Your favorite radio stations without commercial interruptions.
That’s the brand promise of Auddia, the developer of a proprietary AI platform for audio and innovative technologies for podcasts that is now reinventing how consumers engage with audio.
It’s the subject of the latest InFOCUS Podcast, distributed ahead of a major announcement from the Boulder, Colo.-based technology company. Auddia, not to be confused with Audacy (formerly Entercom), says it’s achieved “a major advancement” in its proprietary technology at the core of its Artificial Intelligence engine.
“By leveraging precise audio and metadata from radio stations, Auddia will reduce the costs of processing audio content for AI training and validation to near zero and concurrently realize vastly superior improvements in accuracy,” the company says.
While that statement is loaded with marketing jargon, one thing is perfectly clear for Wall Street: the new AI processing methodology gives Auddia near real-time data processing capabilities, which will likely improve overall performance of the company’s platform while cutting the onboarding time for stations by a factor of five.
The announcement pushed Auddia stock up 11 cents, to $2.88. While that’s hardly newsworthy, as prices topped $3 a share earlier this month, it is the volume that deserves notice.
As of 1:30pm Eastern on Tuesday, volume for AUUD, which trades on the Nasdaq GlobalSelect market, reached 9.58 million shares; average volume for Auddia stock is just 54,443 shares.
Helping Auddia’s Wall Street rise is the company’s decision to use the new AI methodology for its trials with Lakes Media and Sonoma Media, discussed in the InFOCUS Podcast featuring Lakes owner Tom Birch.
A full national launch is expected for the second half of 2021.
“Our latest advancement in AI takes advantage of what we always understood to be one of the most valuable elements of the audio content ecosystem, which is the abundance and open availability of audio data,” Auddia Chief Technology Officer Peter Shoebridge said. “Accurately tagging that audio data with precise metadata is the ultimate objective, and our new methodology enables us to meet that objective. Recent test results that allow us to compare our new approach to previous methods reveals orders of magnitude improvement in areas that are critical to the business, including accuracy, speed and timeliness of AI training, and the costs of operation.”
Auddia Chief Executive Officer Michael Lawless added, “While our initial AI engine produced suitable results, this major advancement in technical capability is a game changer for the company. We always had a sense that a significant leap forward was on the horizon, so we are pleased to achieve this major milestone now, as we launch our first commercial consumer facing trials and anticipate a rapid increase in radio station deployments. The expectation is that the user experience will be positively impacted as a result of this advancement.”
The technology advancement, for example, would allow Auddia to train the AI model on a group of six radio stations; the previous approach required a minimum of 50 hours of audio to achieve satisfactory results, the company notes. “This human-intensive process would take five days with hard costs over $2,100. With the latest advancement, the same group of stations can be trained on 1008 hours of audio data — a 20X increase in data volume — with zero hard costs, completed in a single day (versus 5 days).”
The important fact: the AI-powered method yielded “far greater accuracy.”
