If one theme defined VentureBeat’s inaugural Transform conference on artificial intelligence (AI), it’s metamorphosis. Luminaries from Samsung, Google, Gogo, Uber, Intel, Pinterest, and others spoke about AI‘s increasing ability to handle tasks no human could perform at scale, like creating onboarding guides for tens of thousands of ridesharing drivers and predicting hundreds of millions of users’ taste in fashion.
“It’s about enabling companies to [innovate] faster,” said Faizan Buzdar, senior director and platform manager at cloud storage provider Box. “Think about data entry. When you replace it with machine learning, the validation process looks [the same], but you [as a business] saved a lot of money.”
An air of optimism pervaded panel discussions, product showcases, and fireside chats about AI in apparel, travel, food delivery, retail, and countless other markets. The consensus? Predictive systems not only have the potential to boost bottom lines and optimize workflows, they are set to improve user experiences.
Tim Correia, senior vice president and general manager at Trulia, talked about an AI-driven scoring system that helps surface neighborhood reviews, photos, and other tidbits for prospective home buyers. Uber director of product Jairam Ranganathan described AI that fields phone calls and text messages for ridesharing customers. And Linda Crawford, CEO of Helpshift, spoke about machine learning-powered chatbots that handle customer service transactions full stop.
“Customers are after a great experience,” Crawford said during a panel discussion. “Most people would rather clean their bathroom than talk to customer service, by a large percentage. They’re happy to interact with [AI] as long as they get their issue resolved straight away.”
John Koetsier, VP of insights at marketing data platform Singular, spoke during a session about how one of its clients — a video game developer — ran an advertising campaign without showing any actual gameplay, informed in part by AI algorithms.
“You can try many, many things, because you can let the machine [learning] then figure out in real time what’s generating impact,” Koetsier said. “You can do stupid stuff, and sometimes stupid stuff [turns out to be] smart stuff.”
Rishi Shiva, CMO of Bidalgo, explained during a product showcase about how his company’s platform — Creative AI — analyzes images, videos, and other media to identify successful marketing strategies before they’re implemented.
“Before you go investing hundreds of thousands of dollars developing video assets, you can actually run your historical images and videos through our system, and it will actually give you insights,” Shiva said. “What actually had a positive impact on the audience? What is it that people liked?”
Despite the enthusiasm for AI among Transform’s attendees, most acknowledged it isn’t a cure-all.
Even the best natural language processing engines can’t understand the context of unusual requests, said Stitch Fix chief algorithms officer Eric Colson. Algorithms are susceptible to bias, conceded ZipRecruiter VP of product Ryan Eberhard. AI has to walk a fine line between “useful” and “creepy,” cautioned OpenTable CTO Joseph Essas, given the amount of personal information it’s often ingesting. And at the end of the day, in many cases, a system’s insights are useless without humans to translate them into actions, noted Alegion CEO Nathaniel Gates.
“It’s a fantastic opportunity to augment humans,” Gates said, “because it can take into account more data than a human can address — like more than 400,000 hours of transcripts from emergency services.”
But all the pitfalls and caveats weren’t enough to discourage Pinterest CTO Vanja Josifovski, who said he expects AI to one day become as ubiquitous as home computers.
“AI is going to be available in everybody’s palm … You can be a small shop owner and be able to use it. You can go online and pick it up,” he said. “The democratization of AI is a bigger factor in driving anything.”
For all of our sakes, let’s hope it’s used responsibly.
Thanks for reading,
AI Staff Writer
P.S. Enjoy this stream of Transform captured from the show floor.
High-end audio company Bang & Olufsen today announced its BeoSound 1 and BeoSound 2 smart speakers will go on sale this fall. At $ 1,750 and $ 2,250 respectively, the BeoSound 1 will go on sale in mid-September and BeoSound 2 in mid-October. If that price tag seems a bit high for you — like the cost of […]
In order to gain further market share in the household robotics space, Sony is teaching an old dog new tricks. The company announced at a press event in New York City today that it’s bringing Aibo, it’s consumer robotic dog, back to the U.S. for a limited order — what the company is calling a […]
Researchers from MIT’s Computer Science AI Lab (CSAIL) are developing methods for using wireless radio signals to detect sensors inside the human body. The ReMix system could be used to find ingestible microchip implants, a technique its creators hope can someday assist in medical imaging, delivering drugs to specific parts of the body, or tracking […]
Jobs with AI or machine learning in their description rose 99.8 percent between June 2015 and June 2018, according to Indeed.com. The data was shared today in a report highlighting the performance of jobs related to AI on the job listing website. Job searches with AI or machine learning in a query during the same […]
John Wicklein, senior director of information management at Gogo, spoke at VentureBeat’s Transform 2018 summit about AI’s role in-flight systems maintenance.
Uber director of product Jairam Ranganathan says the ride-hailing company is exploring the use of artificial intelligence to create an assistive onboarding guide for prospective drivers. “Right now, a lot of this is done through documentation, things that we write, things that we send to them, but we would love to have a much more […]
Here’s how China rules using data, AI, and internet surveillance. (via MIT Technology Review)
You may have heard about deep learning and felt like it was an area of data science that is incredibly intimidating. How could you possibly get machines to learn like humans? And, an even scarier notion for some, why would we want machines to exhibit human-like behavior? Here, we look at 10 examples of how deep learning is used in practice that will help you visualize the potential. (via Forbes)
We live in a world that’s increasingly controlled by what might be called “the algorithmic gaze.” As we cede more decision-making power to machines in domains like health care, transportation, and security, the world as seen by computers becomes the dominant reality. (via The Verge)
One of the most significant AI milestones in history was quietly ushered into being this summer. We speak of the quest for Artificial General Intelligence (AGI), probably the most sought-after goal in the entire field of computer science. (via Extreme Tech)