Formed in 2009, the Archive Team (not to be confused with the archive.org Archive-It Team) is a rogue archivist collective dedicated to saving copies of rapidly dying or deleted websites for the sake of history and digital heritage. The group is 100% composed of volunteers and interested parties, and has expanded into a large amount of related projects for saving online and digital history.
History is littered with hundreds of conflicts over the future of a community, group, location or business that were "resolved" when one of the parties stepped ahead and destroyed what was there. With the original point of contention destroyed, the debates would fall to the wayside. Archive Team believes that by duplicated condemned data, the conversation and debate can continue, as well as the richness and insight gained by keeping the materials. Our projects have ranged in size from a single volunteer downloading the data to a small-but-critical site, to over 100 volunteers stepping forward to acquire terabytes of user-created data to save for future generations.
The main site for Archive Team is at archiveteam.org and contains up to the date information on various projects, manifestos, plans and walkthroughs.
This collection contains the output of many Archive Team projects, both ongoing and completed. Thanks to the generous providing of disk space by the Internet Archive, multi-terabyte datasets can be made available, as well as in use by the Wayback Machine, providing a path back to lost websites and work.
Our collection has grown to the point of having sub-collections for the type of data we acquire. If you are seeking to browse the contents of these collections, the Wayback Machine is the best first stop. Otherwise, you are free to dig into the stacks to see what you may find.
The Archive Team Panic Downloads are full pulldowns of currently extant websites, meant to serve as emergency backups for needed sites that are in danger of closing, or which will be missed dearly if suddenly lost due to hard drive crashes or server failures.
Posterous launched in 2008. Our mission was to make it easier to share photos and connect with your social networks. Since joining Twitter almost one year ago, we’ve been able to continue that journey, building features to help you discover and share what’s happening in the world – on an even larger scale.
On April 30th, we will turn off posterous.com and our mobile apps in order to focus 100% of our efforts on Twitter. This means that as of April 30, Posterous Spaces will no longer be available either to view or to edit.
Right now and over the next couple months until May 31, you can download all of your Posterous Spaces including your photos, videos, and documents.
Here are the steps:
Go to http://posterous.com/#backup.
Click to request a backup of your Space by clicking “Request Backup” next to your Space name.
When your backup is ready, you'll receive an email.
Return to http://posterous.com/#backup to download a .zip file.
If you want to move your site to another service, WordPress and Squarespace offer importers that can move all of your content over to either service. Justmigrate offers a service to move your site to Tumblr.
More information on these services can be found here:
We’d like to thank the millions of Posterous users who have supported us on our incredible journey. We hope to provide you with as easy a transition as possible, and look forward to seeing you on Twitter. Thank you.
Sachin Agarwal
Founder and CEO
TIMESTAMPS
The Wayback Machine - https://web.archive.org/web/20130517215753/http://mikhas.posterous.com/tag/presage
I had to hack the Presage engine a bit to provide word prediction in a similar fashion to what you see in the 2-3 seconds of the Blackberry video. Then I added some space between the rows of the keyboard, so that I could place additional word ribbons there. The word candidates appear next to their starting letters, though it’s only one candidate per letter. I need to find a better solution here, but then again Blackberry guys also haven’t solved it either ;–) Tapping on the word candidates inserts then into the text editor (no gestures, for now).
The code is very hackish, certainly nothing I would publish. I am going to put it onto a tablet so that I can show it around to you guys at the TiZen Developer Conference or the Ubuntu Developer Summit.
Jon is going to bring a camcorder on Sunday, so perhaps we can actually record a real, youtube-worthy video then.
This is a feature that I personally wanted for a long time. Interrupted by FOSDEM, some Wayland research and many other things, I finally managed to get word prediction and error correction beyond prototype quality. The video shows just how amazingly good the Presage word prediction can be, even without extensive training (in fact, for the video we used the minimal language model training that comes with a regular Presage installation). The second part of the video shows how combining Presage with a spellchecker such as Hunspell further improves the provided word candidates.
Presage uses a very scalable approach called text n-grams. There is a lot of research in that area, but language models of contemporary language usage are either well guarded or cannot be freely distributed. Luckily, Presage comes with training tools such as text2ngram. Users can feed arbitrary language corpora to it, though one should be careful to perhaps not mix different languages too much.
Matteo Vescovi, the author of Presage (formerly known as Soothsayer), started the work as part of his master thesis a couple of years ago. The heart of Presage are the different predictors. They can be queried in parallel and the result lists are merged, using probability analysis.
Presage certainly has a lot of potential. It comes with an easy to use C++ API but also provides bindings for C and Python. In fact, it even provides a D-Bus API, which would make it possible to run it as a system service. The user could then benefit from (and train!) the same language models from different applications.
Hunspell probably doesn’t need much introduction. It is used in many Linux desktops. It’s a fine library and comes with many dictionaries. However, one should be aware that Hunspell itself cannot provide word prediction, which is why it wasn’t enough for mobile text input. As a fallback for Presage, it works very well though.
Of course there are a couple of things we could do from here. As Jon mentioned in the video, the virtual keyboard’s word ribbon UI could host word suggestions from other applications, such as the Google search in the browser. For Unity’s dasher input or Gnome Shell’s search, the application names could be shown instead. Or we could hook it up to Bash completion.
PS: Anyone up to package Presage for Fremantle or Nemo? It could be pretty interesting to see the next release of Maliit running on the N900.