<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>tokenadult</author><text>Thanks for the interesting detailed information about EEG resolution, which I can attest is in accordance with what I have read about neuroelectrical interaction in other contexts.&lt;p&gt;But what is to me implausible about thinking &quot;phone Mom&quot; and having my computer do it for me is that this scenario envisions an unusually high degree of usability that no consumer-facing software writers have ever achieved. Right now, on a BRAND NEW computer system using mostly application programs recommended by Hacker News readers (for example, I am using Chrome to Web browse), I can&apos;t count on my computer doing what I want even if I have my hands on the keyboard or a hand on my mouse. User-interface design appears to be HARD--or at least, it is rarely done right--so I am very doubtful that in five years or even twenty-five years I&apos;ll be able to use a computer that really does what I think.</text><parent_chain><item><author>lars</author><text>I&apos;ve recently completed a masters thesis on EEG based mind reading, and I think I have a fairly good grasp on the state of the art in this field. I also have a copy of Kurzweil&apos;s The Singularity is Near by my bed, and I&apos;m usually strongly optimistic about technology. But if IBM are talking about EEG based technology here, I would have to bet that they are flat out wrong on this one. I&apos;ll explain why.&lt;p&gt;Something like moving a cursor around by thinking about it, or thinking about making a call and having it happened requires a hell of a lot of bits of information to be produced by the brain computer interface. With the current state of the art we can distinguish between something like 2-6 classes of thoughts sort-of reliably, and even then it&apos;s typically about thinking of particular movements, not &quot;call mom&quot;.&lt;p&gt;Importantly, what most people look for in the signal (the feature in machine learning terms) are changes in signal variance. And there are methods to detect these changes that are in some sense mathematically optimal (which is to say they can be still be improved a little bit, but there won&apos;t be any revolutionary new discoveries.) There may be other features to look for, but we wont be getting much better at detecting changes in signal variance.&lt;p&gt;Some methods can report results like a 94% accuracy over a binary classification problem. Such a result may seem &quot;close to perfect&quot;, but it is averaged over several subjects, and likely varies between for example 100% and 70%. For the people with 70% accuracy, the distinguishing features of their signals are hidden for various reasons. And this is for getting one bit of information out of the device. Seems like such a device would need to work for everyone to be commercially successful.&lt;p&gt;In computer vision we have our own brains to prove that the problems can be solved. For EEG based brain computer interfaces, such proofs don&apos;t exist. There are certain things you probably can&apos;t detect from an EEG signal, meaning the distinguishing information probably isn&apos;t there at all. I&apos;m easily willing to bet IBM money that who I would like to call can not be inferred from the electrical activity on my scalp. (Seriously IBM, let&apos;s go on longbets.org and do this.)</text></item></parent_chain></comment><story><title>IBM: Mind reading is less than five years away. For real.</title><url>http://news.cnet.com/8301-13772_3-57344881-52/ibm-mind-reading-is-less-than-five-years-away-for-real/?tag=rtcol</url></story>
<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>kevinalexbrown</author><text>&amp;#62; I&apos;m easily willing to bet IBM money that who I would like to call can not be inferred from the electrical activity on my scalp. (Seriously IBM, let&apos;s go on longbets.org and do this.)&lt;p&gt;Be more precise. If you can distinguish two classes, you can convey anything through EEG, however slowly (think &apos;bits&apos;). With error, use error-correcting codes and you can get relatively high accuracy.&lt;p&gt;Pedantics aside, I agree in sentiment. Even with invasive techniques we can only roughly decode movement.</text><parent_chain><item><author>lars</author><text>I&apos;ve recently completed a masters thesis on EEG based mind reading, and I think I have a fairly good grasp on the state of the art in this field. I also have a copy of Kurzweil&apos;s The Singularity is Near by my bed, and I&apos;m usually strongly optimistic about technology. But if IBM are talking about EEG based technology here, I would have to bet that they are flat out wrong on this one. I&apos;ll explain why.&lt;p&gt;Something like moving a cursor around by thinking about it, or thinking about making a call and having it happened requires a hell of a lot of bits of information to be produced by the brain computer interface. With the current state of the art we can distinguish between something like 2-6 classes of thoughts sort-of reliably, and even then it&apos;s typically about thinking of particular movements, not &quot;call mom&quot;.&lt;p&gt;Importantly, what most people look for in the signal (the feature in machine learning terms) are changes in signal variance. And there are methods to detect these changes that are in some sense mathematically optimal (which is to say they can be still be improved a little bit, but there won&apos;t be any revolutionary new discoveries.) There may be other features to look for, but we wont be getting much better at detecting changes in signal variance.&lt;p&gt;Some methods can report results like a 94% accuracy over a binary classification problem. Such a result may seem &quot;close to perfect&quot;, but it is averaged over several subjects, and likely varies between for example 100% and 70%. For the people with 70% accuracy, the distinguishing features of their signals are hidden for various reasons. And this is for getting one bit of information out of the device. Seems like such a device would need to work for everyone to be commercially successful.&lt;p&gt;In computer vision we have our own brains to prove that the problems can be solved. For EEG based brain computer interfaces, such proofs don&apos;t exist. There are certain things you probably can&apos;t detect from an EEG signal, meaning the distinguishing information probably isn&apos;t there at all. I&apos;m easily willing to bet IBM money that who I would like to call can not be inferred from the electrical activity on my scalp. (Seriously IBM, let&apos;s go on longbets.org and do this.)</text></item></parent_chain></comment><story><title>IBM: Mind reading is less than five years away. For real.</title><url>http://news.cnet.com/8301-13772_3-57344881-52/ibm-mind-reading-is-less-than-five-years-away-for-real/?tag=rtcol</url></story>