How will India contribute to AI innovation in the world?

India has all the right markers of being a leader in the global AI-sphere. There’s a massive engineering workforce that can be trained in AI skills. A thriving start-up and enterprise scene spread out across the country that can foster innovation. There’s also a large amount of data being generated due to increased technology use with the proliferation of smartphones leading to large swathes of the population going online.

What’s holding AI progress back right now is the lack of existing skilled professionals who can work on AI problems. 76% of companies in India feel the shortage of skilled professionals is slowing down their AI adoption. Fundamental research and progress has largely been concentrated in the US and China, but that development will quickly reach India with the internet facilitating an easy exchange of ideas and data.

What this is means is that India is in a peculiar position right now. It is brimming with the potential to play a part in shaping the technological future of the world, but the path to that is filled with many significant hurdles.

It has been evident for a long time that AI is the way of the future, and India has already woken up to this reality. There’s a burgeoning AI scene that has silently been transforming how small companies and enterprises have been running their operations. It has progressed from being a nascent trend from a few years ago and is on the brink of explosive growth. This has been a gently nudged along with comprehensive and relevant technical expertise being offered by organisations such as Great Learning, who offer programs that help candidates participate in the new job market.

Since the state of the AI job market is in a growing phase right now, it can be challenging to take a snapshot of how it’s currently faring. That why Great Learning, one of India’s leading technical education companies has partnered with Analytics India Magazine to put together The Hitchhiker’s Guide to AI 2018-19, which offers an extensive look at the AI Landscape in India.

This report is a result of extensive primary and secondary research, carried out over a period of six months. The research methodology included a systematic plan to identify the various factors influencing job scenarios around artificial intelligence in India. The data was collected through research on leading job portals in India, interactions with 100+ companies and 1000+ professionals across all major cities in India. The samples were collected by quizzing participants on employment trends in AI, salary structure from fresher to managerial level, cities that offer best opportunities for these jobs, tools and skills that companies are looking for, analytics jobs across company types, and much more.

For a free copy of the report, just click below:

Secrets of a successful Data Scientist: Data Science Skills Report 2018

The current pace of data creation stands at 2.5 quintillion bytes being generated every single day. This is a staggering amount of data, and the most interesting part is that 90% of all the data available in the world right now has been generated just in the past two years. These vast amounts of data bring with them the challenge of making sense of all this information.  

Organisations across the world are sitting on large troves of data that are ripe with insights. Companies need to mine this data to hold their competitive edge by improving efficiencies and finding new avenues to innovate. In the quest to leverage all this data, companies need qualified data scientists.

Growing demand for Data Scientists

Data Scientists are all set to become the hottest new hires for companies, to help executives to make informed decisions driven by data to achieve better outcomes. In an effort to understand the world of data science better, Great Learning has partnered with Analytics India Magazine to put together the Data Science Skills Study for 2018. This comprehensive report takes a look at what makes a good data scientist, exploring areas such the tools they use. We’ll be looking at:

  • – Common libraries used by data scientists
  • – How data visualisation makes data presentable
  • – What operating systems are most conducive for data science
  • – Tools for integrating big data into data analysis
  • – Best cloud provider for storing all their data
  • – Where data scientists source their open data
  • – How data scientists share codes between themselves
  • – And much more.

We’ve unearthed key insights about what the most successful data scientists are using to excel in their jobs, that will help beginners and job seekers to set a benchmark to gauge their expertise. You can download the full report here.

What does the cloud industry hold in store for aspiring job seekers?

Cloud computing as a concept has been around for a long time, and it’s constantly evolving nature has given way to a big growth spurt in terms of industry penetration and job growth. For enterprises of all sizes across the world, cloud computing has the potential to cuts costs and improve efficiencies through virtualization and a range of managed services and automation.

In 2018 alone, the cloud industry market has been valued at $186.4 billion by Gartner, a 21% jump from the previous year. At this rate of growth, the coming years are bound to see an increase in job opportunities for skilled professionals.

Almost every company today needs to maintain some kind of cloud infrastructure (or at least outsource it to another company) to maintain all their data, and there’s a whole army of experienced professionals that keep the cloud show running. Let’s take a look at how these roles contribute to the cloud environment, and what kind of skills you’ll need to thrive in these roles.

Entry/Mid Level Roles

Cloud Engineer & Cloud DevOps Engineer

Role Description

A Cloud Engineer needs to manage existing cloud infrastructure, create new infrastructure for new applications, migrate existing application components to one or more cloud platforms, automate cloud operations using Infrastructure as Code techniques while monitoring, reporting, fixing and optimizing all cloud resources and processes.  

Required Skills

Knowledge of cloud platforms like AWS

DevOps & Automation

Monitoring & Logging Tools

Agile Processes and Techniques

Cloud Costing and Resource Optimization

Scripting Skills

Cloud Native App Developer

Role Description

A cloud native app developer is skilled at designing and building microservices based modular applications that leverage the many benefits of Cloud, DevOps, Automation, Cloud Design Patterns, Microservices base architectural practices and Serverless. Cloud native doesn’t mean that everything is done and deployed on cloud, but is rather an app development approach that follows the principles and techniques listed above.

Required Skills

Microservices Architecture (Patterns and Principles)

API based Development

Discovery and Invocation of RESTful services

Architectural Patterns (e.g. Circuit Breaker etc)

Pipelines,Authentication, Logging, Monitoring

Advanced Deployment Techniques

Monolith to Microservices migration

Experience with Agile software development methods

Experience deploying services on Service-Oriented Architecture platforms

Programming Stack with either Java, Ruby, Python, .NET etc.

Senior Cloud Roles

Cloud Presales Consultant

Role Description

This is not a completely technical role but the job of a Cloud presales consultant requires significant understanding of cloud platforms and services, apart from having a having an understanding of the features and benefits of technical products.

Pre-sales consultants spend a lot of time with potential customers trying to understand their challenges, requirements and business road maps.So they’ll need to be able to compare pros and cons of a particular product or a set of features. They’ll also need to be able to compare multiple cloud services and recommend the best fit for the customer. This is a business-tech role that requires skills which are quite broad, and not necessarily deep in terms of technical hands-on expertise.

Required Experience

Proficient understanding of multiple cloud platforms (AWS, Azure and GCP)

Understanding of latest tech developments like Containers, Big Data, DevOps, Analytics etc.

Understanding of Cloud Economics and Financials

Knowledge of Cloud Adoption & Migration Practices

Cloud Architect

Role Description

The role of the Cloud Architect is to design, build and create reliable global scale cloud systems, (app and infrastructure) for their organizations or customers. It’s a senior role which requires a multitude of technology and business skills.

Required Experience

7-10 years of IT experience

Proficient understanding of multiple cloud platforms (AWS, Azure and GCP)

Understanding of latest tech developments like Containers, Big Data, DevOps, Analytics etc.

Understanding of Cloud Economics and Financials

Knowledge of Cloud Adoption & Migration Practices

Solid understanding of industry trends and best practices

If you are looking to enter into the Cloud computing domain, you’ll need the right knowledge and credentials. Great Learning’s PGP course in Cloud Computing is the best place to start.

Why is an Artificial Intelligence Generated Piece of Art Worth $432,500?

October 25th, 2018 was a turning point in the world of Artificial Intelligence-generated art. That was the day when “Portrait of Edmond Belamy”, was auctioned off for an unprecedented price at Christie’s. It was ‘painted’ by Obvious who are a collective of French students, using a Generative Adversarial Network algorithm (GAN). The price that the auction at Christie’s generated is sure to raise a few eyebrows, more so because that the auction house had made a conservative estimate that the painting would sell for $7000-10,000. On the contrary, the $432,500 bid placed by an anonymous phone bidder signalled the arrival and legitimacy of AI-generated art onto the world stage.

An Algorithm’s Artistic Process

At first glance, the portrait looks like a work in progress due to the white patches on the sides and the slightly out-of-focus look of the subjects’ face. This painting is a part of a series of 11 portraits on the fictional Belamy family. The Obvious team used a generative adversarial network, which are algorithms used in unsupervised machine learning. They make two neural networks compete against each other to deliver a superior result. This GAN scoured images of paintings since the 14th century and used that data to generate a distinctive image. These generated images are then ‘evaluated’ by the program to see if they look anything like a work of art.

Courting Controversy

Most rapid advances with technology are met with disdain by critics, and this one was no different. There have been accusations of plagiarism, not of the painting itself, but of the GAN code that was written by 19-year old Robbie Barrat. But since the code was open-source Obvious have themselves admitted to modifying Baratt’s code and using it. Even before the auction was underway, critics derided the quality of the artwork citing that the art was not original and uninteresting.

Is the Portrait Worth the Price?

Most people question why it’s worth so much. The seemingly inflated price follows the high prices commanded by most other human made paintings. Auctions tend to be breeding grounds for bidding-wars and can drive up the price of any artifact. Since this was a painting exhibited by an esteemed auction house, and the exclusivity associated with one of the first Artificial Intelligence generated paintings could have driven up the price.

Thankfully, it’s all for the progress of technology, because the group has stated that they are going to use the money to train the algorithm further, and purchase some better hardware needed to run the program. But still there have always been questions about who is the rightful owner of the copyright of the art. Is it the algorithm, or is it the people who wrote the program in the first place. Questions such as these show us that there is still a long way for us to go in terms of accepting this Artificial Intelligence powered reality, and framing new rules and frameworks to coexist with these incredible machines.

Other AI-Generated Art

The genesis for these particular series of portraits has been Robbie Baratt’s code, and he has generated a similar series of portraits a year ago. There has also been another effort by Gumgum, an AI company, who commissioned 5 human artists and 1 AI-powered Cloudpainter algorithm to create paintings inspired by 20th-century American abstract expressionists. They then let viewers guess which painting was done by the robot, which showed how close algorithms are getting to mirroring human artistic output.

What Does This Mean for the Future?

Art movements across the centuries have been shaped by the kind of technology available to artists, and this has been true of engravings, wood carvings, photography, 3D printing and so on. Initially, most of these art-forms had to contend with a hostility regarding the legitimacy, whether it can really be considered art. Over time, they have all been accepted and even celebrated. We are on a similar cusp for AI-generated art where it is just getting mainstream acceptance. Contrary to popular belief that AI might replace artists, the accurate way to look at this is that Artificial Intelligence will serve as a tool, that helps the artists reach new artistic heights in the same way that the paintbrush, camera, and the word processor has. Because of this, it’s important that artists and viewers are familiar with AI concepts so that they can be ready for what the future holds in store.