Twilio often closes its events with a developer-focused sign-off: “We can’t wait to see what you build.”

This phrase is on my mind as we set up our remote interview with Twilio’s CEO, Jeff Lawson. Brent Schooley, a pandemic-tempered livestreaming expert, sets up to record high-quality video remotely. He developed this system while building for Twilio’s remote SIGNAL conference last year. While he does my mic check, I click through browser windows and close sixteen tabs for completed or abandoned projects, hardware hacks, and other idle Googling.

I’ve heard stories about building from Developer Relations teams before, but none have felt as genuine as those I’ve heard at Twilio. At this company, builders are in major supply. From engineering to marketing, we are moving and creating and iterating, setting up potential solutions, and reworking them together.

Jeff Lawson joins at 5:31 p.m. sharp.

“I gotta show you what I built …

When Mel Feuerman first saw the Stanley Kubrick film 2001: A Space Odyssey, he couldn’t have predicted just how those concepts would stick with him. The movie, which follows a space journey to Jupiter with help from the sentient computer HAL, had an enormous impact on cinema—and on our perception of artificial intelligence in computers.

HAL and his cinematic counterparts followed an era of computer science research in automated interaction. As Feuerman watched HAL in 1968, he recalled a natural language chatbot created at MIT four years earlier. ELIZA, Joseph Weizenbaum’s staple experiment in the history of HCI, simulated a Rogerian therapist by reflecting the questions and themes of a conversation back at its user.

It was HAL and ELIZA who came to mind fifty years later, when Feuerman began building his first chatbot with Twilio.

“I called my version of ELIZA, ‘HALTWILIO,’’ or HAL for short,” said …

Several years back, when California began having increasingly severe wildfire seasons, Naomi Quinones found herself spending hours on the phone to communicate with her students. As an instructor for the Berkeley Adult School, Quinones teaches ESL classrooms with as many as six different language backgrounds. When the fires hit and forced the school to close down, she had to send out text messages in a number of different languages.

“With Google Translate you can do one language at a time, so I would copy and paste it for each student, switch the language, if they responded I would translate what they said, get my answer and translate that—it took more than two hours to get through the whole class,” Quinones says. “I kept thinking, if there was some other way I could get Google Translate to let me do all the languages at once and send a message to my …

If you’ve built a chatbot or application flow with Twilio Studio, an integral part of bringing your app into production is being able to store relevant user data and access data you need to remit to your user. This means you need a database.

In this article, you’ll learn how to use Twilio Functions and Node.js to store and access data in an Airtable base. This article builds off the specific example project created in Build a Trick or Treat Chatbot with Twilio Studio and Functions, and Node.js.

To follow along step by step with this article, having built the Trick or Treat chatbot will be required, but if not, have no fear! This article contains valuable information about connecting with and using the Airtable API with Node.js for all readers.

Prerequisites

To get started with this tutorial, you’ll need the following:

• A free Twilio account ( …

With Halloween around the corner, I decided I wanted to build a chatbot to help people find trick or treat locations in their neighborhood. The idea was that a user could send an SMS to the chatbot’s phone number and interact with the bot to either find trick or treat locations, or add their location to the list of places giving out candy or hosting spooky events.

In this article, you’ll learn how to build a chatbot like mine that you can customize however you like.

Prerequisites

To get started with this tutorial, you’ll need the following:

• Node.js installed on your machine, along with a package manager like npm or yarn
• A free Twilio account (sign up with this link and get $10 in free credit when you upgrade your account)
• A Twilio phone number

Overview of the chatbot architecture

The chatbot you’re about to build will use the …

When users join Dialup, they can choose from a list of topics they'd like to discuss: tarot, their boss, woodworking, relationships, and more. It’s a list of topics you might discover in a passing conversation on a bus, in an airport, or at a wedding. In a digital recreation of conversational happenstance, the app sends your interests to a stranger picked at random-- another curious soul seeking ephemeral social contact. Your lists of interests become conversation starters. And much like those passing conversations at crosswalks, movie theater lines, and plane rides, the exchange is fleeing by default. The strangers meeting on Dialup have no way of getting back in touch when the call ends.

At the beginning of 2020, Dialup had 2,000 users. Today it has 31,000 users from 190 countries, and has been written up by the New York Times and The Guardian. Creator Danielle Baskin’s favorite story …

For the last two decades, the A.I. and machine learning have been thrown around with more and more frequency. Research centers are investing in their development, more companies are using them to promote their products and – of course – more movies using them because they sound cool.

But what do they actually mean?

Artificial Intelligence is a technique for building systems that mimic human behavior or decision-making. Machine Learning is a subset of AI where algorithms are created which learn from data sets in order to solve specific tasks. These solvers are trained models of data that learn based on the information provided to them. All of this is derived from probability theory and linear algebra. ML algorithms use our data to learn and automatically solve predictive tasks.

And let’s be honest: is there a better way to use A.I. and machine learning than searching for the best spots …

In 2017, Ifat Ribon created a scheduling app for Olympus, a janitorial service company for colleges and universities. The app, meant as a replacement for paper schedules, sent electronic records to employees so they would know where they were going and what tasks they would do. Originally intended to prevent lost schedules and out-of-date task lists, in 2020 the app also served to prevent potential COVID infections.

As a convenient, robust, and familiar resource for the staff, Olympus became an essential backbone for COVID communications. The app was able to push out mass text messages, including information about new safety protocols, or whether or not it was safe to go to work. It also included a messaging feature that allowed managers at Olympus to keep tabs on how employees were feeling during the pandemic.

Meet the creator: Ifat Ribon

Ifat Ribon is a senior software developer at Launchpad, a Chicago-based …