How Artificial Intelligence And Robots Are Benefiting From Data Science

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How Artificial Intelligence And Robots Are Benefiting From Data Science

Techno Dairy

@rohitrohi

March 2, 2023

Data Science & AI Community

282

By Using ground-breaking (AI), automation (ML), and deep learning, big data combined with data science are poised to usher in a digital revolution. The core underpinning data science is delving through enormous datasets to draw out valuable information. The key ingredient altering everything around us quickly is the insights data scientists and analysts derive from vast amounts of data. The industry's institutions and organizations now utilize data science tools to foster innovation and change.

Data analysts, ML designers, data scientists, big data experts, and other professionals are finding new and interesting job prospects as more and more businesses turn to data science to improve their organizational architecture. So, the opportunity is now if you want to begin a data science profession.

Data science and Artificial Intelligence

Data science, artificial intelligence, and machine learning are all related areas. Machine learning is a form of artificial intelligence that focuses on teaching machines how to "learn" via sophisticated algorithms and perform particular tasks while enhancing performance through experience. Whereas ai technology is a broad collective term that includes a multitude of uses, right from text processing to robotics, machine learning belongs to the category of artificial intelligence. Data science is a subfield of computer science that primarily deals with extracting insightful information from huge datasets using a combination of mathematical, machine learning, statistical, and data engineering techniques.

Consider intelligent personal assistants, including Siri, Alexa, etc. Cortana as an illustration. These intelligent assistants, known as "Narrow AI," can converse with you and carry out a small number of tasks, such as playing music for you, providing you with information about the day's weather, or even doing some light shopping. Yet because they have only been specifically "taught" to do so, as we previously stated, they can only accomplish "restricted" activities. Future data scientists may be able to modify these assistants' algorithms into more complicated ones (General AI). At this point, intelligent assistants could carry out more intricate jobs with a great deal more accuracy than humans.

Data science And Robotics

Robotics has undoubtedly advanced significantly with the development of data science. Two significant problems plagued researchers in the early stages of development: first, predicting every move a robot would make, and second, lowering the computational cost of real-time vision tasks.

Robots could perform specific tasks, but scientists could not foresee their next step. The operation was arduous because a robot must be reprogrammed each time a new functionality was added. Another significant problem with robots is that they can only conceptualize the world as a series of ones and zeros, versus humans using their special vision to comprehend the world around them. Hence, completing real-time visual challenges.

Data scientists are learning more about data science as a whole as they work to create intelligent robots by utilizing AI and ML. Thanks to AI and ML, data scientists and statisticians might process, examine, and interpret big datasets much more quickly than ever before.

For example, the MIT Computer Science Machine might process massive amounts of data and generate improved prediction models between 2-12 hours, when data scientists would need months to do so manually.

Consequently, there is a close symbiotic interaction between data science, AI, and robotics. Each strengthens one to power cutting-edge tools and technology that make life easier than ever. Data science, AI, or ML work together to create self-driving cars, intelligent personal assistants, robot nurses and doctors, and so much more. There will be more in the future!

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