The next killer AI application may be developed by someone who has never heard of gradient descent.

What’s new: A rising generation of software development platforms serves users who aren’t familiar with AI — and even programming. The New York Times surveyed the scene.

Robocoders: Using no-code AI platform — an automated programming tool that either generates new code or customizes pre-existing code according to user input — generally requires access to a web browser and training data. From there, a user-friendly interface lets users train a prebuilt architecture.

  • Teachable Machine from Google (pictured above) and Lobe from Microsoft make building vision models a point-and-click process. Users supply training images.
  • Power Platform and AI Builder, both from Microsoft, are aimed at business users who want to process text in documents and images.
  • Juji enables users to build chatbots by choosing from a list of topics and question-and-answer pairs.
  • Akkio helps users build models that predict business outcomes from spreadsheets. For instance, Ellipsis, a marketing company, uploaded a spreadsheet of keywords, blog titles, and click rates to train a model that predicts which words and phrases rank highly in Google search results.
  • Amazon Sagemaker offers Canvas, which is designed to help business analysts derive insights from data.
  • eBay deployed proprietary low-code and no-code AI tools internally, enabling nontechnical employees in areas like marketing to roll their own models.

Behind the news: Similar tools for building non-AI applications like websites (Wordpress), ecommerce stores (Shopify), and video games (RPG Maker) undergird a significant portion of the online economy. OpenAI and DeepMind offer natural language tools that write code using plain-English prompts. Source AI, available in a beta-test version, extends such auto-coding functionality to French, German, and Spanish to generate programs in at least 40 languages.

Why it matters: Platforms that automate coding, data collection, and training are an important part of AI’s future. Although no-code AI tools are still maturing — for example, they’re limited to particular tasks and some aren’t yet suitable for commercial-grade applications — they’re on track to open the field to a far broader range of users, enabling them to apply tried-and-true approaches to certain classes of problems. And they may be useful to experienced AI developers, too. For instance, trained engineers may also use them to build wireframe versions of more intensive projects.

We’re thinking: No-code tools have a long way to go, and even when they get there, education in AI technology will be necessary to handle difficult problems, high-stakes situations, and cutting-edge developments. Skilled engineers will exceed the capabilities available at the press of a button for the foreseeable future.


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