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posted by martyb on Monday May 29 2017, @03:27AM   Printer-friendly
from the it's-all-gone-to-bits dept.

From the RooshV Forum:

I constantly get the vibe from people that they think our technology is skyrocketing, that we're living in a new tech age, "where was all this ten years ago?!" etc.

But I disagree with this assessment of our technology. It has made steady improvements in one specific space: software and electronic hardware. That is all. On top of that, the improvements on the hardware have not even been ground breaking. GPS is a ground-breaking invention. Smaller screens are not: they are just an incremental improvement.

Smartphones are merely the result of incremental improvements in the size and quality of electronic components. The only breakthroughs involved are ages old. The invention of the transistor, the laser, etc. The existence of google, facebook, uber, and so on, are merely inevitable "new applications" stemming from these improvements. They are not breakthroughs, they are merely improvements and combinations upon the telephone, the directory, and the taxi.

In my opinion, technology as a whole is borderline stagnant.

A list of why technology is still shit:

The posting goes on to list examples of incremental, rather than breakthrough, changes in the areas of:

  • Electronics & Machines
  • Energy
  • Medicine
  • Clothes
  • Food
  • Finance

Have we really stagnated? Have we already found all of the "low-hanging fruit", so new breakthroughs are harder to find? Maybe there is greater emphasis on changes that are immediately able to be commercialized and less emphasis on basic research?

 
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  • (Score: 2, Insightful) by Anonymous Coward on Monday May 29 2017, @06:56AM (3 children)

    by Anonymous Coward on Monday May 29 2017, @06:56AM (#517049)

    That's the interesting thing. These changes are not about hardware, but revolutions in how software is created. Google has released data on the performance of AlphaGo on various architectures and while it did play on a beastly setup for its penultimate performance, it probably wasn't necessary. On commercially available hardware with 8 GPUs, it's performance wasn't all that different than its performance on their beastly machine. It would likely still have defeated the world's best human, though granted it would have been closer.

    Nobody is "trying" to monetize AI. It's already being done and paying vast dividends. The whole market of user exploitation is largely driven by AI. Each time anybody posts anything on Facebook that is parsed, sorted, and utilized by AI to more effectively squeeze money out of that individual. That is not speculation, but when we enter into speculation things get even more interesting. Facebook has previously engaged in [research](https://www.theatlantic.com/technology/archive/2014/06/everything-we-know-about-facebooks-secret-mood-manipulation-experiment/373648/) on exploiting users mood by changing what content is delivered to them. That manipulation is now almost certainly be actively engaged in by Facebook's AI algorithms. Perhaps most interestingly is the discovery that people tend to write more when their emotions are 'tweaked', either positively or negatively. Delivering cold bland information leads to a dead social media site.

    Another example would be the stock market. Humans are now competing against AIs without ever realizing it. These AI started as tools to help traders make better, faster decisions. But as the tools became more effective than their users - the users became obsolete. Now [84%](https://www.ft.com/content/da5d033c-8e1c-11e1-bf8f-00144feab49a) of all trades in the stock market are carried out by AIs creating, formulating, and executing trades in real time. To be clear - that 84% does not include you setting a sell-at trigger for your stocks. These are high frequency traders actively creating new and original orders and trading plans. The same is now happening to hedge funds which are increasingly becoming automated.

    Or Google. The reason they're popular and consequently having the position of power to begin taking over vast swaths of the entire tech world is because using their service you will you tend to actually find what you're looking for with them. That's in no small part a result of extensive machine learning and AI. Think about how cool it is that you can search even for Jeopardy like queries and get the 'answer.' "This story tells the tale of a captain's relentless search of revenge against a whale." 15 years ago there's no telling what you'd get with that query - probably hardcore porn. Google's initial improvements over the old was human driven, but now human-AI coops have produced vastly greater performance than that, and in the future AI will likely be the one responsible for further improvements in access to content.

    Or Watson. The last you heard of IBM's toy was probably crushing human's at Jeopardy. Rather than give the cliff notes of its vast progress since then, I'll just reference the wiki [wikipedia.org] page.

    You see the reason you want things wrapped up and delivered to you at a store is because you've come to expect marketing. Modern social media is little more than a device through which complicit users (and their information in particular) is turned into products that are bought and sold by various companies looking to remove them from their burdensome disposable income. It's like praising the slot machine as a revolution in technology. The only reason it's seen as difference is because we have this sort of plausible deniability of the value of bringing people together. In any case this marketing value is why it's seen as "hot" and "trendy." Trends are mostly driven through marketing - not merit. The wiki page on Fidget Spinners [wikipedia.org] is a contemporary example. Dead - then a nice little bit of marketing and boom the trend line shot upwards damn near 90 degrees. If you want to actually dig into AI then there are vast resources available. OpenAI [openai.com] has an amazing framework and vast amounts of information available. As much as I hate to admit it, I think the world is becoming increasingly segregated into drivers and passengers. And passengers are increasingly becoming second class citizens of this world. And there may be no real solution. Basic income will likely only accelerate this divide. Don't become a passenger waiting for your train to arrive.

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  • (Score: 2) by kaszz on Monday May 29 2017, @09:19AM

    by kaszz (4211) on Monday May 29 2017, @09:19AM (#517079) Journal

    To rival the performance of dedicated hardware. It's necessary to be able to buy AI chips. It's not about marketing but access to tools.

  • (Score: 2) by TheRaven on Monday May 29 2017, @12:57PM (1 child)

    by TheRaven (270) on Monday May 29 2017, @12:57PM (#517114) Journal

    That's the interesting thing. These changes are not about hardware, but revolutions in how software is created

    Nonsense. The techniques used by AlphaGo are 30 or more years old. They're popular now for two reasons:

    • Computers are a lot faster now. Throwing a huge amount of compute at a problem without properly understanding it will get you an approximation of a solution and that's often good enough.
    • A whole generation of people who understood the limitations of these techniques has now retired or died and so people are learning them again.
    --
    sudo mod me up
    • (Score: 0) by Anonymous Coward on Monday May 29 2017, @03:08PM

      by Anonymous Coward on Monday May 29 2017, @03:08PM (#517161)

      I really hate to respond to a post with just an article, but really: A Brief History of Neural Nets and Deep Learning [andreykurenkov.com]. You just repeated an oft repeated line, but it's simply not true. However, proving that is no trivial task and is not a wheel I care to attempt to reinvent.

      And you're never going to get even an approximation of strong play (let alone a solution) to Go through brute force. The search space in that game is absurd, and tactical nuance (which can decide games) is not present to the degree in a game like chess that helps not only with performance against humans but also in rapid culling. Another issue is that hardware sees extremely rapid diminishing returns beyond a baseline which depends on the task at hand. For instance here [wikipedia.org] is a wiki page listing some configuration:performance results for an earlier version of AlphaGo. It's interesting that the first doubling of GPUs (from 1 to 2) lead to an increase in performance of about 26%. The next doubling saw a gain of about 5%. The next doubling saw a gain of 1%. Going from the final setup (with 8 GPUs and 40 CPUs) to a monster of distributed computing with 1,920 CPUs and 280 GPUs saw a performance gain of less than 10%. Of course even that baseline level was generally out of reach not all that long ago, yet that's for playing Go. Chess is simpler and checkers even moreso. Given today's knowledge, these games could potentially have seen computers become dominant much faster than going for the more traditional min-max eval+culling route that was used for decades.

      It would be interesting to see the effort required to develop a deep learning system capable of defeating Stockfish (currently the strongest chess program) and what the final product would require in terms of relative performance to remain dominant. E.g. would a deep learning system's final product operating on 1.5 units of compute be able to defeat a stockfish running on 3 units of compute? Alas, I think Google is looking to even grander displays of AI dominance - StarCraft 2 is next on the chopping block.