Today’s topics include democratic lawmakers’ proposal for new disclosure rules for political web ad sources; Google’s release of new YouTube advertising tools; SAP’s acquisition of Gigya for its customer ID management tools; and Microsoft’s announcement of a new Azure Machine Learning Experimentation Service.
In a rare unanimous vote, the Federal Election Commission has decided to reconsider updating its online disclosure rules for internet advertising put in place in 2006. They plan to invite representatives from Facebook, Twitter, Google and other large services to attend public hearings on new regulations.
Democratic Senators Mark Warner and Amy Klobuchar are asking their senate colleagues to support a bill that would place disclosure requirements on online platforms similar to the ones for television.
Platforms with a million or more users would be required to create a public database of all “electioneering communications” purchased by any person or group who spends more than $10,000 on online political ads. The database would include a digital copy of each ad, the intended audience, number of views, when the ad ran, its price and who paid for the ad.
Google has released a set of new tools to help advertisers deliver highly personalized ads on YouTube using an individual’s search history, the places they visit, or the apps they have downloaded.
One of the new tools is called Director Mix, which mixes building blocks like voice-overs, copy, and background to deliver thousands of different versions of the same ad.
A feature called Custom Affinity Audiences targets people based on browsing data and app downloads, giving businesses a way to reach people who might be interested in products and services similar to their own even as people search for or watch videos of other products on YouTube.
Finally, Video Ad Sequencing lets organizations string together and use a series of short, 15-second or so sequential ads to communicate a marketing message.
SAP, best known for its durable enterprise apps and the HANA in-memory database, is expanding its customer identity and access management by acquiring Gigya, which currently manages 1.3 billion customer identities, for a reported estimated $350 million.
Gigya’s customer identity and access management platform enables enterprises to build lasting relationships with their customers, allowing companies to manage customers’ profile, preference, opt-in and consent settings.
“Combining the data matching and enrichment capabilities of SAP Hybris Profile with Gigya’s consent-based identity data and access management platform will allow us to identify consumers across channels and offer a robust single consumer profile,” Gigya CEO Patrick Salyer said.
Microsoft unveiled the new Azure Machine Learning Experimentation Service at its Ignite conference on Sept. 25 which provides AI developers with the “resources to run on a large cluster [along with the] version control” required for developers and data scientists to both accelerate and effectively track AI projects.
Anchored by Git repositories, users can create a history of how their models evolve over time and use that information to pick the AI models that work best for their applications in less time.
To establish sustainable and repeatable workflows, projects are managed with a simple command line tool that handles training runs.
Based on program synthesis and data cleaning technologies from Microsoft Research, the new AI-powered data preparation tools reduce the time it takes to perform data science, said Joseph Sirosh, corporate vice president of Cloud AI at Microsoft.
