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Today, we are talking about the impact of artificial intelligence (AI) – positive or negative – and how it will surpass the human workforce.
The possibilities of AI are numerous but everything depends on big data. Big data is still as relevant as it was 10 years ago as it is still underutilized.
In the world of science fiction, AI systems often overpower human civilization. Similarly, artificial intelligence is already predominant in the real-world around us. Think about Google, Facebook, and Amazon who are changing the game with AI discoveries.
To elaborate – Facebook’s facial recognition system captures massive data about existing users and uses this information for face recognition. Similarly, Google’s self-driving cars capture data from its surroundings and process this data to make intelligent driving decisions on the road.
These accomplishments are because of the massive amounts of data they have without much fanfare.
Artificial Intelligence is a replica of human intelligence functions by machines. AI application includes- speech recognition, planning, learning, and problem solving. To make machines smart, we need a lot of data to empower them to do human-like thinking and make decisions.
Data science is the extraction of insights from huge dumps of data. It uses mathematics, computer programming, machine learning and data engineering skills to analyze and predict business trends.
A data science expert then applies these statistics, programming, and mathematics to solve complex data problems and bring out hidden insights relevant to a business.
This means data scientists help AI to find out meaningful information and solutions to problems by correlating data patterns from huge piles of data more efficiently.
Remember Herbert Simon predicted in the 60s that “machine will be capable, within twenty years, of doing any work a man can do.” Well, he was wrong. Why you ask?
The main reason is that businesses haven’t figured out how to utilize or understand their data. This is where data scientists play a crucial role. They gather extremely massive and unstructured datasets and analyze them to draw an understandable conclusion. AI needs to inhabit this skill to manipulate data for business benefit.
As of now, data scientists are forced to write custom codes and detect relevant predictions by generating thousands of variations and building models through intuitive interfaces. Artificial intelligence has the potential to automate menial data science tasks and empower them to transit from routine coding to adding real-value to business challenges.
AI will help data scientists generate millions of variations of models by applying several prediction features and creating simulations to choose the best one.
An automated multi-faceted decision process will outperform a single algorithm by monitoring, iterating, and testing data quality as they become available and reported wisely in real time.
With AI, lower-level steps in raw data preparation, cleansing and checking for accuracy will be automated. However, AI still needs human judgment to turn raw data into an actionable insight.
AI-based engineering can automate data visualization, but making sense of the available data is the core task of data scientists.
As a result, AI needs data scientists and vice versa to enhance human problem-solving skills. AI is rightfully termed as an intelligent assistant to data scientists, allowing them to play with complex data simulations.
Lymbyc, being the world's first virtual analyst has proven its mettle in the industry . Be it the "Most innovative Data science Product" by Aegis or "the top 10 emerging Analytics startups in India to watch out for in 2018" by Analytics India Magazine, Lymbyc is making heads turns and making headlines