The Next Future Powered By Deep Learning

The Next Future Powered By Deep Learning

Deep learning is not unknown to you. How, you ask?

Think back to the last time you were scrolling through Netflix or YouTube’s homepage. You might have had no issue finding what you wanted to watch next because of the exclusively curated ‘Suggested for you’ list. You might have then clicked on something and found that it fits your interests and likes almost perfectly.

Have you ever wondered how Netflix could so accurately (read: eerily) note your interests and present recommendations for you? Or, have you wondered about how Tesla's autopilot feature of navigating and lane changing worked?

If noticed closely, you might wonder how a machine built like that could work so much like… a human being would?

All of this is possible because of artificial intelligence or, more specifically, deep learning.

We are in a world where we are increasingly dependent on technology. This is to help us progress in our work and entertainment. Therefore, it’s not just data scientists that benefit from this seemingly complex concept.

It’s time for us to understand this better.

What is deep learning?

Deep learning is a subfield of machine learning, which itself comes under artificial intelligence. We can consider it as an imitation of human thought and processing. These mechanisms allow machines to make decisions and predict outcomes as human beings would.

Thanks to deep learning, machines can mimic how we gain knowledge and synthesize it to do tasks that we would normally do using our intelligence - all this with incredible accuracy.

Deep learning involves machines acquiring access to a huge amount of training data and skills sans the involvement and interference of human beings.

Years of studying the way our brains work has inspired the development of complex algorithms that can make machines process information a little closer to the way humans do.

A computer’s computing capabilities to make real-time decisions among the choices presented is very similar to the way neural networks are created and maintained in our brains. This is what we call artificial neural networks.

The human brain is wired in a manner that allows us to typically learn new things by either repetition or associating something new to something we have already learned and experienced.

This ‘learning based on past experiences’ is what artificial intelligence machines using deep learning rely on as well.

Deep learning algorithms perform a certain task repeatedly to achieve an improved outcome each time so that an artificial neural network that is created is strengthened.

Why do we call it deep learning?

This is because deep learning employs multiple layers -- three or more layers -- in its neural network.

Neural networks create a brain simulation which allows deep learning algorithms to learn from large amounts of data. Stacked in multiple layers, these algorithms allow the learning process to be more optimized, refined and accurate.

What does this mean for us?

We are moving towards an era that is revolutionary in the truest sense because deep learning has enabled us to develop machines and tools that better understand how we work and what we want. More and more machines can do what human beings do sitting behind their desks all day.

Contrary to popular belief, this allows us to increase our productivity by reducing workload by half, accelerating work processes, delegating repetitive prediction and calculation-based tasks to machines, and reducing the frequency of human-made errors in processing and creating.

Allowing this level of access to data will only help us amplify the level of output exponentially because we will have managed to “train” machines to analyze raw data and “predict” outcomes that are useful to us without any need for further human intervention.

What are the applications of deep learning?

We live in a world where AI is making its presence known in every arena. Now, we are approaching a future that might be run wholly by the power of deep learning. This means we have to upgrade our approach to solving issues around us by making full use of the capabilities of artificial intelligence.

Tooliqa, AnyClip, and Neuromation do exactly this- using the power of AI, machine learning and deep learning to build tools that can stand shoulder to shoulder with us in tackling complex multi-layered real-world problems.

Thanks to the accessibility and unending uses of AI, and particularly deep learning, processes like 3D reconstructing simplifying 3D modelling in design, surveying and analyzing have never been easier. These benefits designers, architects and every other individual involved in this field because it saves time and effort that can be redirected towards the execution and completion of projects.

We are improving the quality of services that innovators have already developed (voice-activated machines, digital assistants, predictive recommendations online etc.) because of daily advancements in this direction. We are also making big strides in technology that is only emerging (self-driving vehicles and facial recognition).

For example, deep learning allowed us to create human-like chatbots that have helped many millions cope with the stresses of the pandemic early on. How? By mimicking the tactics of a support person and directing people to more resources, thanks to their access to huge amounts of data.

The face of healthcare has been changing rapidly with the implementation of deep learning mechanisms for the detection of disease and the personalization of medication. As fairly recent as this technology is, it is something people the world over are keenly observing to make the most out of.

What does the future look like?

We are only beginning to see what deep learning can bring to the table in every other conceivable field like entertainment, industry regulations, marketing and finance, and customer experience.

We hold this exciting prospect in our hands that can have far-reaching effects. The future is inconceivable without deep learning.

We cannot imagine a world without automatic translations or virtual assistants since they are already so integral to our lives. In the past, the concept of a world that isn’t fully run by humans seemed as far-fetched as being able to walk on air. But it is not so anymore.

The existence of AI in everyday items, along with the rapid growth of deep learning mechanisms only proves this.

This is just the beginning. Machines are only going to keep refining their learning processes in the years to come. In the process, we might have to accept that they’d probably know more than we fathom.

Also read: Deep Learning and AI: Applications | Insights - Tooliqa

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Quick queries for this insight

Why is deep learning referred by this name?
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According to MIT Press, Ian Goodfellow and Yoshua Bengio and Aaron Courville, by constructing complex ideas out of smaller ones, the hierarchy of concepts enables computers to learn intricate ideas. If we visualize how these ideas are stacked upon one another as a graph, the graph is deep and has numerous layers. That is the reason this concept is called 'deep' learning.

How is deep learning beneficial for organizations and businesses?
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Deep learning has made it possible for us to create tools and technologies that are better at understanding how we function and what we desire, which means that we are headed towards a period that is truly revolutionary. More and more machines can perform tasks that people once had to complete while working all day at a desk. Contrary to common assumption, this enables us to enhance productivity by halving effort, speeding up work processes, giving computers repetitious prediction and calculation-based duties, and decreasing the frequency of human-made processing and creation errors.

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