AI- the new age(part-1)

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.

The significance of Artificial intelligence:

AI is important because it can give enterprises insights into their operations that they may not have been aware of previously and because, in some cases, AI can perform tasks better than humans. Particularly when it comes to repetitive, detail-oriented tasks like analyzing large numbers of legal documents to ensure relevant fields are filled in properly.

“[AI] is going to change the world more than anything in the history of mankind. More than electricity.”— AI oracle and venture capitalist Dr. Kai-Fu Lee, 2018.

Well they say only change is constant and for that matter AI’s change is quite in progressive mode. Artificial intelligence is like electricity, everyone in going to use it one way or another.

Ways in which AI is impacting quiet constantly.

1. Transportation:

Although it could take a decade or more to perfect them, autonomous cars will one day ferry us from place to place.

2. Manufacturing:

AI empowering robots work alongside humans to perform a limited range of tasks like assembly and stacking, and predictive analysis sensors keep equipment

3. Healthcare:

In the comparatively AI-nascent field of healthcare diseases or more quickly and accurately diagnosed, drug discovery is sped up and streamlined, virtual nursing assistants monitor patients and big data analysis helps to create a more personalized patient experience.

4. Education:

Textbooks is harnessing AI, early-stage virtual tutors assist human instructors and facial analysis gauges the emotions of students to help determine who’s struggling or bored and better tailor the experience to their individual needs.

5. Media:

Journalism is harnessing AI, too and will continue to benefit from it. Blooming uses Cyborg technology to help make quick sense of complex financial reports.

6. Customer service:

Last but not least, Google is working on an AI assistant that can place human-like calls to make appointments at, say and your neighborhood hair saloon. In addition to words, the system understands context and nuance.

AI and big data:

Big data is most assuredly here to stay at this point, and AI (artificial intelligence) will be in high demand for the foreseeable future. Data and AI are merging into a synergistic relationship, where AI is useless without data, and mastering data is insurmountable without AI.

By combining the two disciplines, we can begin to see and predict upcoming trends in business, technology, commerce, entertainment, and everything in between.

How AI is used in big data

The internet now provides a level of concrete information about consumer habits, likes and dislikes, activities, and personal preferences that was impossible a decade ago. Social media accounts and online profiles, social activity, product reviews, tagged interests, “liked” and shared content, loyalty/rewards apps and programs, and CRM (customer relationship management) systems all add potentially insightful data to the big data pool.

Collecting consumer information

Regardless of the industry, one of AI’s greatest assets is its learning ability. Its capacity to recognize data trends is only useful if it can adapt to changes and fluctuations in those trends. Through identifying outliers in the data, AI knows what pieces of customer feedback are considered significant and can adjust as necessary.

AI’s ability to expertly work with data analytics is the primary reason why artificial intelligence and big data are now seemingly inseparable. AI machine learning and deep learning are pulling from every data input and using those inputs to generate new rules for future business analytics. Problems arise, however, when the data being used is not good data.

Business analytics

According to Forbes, the most recent research indicates that a combination of AI and big data can automate nearly 80% of all physical work, 70% of data processing work, and 64% of data collection tasks. This suggests that the two concepts have the potential to tremendously affect the workplace, in addition to their contributions to marketing and business efforts.

Fulfillment and supply chain operations, for instance, are both particularly reliant on data, so they’re turning to the developments within AI to provide real-time insights on customer feedback. Through this, businesses can form their finances, strategies, and marketing around the flow of new information.

Essentially, there must be an agreed-upon methodology to data collection (mining) and data structure before running the data through a machine learning or deep learning algorithm. This is where professionals with degrees in business data analytics come in. They will be highly prized by companies that are serious about getting the most out of their data analytics.

There are three main types of AI based on its capabilities – weak AI, strong AI, and super AI.

• Weak AI – Focuses on one task and cannot perform beyond its limitations (common in our daily lives)
• Strong AI – Can understand and learn any intellectual task that a human being can (researchers are striving to reach strong AI)
• Super AI – Surpasses human intelligence and can perform any task better than a human (still a concept)