Emerging Technologies
What is Emerging Technology? Emerging technology is a term generally used to describe a new technology, but it may also refer to the continuing development of existing technology. The term commonly refers to technologies that are currently developing or that are expected to be available within the next five to ten years. Emerging technologies can help organizations scale on demand, improve resiliency, minimize infrastructure investments and deploy solutions rapidly and securely. Emerging Technologies that are creating, or are expected to create, significant social or economic effects and also Creating New Ways to Solve Business Problems
Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, speech recognition, and machine vision. Characteristics/meaning of AI
Artificial Intelligence having three stages:
Artificial Narrow Intelligence [ANI] is limited to one or two functional areas for recognizing an object, it is not self-aware or self-conscious, and it appears to be making decisions; but it is the statistic/maths in action in the background. Artificial Narrow Intelligence [ANI] Examples
Artificial General Intelligence covers more than one functional area, such as reasoning, problem-solving, abstract thinking, etc. Artificial General Intelligence [AGI] Examples
Artificial Super Intelligence [ASI] is expected to surpass human intelligence in 2050. Artificial Super Intelligence [ASI] Examples
Some Applications of Artificial Intelligence
Data Science is the field of study that deals with Modern Scientific Techniques, Statistical Methods, and algorithms to derive insights from vast volumes of data. Data science 25 years ago referred to gathering and cleaning datasets and then applying statistical methods to that data. In 2018, data science grew to a field that encompasses data analysis, predictive Analytics, data mining, business intelligence, machine learning, deep learning, and so much more. The data Science Lifecycle includes five stages, and it starts from the Data Discovery stage. Data Science Lifecycle in Details
In the Data Science world, there are different Languages, but Python is the most popular language Different Roles in Data Science These are different roles in the Data Science field The data Scientist role is the most popular, and it requires multiple Technical Skills In-Demand Technical Skills for Data Scientists At least below Technical Skills required to become a Data Scientists In-Demand Technical Skills in Details for Data Scientists
1. Programming Skill
Python Programming Language Details
2. Machine Learning
Machine Learning Details
3. Mathematics and Statistics
4. Analytical Tools
5. Data Visualization
6. Data Wrangling / Data Cleaning
7. Business Acumen and Business Knowledge
Conclusion
Emerging technologies are the up-and-coming technologies that are either new or in the developing stages. The term generally implies technologies that are to be available in the next five to ten years.
Some examples of such technologies in 2023 are AI, Data Science, ML, Robotic Process Automation, Deep Learning, Blockchain, IoT, VR, AR, Mixed Reality, Cloud computing, and many more. Today, we have discussed the role of artificial intelligence, machine learning, and Data science in depth.
If you are also looking forward to being ahead of the curve by integrating these technologies to your enterprise’s services, our Digital Enterprise Solutions can help you build robust systems that are future-ready.
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