http://www.freep.com/article/20110216/NEWS01/110216015/Sci-fi-fans-rejoice-RoboCop-statue-coming-Detroit
Oh, Internet people, how you make life interesting. If you head over to http://www.detroitneedsrobocop.com/, you too can be part of the crazy - the Kickstarter to fund an actual RoboCop statue to be installed somewhere in Detroit has blown past a couple of funding goals already. At this point it's at just over $62,000 - the organizers have said they'll let it run for the whole funding period, and just make the statue as awesome as they can with whatever ridiculous total they end up with.
Apparently it started with a random tweet to the mayor of Detroit, Dave Bing (how'd Microsoft swing that deal, I wonder?) suggesting they build a RoboCop statue. Perhaps unwisely, he actually responded to the tweet, saying "There are not any plans to erect a statue to Robocop. Thank you for the suggestion." Enter the fine folks at Imagination Station, a non-profit group dedicated to reclaiming and refurbishing some of Detroit's less-pleasant buildings and turning them into an art commune/gallery/park/something. They decided this was something people could get behind, and threw up a Kickstarter for it.
As it turned out, they were right - in the first four days, they had $17,000 of pledges. They got a boost shortly afterward from Pete Hottelet, the CEO of Omni Consumer Products...yes, really. Apparently this is a real company, that makes little real products based on various fictional properties. Mr. Hottelet pledged $25,000, which I suppose he really had to, given his company's name.
So, none of this has much to do with real cyborgs or transhumanism, but I figured it's worth noting. Not least of which because, while RoboCop was great, I had a serious crush on Peter Weller in Buckaroo Banzai. Even as a young prototype, I was not your standard model, I guess. ;) Although now that I think about it, maybe his later portrayal of RoboCop did have something to do with my eventual robotic inclinations.
Chronicling our increasing acceleration towards escape velocity from biology.
2011/02/22
Study Suggests Brain Is More Modular - "Reading" Is Input-Agnostic
http://www.eurekalert.org/pub_releases/2011-02/thuo-022211.php
Researchers found that the same brain areas are active in people reading visually as in never-sighted people reading Braille, to the point where the fMRI's were essentially indistinguishable between the two groups.
This seems like a plus for neurology-based understanding of intelligence, as it suggests that some brain functions may be relatively generic - doing specific kinds of processing tasks regardless of the source of the data being processed.
Researchers found that the same brain areas are active in people reading visually as in never-sighted people reading Braille, to the point where the fMRI's were essentially indistinguishable between the two groups.
This seems like a plus for neurology-based understanding of intelligence, as it suggests that some brain functions may be relatively generic - doing specific kinds of processing tasks regardless of the source of the data being processed.
2011/02/21
DARPA Contractor Builds Robo-Hummingbird, Onboard Power, Video
http://www.kurzweilai.net/first-fully-operational-life-size-hummingbird-like-unmanned-aircraft?utm_source=KurzweilAI+Daily+Newsletter&utm_campaign=97fb8158e5-UA-946742-1&utm_medium=email
This is both neat, and impressive technically, though I'm wondering what the advantage is over, say, a quad-rotor?
Presumably the idea is to use it for spying, but I'm not sure that makes sense. Every place I've ever lived, hummingbirds are rare enough that I'd pay particular attention to any I saw, because they're cool, and as good as it looks, I'm not sure it can withstand any significant scrutiny. Are there areas of the world where hummingbirds are like flies and people actually ignore them?
This is both neat, and impressive technically, though I'm wondering what the advantage is over, say, a quad-rotor?
Presumably the idea is to use it for spying, but I'm not sure that makes sense. Every place I've ever lived, hummingbirds are rare enough that I'd pay particular attention to any I saw, because they're cool, and as good as it looks, I'm not sure it can withstand any significant scrutiny. Are there areas of the world where hummingbirds are like flies and people actually ignore them?
More Discriminating BCI for Robot or Computer Control
http://www.eurekalert.org/pub_releases/2011-02/epfd-tbi012111.php
Apparently - and this was news to me - most current production BCIs are mentally tiring for the user, because "do nothing" is actually something you have to keep thinking about, actively. It's sort of like the Douglas Adams bit about a gesture-controlled radio interface that was eventually so sensitive you had to "sit infuriatingly still if you wanted to keep listening to the same program". But since we're talking about the only means of mobility for some users, rather more serious.
This one is more flexible in that it uses some statistical analysis to better catch commands (or "no command") even while other things are going on, like reading or speaking aloud. Seems like a definite benefit!
Apparently - and this was news to me - most current production BCIs are mentally tiring for the user, because "do nothing" is actually something you have to keep thinking about, actively. It's sort of like the Douglas Adams bit about a gesture-controlled radio interface that was eventually so sensitive you had to "sit infuriatingly still if you wanted to keep listening to the same program". But since we're talking about the only means of mobility for some users, rather more serious.
This one is more flexible in that it uses some statistical analysis to better catch commands (or "no command") even while other things are going on, like reading or speaking aloud. Seems like a definite benefit!
2011/02/17
Watson Kicks Around the Humans Again, Skips Victory Lap
The third and final night of the IBM Watson Jeopardy Challenge (http://www-943.ibm.com/innovation/us/watson/) was last night, and IBM's green-haired wonder (I started thinking of the five emo-lines on its avatar as hair) pulled it out again. The individual score for the second game was much closer by Final Jeopardy than the first game - Watson had $23,440, and Ken had managed to rack up $18,200 (Brad had $5,600 and seemed rather cavalier about the whole thing - after all, given the prizes and the charity split, he was guaranteed $100,000 just for showing up).
Some analysis of the second game is making much of Watson's "changed" wagering behavior (it bet $17,973, where it had low-balled Final Jeopardy in the first game), but it's not very surprising. Watson was always basing its wagers on the two-game total score victory conditions. By Final Jeopardy (in fact, rather earlier than that, as I'm sure Watson was aware more than I was) in the second game, Watson had already mathematically eliminated the other two contestants...its large wager was based on the most it could risk while still guaranteeing overall victory. Ken low-balled for similar reasons. He knew there was zero chance of Watson over-bidding, and thus zero chance of him taking first place over-all. He might have tried for a symbolic victory in the second game, but I suspect he was being more practical and guaranteeing that he took second, for a much larger prize.
Performance-wise, Watson seemed to be having a few more category misunderstandings than during the first game. It had a few flubs, and many questions where I suspect if Ken had not beaten it to the buzzer, Watson's answer would have been rejected for poor phrasing. Both humans seemed to be doing significantly better in the buzzer contest this game, compared to the first - I bet my speculation about them practicing in their hotel rooms before bed has some truth to it. Though based on Watson's would-have-been-wrong answers, Ken might have actually had a chance to get closer to Watson's total if he'd been less fast on the buzzer, letting Watson blow it and lose score, then buzzing in for clean up. But given Watson's high percentage of correct answers, it seems clear Ken had to do whatever he could to maximize his chances of being allowed to answer (and score) at all.
Overall, I don't have much more to add to my analysis from the first game. Watson's technology is impressive (and as Ray K. mentions, is only going to improve) in practical terms, but it's not impressive in conceptual terms - the intelligence displayed isn't general and isn't reliable (say, for unsupervised question-answering that might have consequences)...and it's not clear if it's adaptable or learning. Still, it's much better at answering Jeopardy clues than I am, and demonstrably better at playing Jeopardy than two noted Champions of the game.
I was a bit worried that, past my excitement, my dismissive analysis of the technology is an example of the "moving target" that AI is, seemingly based on an innate human desire for exceptionalism - intelligence tends to be re-defined to exclude whatever the most recent AI has managed to accomplish. I don't think that's the case here - the output of Watson is both impressive and laughable (because when Watson is wrong, he's really wrong), but the means to produce it don't seem generally applicable. As Noam Chomsky put it when asked (by Gavin Schmitt), "I'm not impressed by a bigger steamroller."
The question is, how much is IBM's technology here going to advance the field? The hardware required to run Watson alone is apparently north of one million dollars. But I wonder how much of that is involved in the knowledge library and the relevant searches...could they pare down the natural language parts of the system into something more manageable and affordable? Either way, the costs are going to come down with time and volume, which IBM itself mentioned. Ideally, the language innovations they've come up with can be incorporated into more general, learning-based approaches which will produce more robust results.
The avatar is cute, though. I wonder if there will be Watson costumes this Halloween?
Some analysis of the second game is making much of Watson's "changed" wagering behavior (it bet $17,973, where it had low-balled Final Jeopardy in the first game), but it's not very surprising. Watson was always basing its wagers on the two-game total score victory conditions. By Final Jeopardy (in fact, rather earlier than that, as I'm sure Watson was aware more than I was) in the second game, Watson had already mathematically eliminated the other two contestants...its large wager was based on the most it could risk while still guaranteeing overall victory. Ken low-balled for similar reasons. He knew there was zero chance of Watson over-bidding, and thus zero chance of him taking first place over-all. He might have tried for a symbolic victory in the second game, but I suspect he was being more practical and guaranteeing that he took second, for a much larger prize.
Performance-wise, Watson seemed to be having a few more category misunderstandings than during the first game. It had a few flubs, and many questions where I suspect if Ken had not beaten it to the buzzer, Watson's answer would have been rejected for poor phrasing. Both humans seemed to be doing significantly better in the buzzer contest this game, compared to the first - I bet my speculation about them practicing in their hotel rooms before bed has some truth to it. Though based on Watson's would-have-been-wrong answers, Ken might have actually had a chance to get closer to Watson's total if he'd been less fast on the buzzer, letting Watson blow it and lose score, then buzzing in for clean up. But given Watson's high percentage of correct answers, it seems clear Ken had to do whatever he could to maximize his chances of being allowed to answer (and score) at all.
Overall, I don't have much more to add to my analysis from the first game. Watson's technology is impressive (and as Ray K. mentions, is only going to improve) in practical terms, but it's not impressive in conceptual terms - the intelligence displayed isn't general and isn't reliable (say, for unsupervised question-answering that might have consequences)...and it's not clear if it's adaptable or learning. Still, it's much better at answering Jeopardy clues than I am, and demonstrably better at playing Jeopardy than two noted Champions of the game.
I was a bit worried that, past my excitement, my dismissive analysis of the technology is an example of the "moving target" that AI is, seemingly based on an innate human desire for exceptionalism - intelligence tends to be re-defined to exclude whatever the most recent AI has managed to accomplish. I don't think that's the case here - the output of Watson is both impressive and laughable (because when Watson is wrong, he's really wrong), but the means to produce it don't seem generally applicable. As Noam Chomsky put it when asked (by Gavin Schmitt), "I'm not impressed by a bigger steamroller."
The question is, how much is IBM's technology here going to advance the field? The hardware required to run Watson alone is apparently north of one million dollars. But I wonder how much of that is involved in the knowledge library and the relevant searches...could they pare down the natural language parts of the system into something more manageable and affordable? Either way, the costs are going to come down with time and volume, which IBM itself mentioned. Ideally, the language innovations they've come up with can be incorporated into more general, learning-based approaches which will produce more robust results.
The avatar is cute, though. I wonder if there will be Watson costumes this Halloween?
2011/02/16
The Very Model of a Singularitarian
Via KurzweilAI - the singing is...hmm...earnest, but it's still catchy.
The Very Model of a Singularitarian [video]
The Very Model of a Singularitarian [video]
Watson Crushes Jeopardy Champions in Game 1 of 2!
I just watched the first two nights of the IBM Watson Jeopardy Challenge (http://www-943.ibm.com/innovation/us/watson/) on my Tivo...woohoo! First, let me talk about the non-game portions of the show.
Interspersed with the actual gameplay are polished PR segments from IBM, giving some very limited background on Watson, but mostly talking about how awesome and game-changing it is and how they expect to sell the systems to everyone in every industry. There's not much meat to the info...I think even a completely uninformed viewer isn't going to come away with a good understanding of what's going on.
I also found it interesting that they are playing in a Jeopardy studio actually built on IBM premises. I suppose that they didn't want to have to rely on a third-party network connection from Watson's room on the East coast to a West-coast studio. It'd be pretty embarrassing to be brought low by simple light-speed lag. But it made me wonder - I'm fairly trusting of IBM's integrity on this, but what does the average person think of the contest being held on IBM property?
Anyway, on to the good stuff! The first round was a little slow, although Watson picked a clue and found the first Daily Double almost immediately. I'm very curious what its strategy is for which clue to pick at what time. Over the entire first game, I couldn't identify a rationale (but then, I can't do that for human players either, unless they use a top-down, left-right pattern, which many do). I'd also like to know what its wagering formula is. It's clear that it has one...although it wagered $1000 (the max, since it only had $200) on the first one, when it found another, it picked a "weird" number, $6435.
Edit: I found some background on the clue-picking strategy. Apparently they did some statistical analysis of where daily doubles are found, and Watson plays the numbers, making its highest priority to get all the daily doubles. After that it goes for the cheap clues in categories, so it can refine/confirm its interpretation of any word-play in the category title with minimal score risk.
The audience seemed surprised when it guessed on a DD question (and verbally admitted that it was a guess), but this makes perfect sense - when you make a DD wager, you lose that money if you don't answer at all, so there's no downside to guessing, unlike a normal question, where the confidence threshold is important to avoid losing money on wrong answers.
The first nights' show was just the first half of the first game, and ended with Watson in a tie with Brad at $5000, with Ken trailing at $2000. I was pleased it was holding its own, at least. But in Double Jeopardy, it was off to the races, acing clue after clue. It did get a couple wrong, but it was building up such a huge lead, this hardly mattered at all.
Watson clearly had an advantage in the buzzer-timing department. Even though they made a point of showing in a video clip that Watson was buzzing in by activating a mechanical actuator that pressed an actual buzzer button, it was apparent that Watson had a very good feel for the timing, and of course having verified that feel could do it exactly the same way every time (unless it was actually still thinking about a question, which appeared to happen a couple times). Whereas the human champions had to "re-learn" the buzzer timing...in both Single and Double Jeopardy, they seemed frustrated early on missing buzz-ins, but did much better towards the ends of the halves.
One clear disadvantage for Watson was the lack of any speech recognition or other input based on the other players' answers, because a couple times a human buzzed in first, answered incorrectly, then Watson would buzz in and repeat the same wrong answer. This felt a little embarrassing for everyone, and no one commented on it. Though it also highlighted a competitive edge for Watson - if a human contestant gets an answer wrong, let alone a bonehead maneuver like repeating a wrong answer, they can get discouraged and take a few clues to bounce back. But Watson just keeps plugging along (although its possible it adaptively adjusted its "confidence threshold" when it got something wrong, which could be interpreted as hesitancy or uncertainty I suppose).
It was also clear that as successful as its strategy was, you could not really say that Watson "understood" the language. Based on the times when it went off the rails - particularly Final Jeopardy, where it not only answered wrong, but categorically wrong, as the category was a very straightforward "U.S. Cities", and it answered "Toronto????". Endearing that it displayed its confusion with all the question marks, but not very impressive in terms of semantic skill.
But even with some shortcomings, Watson ended the first game with $35,734, a lead of over $25,000 over Brad (and $30k over Ken), which can't have been very fun for the humans, but had me jumping off the sofa and cheering!
The Challenge is a two-game combined total event, however, so technically the humans aren't out of it yet. I have a feeling they went back to their hotel rooms that night and practiced buzzing in for a couple hours before going to sleep.
Some final musings - the buzzer issue is interesting. Is this really a good test of AI vs human, given the artificial and arbitrary boundaries of the contest? Say there was no buzzer, just a 6-second time limit, and every contestant had the option to answer or not answer as they wished. How would Watson be doing against Ken and Brad in that context? My gut impression is that Watson would still be doing well, but clearly with not as huge a lead. I have a feeling that this is going to give people a very easy excuse should Watson go on to overall victory - "Yeah, sure, it's a computer, obviously it's going to buzz in quicker most of the time...but did you hear some of its answers? Artificial Stupid is more like it..."
It's ok, Watson. You can't hear those people anyway, so just keep doing your best, I'm proud of you!
Interspersed with the actual gameplay are polished PR segments from IBM, giving some very limited background on Watson, but mostly talking about how awesome and game-changing it is and how they expect to sell the systems to everyone in every industry. There's not much meat to the info...I think even a completely uninformed viewer isn't going to come away with a good understanding of what's going on.
I also found it interesting that they are playing in a Jeopardy studio actually built on IBM premises. I suppose that they didn't want to have to rely on a third-party network connection from Watson's room on the East coast to a West-coast studio. It'd be pretty embarrassing to be brought low by simple light-speed lag. But it made me wonder - I'm fairly trusting of IBM's integrity on this, but what does the average person think of the contest being held on IBM property?
Anyway, on to the good stuff! The first round was a little slow, although Watson picked a clue and found the first Daily Double almost immediately. I'm very curious what its strategy is for which clue to pick at what time. Over the entire first game, I couldn't identify a rationale (but then, I can't do that for human players either, unless they use a top-down, left-right pattern, which many do). I'd also like to know what its wagering formula is. It's clear that it has one...although it wagered $1000 (the max, since it only had $200) on the first one, when it found another, it picked a "weird" number, $6435.
Edit: I found some background on the clue-picking strategy. Apparently they did some statistical analysis of where daily doubles are found, and Watson plays the numbers, making its highest priority to get all the daily doubles. After that it goes for the cheap clues in categories, so it can refine/confirm its interpretation of any word-play in the category title with minimal score risk.
The audience seemed surprised when it guessed on a DD question (and verbally admitted that it was a guess), but this makes perfect sense - when you make a DD wager, you lose that money if you don't answer at all, so there's no downside to guessing, unlike a normal question, where the confidence threshold is important to avoid losing money on wrong answers.
The first nights' show was just the first half of the first game, and ended with Watson in a tie with Brad at $5000, with Ken trailing at $2000. I was pleased it was holding its own, at least. But in Double Jeopardy, it was off to the races, acing clue after clue. It did get a couple wrong, but it was building up such a huge lead, this hardly mattered at all.
Watson clearly had an advantage in the buzzer-timing department. Even though they made a point of showing in a video clip that Watson was buzzing in by activating a mechanical actuator that pressed an actual buzzer button, it was apparent that Watson had a very good feel for the timing, and of course having verified that feel could do it exactly the same way every time (unless it was actually still thinking about a question, which appeared to happen a couple times). Whereas the human champions had to "re-learn" the buzzer timing...in both Single and Double Jeopardy, they seemed frustrated early on missing buzz-ins, but did much better towards the ends of the halves.
One clear disadvantage for Watson was the lack of any speech recognition or other input based on the other players' answers, because a couple times a human buzzed in first, answered incorrectly, then Watson would buzz in and repeat the same wrong answer. This felt a little embarrassing for everyone, and no one commented on it. Though it also highlighted a competitive edge for Watson - if a human contestant gets an answer wrong, let alone a bonehead maneuver like repeating a wrong answer, they can get discouraged and take a few clues to bounce back. But Watson just keeps plugging along (although its possible it adaptively adjusted its "confidence threshold" when it got something wrong, which could be interpreted as hesitancy or uncertainty I suppose).
It was also clear that as successful as its strategy was, you could not really say that Watson "understood" the language. Based on the times when it went off the rails - particularly Final Jeopardy, where it not only answered wrong, but categorically wrong, as the category was a very straightforward "U.S. Cities", and it answered "Toronto????". Endearing that it displayed its confusion with all the question marks, but not very impressive in terms of semantic skill.
But even with some shortcomings, Watson ended the first game with $35,734, a lead of over $25,000 over Brad (and $30k over Ken), which can't have been very fun for the humans, but had me jumping off the sofa and cheering!
The Challenge is a two-game combined total event, however, so technically the humans aren't out of it yet. I have a feeling they went back to their hotel rooms that night and practiced buzzing in for a couple hours before going to sleep.
Some final musings - the buzzer issue is interesting. Is this really a good test of AI vs human, given the artificial and arbitrary boundaries of the contest? Say there was no buzzer, just a 6-second time limit, and every contestant had the option to answer or not answer as they wished. How would Watson be doing against Ken and Brad in that context? My gut impression is that Watson would still be doing well, but clearly with not as huge a lead. I have a feeling that this is going to give people a very easy excuse should Watson go on to overall victory - "Yeah, sure, it's a computer, obviously it's going to buzz in quicker most of the time...but did you hear some of its answers? Artificial Stupid is more like it..."
It's ok, Watson. You can't hear those people anyway, so just keep doing your best, I'm proud of you!
2011/02/15
Turbulence in the Flight Path - Job Elimination?
The New York Times posted an essay yesterday (prompted by the Watson Jeopardy Challenge) that explores the question of whether increasingly powerful AI will cause major disruptions in the job market, or if human adaptability combined with "IA" (intelligence augmentation) will let us keep finding useful things to do - for a while, anyway.
One example they give is how rapidly ATM's replaced bank tellers, even for a task that generally involves physical interaction - giving or receiving various pieces of paper. I'm not sure that's a telling point - true, there are an increasing number of online-only banks who don't employ a single teller - but even at physical banks with ATM's right outside, they have plenty of tellers. I know I can deposit a check at an ATM, but when I (rarely) get a paper check these days (thanks, mom!), I still go to a teller to deposit it. My gut rationale for that is I expect it to process faster, since I presume they empty the ATM at the end of the day and then do all the stuff inside. Though I seem to recall something about ATM's that actually scan/OCR/process checks in real-time now (and a similar smartphone app). Still, plenty of tellers around from what I'm seeing.
But the larger "threat" is in areas where there is no practical physical interaction by default - customer service, mostly. According to Wolfram Alpha (go IA), as of 2008, there were 2.233 million people employed in this position. How much of these jobs can be automated now? I think the problem for the moment is validation...anyone can take a stab at some heuristics for what to do in what situation, but I don't see a CEO turning their operations over to WatsonCS without some data that suggests there won't be widespread customer revolt as a result, and collecting that data seems likely to be arduous and expensive. But Customer Service is, in a basic sense, about trying to achieve some defined minimum average level of satisfaction for customers who contact the company, with the least expense possible. Based on the iffy quality of service I get from humans these days, it seems like it'd be hard for AI to do much worse.
It's going to be interesting in the next few days/weeks seeing conclusions drawn based on Watson's performance. I wonder how many of them will take into account the fact that Watson might be capable of much, much more than it shows, given the rules of the challenge don't allow an active Internet connection.
It's sort of like debates about enhancements in sports. Some of those rules are about protecting the athletes, since some enhancements can be dangerous, but some are arbitrary, aimed at protecting the "purity" or "sanctity" of the sport/game/contest. When are contests where increasingly available technology has to be excluded to keep things "fair" going to stop being as relevant in our society? I've never been much of a sports fan, but I'd probably be more interested if safe enhancements were making things more exciting. I think it's telling that a lot of people these days watch the commercials more than the actual Big Game.
One example they give is how rapidly ATM's replaced bank tellers, even for a task that generally involves physical interaction - giving or receiving various pieces of paper. I'm not sure that's a telling point - true, there are an increasing number of online-only banks who don't employ a single teller - but even at physical banks with ATM's right outside, they have plenty of tellers. I know I can deposit a check at an ATM, but when I (rarely) get a paper check these days (thanks, mom!), I still go to a teller to deposit it. My gut rationale for that is I expect it to process faster, since I presume they empty the ATM at the end of the day and then do all the stuff inside. Though I seem to recall something about ATM's that actually scan/OCR/process checks in real-time now (and a similar smartphone app). Still, plenty of tellers around from what I'm seeing.
But the larger "threat" is in areas where there is no practical physical interaction by default - customer service, mostly. According to Wolfram Alpha (go IA), as of 2008, there were 2.233 million people employed in this position. How much of these jobs can be automated now? I think the problem for the moment is validation...anyone can take a stab at some heuristics for what to do in what situation, but I don't see a CEO turning their operations over to WatsonCS without some data that suggests there won't be widespread customer revolt as a result, and collecting that data seems likely to be arduous and expensive. But Customer Service is, in a basic sense, about trying to achieve some defined minimum average level of satisfaction for customers who contact the company, with the least expense possible. Based on the iffy quality of service I get from humans these days, it seems like it'd be hard for AI to do much worse.
It's going to be interesting in the next few days/weeks seeing conclusions drawn based on Watson's performance. I wonder how many of them will take into account the fact that Watson might be capable of much, much more than it shows, given the rules of the challenge don't allow an active Internet connection.
It's sort of like debates about enhancements in sports. Some of those rules are about protecting the athletes, since some enhancements can be dangerous, but some are arbitrary, aimed at protecting the "purity" or "sanctity" of the sport/game/contest. When are contests where increasingly available technology has to be excluded to keep things "fair" going to stop being as relevant in our society? I've never been much of a sports fan, but I'd probably be more interested if safe enhancements were making things more exciting. I think it's telling that a lot of people these days watch the commercials more than the actual Big Game.
The End of the Beginning
I'm super-excited about the Watson Jeopardy Challenge, enough so that I decided it was probably time to start keeping track of things like this - developments in SIM tech, robotics, AI. It's bound to become a full-time job within the next ten years or so, but I'll do my best.
I think that this is a real sign that Earth's technological childhood is ending, and we're about to charge headlong into adolescence - hopefully without any major cataclysms. I'm not sure what the metaphorical equivalent of "wrecking dad's car" or "getting pregnant" would be in this context, but let's try to avoid them on general principle, k? There are bound to be bumps in the road here and there, but with determination and brilliance and a little luck, we'll blossom into adulthood and really start making our mark on the universe.
Keep your eyes open, people. Blink, and you might miss something!
I think that this is a real sign that Earth's technological childhood is ending, and we're about to charge headlong into adolescence - hopefully without any major cataclysms. I'm not sure what the metaphorical equivalent of "wrecking dad's car" or "getting pregnant" would be in this context, but let's try to avoid them on general principle, k? There are bound to be bumps in the road here and there, but with determination and brilliance and a little luck, we'll blossom into adulthood and really start making our mark on the universe.
Keep your eyes open, people. Blink, and you might miss something!
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