Google placed a big bet on low-code and no-code software development by launching Vertex AI about a year ago. But with a new release, analysts believe the internet giant may finally be able to make a dent in the highly competitive market.
At the Applied ML Summit on Thursday, Google Cloud announced several new Vertex AI features, including Training Reduction Server, Tabular Workflow, and Example-Based Explanations, which aim to help customers better use machine learning and reduce their reliance on machine learning. regard to trained experts.
“Our performance tests revealed a 2.5x increase in the number of ML predictions generated by Vertex AI and BigQuery in 2021, and a 25x increase in the number of active clients for Vertex AI Workbench in the last six months alone. , customers have made it clear that managed and integrated ML platforms are crucial to accelerating the deployment of ML 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 the acquisition. Despite the acquisition, Google is not yet considered a serious competitor in the low-code/no-code market. Analysts believe Vertex could give Google one more chance to make a dent in the public eye for low-code/no-code software development.
“Vertex AI with a value proposition of 80% fewer lines of code compared to other platforms to train a model with custom libraries will further improve Google’s positioning in the low code/no code space” , said Pareekh Jain, founder of Pareekh Consulting. “Google is not yet counted among the major low-code/no-code platforms and this will help improve Google’s positioning. »
According to Gartner’s Magic Quadrant for Enterprise Low-Code Applications, top industry players include OutSystems, Mendix, Microsoft, Salesforce, and ServiceNow. Google was not 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
Although players like Oracle, Microsoft, Salesforce, and Google offer low-code/no-code solutions, they haven’t seen the kind of adoption one would generally expect, given its promise to eliminate the coding and to allow people other than data scientists or machine learning professionals to build AI code.
“Low-code/no-code platforms are good for improving efficiency and creating simple use cases, but often after using them for a while developers tend to revert to traditional development tools . The challenge is that most traditional LCNC tools have a huge license cost and don’t work well by the time you start building a level of complexity into your code,” said Saurabh Agrawal, senior vice president of analytics. and CRM at Lenskart.com.
“There are three key aspects of any AI project: the data layer, the data visualization layer, and ML [machine learning] layer of algorithms. Most LCNC platforms start working on only one of the layers. Google offers strong solutions such as BigQuery, Google Analytics, and Lookr, which are mostly used in digital use cases. We hope that if the company is able to decipher all the layers with Vertex AI in the automation platform approach, it could become a significant player in the segment,” added Agrawal.
Low code/no code has opportunities among SMBs
While most vendors tout low-code/no-code programming as a way to reduce reliance on hard-to-find machine learning talent, analysts believe the biggest opportunity may lie in targeting SMEs looking to create simpler solutions.
“So far, companies are focusing more on the low-code/no-code B2B market to attract business users, but I think the biggest opportunity for low-code/no-code platforms is to democratize technology for SMBs and individuals,” said Jain. “I think Google and Microsoft have a better chance for SMEs. It’s like the cloud market. It grew due to AWS’ initial focus on SMBs. Later, it became an attractive proposition for businesses. »
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