[HN Gopher] Why can 2 times 3 sometimes equal 7 with Android's N... ___________________________________________________________________ Why can 2 times 3 sometimes equal 7 with Android's Neural Network API? Author : aga_ml Score : 32 points Date : 2021-01-23 19:58 UTC (3 hours ago) (HTM) web link (alexanderganderson.github.io) (TXT) w3m dump (alexanderganderson.github.io) | kristjansson wrote: | It's an interesting observation, and a shocking title, but the | applicable lesson seems to be "don't use an aggressively | quantized network if your application is sensitive to | quantization errors" | throwaway2245 wrote: | So, computers are getting closer to human-like mistakes. | Hallucinaut wrote: | Reminds me of this classic | | https://joelgrus.com/2016/05/23/fizz-buzz-in-tensorflow/ | fuzzfactor wrote: | Never forget there's a reason why they call it Artificial | intelligence. | | Sometimes nothing but the real thing can put you on the correct | path. | Blikkentrekker wrote: | That has nothing to do with it's "artificiality". | | Some intelligence is simply less intelligent than others. | oso2k wrote: | Because of "The Secret Number" (https://youtu.be/qXnFr1d7B9w)? | bluejay2387 wrote: | Don't use an function approximator if you need the exact output | of a function? | Avalaxy wrote: | Using a neural network for things that have clear cut rules is | wrong. When you know the exact rules, implement them as such, | instead of bruteforcing a guesstimation. This is also why I'm | sceptical of the usr of GPT-3 for all sorts of purposes where | accuracy is important. Think of the code generation case. Bugs | may be very subtle and may go unnoticed. | Grimm1 wrote: | Code generation only needs to generate code with n bugs where n | is less than the number of bugs a human developer generates for | it to have usefulness, and maybe some other factor of severity | where they are generally less severe than human developers. I | think it'll make neat autopilot functionality for developers | but not replace the need to have someone look over and | understand the code. | yuliyp wrote: | This is a very simplistic of what code is and the role it | plays in a system. | | There are many implementations that can fulfill a set of | requirements. Not all of them are created equal. The ways in | which they behave as the system changes can be wildly | different. Well-written code will be able to handle those | changes gracefully. Poorly-written code may end up proving | brittle and bug-prone. Generated code will be completely | unpredictable. | | Imagine you're trying to build a street network for a city. | Some designs are much more predictable than others. If you've | played Factorio, the distinction between a spaghetti base and | one that has some design is abundant. Even if they currently | fulfill the same requirements now, the ability to improve | upon and reason about how it will behave after changes is | vastly different. | danfang wrote: | This is naive. The point is that code is a well defined | system with clear rules that can be expressed through logic | and mathematics. GPT is suited to approximate systems where | the rules are not well defined. Until AI can actually learn | the principles of logic, it may not be useful for code | generation on a meaningful scale, other than things just like | simple auto-completions. | | Not only that, AI would also have to learn the principles of | system design, performance, security, readability, | maintainability. That's what makes "good" software. It's a | far stretch to say that AI could achieve anything of the sort | based on current abilities. | kulig wrote: | Its not that simple. | | People are understanding when car crashes happen in busy | roads amongst other cars. | | They are _not_ understanding if a self-driving car swerves | into the sidewalk and kills a group of children. | ben_w wrote: | I disagree that that is enough to be useful. To give a | deliberately extreme example: if it produces code which has | half the number of bugs as a human, but it only outputs | Malbolge source code, nobody else will be able to fix those | bugs which remain. | perl4ever wrote: | This is a perfect satire of the logic people use to advocate | self driving cars being rushed into production. | | Only every time I read something similar, I think "surely no | programmer could think this". Are you a programmer? | Grimm1 wrote: | I sure am, and if I can code gen 90% of the boiler plate | away I'll do it happily. Besides attacking me, do you have | any point you'd like to make? | bobthebuilders wrote: | Do you want to die when your self driving car crashes? | Debug issues when your app des at 12am? Same concept. | Grimm1 wrote: | I don't want to die when I crash my own car, and I | already debug my own apps at 12am. If your argument is | that things need to be perfect than my god you must never | leave your home! I'd trust a machine to drive more | accurately than most people I see on the highway. | | Humans aren't special, in fact more often than not we're | sloppy, subject to fatigue, and a whole bunch of other | negative things. | | That considered, I had a pretty strict qualifier in my | above post which means the machine must perform better | than the average human in the respective task and | therefore I'd be more likely to die driving my own car | than a machine meeting my prerequisites. | Judgmentality wrote: | > I'd trust a machine to drive more accurately than most | people I see on the highway. Humans aren't special, in | fact more often than not we're sloppy, subject to | fatigue, and a whole bunch of other negative things. | | Humans are much, much, much more capable than the | absolute state-of-the-art robots when it comes to doing | things in an uncontrolled environment. | | https://www.youtube.com/watch?v=g0TaYhjpOfo | Hasnep wrote: | One of the advantages of an autonomous driver is that its | superhuman reflexes, never driving while tired, never | getting road rage, etc., will make it less likely to get | into an uncontrolled environment. | | Would you prefer your pilots to fly your plane with no AI | assistance? | Judgmentality wrote: | > One of the advantages of an autonomous driver is that | its superhuman reflexes, never driving while tired, never | getting road rage, etc. | | First of all, when you actually understand a self-driving | car stack, you'll realize those super-human reflexes are | more human than you think. The stack is complicated and | not only are there delays to be expected, some hardware | syncing requirements guarantee certain delays in the | perception pipeline. It's still better than a person, but | it's nothing close to approaching instantaneous. | Likewise, sensors can get dirty, and blah blah blah there | are other weaknesses robots have that humans don't. My | point is simple: robots aren't perfect. In fact, they are | almost always much worse than most people realize. | | > will make it less likely to get into an uncontrolled | environment | | You're misunderstanding me. I'm not saying less likely to | get into an accident. I'm saying the world, where cars | drive, is an uncontrolled environment - and the current | state of robotics is such that humans are better for | doing things in the real world. There is no "less likely | to get into an uncontrolled environment" because by | definition you are always putting it into that situation. | | > Would you prefer your pilots to fly your plane with no | AI assistance? | | AI assistance is fine. AI replacement is not. | dealforager wrote: | For code, I could see it being super useful for a beefed up | auto-complete. There are many times I find myself searching for | things like "how do I do X in Y language" to copy a snippet | that I'm sure has been written 10000x times before. I can | review the code and verify its correctness by writing tests. | [deleted] | [deleted] | jzer0cool wrote: | Why would use use a neural net to approximate 2 x 3 when there is | a clear definition of the result. Or as a fun side affect, neural | nets are prone to off by one errors too :) | unnouinceput wrote: | Famous Pentium F-DIV 20 years later, the sequel? | segfaultbuserr wrote: | It's a neural network. It gives approximate results. Here's a | newbie question that asks basically the same question, with | some interesting answers. | | > codesternews: Any deeplearning expert here. Why Neural | network can't compute a linear function Celsius to Fahrenheit | 100% accurately. Is it data or is it something can be | optimised. print(model.predict([100.0])) | // it results 211.874 which is not 100% accurate | (100x1.8+32=212) | | https://news.ycombinator.com/item?id=19708787 | techbio wrote: | Baker's (half-)dozen? | moonbug wrote: | if only there was some way of doing computatiin without | Tensorflow. | YarickR2 wrote: | Well, every tool has it's own range of use cases; doing integer | math is not a use case for a guesstimate engine . | justicezyx wrote: | Or one can claim that it's entirely obvious when relating that | with human beings making mistakes, where not only 2*3 can be 7, | millions can die of some obscure disctators whim, without much | conacusoly realized the insanity... | vmception wrote: | Did someone just train a GAN on HN comments? | justicezyx wrote: | "The real question is not whether machines think but | whether men do. The mystery which surrounds a thinking | machine already surrounds a thinking man." | | -- B F Skinner | MayeulC wrote: | It would be fairly interesting to try, and take votes as | feedback. That's what we all do here, anyway... | | ...Although you can reach a point where you have enough | karma not to care and troll a bit/speak more freely, which | if you only look at the vote outcome, can net you big in | both directions (though there is a lower bound). In the | end, it's exactly like an optimization problem, if you're | "farming" karma: a lot of safe bets, and a few more risky | ones to maybe discover a new class of safe ones. | | Reddit is full of safe gamblers who are farmink karma by | repeating canned patterns. ___________________________________________________________________ (page generated 2021-01-23 23:00 UTC)