DataRobot’s vision to democratize machine learning with no-code AI – TechTalks

datarobot without ai code

This article is part of our series exploring the artificial intelligence business

The increasing digitization of almost every aspect of our world and our lives has created immense opportunities for productivity application of machine learning and data science. Organizations and institutions of all persuasions feel the need to innovate and reinvent themselves by using artificial intelligence and enhancing their data. And according to several surveys, data science is among the fastest growing in-demand skills across different industries.

However, the growing demand for AI is hampered by the very low supply of data scientists and machine learning experts. Among the efforts to address this talent shortage is the rapidly evolving field of no-code AI, tools that make building and deploying ML models accessible to organizations that lack enough data scientists and highly skilled machine learning engineers.

In an interview with TechTalksNenshad Bardoliwalla, Chief Product Officer at DataRobot, discussed the challenges of meeting machine learning and data science needs across different industries and how no-code platforms are helping to democratize artificial intelligence.

Not enough data scientists

the business value of machine learningwhether it’s predicting customer churn, ad clicks, the possibility of engine failure, medical outcomes, or something else entirely.

“We’re seeing more and more companies recognizing that their competitors are able to leverage AI and ML in interesting ways and they’re looking to keep pace,” Bardoliwalla said.

At the same time, the growing demand for data science skills has driven a gap in the AI ​​talent gap. And not everyone is served the same way.

Underserved Industries

The shortage of experts has created fierce competition for talent in data science and machine learning. The financial sector leads the way, aggressive hiring of AI talent and implement machine learning models.

“If you look at financial services, you will clearly see that the number of machine learning models put into production is by far the highest of any other segment,” Bardoliwalla said.

At the same time, big tech companies with deep pockets are also hiring the best data scientists and machine learning engineers – or outright acquire AI labs with all their engineers and scientists – to further strengthen their data-driven business empires. Meanwhile, small businesses and sectors that don’t have cash have been largely excluded from the opportunities presented by advances in artificial intelligence because they can’t hire enough data scientists and machine learning experts. .

Bardoliwalla is particularly passionate about what AI could do for the education sector.

“How much effort is put into optimizing student outcomes using AI and ML? How much do the education industry and school systems have to invest in this technology? Education as a whole is likely to be a laggard in the space,” he said.

Other areas that still have a long way to go before they can take advantage of advances in AI are transportation, utilities, and heavy machinery. And part of the solution could be building ML tools that don’t require a data science degree.

The No-Code AI Vision

ai platform without code

“For each of your data scientists, you have ten analytically savvy business people who are able to properly define the problem and add the specific business-relevant calculations that make sense based on knowledge of the domain of these people,” Bardoliwalla said.

As Machine Learning Requires knowledge of programming languages such as Python and R and complex libraries such as NumPy, Scikit-learn and TensorFlow, most business people cannot build and test models without the help of expert data scientists. This is the area that no-code AI platforms address.

DataRobot and other vendors of no-code AI platforms are building tools that allow these domain experts and savvy individuals to build and deploy machine learning models without having to write code.

With DataRobot, users can upload their datasets to the platform, perform the necessary preprocessing steps, choose and extract features, and build and compare a range of different machine learning models, all through one user interface. easy to use chart.

“The whole notion of democratization is to empower companies and people within those companies who otherwise couldn’t take advantage of AI and ML to be able to do so,” Bardoliwalla said.

No-code AI does not replace the data scientist. But it increases ML productivity in all organizations, allowing more people to create models. This relieves much of the burden from the overworked shoulders of data scientists and allows them to put their skills to use more effectively.

“The only person in this equation, the data scientist, is able to validate and govern and ensure that the models generated by the analytically savvy business people are accurate enough and logical enough from the point of view of interpretability – that they are trustworthy,” Bardoliwalla said.

This evolution of machine learning tools is analogous to how the business intelligence industry has changed. Ten years ago, the ability to query data and generate reports in organizations was limited to a few people who had the special coding skills required to manage databases and data warehouses. But today, the tools have evolved to the point that non-coders and less technical people can do most of their data querying tasks with easy-to-use graphical tools and without the help of data analysts. expert data. Bardoliwalla believes the same transformation is happening in the AI ​​industry thanks to no-code AI platforms.

“While the business intelligence industry has historically focused on what happened – and this is helpful – AI and ML are going to empower every person in the business with the ability to predict what will happen,” Bardoliwalla said. “We believe we can put AI and ML into the hands of millions of people in organizations because we’ve simplified the process to the point that many analytics-savvy business people – and there are millions – work with the several million data scientists can provide AI and ML specific results.”

The evolution of no-code AI at DataRobot

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