AI: Artificial Intelligence
On behalf of the Journal, as Editor-in-Chief, it is my distinct honour and privilege to welcome you to the Journal of Theoretical and Computational Science.
The Journal of Theoretical and Computational Science aims to spread knowledge and promote discussion through the publication of peer-reviewed, high quality research papers on all topics related to Modern Scientific Techniques. The open access journal is published by Longdom Publishing who hosts open access peer-reviewed journals as well as organizes conferences that hosts the work of researchers in a manner that exemplifies the highest standards in research integrity.
Artificial intelligence (AI) makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks. Most AI examples we hear today is from chess-playing computers to self-driving cars.
The term artificial intelligence was coined in 1956, but AI has become more popular today thanks to increased data volumes, advanced algorithms, and improvements in computing power and storage.
This early work paved the way for the automation and formal reasoning that we see in computers today, including decision support systems and smart search systems that can be designed to complement and augment human abilities.
Why is artificial intelligence important?
- AI automates repetitive learning and discovery through data.
- AI adds intelligence to existing products.
- AI adapts through progressive learning algorithms to let the data do the programming.
- AI analyzes more and deeper data using neural networks that have many hidden layers.
- AI achieves incredible accuracy through deep neural networks – which was previously impossible.
- AI gets the most out of data.
AI works by combining large amounts of data with fast, iterative processing and intelligent algorithms, allowing the software to learn automatically from patterns or features in the data. AI is a broad field of study that includes many theories, methods and technologies, as well as the following major subfields:
- Machine learning
- A neural network
- Deep learning
- Cognitive computing
- Computer vision
- Natural language processing
Artificial intelligence is going to change every industry, but we have to understand its limits.
Today’s AI systems are trained to do a clearly defined task. The system that plays poker cannot play solitaire or chess. The system that detects fraud cannot drive a car or give you legal advice. In fact, an AI system that detects health care fraud cannot accurately detect tax fraud or warranty claims fraud.
In other words, these systems are very, very specialized. They are focused on a single task and are far from behaving like humans.
Our Journal emphasizes high-level research and education. Original research articles, reviews, short communications, and letters to the editors in the fields of ecotoxicology are welcome. Every effort is made to have a speedy and critical peer-review process.
We always encourage your research works under the scope of our Journal of Theoretical and Computational Science. (Tap on the link to submit your research work)
Journal of Theoretical and Computational Science