Big Data Is Overrated

//Big Data Is Overrated

Big Data Is Overrated

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Big Data Is Overrated

Big data is a huge thing nowadays. Furthermore, big data is used to create beautiful correlations of data. Indeed, you need to understand the math behind it in order to know what you’re doing.

Big data is everywhere (in our cars, our homes, our cities). There are investors that want to invest in big data software. Many CEOs are interested in “big data initiatives.” Machine learning is used to find patterns, so it can tell you things, recognize objects, predict something, and so on. So, CEOs wants to use this technology to learn and discern meaning.

Nvidia said that deep learning is the “use of massive clusters of GPUs to teach computers new skills.” Deep learning can be defined as “a subfield of machine learning concerned with algorithms inspired by the structure and function of the brain called artificial neural networks”. Nvidia also said that deep learning is a field of machine learning that “uses many-layered Deep Neural Networks (DNNs) to learn levels of representation and abstraction that make sense of data such as images, sound, and text.”

Nvidia’s Huang turned his own hardware company into one that is prepared for deep-learning commoditization. Nvidia makes GPUs (Graphics processing units), which were usually reserved for high-tech gaming and visual design.

Huang will succeed by powering the future making powerful GPUs for deep learning. GPUs make the training of the deep-learning model faster because it uses parallel computing.

Big data, machine learning, and deep learning aren’t overrated on their own.

In five years, it’s not going to be possible to build a big data startup. For example, there is an Apple’s acquisition of a “dark data” (a term referring to unstructured data) company for $200 million, and an Amazon’s $20 million purchase of machine learning and artificial intelligence security company harvest.ai, so it is the sign that there won’t be another big tech company.

So, Amazon Web Services’ algorithms are able to build other algorithms to make sense of your big data.

Actually, Amazon just opened up an entire consultancy service. Furthermore, Amazon machine learning experts with customers looking to build solutions using the AI tech. Amazon launched Amazon Recognition, which is a deep learning-based image recognition platform for real-time face recognition and is able to recognize text in images.

Furthermore, an algorithm may be able to cover sports, but it cannot clone or generate whimsy or humor, which is what makes writing enjoyable to read. Nowadays, computers are not able to have full conversations, and computers don’t have the creativity to come up with ideas.

Actually, interpreting the results of big data will soon become far more important than the big data’s algorithm.

An algorithm is able to ask questions on a high level, but not at the same level of a human. The CEOs of the future will understand how to interpret results in order to ask the next question and take those questions to the next level.

A machine will never have our gut that will always be part of decision making. That gut cannot necessarily correlate to a piece of data. Machines don’t have that gut for your future success.

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By |2019-03-15T19:30:21+00:00October 1st, 2018|Categories: Blog|Tags: , , , , , , |0 Comments

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