If Trump were to be impeached and removed from office because of the Ukraine shakedown, Mike Pence would not become President, or at least not for long. He also participated in the wheeling and dealing, so would also be impeached.
Back in the days when only scientists and software engineers knew about algorithms, and the words “filter” and “bubble” were only next to each other on a Scrabble board, we had blogrolls. This would be a selective list of the blogs that you subscribed to placed on your own blog. Selective because only the bravest people put all their feed subscriptions on public show, unless you didn’t mind everyone knowning you had a thing for Selzer drinks or dogs dressed as Star Wars characters.
If I write a blog post in reply to somebody else’s blog post, there should be a link back to my post from the one I commented on.
Trackbacks are used primarily to facilitate communication between blogs; if a blogger writes a new entry commenting on, or referring to, an entry found at another blog, and both blogging tools support the TrackBack protocol, then the commenting blogger can notify the other blog with a “TrackBack ping“; the receiving blog will typically display summaries of, and links to, all the commenting entries below the original entry. This allows for conversations spanning several blogs that readers can easily follow.
You recoil at the spamminess of this, I know. Yes, this leads to more spam than ham. That is why the world does not work this way. Trackback is dead.
Some individuals or companies have abused the TrackBack feature to insert spam links on some blogs. This is similar to comment spam but avoids some of the safeguards designed to stop the latter practice. As a result, TrackBack spam filters similar to those implemented against comment spam now exist in many weblog publishing systems. Many blogs have stopped using trackbacks because dealing with spam became too much of a burden.
It is also true but irrelevant that spam is an AI for truthtelling.
Trackback has nasty technical problems, and for that reason there are a number of alternative protocols, such as (notably) Webmention. (Here’s a good article on all the options: Linkback).
But spam is the blocker, and it’s so bad that none of the options gets used much. That’s really really really too bad, because linkbacks are critical for a lively and vital ecosystem of decentralized social networking.
It doesn’t have to be this way. There is a trivial solution to all linkback spam: a whitelist of friends, such as you find in a blogroll.
I envision a WordPress plugin with these features:
On the inbound side, it receives and displays linkbacks. On the outbound side it sends them.
When a linkback is received, it checks the whitelist. If the sender is whitelisted, it is auto-approved. Otherwise the linkback goes into the spam queue for manual approval.
When a linkback is manually approved, the source site goes into the whitelist.
Maintain a blogroll. Allow the blog owner to add sites. Display the blogroll. Use the blogroll to populate the white list.
P.S. On this blog I have a plug-in which implements Webmention linkbacks, but to my knowledge this has never caused any outbound or inbound linking. The only utility of this plugin is that it helps me signal that I approve of the protocol design.
At Dorkbot SF last night there was a super creative talk on telepresence by Alex Glow. She had a lot of ideas on modalities for social connection at a distance.
Inspired by that I dreamed up a hand-holding telepresence romance bot.
There would be two linked hand sculptures, one from each member of a couple. Each one would be a model based on a casting. The two source hands would remain in the picture, so there’s living hand A, copy of A, living hand B, copy of B.
The hands would be robotic in that the fingers and wrist could move just like a normal hand. The hands could wave, do a peace sign, a vulcan hello, a firm grasp, a soft grasp, etc. Like Thing in the Adddams Family.
The handbot could be held. The expectation is that a living human hand’s would grasp the handbot. The specific living hand doing the holding would belong to one member of the couple. The bot would have sensors to detect pressure and convert that into a model of the actions of the living hand holding the bot hand.
That model would be transmitted to the linked handbot based on the living hand. The linked handbot would execute the model. Performance of the model would complete transmission.
Since this is all about touch the texture matters. Instead of metal or fake skin the robotic hands could be covered with a textured fabric like velvet.
This apparatus would be a remote hand holding device.
Romance is the main reason people would use it, but romance isn’t the only reason people hold hands. We shake hands. We thumb wrestle. I held my father’s hand when he was in bed, very ill. My seven year old holds my hand just because he wants to.
I envision couples separated by distance holding hands during a phone call. For example one member is on a spaceship, one is at home.
While Hoffman and Yeh’s book claims that companies like Google, Facebook, Microsoft, Apple, and Amazon are icons of the blitzscaling approach, this idea is plausible only with quite a bit of revisionist history. Each of these companies achieved profitability (or in Amazon’s case, positive cash flow) long before its IPO, and growth wasn’t driven by a blitzkrieg of spending to acquire customers below cost, but by breakthrough products and services, and by strategic business model innovations that were rooted in a future that the competition didn’t yet understand. These companies didn’t blitzscale; they scaled sustainably.
Facebook’s rise to dominance was far more capital-intensive than Google’s. The company raised $2.3 billion before its IPO, but it too was already profitable long before it went public; according to insiders, it ran close to breakeven from fairly early in its life.
To my own mind the fundamental problem with blitzscaling is that it salts the fields. When an investor-funded company like Uber enters a market with a nonsensical business, it undermines the economics for companies in that same space. Cab drivers, for example, were able to make a real living before Uber.
Given a randomly selected stack of photos, an algorithm could put them in order such that they appear to be morphing. What’s creative is that the morphing would be done without transforming any of the images.
Here’s a black car turning into a white cat.
The simplest algorithm would start with a set of random images and a similarity score between every pair of images, and a randomly chosen starting image. Then, given any previous image, the next would be the most similar unused one.
Choosing the starting image at random will lead to missed opportunities. In the example sequence above, if it had started with any image but the black car, the black car would have been left until last, and ended up appearing after the white cat. This would make no sense visually. It would create a breaking point in the sequence where everything went off the rails.
A different algorithm:
Start with a set of random images, a similarity score between every pair of images, and a randomly chosen starting image. Then, for any unused image, insert it into the sequence at the point where the sum of the distances between the inserted image and the adjacent ones is smallest.
However, at each step you might be planting problems for later. Another strategy would be to invent a metric for the chain as a whole, start to finish, and use a Markov Chain to find the optimal sequence.
(Idea for the metric:
sum of all pairwise distances. This would capture places where a choice earlier forced a bad selection later
largest jump between any pair of images).
Ok, I have to go to work. This has been an entry in an open notebook.
Podcasting needs metrics. There’s no reliable way to track listenership.
Advertisers need to know what they’re buying. The ad business is utterly reliant on hard data about listeners. They need to know how many listeners they’re reaching and what the listener demographics are. To prevent fraud by podcasters, advertisers also need provability.
On the content creation side, podcasters need to know what listeners like and don’t like. Youtube has a feature to show video creators when viewers drop off. Podcasting has nothing like that.
These are solvable problems. A simple-ish way to create metrics is to provide streaming audio rather than downloadable. Technically this is well-known territory. Mozilla has excellent documentation.
It’s simple in theory, but in practice there are hurdles.
This approach would exclude listeners who download their audio in advance. I doubt this is a big proportion.
Podcasting portals may serve up their own copies of podcast audio files, rather than redirecting to the original URL hosted by the podcaster. Streams can’t be cached.
Podcast listening tools may not support streaming MP3. How bad a problem this is depends on which streaming technology the podcaster is using.
Podcasters probably would lose listeners. How many listeners would they lose? They would probably be able to charge higher ad rates, and sell to more advertisers. Would that advantage in ad rates and sell-through outweigh the drop-off in listenership?
After more important expenses, there’s no way these are acceptable costs for most Americans.
ultimately, consumers will be paying huge monthly sums and subject to the bundling deals of whichever network they choose to be connected by, albeit with the ability to pay a la carte for additional subscriptions on top of our bundles. We’ll swap one set of gatekeepers with another set of gatekeepers.
I think he’s missing the simplest solution: only subscribing to one source. Netflix is insanely deep. A family could easily get by with nothing but paid Netflix and free Youtube.
If that’s the path the masses eventually take, we’ll have a situation like the desktop OS market, which has only three real competitors.