The Twitter Annual Meeting was held yesterday at the Twitter headquarters in San Francisco on Market Street. Jack Dorsey, the CEO, spoke about the goals for the company.
Areas covered were:
Improving Timeline
Notifications
Safety, with regard ti transparency, better tools, and deep learning & machine learning
Improving Timeline
Notifications
Safety, with regard ti transparency, better tools, and deep learning & machine learning
Dorsey talked about three major improvements:
- Twitter Lite – for Safari or Chrome on mobile devices
30% faster load times
Uses less than 1 meg of data
Looks identical to the app
Can turn on Data Saver – all images, videos, gifs blurred
Reduce data usage by 70% - Explore tab -brings everything together
Trends, Moments, Live Events - Mute – Safety control
Notifications -muted words -pause and not see
Anthony Noto, Twitter’s CFO, then spoke. He talked about the Live Streaming Video and expansion into:
Sports
News
Entertainment
ESports
Sports
News
Entertainment
ESports
He said that in Q1, there was 800 hours of live video content, over 450 events, with more than 200 premium content partners.
All the shareholder resolutions passed except the one that proposed that Twitter become a user owned company. The proposal said:
“A community-owned Twitter could result in new and reliable revenue streams, since we, as users, could buy in as co-owners, with a stake in the platform’s success. Without the short-term pressure of the stock markets, we can realize Twitter’s potential value, which the current business model has struggled to do for many years. We could set more transparent accountable rules for handling abuse. We could re-open the platform’s data to spur innovation. Overall, we’d all be invested in Twitter’s success and sustainability. Such a conversion could also ensure a fairer return for the company’s existing investors than other options.”
The questions and answers were related to looking into a Twitter Prime type service where some users could pay for a premium service, and utilizing artificial intelligence through machine learning and deep learning for timelines and notifications.