When same-day-delivery service Jetblack launched last week out of Walmart’s incubator, Store No. 8, it was billed as a new order-by-text service. But Katie Finnegan, founder and principal of Store No. 8, told the audience at MIT Technology Review’s EmTech Next event today that audio ordering and “conversational commerce” is the final goal.
For $50 a month, Jetblack customers in New York City can order a product via text message and have it delivered to their door that day or the next. But Store No. 8 hopes that a voice interface will soon make it possible to remove the texting step. Sound familiar? It may if you already have an Amazon Alexa–enabled device.
For now, text is where Walmart hopes to gauge customer interest and prove the viability of the Jetblack service. “Text is something where consumers are extremely comfortable. There is no barrier to entry for the consumer,” said Finnegan. “But over time, our thesis is, people will start doing this over voice.”
Finnegan says the primary reason for not jumping straight to voice is the need to train Jetblack’s AI to master audio product recommendations. “In audio it’s hard to give recommendations proactively and get ahead of needs and wants,” she said. Users of home assistants don’t want to listen to a list of 12 potential product recommendations. They want succinct and refined options.
While audio is the eventual goal, Finnegan knows that the company needs to concentrate on its growing customer base before branching out into different interfaces. “The focus is around making the customer experience magical,” she said. “Given the stage the company is at right now, that’s the top priority.”
Yann LeCun has a bold new vision for the future of AI
One of the godfathers of deep learning pulls together old ideas to sketch out a fresh path for AI, but raises as many questions as he answers.
The dark secret behind those cute AI-generated animal images
Google Brain has revealed its own image-making AI, called Imagen. But don't expect to see anything that isn't wholesome.
The hype around DeepMind’s new AI model misses what’s actually cool about it
Some worry that the chatter about these tools is doing the whole field a disservice.
AI’s progress isn’t the same as creating human intelligence in machines
Honorees from this year's 35 Innovators list are employing AI to find new molecules, fold proteins, and analyze massive amounts of medical data.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.