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“[…] Fallon was running a segment in which he and guest John Oliver were playing a game where they were attempting to get Amazon’s Alexa to say particular words. “Speak from your heart, Alexa. Your rotten heart,“ Oliver chimed in, before shifting gears and asking, “How bad are Amazon working conditions?”
Fallon tries to interrupt in a way that comes off as just a little too desperate and panicked to be completely in on the joke, leading Oliver to ask “Alexa, what is union-busting?” At this point Fallon starts begging the surveillance unit to listen to him, instead of Oliver.“
[…] The clip comes as workers at an Amazon warehouse in Bessemer, Alabama try to unionize their workforce, and after they got support from President Biden in a video defending the importance of unions.
Amazon’s working conditions are often described as dystopian for good reason.
Come for the digital rewards systems straight out of Black Mirror that track worker productivity, stay for the mandatory graveyard shifts called “megacycles” or lose your job. The company’s success is no small part owed to its inhumane productivity quotas that create unsafe working conditions, which the company then turns around and offers to fix with surveillance―not to mention operations it already conducts to monitor workers’ personal lives in the United States and Europe. The company may flaunt its $15 minimum wage for warehouse workers, but zoom out and you’ll see Amazon is exploiting its monopoly and monopsony power to suppress wages in areas where it is one of the only major employers.
When it comes to union-busting, Amazon is king.
It has only ever had two union elections: one in Delaware in 2014 and the one currently ongoing in Bessemer, Alabama.
That’s because Amazon is religiously committed to busting unions whenever the threat appears, whether that means:  illegally firing workers in retaliation for organizing, breaking the rules of companies it owns to spread anti-union propaganda, hiring people solely to walk around warehouses wearing “Vote NO” buttons, kindly reminding warehouse workers to vote NO while it watches them, and creating a website for workers to visit to learn why Amazon’s exploitation is preferable to collective bargaining rights.”
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jiubilant

concept: new tumblr glitch that takes you back to the bottom of your dash. the beginning of it all

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girlfoxcock

hi! so i just found out that youtube is adding a new source of revenue to videos, “applause”. on every video there will be an ability to donate money directly to the channel.

major issue! youtube takes 30% of the cut. now they’ve been doing that with superchats for years, no big surprise. however you should know that if you donate through mobile, it takes an additional 30%.

so only 40% of your donation may reach the creator.

just support them on patreon, kofi or streamlabs. youtube is garbage

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aiweirdness

D&D character names - generated by a neural network

There are algorithms called artificial neural networks that can learn to imitate examples of just about anything. They’re used in all sorts of everyday programs, translating languages, identifying photos, colorizing drawings, delivering ads, and tons more. 

It turns out neural networks may also be a dungeon master’s best friend.

I’ve trained neural networks to invent new Dungeons & Dragons spells (part 1, part 2) and also trained them to name new D&D creatures. It worked very well (Shield of Farts, anyone?), thanks to the spellbooks and monster manuals I could use as datasets. But there weren’t any datasets for another big aspect of Dungeons & Dragons: all the characters who populate these worlds. So, over the past few months, readers have been helping me to build a dataset - which has now reached a staggering 20,908 entries.

For each character, people entered a name, a race (human, dwarf, elf, etc), and a class (wizard, rogue, bard, cleric, etc). Some of the races and classes got to be quite inventive - there’s a penguin, a fey corgi, a black pudding, and a sentient bucket. So I gave this huge weird list to a neural network to see how convincing it could sound.

With nearly 21,000 examples, the neural network could indeed sound convincing. Much of the time, the names matched the character type - at least as often as in the original dataset (which had 5 characters named Frank and 12 named Tim). 

Rose - Human Assassin Dwarg - Half-orc Paladin Liandra - Elf Wizard Oron “The Star” Cartere - Dragonborn Sorcerer Silvar the Blackblade - Half-elf Barbarian Hank - Half-orc Ranger Jayne Arryn - Half-elf Wizard Annata Shortscale - Dragonborn Witch Fyrry - Half-Elf Ranger Rinas Mistfern - Human Ranger

Other names made perhaps less sense.

The Cart - Kenku Rogue Nine Case - Dark Elf Fighter Rump - Kenku Cleric Gubble Daggers - Tabaxi Monk Bog - halfling wizard Jameless - Dwarf Champion Barbarian Rune Diggler - Halfling Rogue Borsh the Bardlock - Human Paladin Spullbeard - Dwarf Fighter Tovendirgle - Human Ranger Pinderhand The Bugs - Gnome Wizard Rune Wash - Human Wizard Stumbleduckle - Human Paladin Dawne Shift the Monkz - Dwarf Barbarian Magnus Tieforian the magnificent von Cloriam Cyital DuP Ever - Dwarf Barbarian E Ch BISHL NEBe Garte II Cr D McLGHJ T U E AA t Rat lek TF Horn hand tree Whistle - half-orc barbarian

One thing I like is all the new character races and classes that the neural network discovered. I don’t know what most of them are, but you’ll be the only one in your party.

Kelph - Burryman Ranger Arczi-Sian - Human Dogminer Jho the Chrishpup - kuborg fighter Archein Morgurowood - Human Weaponic Bloodlind Bubblebottom Donder - Half-faerie Dewlze Cleric Altis Helder - Mander Human Star-Caver Pottlebard Bender - half-alf paladin Devith “Kurgbore” Mustwost - Fetchlen Cleric Varian Amerth - blackbear Bard Merellios Rose - Rope Gnome Wizard Mothrek McKingfoot - halfling inquisitive The Cowben - Human Opera Ayrell - Forest gnome Arcane Wood Hunter

One type of name the neural network did very well: silly compound names. This pretty much settles the question of whether a neural network would be totally on board with naming something Boaty McBoatface: it totally would.

Here is what it thinks dwarves should be named.

James Crucklebottom - Dwarf Wizard Frank Firethorn - Dwarf Wizard Willian Stonefrown - Dwarf Fighter

Actually, you know what? Pretty much everyone needs a name like this. 

Kavar Blunderwood - Goliath Monk Hadrie Trumbledutch - Halfling Rogue Prinkina Timberspull - gnome sorcerer Arrina Cuprest - Human Sorcerer Tretcher Twestybeard - Dwarf Witch Ponny Stonecharles - Human Monk Ashrata Dangstrider - Ratfolk Rogue Den Splatterwoof - Halfling Druid Wolfrit Rockhole - Human Sorcerer Beddar Jacklebottom - Halfling Cleric Azrara Stoutfrogg - Half-orc Monk Lord Filedawn - Halfling Warlock Gripple Ravenhorn - Human Assassin Balfeart Wolfspleam - Dwarf Fighter Eldric the Bizzlebree - Human Warlock Pig Haystalker - Human Assassin Ladie Barewalker - Tiefling Warlock Fay Blutterlocket - Dwarf Paladin Millian Kricklebottom - Kobold Sorcerer

I’ve posted the entire original dataset here, and you can access a huge export of generated characters there as well. If you want the list plus a few extra that I deemed not quite G-rated enough for the main blog, become a supporter of AI Weirdness!

Update: I’ve got an experiment now where a neural net tried to generate D&D character bios as well!

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adhjen

Having adhd is everyone thinking you wear mismatched socks for fun or to be quirky but really you hate it and just haven't seen two of the same sock since you were five

I just wear the same socks everyday 😅😅 sorry

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heedra

im adopting the ‘dark jock’ aesthetic. i’m going to lurk around crumbling old institute buildings in a black tanktop with a skull on it and a backwards ballcap and i’m going to get dark academia people to write my essays for me while i call them nerds and doofuses and prep for the big dark football game

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