- Artificial intelligence
- Computational neuroscience and bioscience
- Cloud computing
- Decision support systems
- Evolutionary computing
- Human computer interface
- Information retrieval
- Intelligent agent and web applications
- Intelligent business computing
- Intelligent control and automation
- Intelligent fault diagnosis
- Intelligent sensor networks
- Knowledge discovery and data mining
- Next generation Internet
- Machine learning theory and methods
- Pattern recognition
- Reasoning and expert systems
- Soft computing
- Speech, image, and video processing
- The Internet of things
- Virtual reality and human-computer Interaction
Machine Learning and A.I:
It has been quite some time since artificial intelligence is making headlines owing to a plethora of applications which could be derived from it. The technology could be enabled to allow computers to read, see, listen and even respond to human queries. However, recent times have made A.I. be quite a buzzword. A.I. is powered by the technologies of machine learning.
Machine learning is essentially an ability of a computer to learn with or without human interference. This is done by analyzing data and tracking repeating patterns. Machine learning is changing the way companies perform and interact with their customers as well meet their needs easily.
In the simplest of terms, a blockchain refers to an append-only transaction ledger. This ledger can be used to write new forms of information but the previously written information cannot be edited, adjusted or changed. This is made possible with cryptography to link the newly added block.
Bitcoin was created by a group of people referred to as Satoshi Nakamoto. Since then, it has become something much bigger. Previously, it had been used only in the field of generating digital currency or cryptocurrency. However, the technology could be used in various other areas. There are numerous reasons for Blockchain’s popularity, such as:
- Being consensus-driven
- Highly secure owing to cryptography implementation
- Can be publicized unhesitatingly
Cognitive technology lies in the same basket as machine learning and deep learning. However, it is powered by a much larger concept. Cognitive technology is powered by NLP or Natural Language Processing and speech recognition. This is a form of technology which mimics the functions of the human brain on numerous levels which include data processing, data mining, pattern recognition etc.
The technology could be made even more mainstream in the years upcoming via implementing it in the fields of automation, information technology etc. The various mainstream uses of cognitive technology are:
- Application in the supercomputers
- Uses in the business sector
- In media streaming services to generate user recommendations.
Humanized Big Data:
Big data is essentially a technology which collects and analyzes data created from a plethora of sources which include the IoT, advanced machines constantly sending and receiving data, alerts, maintenance etc. Collecting and analyzing, which is the greatest strength of Big Data, also forms to be its greatest weakness. It is difficult to derive concrete action guidelines or actionable meaning from a large heap of data.
This is what led towards humanized big data. Humanizing big data refers to collecting or accumulating data in a manner in which non-data scientists too can infer clear answers from. They can then use this data to make their daily decisions. However, humanizing big data isn’t something which can be automated.
The human element is crucial in understanding the data. This is something which is being researched. Big data is being developed so that a soulless technology can replace the human element in the process.