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As long as you bring the data, Oracle wants to make machine learning development as easy as typing in a chatbot.
The company seeks to patent a system that uses an intelligent assistant to "enable a user to generate a machine learning system." Oracle's system allows a user to automatically create an AI-based system using a chatbot that translates natural language commands into a "structural representation of a machine learning solution."
"In this way, a user can work with artificial intelligence without being a data scientist," Oracle noted in its filing.
Think of it like Build-A-Bear for machine learning models: In chatting with the user, the system ascertains where the user's data is stored, what problem they're hoping to solve, and what kind of predictions or performance they want. Oracle noted that this interaction can be "aural, textual, or through a graphical user interface."
The system then generates a prototype AI model by picking out the proper building blocks from a "library of machine learning applications" and locating the necessary data from a user's database, as well as recommending how a user can best deploy that model.
Oracle's system also can monitor the output of the new models after the fact, allowing for feedback and adjustments. The model can be "trained, tested, and compiled for export as stand-alone executable code." Plus, for those repeat users, the platform can create user profiles and make recommendations based on historical user preferences, as well as use previously generated models to build news ones.
Oracle isn't the only company looking to helping people understand their data better with little to no data science experience. JPMorgan Chase is seeking to patent a similar invention for "no-code machine learning" that creates an executable custom code based on a user's specification and data. Even Amazon's system discussed above offers similar guidance to its non-techy clients. The only difference is that Oracle is using a chatbot to do so.
The filing also signals that major companies are starting to catch on to the low-code and no-code development movement, or the trend toward developing apps, products and tools with as little coding as possible. In December, a Gartner study found that the low-code and no-code development sector could grow by 20% this year, with the uptick attributable to the growing demand for customizable automated workflows and analytics.
And with the rise of machine learning as a way to gain insight from data stockpiles, companies may look to low-code and no-code development as a way to take advantage of their data without needing to hire a ton of AI experts.
Data is at the heart of Oracle's business. The database management and cloud services company already works with a number of Fortune 500 companies, including Siemens, Cisco and Zoom. But Oracle has stiff competition in the data services market from Amazon, Google and Microsoft.
Oracle already offers some AI infrastructure integrated into its cloud services, and has sought to patent an AI-enabled system for cleaning up large databases. But with its competitors stepping up their AI game in more ways than one, it makes sense that Oracle is following suit and continuing to build.
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