Teleport enables teams to easily adopt the best SSH practices like: Integrated SSH credentials with your organization Google Apps identities or other OAuth identity providers. No need to distribute keys: Teleport uses certificate-based access with automatic expiration time. Enforcement of 2nd factor authentication. Cluster introspection: every Teleport node becomes a part of a cluster and is visible on the Web UI. Record and replay SSH sessions for knowledge sharing and auditing purposes. Collaboratively troubleshoot issues through session sharing. Connect to clusters located behind firewalls without direct Internet access via SSH bastions.
Many DynamoDB users store data that has a limited useful life or is accessed less frequently over time. Some of them track recent logins, trial subscriptions, or application metrics. Others store data that is subject to regulatory or contractual limitations on how long it can be stored. Until now, these customers implemented their own time-based data management. At scale, this sometimes meant that they ran a couple of Amazon Elastic Compute Cloud (EC2) instances that did nothing more than scan DynamoDB items, check date attributes, and issue delete requests for items that were no longer needed. This added cost and complexity to their application. In order to streamline this popular and important use case, we are launching a new Time to Live (TTL) feature today. You can enable this feature on a table-by-table basis, specifying an item attribute that contains the expiration time for the item.
This is so spot on. I hope Google address this issue —
YouTube is crucial part of the misinformation ecology. Not just a demand issue: its recommender algo is a “go down the rabbit hole” machine. You watch a Trump rally: you get suggested white supremacist videos, sometimes, auto-playing. Like a gateway drug theory of engagement. I’ve seen this work across the political spectrum. YouTube algo has discovered out-flanking and “red-pilling” is.. engaging. So it does.This thread was in response to this Buzzfeed article on the same topic: https://www.buzzfeed.com/josephbernstein/youtube-has-become-the-content-engine-of-the-internets-dark
At dinner I asked some of the women to speak to me about this, how astronomy became so (relatively) egalitarian. And one topic became clear: role models. Astronomy has a long history of women active in the field, going all the way back to Caroline Herschel in the early 19th century. Women have made huge contributions to the field. Dava Sobel just wrote a book about the women who laid the foundations for the discovery of the expansion of the universe. Just a couple of weeks ago, papers ran obituaries of Vera Rubin, the remarkable observational astronomer who discovered the evidence for dark matter. I could mention Jocelyn Bell, whose discovery of pulsars got her advisor a Nobel (sic). The most famous astronomer I met growing up was Helen Hogg, the (adopted) Canadian astronomer at David Dunlap Observatory outside Toronto, who also did a fair bit of what we now call outreach. The women at the meeting spoke of this, a history of women contributing, of role models to look up to, of proof that women can make major contributions to the field. What can computing learn from this? It seems we’re doing it wrong. The best way to improve the representation of women in the field is not to recruit them, important though that is, but to promote them. To create role models. To push them into positions of influence.
[The] results suggest that classifiers based on modern machine learning techniques, even those that obtain excellent performance on the test set, are not learning the true underlying concepts that determine the correct output label. Instead, these algorithms have built a Potemkin village that works well on naturally occuring data, but is exposed as a fake when one visits points in space that do not have high probability in the data distribution.