AI changes the World!
AI role in Future --- AI changes the world
(AI has one rule that rules them all: think simple.)
AI, or artificial intelligence, seems to be on the tip of everyone’s tongue these days.
AI appearing more and more as one of the most in-demand areas of expertise for job seekers. AI is already at work all around us, impacting everything.
Data shows that the use of AI in many sectors of business has grown by 270% over the last four years.
Before we do a deep dive on the ways in which AI will impact the future of work, it’s important to start simple: what is AI?
What is AI?
Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems
Artificial intelligence is “the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings.”
“AI” has become a catchall term to describe any advancement in computing, systems and technology in which computer programs can perform tasks or solve problems that require the kind of reason we associate with human intelligence, even learning from past processes.
So Specific applications of AI include expert systems, natural language processing, and speech recognition and machine vision.
This ability to learn is a key component of AI. Algorithms “set of instructions,” a formula for processing data often associated with AI.
AI Is becoming standard in all businesses, not just in the world of tech
90% of leading businesses already have ongoing investment in AI technologies. More than half of businesses that have implemented some manner of AI-driven technology report experiencing greater productivity.
AI is likely to have a strong impact on certain sectors in particular:
C. Cyber security
AI can have a big impact on the job search
AI is also a great place to focus your energy if you are looking to up skill in your career, or make your professional profile more competitive in the job market.
AI and machine learning are at the top of many lists of the most important skills in today's job market. Jobs requesting AI or machine-learning skills are expected to increase by 71% in the next five years.
What a AI engineer do?
An AI engineer builds AI models using machine learning algorithms and deep learning neural networks to draw business insights, which can be used to make business decisions that affect the entire organization. These engineers also create weak or strong AIs, depending on what goals they want to achieve.
Responsibilities of an AI Engineer
As an AI engineer, you need to perform certain tasks, such as develop, test, and deploy AI models through programming algorithms like random forest, logistic regression, linear regression, and so on.
Convert the machine learning models into application program interfaces (APIs) so that other applications can use it
Build AI models from scratch and help the different components of the organization (such as product managers and stakeholders) understand what results they gain from the model
Build data ingestion and data transformation infrastructure
Automate infrastructure that the data science team uses
Perform statistical analysis and tune the results so that the organization can make better-informed decisions
Set up and manage AI development and product infrastructure
Be a good team player, as coordinating with others is a must
Skills needed to be an AI engineer
Skills related to AI, ML, and data science require data analysis tasks and exploring top platforms.
a. Build advanced-level algorithmic techniques.
b. Learn how to analyze data.
c. Master the machine learning capabilities.
1. Programming Language --- To become expert in Machine learning it’s important to grow your experience with programming languages like Python, C++, Java, R etc.
Python and Scala are common languages in machine Learning’s.
2. Linear Algebra, Probability, and Statistics
3. Algorithms and Frameworks
If you are tech savvy, it would be wise to dive deep and learn as much as you can about interacting in the AI space.
AI will probably not make human workers obsolete, at least not for a long time.
To put some of your fears to bed: the robots are probably not coming for your jobs, at least not yet.
After all, as technology has advanced, many tasks that were once executed by human hands have become automated.
But A recent paper published by the MIT Task Force on the Work of the Future entitled “Artificial Intelligence And The Future of Work,” looked closely at developments in AI and their relation to the world of work.
Based on these factors and many others, the MIT CCI paper argues that we are a long way from reaching a point in which AI is comparable to human intelligence, and could theoretically replace human workers entirely.
There are many other factors that could limit runaway advancement in AI. AI often requires “learning” which can involve massive amounts of data, calling into question the availability of the right kind of data, and highlighting the need for categorization and issues of privacy and security around such data. There is also the limitation of computation and processing power. The cost of electricity alone to power one supercharged language model AI was estimated at $4.6 million.
Also Humans, however, possess “generalized intelligence,” with the kind of problem solving, abstract thinking and critical judgement that will continue to be important in business. Human judgement will be relevant, if not in every task, then certainly throughout every level across all sectors.
Rather than considering that AI will be causes the obsolescence of human labor, accept that AI will continue to drive massive innovation that will fuel many existing industries and could have the potential to create many new sectors for growth, ultimately leading to the creation of more jobs.
Conclusion:--To better prepare for the future society in which artificial intelligences (AI) will have much more pervasive influence on our lives, a better understanding of the difference between AI and human intelligence is necessary. Human and biological intelligence cannot be separated from the process of self-replication.