Former NASA chief unveils $100 million neural chip maker KnuEdge - Page 1
Forum section: electronics / general

author: Kjelt
author_rank: Super Contributor
timestamp: June 06, 2016, 05:10:01 pm
content: Neural chips, sounds that will become interesting new technology and programming. O0http://venturebeat.com/2016/06/06/former-nasa-chief-unveils-100-million-neural-computing-chip-company-knuedge/

author: JoeN
author_rank: Frequent Contributor
timestamp: June 07, 2016, 10:03:24 am
content: Quote from: Kjelt on June 06, 2016, 05:10:01 pmI read exactly that. In the 80s. In the 90s. In the aughts. etc. Let's see if it happens this time.

author: Alex Eisenhut
author_rank: Super Contributor
timestamp: June 08, 2016, 12:20:18 am
content: Quote from: JoeN on June 07, 2016, 10:03:24 amBah, try the 1960s.http://www.itproportal.com/2013/01/02/the-neuristor-and-the-future-of-computing/

author: JoeN
author_rank: Frequent Contributor
timestamp: June 08, 2016, 04:44:24 am
content: Quote from: Alex Eisenhut on June 08, 2016, 12:20:18 amHeh. I only started reading that stuff in the 80's, gramps.

author: Dubbie
author_rank: Unknown
timestamp: June 09, 2016, 06:18:32 am
content: Well this time around neural networks are kicking tons of previously 'state of the art' systems to the kerb. Problems like image recognition, speech parsing, text recognition and hundreds more problems are all falling like dominoes to neural networks.Sent from my phone using Tapatalk

author: photon
author_rank: Frequent Contributor
timestamp: June 09, 2016, 06:42:05 am
content: It's very deju vu: egos, clever company names and the hard sell.

author: EEVblog
author_rank: Unknown
timestamp: June 09, 2016, 07:43:33 am
content: The already have $20 million in revenue? Selling to who?

author: EEVblog
author_rank: Unknown
timestamp: June 09, 2016, 07:46:20 am
content: QuoteCall me skeptical, but that doesn't sound game changing.

author: coppice
author_rank: Super Contributor
timestamp: June 09, 2016, 08:02:37 am
content: Quote from: Dubbie on June 09, 2016, 06:18:32 amI read lines like that in the 60s, 70s, 80s, 90s, and 00s. You never know. It might actually be true this time around.

author: Dubbie
author_rank: Unknown
timestamp: June 09, 2016, 08:12:54 am
content: Last time around it was the promise that these things will happen. They didn't. But this time it isn't empty promises. It has already happened.Sent from my phone using Tapatalk

author: coppice
author_rank: Super Contributor
timestamp: June 09, 2016, 08:17:29 am
content: Quote from: Dubbie on June 09, 2016, 08:12:54 amI think you read too much marketing blurb. Most of the things you listed have slowly incorporated aspects of neural type techniques since the 80s. They are not that new, and generally not that effective.

author: photon
author_rank: Frequent Contributor
timestamp: June 09, 2016, 08:25:52 am
content: Quote from: EEVblog on June 09, 2016, 07:43:33 amYes, and $100 million in investments. Did they mention a customer? Or an investor? That seems odd given all the other big names that were thrown around in the article. Call me a skeptic but I immediately started to sniff.

author: Dubbie
author_rank: Unknown
timestamp: June 09, 2016, 08:33:19 am
content: Quote from: coppice on June 09, 2016, 08:17:29 amHow do you think technology like Google reverse image search, Apple Siri, Self driving cars and many other applications work? The reason why they went nowhere much before is because it's only been recently possible to perform the vast number of computations in a reasonable time using compute clusters and gpus.Sent from my phone using Tapatalk

author: coppice
author_rank: Super Contributor
timestamp: June 09, 2016, 09:44:18 am
content: Quote from: Dubbie on June 09, 2016, 08:33:19 amAs far as I know Google reverse image search works by feature extraction producing a "key elements" kind of representation of the image, which is them matched against similar representations of other images. i.e. Its is a DSP solution.Siri, and the Google and MS equivalents, are fun to play with, but too unreliable to be useful. That's about where things were 20 years ago. They are faster now, of course, but still pretty useless. Its not compute power which is currently holding them back.Self driving cars are something of an unknown right now. There's lots of marketing, but very little detail about the real world ups and downs of the test systems is available. From what I have read, they are not using particularly exotic compute resources.A number of applications which started out in the 70s and 80s as neutral network type solutions have migrated to something more DSP based. e.g. finger print recognition. You can argue that there are numerous similarities between many DSP algorithms, especially adaptive ones, and neural networks. I'd say the similarities are rather superficial, and just stem from trying to solve similar problems.

author: TJ232
author_rank: Frequent Contributor
timestamp: June 09, 2016, 09:44:38 am
content: Quote from: photon on June 09, 2016, 08:25:52 amRead behind the lines. Spell with me: M I L I T A R Y sector funding & applications.Try another word: B L A C K H O L E.I am not confirming or denying anything. I am not even confirming the fact that I can confirm or deny anything. To the end of the day, What is "anything" ? Or a "thing"? hmmm...

author: coppice
author_rank: Super Contributor
timestamp: June 09, 2016, 09:54:22 am
content: Quote from: TJ232 on June 09, 2016, 09:44:38 amThat was my assumption when reading the article, especially you consider the guy has a defence contractor background. The military has always been eager to fund neural approaches.

author: Kjelt
author_rank: Super Contributor
timestamp: June 09, 2016, 12:30:16 pm
content: Quote from: coppice on June 09, 2016, 09:44:18 amNo just a bunch of high end computers as far as I could see during a demonstration here two weeks ago. The whole trunk is filled with computers and screens in the car, but that is because at this moment there are still people in the car that can interfere and have to check what the car does all the time.It was nice though 8 cars from different countries/universities talking to eachother, three of them driving to a crossing point and they had to decide themselves who had and got priority. They crossed eachother with 25cm between the cars, that is why in the final product there will be no user killswitch as seen in these prototypes. The user will be fully out of control and the number of accidents will drop significantly to almost 0, and another good thing drunk and high driving and other stupid people who think they can drive are out of the game and also traffic jams will be gone. Still we have to wait till 2030 aproximately.

author: rfeecs
author_rank: Frequent Contributor
timestamp: June 09, 2016, 04:37:49 pm
content: Apparently Google is using something like this, a "TPU":http://www.pcworld.com/article/3072256/google-io/googles-tensor-processing-unit-said-to-advance-moores-law-seven-years-into-the-future.htmlThey are not saying exactly what it is or how it works. Sounds like some sort of massively parallel thing.

author: photon
author_rank: Frequent Contributor
timestamp: June 09, 2016, 05:16:16 pm
content: Quote from: TJ232 on June 09, 2016, 09:44:38 amYes, I agree these guys are politically connected. But if they have such good black military funding, why are they presenting the glitzy add? If their $100 million investment is black, or their $20 million customer is black, why advertise it? I conclude their funding (black or otherwise) is running out and they need new sources of money and I'm guessing they don't have much to offer.

author: coppice
author_rank: Super Contributor
timestamp: June 09, 2016, 05:21:30 pm
content: Quote from: rfeecs on June 09, 2016, 04:37:49 pmWell, they are kinda saying its an accelerator forhttps://www.tensorflow.org

author: helius
author_rank: Super Contributor
timestamp: June 09, 2016, 07:08:26 pm
content: Quote from: rfeecs on June 09, 2016, 04:37:49 pmThe same way Google is "using" bullshit "quantum computers"? Be still my heart.

author: TJ232
author_rank: Frequent Contributor
timestamp: June 09, 2016, 07:21:53 pm
content: Quote from: photon on June 09, 2016, 05:16:16 pmWhy they are doing it?1. A quite classic approach for a corporation than want to diversify the sources of investment and income:- Marketing campaign, brand awarness- Smoke and mirrors, look we are so cool, big names, big words, NASA, DoD, omg, this is the new Alpha&Omega blablaMaybe they are preparing a fancy IPO, who knows.Result : a HUGE pile of money for them.OR2. They really have discovered the Holly Grail of Computing and now are thinking to share the news. Why now? Because now are ending the existing confidentiality agreement for this kind of stuff (expecting 20 years or even more for something at such level)Result : a HUGE pile of money for them.Which one do you like more?

author: Alex Eisenhut
author_rank: Super Contributor
timestamp: June 09, 2016, 11:56:26 pm
content: Quote from: EEVblog on June 09, 2016, 07:43:33 amUBER.

author: photon
author_rank: Frequent Contributor
timestamp: December 28, 2018, 12:29:58 am
content: Sniff test was correct.https://www.sdbj.com/news/2018/may/16/100-million-later-ai-startup-may-close/

author: SiliconWizard
author_rank: Super Contributor
timestamp: December 28, 2018, 01:53:56 am
content: Quote from: photon on December 28, 2018, 12:29:58 amThat was to be expected.

author: BravoV
author_rank: Super Contributor
timestamp: December 28, 2018, 02:08:15 am
content: Bored ... yawn ...Quote :... aimed to develop computers with reasoning capabilities, rather than the ability to merely perform calculations. Computers imbued with such "artificial intelligence" could be used to diagnose diseases, analyze lawsuits and understand language.....Source ->Fifth Generation ComputerAs a reminder, this article was written in 1992.The proof of the pudding is in the eating !

author: cdev
author_rank: Super Contributor
timestamp: January 02, 2019, 09:26:56 pm
content: AI using deep learning technologies if measured by the falling cost and increasing rapidity one can do a given task is improving so much from one year to the next that its not hard to see that within a few years its going to be impacting every aspect of our lives. Life altering decisions will commonly be made by computers.For that reason, especially, we should be asking questions, important questions that aren't being asked, about what shifting all this responsibility to machines that have no accountability is likely to do to society. Especially because all that energy is being dedicated to increasing profits. Which may deliver unexpected results.99% of the time they may deliver a result thats not inconsistent with what a person, (perhaps a very amoral person) might do, but in that remaining 1% they could easily make very severe mistakes that no sane person would ever make.Also, what is going to happen as more and more of our jobs, both skilled and unskilled, are automated, for good.Will all that extra time people will have (and they will have a lot of it) be used wisely?The progress being made in AI is a totally different thing than the PR coming from individual companies. Sure there is lots of hype whenever people are investing money.

author: Rasz
author_rank: Super Contributor
timestamp: January 03, 2019, 09:22:00 am
content: Yay 2 year old thread. This "AI" startup failing is just exception proving the rule.https://www.cbinsights.com/research/top-acquirers-ai-startups-ma-timeline/Shitton of machine learning startups bought by big players in last couple of years, and its speeding up.Quote from: coppice on June 09, 2016, 09:44:18 amapart from the whole "representations" being automagically learned at a massive scale part you somehow missed. Its all a child of AlexNet. Image recognition and classification sort of worked, then deep convolutional neural networks happened and all of a sudden everyone and their dog was able to drop error rates from 25% to below 3%https://arstechnica.com/science/2018/12/how-computers-got-shockingly-good-at-recognizing-images/Quote from: coppice on June 09, 2016, 09:44:18 amso thats why they are all successful shipping products then? This is the main difference between AI from the eighties before the AI winter, and now. This time shit actually works and is useful.Quote from: coppice on June 09, 2016, 09:44:18 amno, 20 years ago voice recognition "worked" by shouting single short words, waiting for computer to calculate FFT plot, compare against couple of stored patterns and mostly randomly guess the result, with maybe few exceptions (Dragon actually having some success if you shouted loud enough).This isthestate of the art from merely 10 years ago, pre deep learning:Today even an idiot with rudimentary Python skills is capable to put together basic machine learning demo able to impress most of us here.robbits will eat us all.

author: coppice
author_rank: Super Contributor
timestamp: January 03, 2019, 02:13:28 pm
content: Quote from: Rasz on January 03, 2019, 09:22:00 amDo you mean working and useful for entertainment value? That's all I've ever seen people get out of Siri and the Android equivalent.

author: Mr. Scram
author_rank: Super Contributor
timestamp: January 03, 2019, 02:52:32 pm
content: Quote from: Kjelt on June 06, 2016, 05:10:01 pmI don't see how they plan to outcompete existing giants like Intel and Microsoft. Those opted for FPGA solutions tightly integrated into the rest of the processing and system, as they found their understanding of how neural nets should work evolved too quickly for the manufacturing of ASICs to keep up. You can bet that as soon as that cycle slows down they'll start pumping out those ASICs like there's no tomorrow.I saw too late I'm responding to an old thread. Guess I was right.

author: cdev
author_rank: Super Contributor
timestamp: January 03, 2019, 03:03:55 pm
content: Clearly there are going to be a lot of opportunities for interesting electronics in this field.Trying to use a CPU for deep learning is too slow.Even when (dedicated HW) is expensive to buy it is still much cheaper than hiring people to do those now automatable tasks.The process is simple, once you have the right model you just point the hardware at examples of where the (question) applies and where it doesn't apply. It can be done with still images, video, audio, literally any kind of input that can be presented to computers.That is why its going to impact a lot of jobs.Soon we'll be seeing apps where a business can train an AI to do things people now do..When it becomes as easy or even easier to train an AI binary blob to learn something, than write a program that does it, its going to take off.Even if it still has some issues like it still does now, its still becoming a hot item because of its novelty. But already its much more than a curiosity.

author: coppice
author_rank: Super Contributor
timestamp: January 03, 2019, 03:14:36 pm
content: Quote from: Mr. Scram on January 03, 2019, 02:52:32 pmPeople have been using FPGAs for neural work for a long time. Google and others have already moved beyond that, to produce custom silicon for well establish algorithms, (e.g. TensorFlow acceleration), apparently with some success. When things are only used in house its difficult to judge just how successful they are, though.

author: cdev
author_rank: Super Contributor
timestamp: January 03, 2019, 03:31:01 pm
content: Its used extensively now by Internet firms for content moderation. So much so that there is a debate about how these devices are being trained. The decisions they make depend on who trained them and with what. There is a fear that since AIs are now doing things that only people did before that they are creating a society with burned in algorithmic biases. And that is true.I personally have run into that as some of you might well imagine. And Ive been documenting it as best as I can.What happens when there is an outlier case?The algorithms are being over relied upon- there needs to be mechanisms that allow people some transparency so if a major mistake is being made they can get something escalated to a human with the authority to do something to fix it.-----------The real underlying problem is this relentless and unnecessary pushing towards more and more 'efficiency' when the business case for so much efficiency is really lacking.I think most of us would prefer less efficient more human centered business interactions to be incentivized, not the most automated ones.But the perception is that profit margins will be razor thin, incomes falling for most people so most people wont be able to afford not just personal but human service at all.Is that the world we want to live in where we never deal with humans when we buy or sell things? Where all sorts of important decisions are made by machines basing them on what was done before, not what is known to be right.When products are also delivered by machines? We can bet that lots of crime will occur in that kind of world. Also, as money will be hard to make as real wealth generation opportunities (manufacturing is one) that are profitable and offer personal satisfaction as well.. (doing a job well is a flow experience with its own rewards, apart from just making money)But the fun and interesting jobs will dry up and in their place, we'll see mega businesses, that employ fewer and fewer people, and push those people harder and harder, and also, more and more churning and scams.

author: coppice
author_rank: Super Contributor
timestamp: January 03, 2019, 03:54:41 pm
content: Quote from: cdev on January 03, 2019, 03:31:01 pmThere are now estimates showing the number of fake bot based users exceeding actual human users of the internet. If those are accurate, there has already been an inversion, and moderation systems are being trained to whatever the bot masters want.

author: Mr. Scram
author_rank: Super Contributor
timestamp: January 03, 2019, 03:59:27 pm
content: Quote from: cdev on January 03, 2019, 03:31:01 pmWasn't it you who thought you were censored by a moderator or moderating bot when I abbreviated one of your fairly lengthy posts? Are you sure you're documenting actual cases and not just ones you think you see?

author: Rasz
author_rank: Super Contributor
timestamp: January 03, 2019, 09:58:32 pm
content: Quote from: Mr. Scram on January 03, 2019, 02:52:32 pmTheir (startup from this thread) plan wasnt to outcompete the giants, because Intel didnt compete at all couple of years agoPlan was being acquired, and Intel (and all the other giants) did in fact buy couple of "AI" startups each.Quote from: coppice on January 03, 2019, 02:13:28 pmIt has no value if you are over 40 and still use a bar/flip phone (Like me) Otherwise you use it daily without even noticing. Photo albums you can magically search by content of the pictures without pre labelling anything, BookFace suggesting old "friends" after recognizing your mug on their photos. That instant translation of chinese text on a box of garbage you ordered from Amazon? How about something trivial, like saving your life?https://www.imore.com/siri-calls-911-helps-save-man-injured-exploding-cottageQuote from: coppice on January 03, 2019, 03:14:36 pmGoogle moved past internal usehttps://cloud.google.com/tpu/its already a product you can use today. We are currently entering last stage of Hype cycle - productivity.

author: cdev
author_rank: Super Contributor
timestamp: January 04, 2019, 12:22:08 am
content: Google is by no means the only company investing heavily in deep learning acceleration, but they probably are the largest or one of the largest users of it. Whether the issue is arbitrary demonetization of YouTube videos or pervasive discrimination encountered by Dalits in the US- resulting in their getting shadowbanned arbitrarily on Twitter- we have to realize that these issues may be caused by the totally opaque processes used to create these tools. It likely comes down to the fact that the training sets used to build up the AI was biased. If people with strong biases create or train these tools they are going to have algorithmic biases burned into them, literally.https://en.wikipedia.org/wiki/Tensor_processing_unitThat said, the benefits having software that can do such complex tasks brings to the table is pretty hard to ignore. If only we could incorporate the 'efficiency gains' derived from its power into society in a better less unfair way.I hate to think of what the implications of so many people losing their jobs will be. There just is no way that society is going to be able to offer people much unless we totally rethink a lot of things which seem to be sacred cows. We need to return to progressive taxation. Otherwise in twenty or thirty years we're going to have extreme concentrations of wealth, where maybe twenty people own half the world, (we're actually getting close to that part right now) another ten or twenty million or so own the next 45% (basically, we'll lose the middle to the ends, especially the bottom) and the remaining 5% is owned by everybody else.

author: cdev
author_rank: Super Contributor
timestamp: January 04, 2019, 12:38:33 am
content: What people think are the "AI applications of today" are actually the AI applications of four or five years ago.And the state of the art is moving forward very quickly. The stuff thats being done in labs today - some of which is almost ready for commercialization is way ahead of what we see - companies implementing the stuff people buy or use. During that time, a lot has improved. For example, object recognition in videos, has made huge strides, now we've gone from AI being able to tell us whats in the picture to telling us who is doing what to who with what. Soon they will be telling us why. Thats the biggest jump of all.Each one enables a really big difference in terms of practical application.Quote from: coppice on June 09, 2016, 09:44:18 am

author: NorthGuy
author_rank: Super Contributor
timestamp: January 04, 2019, 01:08:18 am
content: Perhaps, singularity is closer than I think.

author: cdev
author_rank: Super Contributor
timestamp: January 04, 2019, 01:49:51 am
content: How close is that?Quote from: NorthGuy on January 04, 2019, 01:08:18 am

author: diegogmx
author_rank: Contributor
timestamp: January 11, 2019, 07:19:41 am
content: does anyone have more info on neuristor logic? whether useful or not it sounds quite interesting