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        Date: 2022-03-16 11:27:07+00:00
        From: Robert A Amsler <robert.amsler@utexas.edu>
        Subject: NYTimes article, "No-Code AI"

[See below for the New York Times article]

In essence, large collections of data, especially in images, audio
files, or structured text (e.g., spreadsheets), or even unstructured
text can now be used in new A.I. software that doesn't require
programmers to write new code to reach conclusions about what that data
contains. It basically requires the user to identify sufficient examples
of the data that show the traits the user seeks to find and the new
programs will then build a program that identifies instances of the
traits the user is seeking. The manual labor to identify and tag
sufficient numbers of good examples of the things to find is required
and the accuracy is limited by the quality and size of the manually
identified examples. I guess one could even use critical reviews of art,
music, speech, prose to create an artificial intelligence
reviewing program to then turn loose on previously unreviewed similar
data to determine what human reviewers would have said about that work.
Or to sift through photographic images to find "significant" examples
based on giving the software a training set of human-decided prior
"significant" photos. - RA



The New York Times

‘No-Code’ Brings the Power of A.I. to the Masses
https://www.nytimes.com/2022/03/15/technology/ai-no-code.html

A growing number of new products allow anyone to apply artificial
intelligence without having to write a line of computer code. Proponents
believe the “no-code” movement will change the world.

By Craig S. Smith

March 15, 2022

This article is part of a new series on how artificial intelligence has
the potential to solve everyday problems.

Sean Cusack, a software engineer at Microsoft and beekeeper on the side,
wanted to know if anything besides bees was going into his hives. So he
built a tiny photo booth (a sort of bee vestibule) that took pictures
whenever something appeared around it. But sorting through thousands of
insect portraits proved tedious.

Colleagues told him about a new product that the company was working on
called Lobe.ai, which allows anybody to train a computer-vision system
to recognize objects. Mr. Cusack used it to identify his honeybees — but
also to keep an eye out for the dreaded Asian murder hornet.

“It was just really simple,” Mr. Cusack said, adding that the underlying
data science was “over my head,” despite his title. The Lobe platform
allowed him to drag and drop sample photos and click a few buttons to
make a system that could recognize his beloved bees and spot unwelcome
visitors.

Mr. Cusack is part of a growing army of “citizen developers,” who use
new products that allow anyone to apply artificial intelligence without
having to write a line of computer code. Proponents of the “no-code”
A.I. revolution believe it will change the world: It used to require a
team of engineers to build a piece of software, and now users with a web
browser and an idea have the power to bring that idea to life themselves.

“We are trying to take A.I. and make it ridiculously easy,” said Craig
Wisneski, a no-code evangelist and co-founder of Akkio, a start-up that
allows anyone to make predictions using data.

A.I. is following a familiar progression. “First, it’s used by a small
core of scientists,” Jonathan Reilly, Akkio’s other co-founder, said.
“Then the user base expands to engineers who can navigate technical
nuance and jargon until, finally, it’s made user-friendly enough that
almost anyone can use it.”

Just as clickable icons have replaced obscure programming commands on
home computers, new no-code platforms replace programming languages with
simple and familiar web interfaces. And a wave of start-ups is bringing
the power of A.I. to nontechnical people in visual, textual and audio
domains.

Juji, for example, is a tool designed to make building A.I. chatbots as
easy as creating a PowerPoint presentation. It uses machine learning to
automatically handle complex conversation flows and infer users’
particular characteristics to personalize each engagement rather than
simply serving up preprogrammed interactions.

Its co-founder, Michelle Zhou, said the goal was to give Juji chatbots
advanced human soft skills such as emotional intelligence so that they
could connect with users on a more human level than existing systems
have. Using Juji, staff members at the University of Illinois were able
to create and manage their custom A.I. chatbot and scale their student
recruitment operations.

But not all of the existing tools are robust enough to do more than
simple tasks. Google’s Teachable Machines is a computer-vision tool
similar to Lobe.ai. Steve Saling, a former landscape architect who is
now living with A.L.S., worked with the Teachable Machines team for
about a year and a half to train a system to turn switches on and off
using his facial expressions.

“It gets more accurate with more data,” Mr. Saling said in an email. But
he said the process of collecting that data — pictures of his face at
different angles and in varying light — was labor intensive and the
system never reached the level of accuracy required. “Automation needs
to be in excess of 99 percent reliable to be dependent on it,” he said.
“Teachable Machines will get there but it is not there yet.”

Still, it’s early days. “No-code A.I. tools are still on the fringes of
the larger no-code movement, because not many people understand machine
learning enough to dream up what’s possible,” said Josh Tiernan, who
runs No Code Founders, a community of nontechnical entrepreneurs who use
no-code tools such as WordPress or Bubble. But he expects no-code A.I.
to grow as more people understand its potential.

Another force in no-code’s favor: Advances in A.I. itself are making
no-code platforms more powerful. OpenAI, the company co-founded by Elon
Musk, has a vast A.I. system, GPT-3, that can write code when prompted
with simple English. It can even create websites and do other basic
programming tasks. OpenAI has used the system to create GitHub Copilot,
a tool that acts as an autocomplete function for coders, speeding up
their work. DeepMind, a subsidiary of Alphabet, Google’s parent company,
has gone a step further with an A.I. tool capable of writing complete
code to solve complex problems posed to it with normal speech or text.

Already, users of Microsoft’s Power Platform, which includes a family of
no-code products, can generate simple applications by just describing them.

“I could say something like, ‘Look up all the customer records from the
last year,’ and it will go do that for you automatically,” said Charles
Lamanna, Microsoft’s corporate vice president of business apps and
platforms. He estimates that half of all office work could be automated
with A.I. if there were enough developers to do the work. “The only way
to do this is to empower everybody to be a no-code developer.”

Eventually the broader public will be able to create A.I.-enabled
software in much the same way that teenagers today can create
sophisticated video effects that would have required a professional
studio a decade or two ago.

For now, though, most no-code-A.I. users are business professionals who
want to streamline the way things are done without having to involve a
programmer.

Google’s AppSheet, for example, is an open platform where people can
connect data and, with a single click, create apps that can be opened on
a smartphone, tablet or computer. It uses A.I. to understand the intent
of users and enables them to build mobile and desktop applications with
integrated computer vision and predictive analytics features. It costs
nothing to make apps for personal use.

“We’re focused on making this consumable by regular people,” said
Praveen Seshadri, AppSheet’s co-founder and chief executive. There are
many organizations around the world that have teams of people that need
to coordinate schedules and tasks, he added. Each one is unique and more
suited to building a custom app than trying to use something off the shelf.

As an example, he cited New Incentives, an organization that gives small
amounts of cash to mothers in some of the poorest parts of Nigeria to
encourage them to immunize their children. To track that data, they
built an app with AppSheet that their employees now use in the field.

Alex Denning, who runs Ellipsis, a small marketing company for
businesses that use WordPress, turned to Akkio to build an A.I. system
that could predict which keyword and title would get his clients’ blog
posts the most visibility on Google and other search engines. He dragged
and dropped onto Akkio’s site a spreadsheet of past keywords and
blog-post titles along with the number of clicks those posts got on
Google. After a few keystrokes, Akkio created an A.I. to do the job.

“Results for our clients improved by approximately a third as a result
of leveraging Akkio and the A.I.,” Mr. Denning said. Once an A.I. system
is created on Akkio, users can integrate with their existing software.
Mr. Denning renamed the tool Falcon and uses it to market his company.

“I am not a developer,” he said, “but it was easy and intuitive for me
to make it happen.”

And Mr. Cusack, the bee guy? His A.I. system never spotted a murder
hornet, but it did catch plenty of wasps and earwigs sneaking into his
hives — a modest but important step for no-code.

Craig S. Smith is a former correspondent for The Times and hosts the
podcast “Eye on A.I.”



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