Google has a big stake in low-code and no-code software development by launching Vertex AI about a year ago. But in a new release, analysts think the internet giant may finally make a dent in this highly competitive market.
At the Applied ML Summit on Thursday, Google Cloud announced several new features in Vertex AI, including Training Reduction Server, Tabular Workflow, and Example-Based Explanations, aimed at helping customers better use machine models learning and reduce their reliance on trained experts.
“Our performance tests found a 2.5x increase in the number of ML predictions generated by Vertex AI and BigQuery in 2021, and a 25x increase in active customers for the Vertex AI Workbench over the past six months, clarified by customers managed and integrated ML platforms are essential to accelerating ML’s deployment in production, ”Google said in a blog post.
Google entered the low-code/no-code market in early 2020 with the acquisition of AppSheet, which was already an eight-year-old company at the time of acquisition. Despite the acquisition, Google is not yet seen as a serious competitor in the low-code/no-code market. Analysts believe Vertex could give Google another chance at making a dent in the audience for low-code/no-code software development.
“Vertex AI with a value proposition of 80% lower lines of code requirement compared to other platforms to train a model with custom libraries will greatly improve Google’s positioning in low code/no code space, ”said Pareekh Jain, founder of Pareekh Consulting. “Google is not yet among the top low-code/no-code platforms and this will help improve Google’s positioning.”
According to Gartner’s magic quadrant for enterprise low-code applications, the industry’s leading players include OutSystems, Mendix, Microsoft, Salesforce, and ServiceNow. Google does not feature in any of the four quadrants, according to the report, released in August last year.
Google has an uphill battle in the low-code market
Despite players like Oracle, Microsoft, Salesforce and Google offering low-code/no-code solutions, they haven’t seen the kind of adoption one typically expects, due to its promise to eliminate the coding and allow people other than data scientists or machine learning professionals to generate AI code.
“Low-code/no-code platforms are good for development efficiency and for building simple use cases but often after using them for a while, developers tend to go back to traditional development tool. The challenge is that most traditional LCNC tools involve large licensing costs but don’t work well once you start building any level of complexity into your code, “he said. Saurabh Agrawal, senior vice president of analytics and CRM at unicorn ecommerce firm Lenskart.com.
“There are three main aspects of any AI project — the data layer, the data visualization layer, and the ML [machine learning] algorithm layer. Most LCNC platforms only start working on one of the layers. Google has powerful solutions like BigQuery, Google analytics, and Lookr, which are primarily used in digital use cases. We hope that if the company is able to crack all the layers with Vertex AI in the automation platform approach, it can emerge as a strong player in the segment, ”Agrawal added.
Low code/no code has a chance in SMBs
While most vendors cite low-code/no-code programming as a way to reduce dependency on hard-to-find machine learning talent, analysts believe a greater opportunity may be in targeting to SMBs looking for simpler solutions.
“Right now companies are more focused on the B2B market for low-code/no-code for attracting business users, but I think the biggest opportunity for low-code/no-code platforms is the democratizing tech for SMBs and individuals, ”Jain said. “I think Google and Microsoft have a better chance for SMBs. It’s like the cloud market. It grew because of AWS’s initial focus on SMBs. It later became an attractive proposition for SMBs. business. “
Copyright © 2022 IDG Communications, Inc.