51–60 of 286 posts
Since we are on the topic, how do the big firms (Google, Facebook, etc) view Singularity University? Is it considered positive, neutral, or negative? Would appreciate inside perspectives.
Some strident Singularitarians joined the comment thread.
I'm from the camp the singularity already happened! ;)
When you travel away from the Sun, the light from it gets dimmer and dimmer and dimmer, until it becomes single photons appearing with more and more delays but on average energy of 'dimmer' light.
Fly towards the Sun and there isn't a sudden cutoff point where it goes from dark to bright, or bright to incandescent, it's a continual increase.
Same with life, lots of people born, lots of intensity around birth and infant children and parents and education, intensity diminishes with age as people spread out and dissipate, everyone's looking back in at the source of new life while getting further and further from it and more and more separated from each other and lower energy levels and less and less 'happening'.
Singularity? Moving towards the intensity with technological development and more intricate, faster, and sheerly more connectivity all over, more encoding of ideas into information patterns.
Unless you want to imagine it like flying towards the Sun becoming falling towards the Sun, becoming a specific point where everyone burns up and dies. :/
Welcome to the club. Now you know how Economists, healthcare professionals, skateboarders, basket weavers and anybody else whose domain knowledge runs deeper than the average joe's feels whenever their area of technical expertise becomes the subject du jour for the public at large.
Earlier quoted context omitted.
Sounds like a good short selling opportunity.
Hard to time that kind of thing. Not worth it when you risk losing your shirt. You can lose an infinite amount of money shorting, whereas going long you might only lose all of what you put in.
Yeah, terms like "machine learning" and "AI" have basically become buzz words which, to most laymen, probably encourage the idea that we're on the cusp of creating Data from Star Trek. Unfortunately, the reality is that.... sorry... it's mostly just statistical algorithms based around regression and intermediate calculus. State-of-the-art "deep" neural networks are not really anything like the absurdly parallel, asyn…
yep, call function-fitting/optimization "learning" and it's suddenly a form of intelligence!
Here is my annoyance with AI Hype: people seeking extra tailwinds pitch their startups as "ML companies" even with the most tangential usage of ML. It drowns out real ML companies. Most people cannot tell the difference. At a hackathon recently, someone pitched their app as an "ML-driven app" though the only ML in there was some 1-line language translation feature they were consuming off Watson REST services for a ta…
Difficulty level 2: Self-trained CNN on a custom dataset using TensorFlow and changes to start/end layers on the NN
Difficulty level 3: Custom rolled 12 layer CNN trained with with novel hand labeled data.
How many people to you think know the difference between these and the fact that each step is a magnitude or more harder than the last? That's not even getting into trying to apply research grade stuff.
Earlier quoted context omitted.
Sounds like a good short selling opportunity.
Hard to time that kind of thing. Not worth it when you risk losing your shirt. You can lose an infinite amount of money shorting, whereas going long you might only lose all of what you put in.
Broadly, no way do I believe that many people, not even fleets, especially not individuals, will put up with the charging time of a battery powered car. It's just so darned much more convenient to fill up a 20 gallon tank with gasoline.
My guess is that the promise of electric cars was boosted by both the anti-fossil fuel push and the self-driving push. IMHO, with Trump, the anti-fossil fuel people just lost, big time, for a long time. E.g., we won't have carbon taxes, the theme will be "drill, baby, drill", and US gasoline prices are on the way down. For self-driving, my view is that the lawyers will make the insurance rates too high and more lawyers will pass some very restrictive laws. Then self-driving will be for some special cases and/or will need a lot of highway engineering that will take a lot of time and money and won't happen for years. For more, no way can Tesla do something significant that GM, Ford, Chrysler, Toyota, Honda, BMW, MB, Kia, etc. can't do just as well or better. E.g., there were electric cars ~100 years ago, and the story has been the same since then or as a Ford exec once said "You build me a good battery, and I will build you a good electric car." For a while there was some hope for a capacitor, which can be charged as fast as the electric power connection permits, but that approach seems to have flopped. Finally, I'm guessing that Musk has had a lot of subsidies, and I have to guess that Trump will turn off that faucet. Net, I see no real hope for Tesla. IMHO, Tesla is going down, soon. So, some smart and/or lucky short sellers stand to make a bundle.
Yeah, terms like "machine learning" and "AI" have basically become buzz words which, to most laymen, probably encourage the idea that we're on the cusp of creating Data from Star Trek. Unfortunately, the reality is that.... sorry... it's mostly just statistical algorithms based around regression and intermediate calculus. State-of-the-art "deep" neural networks are not really anything like the absurdly parallel, asyn…
Welcome to the club. Now you know how Economists, healthcare professionals, skateboarders, basket weavers and anybody else whose domain knowledge runs deeper than the average joe's feels whenever their area of technical expertise becomes the subject du jour for the public at large.
Earlier quoted context omitted.
yep, call function-fitting/optimization "learning" and it's suddenly a form of intelligence!
What is human intelligence, if not the result of a colossal, distributed function optimisation process driven by evolutionary forces over millions of years?