones in their lives. While many people think of AI as a futuristic technology, AI is something we encounter today in ways that some people may not even realize. For example, when you use an internet search engine, the search terms and predictive text are powered by AI.

This new generation will be much more aware of their AI interactions. They will converse with digital assistants, learn new skills from robots and be driven around in cars that are controlled by AI. Generation AI will become more independent as they grow up, thanks to assistance from AI, which will actually force them to become interdependent on the technology. Discover more about Generation AI and how AI will play a major role in milestones at each stage of life.

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”), 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).

Artificial intelligence designed on

Python is widely used for artificial intelligence, with packages for a number of applications including General AI, Machine Learning, Natural Language Processing and Neural Networks. Haskell is also a very good programming language for AI. The language’s features enable a compositional way of expressing the algorithms.

Future of Artificial intelligence

The machine can react or act like us only if they have plenty of knowledge of Human Beings. It would be impossible for us to live without computer systems. Cars, ATM machines, and everything which works automatically have a computer system inbuilt. Soon Artificial intelligence machines can do all those things that we can barely do. An important advantage of Artificial intelligence is that every work will be perfectly and precisely done. Artificial intelligence drone can replace humans in doing risky task, things like going to areas where terrorist activity is at its highest.

Although people are still in fear that it will dominate the world and replace humans. There will no job left for human to feed their family. Anything that needs human touch will be done by machines or robots. Most harmful technology of computer science is the Autonomous weapon systems; it can harm us in lot because it will do whatever a careless person wanted it to do.

Existing systems on Artificial Intelligence

Siri

Everyone is familiar with Apple’s personal assistant, Siri. She’s the friendly voice-activated computer that we interact with on a daily basis. She helps us find information, gives us directions, add events to our calendars, and helps us send messages and so on. Siri is a pseudo-intelligent digital personal assistant. She uses machine-learning technology to get smarter and better able to predict and understand our natural-language questions and requests.

Alexa

Alexa’s rise to become the smart home’s hub, has been somewhat meteoric. When Amazon first introduced Alexa, it took much of the world by storm. However, its usefulness and its uncanny ability to decipher speech from anywhere in the room has made it a revolutionary product that can help us scour the web for information, shop, schedule appointments, set alarms and a million other things, but also help power our smart homes and be a conduit for those that might have limited mobility.

Netflix

Netflix provides highly accurate predictive technology based on customers’ reactions to films. It analyses billions of records to suggest films that you might like based on your previous reactions and choices of films. This tech is getting smarter and smarter by the year as the dataset grows. However, the tech’s only drawback is that most small-labeled movies go unnoticed while big-named movies grow and balloon on the platform.

Google AI

Google AI can process commands from a user, make phone calls silently in the background and handle natural conversation to request information or book appointments. Some critics are reserved or opposed to the directions Google is taking with AI. Because the Assistant software does not declare itself as a digital assistant, critics say it deceives answering parties who may not wish to speak to an AI. Privacy is also a concern with Google’s AI updates. For example, because Assistant no longer requires users to say “OK, Google” to alert the Assistant before issuing commands, critics argue that this change could enable constant data mining.

Proposed or upcoming AI systems

1. Natural language generation

Natural language generation is an AI sub-discipline that converts data into text, enabling computers to communicate ideas with perfect accuracy. It is used in customer service to generate reports and market summaries and is offered by companies like Attivio, Automated Insights, Cambridge Semantics, Digital Reasoning, Lucid works, Narrative Science, SAS.

3. Virtual agents

A virtual agent is nothing more than a computer agent or program capable of interacting with humans. The most common example of this kind of technology are chatbots. Virtual agents are currently being used for customer service and support and as smart home managers. Some of the companies that provide virtual agents include Amazon, Apple, Artificial Solutions, Assist AI, Creative Virtual, Google, IBM, iSOFT, OpenAI and Microsoft.

4. Machine learning platforms

These days, computers can also easily learn, and they can be incredibly intelligent! Machine (ML) is a sub-discipline of computer science and a branch of AI. Its goal is to develop techniques that allow computers to learn. By providing algorithms,APIs (application programming interface), development and training tools, big data, applications and other machines, ML platforms are gaining more and more traction every day. They are currently mainly being used for prediction and classification. Some of the companies selling ML platforms include Amazon, Fractal Analytics, Google, and Microsoft.

5. AI-Optimized Hardware

AI technology makes hardware much friendlier. Through new graphics and central processing units and processing devices specifically designed and structured to execute AI-oriented tasks You can get access to this technology through Alluviate, Cray, Google, IBM, Intel, and Nvidia.

Basic Types of Artificial Intelligence

Narrow AI: Sometimes referred to as ‘Weak AI,’ this kind of artificial intelligence operates within a limited context and is a simulation of human intelligence. Narrow AI is often focused on performing a single task extremely well and while these machines may seem intelligent, they are operating under far more constraints and limitations than even the most basic human intelligence.

Few examples of Narrow AI include:

Google search
Image recognition software
Siri, Alexa and other personal assistants
Self-driving cars
IBM’s Watson

Artificial General Intelligence (AGI): AGI, sometimes referred to as ‘Strong AI,’ is the kind of artificial intelligence we see in the movies, like the robots from Westworld or Data from Star Trek: The Next Generation. AGI is a machine with general intelligence and, much like a human being, it can apply that intelligence to solve any problem.

a). Advantages of Artificial Intelligence

Error reduction.
Difficult exploration (use in Data mining).
Daily application.
Digital assistant.
Repetitive jobs.

b). Disadvantages of Artificial intelligence

High cost.
No Replicating Humans.
No Improvement with Experience.
No Original creativity.
Unemployment among Humans.

Conclusion

In its short existence, AI has increased understanding of the nature of intelligence and provided an impressive array of applications in a wide range of areas. It has sharpened my understanding of human reasoning, and of the nature of intelligence in general. At the same time, it has revealed the complexity of modelling human reasoning providing new areas and rich challenges for the future.

Abstract

The field of artificial intelligence (AI) has shown an upward trend of growth in the 21st century (from 2000 to 2015). The evolution in AI has advanced the development of human society in our own time, with dramatic revolutions shaped by both theories and techniques. However, the multidisciplinary and fast-growing features make AI a field in which it is difficult to be well understood. In this paper, we study the evolution of AI at the beginning of the 21st century using publication metadata extracted from 9 top-tier journals and 12 top-tier conferences of this discipline. We find that the area is in sustainable development and its impact continues to grow. From the perspective of reference behaviour, the decrease in self-references indicates that the AI is becoming more and more open-minded. The influential papers/researchers/institutions we identified outline landmarks in the development of this field. Last but not least, we explore the inner structure in terms of topics’ evolution over time. We have quantified the temporal trends at the topic level and discovered the inner connection among these topics. These findings provide deep insights into the current scientific innovations, as well as shed light on funding policies.