When thinking of technology, one cannot go without talking about deep learning. Needless to say, deep learning has become one of the most critical aspects of technology. Gone are the days when organizations alone used to show interest in technologies like AI, deep learning, machine learning, etc. Today, even individuals are inclined towards the very aspect of technology, deep learning in particular. One of the many reasons why deep learning draws all the attention is because of its ability to enable improved data-driven decisions and also improve the accuracy of the predictions made.

In a nutshell, companies are in a position to reap out various financial and operational benefits by virtue of deep learning. With many deep learning innovations proliferating with time, it makes every possible sense to have a clear picture as to how does the future of deep learning looks like. In line with what we have seen over the past few years, this is what we could expect in the coming days as far as deep learning is concerned –

• Despite the fact that deep learning is a little on the slower side when compared to traditional AI and other machine learning algorithms, what one can stay assured of is the fact that it is way more powerful as well as straightforward. It is because of this that fields such as medicine, supply chain, robotics, manufacturing, etc. would see immense usage of deep learning in the days that lie ahead.

• A few years from now, it is very much possible that deep learning development tools, libraries, and languages could become standard components of every software development tool kit. These tool kits with modern capabilities will pave the way for easy design, configuration, and training of new models. With these capabilities, style transformation, auto-tagging, music composition, etc. would be a lot easier to accomplish.

• The need for faster coding is at an all-time high. The future is all set to see the deep learning developers adopting integrated, open, cloud-based development environments that provide access to a wide range of off-the-shelf and pluggable algorithm libraries.

• The prediction that neural architecture search would play a pivotal role in building data sets for the deep learning models still stands strong.

• Global marketers have a positive mindset by virtue of Google’s acquisition of DeepMind Technologies.

• It is highly likely that the deep learning networks would demystify computer memory.

• Yet another point that is worth making a note of is the fact that the automation of deep learning tools would mean that there’s an inherent risk that could develop into something so complex that the average developers will find themselves totally ignorant.

• Deep learning should be able to demonstrate learning from limited training materials and transfer learning between contexts, continuous learning, and adaptive capabilities. Wondering why. Well, just to remain useful.

What everything boils down to is the fact that as a result of the growing popularity of deep learning and with the advancement in technology, by the end of this decade, the deep learning industry will simplify its offerings considerably so that they’re comprehensible and useful to the average developer.

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Needless to say, budget presented every year draws attention from all corners of the country. This surely remains a hot topic for quite some time and the progress with respect to what has been promised is kept an eye on, undoubtedly. This time too, the budget garnered attention of many. Be it the agricultural sector, education, technology or healthcare, a lot has been said and promised. But what seems to have stood out from the rest is the discussion pertaining to Artificial Intelligence and machine learning.

Even before the budget was presented, a lot was already been said and speculated about how much importance should be given to AI and analytics. Some were of the opinion that in order to accelerate Research and Development and technology, setting up of robotics centres of excellence, incubation centres, continued research grants for robotics R&D and continuation of income tax deduction could be the key drivers. Also, warehouse automation should be given importance to as it ultimately leads to an increase in customer traction.

Well, the fact that adequate importance if given to technology can not only strengthen the Government’s initiatives like “AtmaNirbhar Bharat”, “Make in India”, “Digital India”, etc. but also increase employability in India.

With a lot being predicted, the Finance minister finally had put an end to all of the speculations and emphasised on the use of Artificial intelligence in the days ahead. She made a statement saying that in the coming fiscal year, there is a plan laid to track the companies that default and also those that fail to comply with the rules of the Ministry of Corporate affairs (MCA).

Plan to come up with a machine learning driven MCA-21 Version 3.0 is in process. This version will have additional modules for e-scrutiny, e-Adjudication, e-Consultation and Compliance Management, said the finance minister. Features such as single source of truth, online compliance monitoring, ease of doing business among others are expected in this version. All of these features aim at making the authenticity and comprehensiveness of corporates even better. Also, with the use of machine learning, data analytics and artificial intelligence, it is no longer required to fill in known details again and also interlink databases. Everything will now be automated. Also, the routine enforcement can be done 24×7 on autopilot basis.

MCA-21 is crucial from the start-up point of view. It also shares crucial information to the various stakeholders such as the regulators, investors and companies. All filings under the ‘Companies law’ are submitted to the ministry through this portal.

Also, measures to deploy deep analytics and artificial intelligence to identify the tax evaders and fake billers have been taken and special drives are launched against them. When it comes to tax evasion, a lot of steps have been taken up in the past that included machine learning tools.

With so much that’s been promised as far as the usage of AI, machine learning and analytics to changing our lives for better, all eyes are now on the implementation aspect. Let’s hope all that is said is implemented soon and we get to see a technology rich India in the days ahead!

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