Spamming "$$$ $TSLA to the moon! Get latest tips on my free Discord bit.ly/ocozxc #TWTR #GOOG #AMC #GME $$$" thousands of times for days before suspension is hardly the hardest problem on the Internet
Heck, you could even just limit the number of hashtags in a single tweet (say, 2) and fix 95% of Twitter's spam problem without harming legitimate users in any way
There must be some expectation about the rate of share issuance, I think that's what the parent comment is getting at. ESOP pools are well understood (and IIRC defined upfront). Threatening to sell massively discounted shares equivalent to existing shares without even so much as an SEC filing about it (as of a few hours ago), that's the part where it becomes questionable for me. If the new shares are marketable, then this is a defensive measure that actively destroys value for all existing shareholders.
A company cannot issue unlimited shares without concern for existing shareholders - taken to the extreme, doing so reduces the value of all holdings to zero.
Because he's a near-10% shareholder and accounts like his are a major driver of new account growth. I wonder if this episode has impacted growth or engagement metrics any. Hard to imagine it hasn't
It is a bit like coal mining.. even the default new account experience encourages subscribing to a bunch of spam, when what is needed is mining one seam in that mess containing just the desired content (people).
Finding a tight-knit specialist community goes against everything the Twitter UI encourages, but it's how most folk who are deeply loyal to the platform actually use it. When configured well, the timeline should be significantly comprised of conversations between known people talking about desirable topics.
Personally I think this is the core of the tool - free, open access to specialist communities with no membership requirements, and no need for upfront reputation. If some conversation between experts interests you and you have a question, you can just ask.
One approach is to start by following one account you really like, then mining their replies following the folk they actively engage with. Do this for a few iterations and the result will quickly become an extremely intimate, engaging, and topical timeline. It only takes a few meaningful questions and comments added to these conversations for the follows and inclusion to start flowing your way.
Bootstrapping a network the size of Twitter is nothing like easy, and might even be impossible this late in the game. Gold rushes of new users tend to wear off as new areas calcify into established concepts.
(The same would be true for launching a modern day FriendFeed / Bebo / MySpace etc)
I know you're being dramatic, but at least charities in the UK do have vastly different treatment by HMRC, and much more granular financial reporting requirements.
Just a suggestion, but please lead with what the company does, not a link to the blog of some engineering micro-bubble. That really gives a bad impression. Many folk here are scanning for companies they want to work for, not tech teams doing "tech stuff". That's everywhere
This is an expensive lesson I think everyone gets to learn at some point. There's no such thing as a file worth excluding from a backup, it always fucks you, some (like me) more than others. Have to buy twice as much disk? Fine, at least you know you actually have a backup
Signal's insistence on doing the wrong thing for 99% of users (storing media blobs in SQLite) drives me crazy. Protect our metadata over the wire, fine, but there is almost no additional protective benefit whatsoever by storing the files inside SQLCipher when the user's fingers can be broken one-by-one until they unlock their phone.
Meanwhile it causes issues just like this, not to mention broken integration with every audio/gallery/video app on the device.
I'm probably slightly tempered from just having read this article, but curious how anyone could confidently arrive at an economic estimate of the global trade in CSAM
The BBC article is only talking about generation time, specifically not download time (including linked assets), and we have no idea about dwell time.
It only takes a 3G connection a few miles outside a city to add another 500ms to that opening request. Say we're up to a second before some readable text appears, now we'd like to know how long the user will actually spend reading the text or waiting for images to load before navigating again.
Intuitively, I think that load time/dwell time ratio probably captures what those studies talk about better than just raw numbers. 1 second between 10 second TikTok video loads would be extremely noticeable, but barely worth mention if the user instead was spending 10 minutes reading e.g. a feature length news article.
My personal BBC reading habit regularly involves clicking into an article just to catch the opening paragraph and seeing which opening image they used (they rarely use the same for the thumbnail). The average is probably not as low as 10 seconds, but it's certainly something much less than 2 minutes.
Dwell time probably isn't a great way to capture it either. My pattern is quite "flicky" but I bet there is a spectrum all the way from "reads every last word" to "literally just loves to click". I guess latency becomes increasingly important for folk further along that spectrum
The CPU throttling of the lower memory settings is often easily visible in a user-facing request, even simple requests just doing some DB IO. I rarely use less than 1024mb for anything
edit: the BBC review is horrifying:
> The page takes around 500ms to render and be delivered to the audience. In that timeframe we invoke around 30 functions. Around 150ms is spent running React to render the content to HTML
> we aim to personalise almost every page in some way — making it relevant for every user on every request
Good luck making perf numbers with all those cold cached personalized pages
I upvoted it as a curiosity. The idea of a cultural agenda-signalling bot loose on GitHub actively breaking code and documentation sparks quite a few feelings. Some questions arise, such as whether or not any of the projects receiving contributions from the bot are improved in any material (technical, inclusiveness) way. It's quite common that absolutely the wrong thing gets done in the name of some noble cause, seems this is a fine example of that.
Given Victoria Metrics is the only solution I've seen to make data comparing it to other systems easily accessible as part of official documentation, it's the only one I pay attention to.
I knew from reading the docs what VM excelled at and areas it was weak in, long before I ever ran it (and expectations from running it matched the documentation). I hate aspirational marketing-saturated campaigns for deep tech projects where standards should obviously be higher, it speaks more about intended audience than it does the solution, and that's why in this respect VM is automatically a cut above the rest.
Thanks. It seems extremely reminiscent of e.g. the Cobalt RaQ ( https://en.wikipedia.org/wiki/Cobalt_RaQ ), but maybe "AWS Outposts for the rest of us" might be a more suitable contemporary parallel
Can anyone explain Oxide's product beyond the (fairly terrible IMHO) site? Seems like some kind of prepackaged VMware-alike including rack + hardware + networking fused into a single uncustomizable product?
Heck, you could even just limit the number of hashtags in a single tweet (say, 2) and fix 95% of Twitter's spam problem without harming legitimate users in any way