This is fascinating: an instructional video from 1988 for British Royal Military Police personnel to watch before travelling the 103 miles of autobahn across East Germany to West Berlin. (A Cold War refresher: West Berlin was completely surrounded by East Germany — the city was not on the border.) Those in transit had to follow many rules:
Approach the Soviet sentry who will be standing close to the small hut on the left of the road. He will salute you. You must, irrespective of your sex, status, or form of dress, return his salute.
They also couldn’t stop anywhere but a few designated areas, could only deal with Soviet personnel (and not East German personnel), were forbidden from speaking Russian, and obviously couldn’t take photos. What a time capsule!
See also this video that reconstructs that journey, from someone who was stationed in West Germany in the late 80s. (via open culture)
More about...
The NY Times has a short documentary on Chris Burden’s Shoot, a conceptual art piece from 1971 in which Burden is shot in the arm by a friend.
Burden passed away earlier this month. (via digg)
More about...
The winners and runners-up of the 2022 World Nature Photography Awards have been announced. An amazing collection of photos as usual — I’ve included some of my favorites above. From top to bottom, photos by Mr. Endy (couldn’t find a website), Jens Cullmann, Jake Mosher, and Sascha Fonseca. Fonseca had this to say about his incredible photo of the snow leopard above:
A beautiful snow leopard triggers my camera trap high up in the Indian Himalayas. I captured this image during a 3-year DSLR camera trap project in the Ladakh region in northern India. The mystery surrounding the snow leopard always fascinated me. They are some of the most difficult large cats to photograph in the wild. Not only because of their incredible stealth, but also because of the remote environment they live in.
More about...
*sigh* I get it. I get why people are so enthused about this Jon Stewart video. If you haven’t seen it, it’s a clip from Stewart’s show on Apple+ where he’s debating a Second Amendment purist gun nut who also happens to be a state senator from one of the states that’s trying to take away health care, reproductive rights, and persecute/prosecute LGBTQ+ people for daring to exist in public — basically a real “rights for me but not for thee” dickbag.
Anyway, I guess it’s fun to see Stewart dismantle this guy but arguing with a dimwitted ideologue in this manner is like that old saying: “What’s the sense of wrestling with a pig? You both get all over muddy…and the pig likes it.” Conservatives in America want what they want and don’t care about the arguments against it or facts or consensus or bipartisan anything. They only care about their radical ideology and their constituents who agree with them (and their constituents who don’t can go fuck themselves, I guess). In fact, they welcome arguments because it wastes the time and energy of people who would argue with them and they can’t lose because they don’t care about facts and they increasingly have no shame. See also Can You Really ‘Back The Blue’ If You’re Weak on Guns? from the same show.
Anyway, anyway, anyway…it’s gonna be a fun Monday here I guess.
More about...
I randomly came across this YouTube video from an engineer (civil, not railroad) who was building virtual railroads using wooden toy tracks, you know from when you were a kid. Anyway, it turns out that he was playing an open-world game called Tracks, which is available on Steam, Nintendo Switch, and Xbox. Looks fun — if I ever get any free time again, I might give this one a shot.
More about...
Ok, this is one where you’re going to have to trust me and just watch it. Grands Canons is a stop-motion animated video by Alain Biet of thousands of meticulously hand-painted images of everyday items moving and dancing to music.
A brush makes watercolors appear on a white sheet of paper. An everyday object takes shape, drawn with precision by an artist’s hand. Then two, then three, then four… Superimposed, condensed, multiplied, thousands of documentary drawings in successive series come to life on the screen, composing a veritable visual symphony of everyday objects. The accumulation, both fascinating and dizzying, takes us on a trip through time.
It’s really just wonderful — once you get into it, you won’t be able to stop watching. More of Biet’s work can be found on his website or on Instagram. (via waxy & colossal)
More about...
A beautiful scene from the 2014 Mauritanian film Timbuktu (which was recently included on Slate’s New Black Film Canon), in which young men under the rule of Islamic extremists quietly and defiantly play a forbidden football match with an imaginary ball. (thx, caroline)
More about...
In 2020, before the current crop of large language models (LLM) like ChatGPT and Bing, Emily Bender and Alexander Koller wrote a paper on their limitations called Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data. In the paper, Bender and Koller describe an “octopus test” as a way of thinking about what LLMs are capable of and what they aren’t. A recent profile of Bender by Elizabeth Weil for New York magazine (which is worth reading in its entirety) summarizes the octopus test thusly:
Say that A and B, both fluent speakers of English, are independently stranded on two uninhabited islands. They soon discover that previous visitors to these islands have left behind telegraphs and that they can communicate with each other via an underwater cable. A and B start happily typing messages to each other.
Meanwhile, O, a hyperintelligent deep-sea octopus who is unable to visit or observe the two islands, discovers a way to tap into the underwater cable and listen in on A and B’s conversations. O knows nothing about English initially but is very good at detecting statistical patterns. Over time, O learns to predict with great accuracy how B will respond to each of A’s utterances.
Soon, the octopus enters the conversation and starts impersonating B and replying to A. This ruse works for a while, and A believes that O communicates as both she and B do — with meaning and intent. Then one day A calls out: “I’m being attacked by an angry bear. Help me figure out how to defend myself. I’ve got some sticks.” The octopus, impersonating B, fails to help. How could it succeed? The octopus has no referents, no idea what bears or sticks are. No way to give relevant instructions, like to go grab some coconuts and rope and build a catapult. A is in trouble and feels duped. The octopus is exposed as a fraud.
The paper’s official title is “Climbing Towards NLU: On Meaning, Form, and Understanding in the Age of Data.” NLU stands for “natural-language understanding.” How should we interpret the natural-sounding (i.e., humanlike) words that come out of LLMs? The models are built on statistics. They work by looking for patterns in huge troves of text and then using those patterns to guess what the next word in a string of words should be. They’re great at mimicry and bad at facts. Why? LLMs, like the octopus, have no access to real-world, embodied referents. This makes LLMs beguiling, amoral, and the Platonic ideal of the bullshitter, as philosopher Harry Frankfurt, author of On Bullshit, defined the term. Bullshitters, Frankfurt argued, are worse than liars. They don’t care whether something is true or false. They care only about rhetorical power — if a listener or reader is persuaded.
The point here is to caution against treating these AIs as if they are people. Bing isn’t in love with anyone; it’s just free-associating from an (admittedly huge) part of the internet.
This isn’t an exact analogue, but I have a car that can drive itself under certain circumstances (not Tesla’s FSD) and when I turn self-drive on, it feels like I’m giving control of my car to a very precocious 4-year-old. Most of the time, this incredible child pilots the car really well, better than I can really — it keeps speed, lane positioning, and distance to forward traffic very precisely — so much so that you want to trust it as you would a licensed adult driver. But when it actually has to do something that requires making a tough decision or thinking, it will either give up control or do something stupid or dangerous. You can’t ever forget the self-driver is like a 4-year-old kid mimicking the act of driving and isn’t capable of thinking like a human when it needs to. You forget that and you can die. (This has the odd and (IMO) under-appreciated effect, when self-drive is engaged, of shifting your role from operator of the car to babysitting the operator of the car. Doing a thing and watching something else do a thing so you can take over when they screw up are two very different things and I think that until more people realize that, it’s going to keep causing unnecessary accidents.)
More about...
