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I think I can explain this that for most people the whole world is basically magic anyway. They don’t understand any of the details about how any digital tech w

I think I can explain this that for most people the whole world is basically magic anyway. They don’t understand any of the details about how any digital tech works so to them they have no framework for which things are impressive and which things are not. The just know that computers can do a great many things that they know nothing about. “Oh I can bank online? Ok.” “Oh, I can have the computer write my book report for me? Ok.” “Oh, this McDonalds is fully staffed by sentiment robots? Ok.”

mortenjorck 4y ago
This is the other side of the classic XKCD "Tasks" (https://xkcd.com/1425/ https://xkcd.com/1425/). A non-technical person in 2014 (when the above was originally published) would likely have the same conception of the difficulty of recognizing a bird from an image as they would in 2022, even though the task itself has gone from near-insurmountable to off-the-shelf-library in eight years. Even as Imagen and Dall-E 2 amaze us today, these feats will likely be commonplace in a few years. The non-technical may have only a vague sense that their new TikTok filter is doing something that was impossible only a few years prior.
- futureshock 4y ago
  Exactly and I was thinking of that XKCD. Very much case in point, I have the Merlin Bird ID app which can determine species from ridiculously blurry photos and can also identify hundreds of birds from their calls alone in noisy environments. In 2014 I would have sworn this would be impossible.
- DonHopkins 4y ago
  The tooltip you get when you hover your cursor over the comic: "In the 60s, Marvin Minsky assigned a couple of undergrads to spend the summer programming a computer to use a camera to identify objects in a scene. He figured they'd have the problem solved by the end of the summer. Half a century later, we're still working on it." I'm working with his son Henry Minsky and other great people at Leela AI on that same old problem, applying hybrid symbolic-connectionist constructivist AI by combining neat neural networks with scruffy symbolic logic to understand video, and it's mind boggling what is possible now: https://leela.ai/ https://leela.ai/ >Our AI system, Leela, is motivated by intrinsic curiosity. Leela creates theories about cause and effect in her world, and then conducts experiments to test these theories. Leela can connect all her knowledge and use this network to make plans, reason about goals, and communicate using grounded natural language. >Leela has at her core a hybrid symbolic-connectionist network. This means that she uses a dynamic combination of artificial neural networks and symbol networks to learn. Hybrid networks open the door to AI agents that can build their own abstractions on the fly, while still taking full advantage of the power of deep learning. https://en.wikipedia.org/wiki/Neats_and_scruffies https://en.wikipedia.org/wiki/Neats_and_scruffies >Neats and scruffies: Neat and scruffy are two contrasting approaches to artificial intelligence (AI) research. The distinction was made in the 70s and was a subject of discussion until the middle 80s. In the 1990s and 21st century AI research adopted "neat" approaches almost exclusively and these have proven to be the most successful. >"Neats" use algorithms based on formal paradigms such as logic, mathematical optimization or neural networks. Neat researchers and analysts have expressed the hope that a single formal paradigm can be extended and improved to achieve general intelligence and superintelligence. >"Scruffies" use any number of different algorithms and methods to achieve intelligent behavior. Scruffy programs may require large amounts of hand coding or knowledge engineering. Scruffies have argued that the general intelligence can only be implemented by solving a large number of essentially unrelated problems, and that there is no magic bullet that will allow programs to develop general intelligence autonomously. >The neat approach is similar to physics, in that it uses simple mathematical models as its foundation. The scruffy approach is more like biology, where much of the work involves studying and categorizing diverse phenomena. We're looking for talented engineers and designers to help, including neats and scruffies working together! https://leela.ai/jobs/ https://leela.ai/jobs/
GrabbinD33ze69 4y ago
A pretty common generalization I've witnessed is many non technical people (even people who are tech savvy but have no CS background do this) is people assuming the feature that is in reality quite difficult to implement won't take much effort, and vice versa.
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endymi0n 4y ago
I think that hits home. A lot of people would just answer something to the likes of "Well, they made The Matrix with a computer 20 years ago", and technically that's just as true. From their remote viewpoint on what's happening in IT, the rest is an implementation detail to them.
firecall 4y ago
"Oh, they have the internet on computers now!" Homer J Simpson.
DonHopkins 4y ago
That is exactly what Will Wright (the creator of SimCity and The Sims, and Robot Wars / Battle Bots contestant) was getting at when we made these one-minute robot reality videos about "Empathy" and "Servitude". His idea was to probe just how much random people on the street (or in a diner) would believe about autonomous intelligent robots operating in the real world. Of course we were actually hiding behind the scenes tele-operating the robots through hidden cameras and a wireless web interface, listening to what the people said and making the robots respond with a voice synthesizer and sound effects, clicking on pre-written phrases and typing ad-libbed responses. Empathy (a broken down robot begs for help from passers by on the streets of Oakland): https://www.youtube.com/watch?v=KXrbqXPnHvE https://www.youtube.com/watch?v=KXrbqXPnHvE Servitude (a robot waiter takes orders and serves food in a diner in Oakland, making stupid mistakes and asking for a good review): https://www.youtube.com/watch?v=NXsUetUzXlg https://www.youtube.com/watch?v=NXsUetUzXlg All his robots aren't as harmless, non-violent, polite, and obsequious as those two. Here's an old interview with Will at Robot Wars 1997: https://www.youtube.com/watch?v=5nmbs0WqDQM https://www.youtube.com/watch?v=5nmbs0WqDQM Here is Super ChiaBot and her MiniBots, created by Will and his daughter Cassidy, getting its leaves shredded and body slammed at BattleBots: https://www.youtube.com/watch?v=DrArvRG2yQA https://www.youtube.com/watch?v=DrArvRG2yQA Here's a more recent video of Will throwing a tantrum about the failure of SimSandwich, destroying his old creations because they're pixely and poorly rendered, then complaining about how those jerks at EA hate him: https://www.youtube.com/watch?v=i-7F7s46-9A https://www.youtube.com/watch?v=i-7F7s46-9A

mortenjorck 4y ago

This is the other side of the classic XKCD "Tasks" (https://xkcd.com/1425/ https://xkcd.com/1425/). A non-technical person in 2014 (when the above was originally published) would likely have the same conception of the difficulty of recognizing a bird from an image as they would in 2022, even though the task itself has gone from near-insurmountable to off-the-shelf-library in eight years. Even as Imagen and Dall-E 2 amaze us today, these feats will likely be commonplace in a few years. The non-technical may have only a vague sense that their new TikTok filter is doing something that was impossible only a few years prior.

futureshock 4y ago
Exactly and I was thinking of that XKCD. Very much case in point, I have the Merlin Bird ID app which can determine species from ridiculously blurry photos and can also identify hundreds of birds from their calls alone in noisy environments. In 2014 I would have sworn this would be impossible.
DonHopkins 4y ago
The tooltip you get when you hover your cursor over the comic: "In the 60s, Marvin Minsky assigned a couple of undergrads to spend the summer programming a computer to use a camera to identify objects in a scene. He figured they'd have the problem solved by the end of the summer. Half a century later, we're still working on it." I'm working with his son Henry Minsky and other great people at Leela AI on that same old problem, applying hybrid symbolic-connectionist constructivist AI by combining neat neural networks with scruffy symbolic logic to understand video, and it's mind boggling what is possible now: https://leela.ai/ https://leela.ai/ >Our AI system, Leela, is motivated by intrinsic curiosity. Leela creates theories about cause and effect in her world, and then conducts experiments to test these theories. Leela can connect all her knowledge and use this network to make plans, reason about goals, and communicate using grounded natural language. >Leela has at her core a hybrid symbolic-connectionist network. This means that she uses a dynamic combination of artificial neural networks and symbol networks to learn. Hybrid networks open the door to AI agents that can build their own abstractions on the fly, while still taking full advantage of the power of deep learning. https://en.wikipedia.org/wiki/Neats_and_scruffies https://en.wikipedia.org/wiki/Neats_and_scruffies >Neats and scruffies: Neat and scruffy are two contrasting approaches to artificial intelligence (AI) research. The distinction was made in the 70s and was a subject of discussion until the middle 80s. In the 1990s and 21st century AI research adopted "neat" approaches almost exclusively and these have proven to be the most successful. >"Neats" use algorithms based on formal paradigms such as logic, mathematical optimization or neural networks. Neat researchers and analysts have expressed the hope that a single formal paradigm can be extended and improved to achieve general intelligence and superintelligence. >"Scruffies" use any number of different algorithms and methods to achieve intelligent behavior. Scruffy programs may require large amounts of hand coding or knowledge engineering. Scruffies have argued that the general intelligence can only be implemented by solving a large number of essentially unrelated problems, and that there is no magic bullet that will allow programs to develop general intelligence autonomously. >The neat approach is similar to physics, in that it uses simple mathematical models as its foundation. The scruffy approach is more like biology, where much of the work involves studying and categorizing diverse phenomena. We're looking for talented engineers and designers to help, including neats and scruffies working together! https://leela.ai/jobs/ https://leela.ai/jobs/

GrabbinD33ze69 4y ago

A pretty common generalization I've witnessed is many non technical people (even people who are tech savvy but have no CS background do this) is people assuming the feature that is in reality quite difficult to implement won't take much effort, and vice versa.

deleted 4y ago
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endymi0n 4y ago

I think that hits home. A lot of people would just answer something to the likes of "Well, they made The Matrix with a computer 20 years ago", and technically that's just as true. From their remote viewpoint on what's happening in IT, the rest is an implementation detail to them.

firecall 4y ago

"Oh, they have the internet on computers now!" Homer J Simpson.

DonHopkins 4y ago

That is exactly what Will Wright (the creator of SimCity and The Sims, and Robot Wars / Battle Bots contestant) was getting at when we made these one-minute robot reality videos about "Empathy" and "Servitude". His idea was to probe just how much random people on the street (or in a diner) would believe about autonomous intelligent robots operating in the real world. Of course we were actually hiding behind the scenes tele-operating the robots through hidden cameras and a wireless web interface, listening to what the people said and making the robots respond with a voice synthesizer and sound effects, clicking on pre-written phrases and typing ad-libbed responses. Empathy (a broken down robot begs for help from passers by on the streets of Oakland): https://www.youtube.com/watch?v=KXrbqXPnHvE https://www.youtube.com/watch?v=KXrbqXPnHvE Servitude (a robot waiter takes orders and serves food in a diner in Oakland, making stupid mistakes and asking for a good review): https://www.youtube.com/watch?v=NXsUetUzXlg https://www.youtube.com/watch?v=NXsUetUzXlg All his robots aren't as harmless, non-violent, polite, and obsequious as those two. Here's an old interview with Will at Robot Wars 1997: https://www.youtube.com/watch?v=5nmbs0WqDQM https://www.youtube.com/watch?v=5nmbs0WqDQM Here is Super ChiaBot and her MiniBots, created by Will and his daughter Cassidy, getting its leaves shredded and body slammed at BattleBots: https://www.youtube.com/watch?v=DrArvRG2yQA https://www.youtube.com/watch?v=DrArvRG2yQA Here's a more recent video of Will throwing a tantrum about the failure of SimSandwich, destroying his old creations because they're pixely and poorly rendered, then complaining about how those jerks at EA hate him: https://www.youtube.com/watch?v=i-7F7s46-9A https://www.youtube.com/watch?v=i-7F7s46-9A