Swayy is an iPhone app startup that allows you to share not your current location, but your next intended location.
I also liked the way the Swayy app allows me to create custom groups.
As Westropp pointed out, as a female founder, she’s acutely aware that being able to control precisely who can see her future location is something she hard-wired into the app.
Of course, Swayy is likely to struggle against the tech giants already toying with location as feature.
It will also be an opportunity for Instagram to appeal to people who were fans of Zenly, a social map app that Snap acquired and then shut down in 2022.
Substack is updating its peer-to-peer recommendation system, the company announced today.
With this new update, Substack is helping writers aid other writers in expanding their reach and potentially getting more subscribers and followers, as the company is now allowing writers to curate and share a list of publications for their readers to subscribe to.
Most social media networks currently leverage algorithms for their recommendation systems, but Substack is instead focused on allowing writers to curate their own networks of recommendations.
Substack says the new update will help writers build up goodwill with other writers by helping them reach more people, while also helping readers curate a worldview.
The platform will show writers how many subscriptions and follows they have driven for people in their network.
Massive training data sets are the gateway to powerful AI models — but often, also those models’ downfall.
Morcos’ company, DatologyAI, builds tooling to automatically curate data sets like those used to train OpenAI’s ChatGPT, Google’s Gemini and other like GenAI models.
“However, not all data are created equal, and some training data are vastly more useful than others.
History has shown automated data curation doesn’t always work as intended, however sophisticated the method — or diverse the data.
The largest vendors today, from AWS to Google to OpenAI, rely on teams of human experts and (sometimes underpaid) annotators to shape and refine their training data sets.
