So use a blender. The tricky part is converting your bitcoin to fiat and vice versa.As soon as someone links your RL identity to your public addresses they can see your entire Bitcoin history
Which is good. Like with most booms, it's better when it's over. We just have to stop pretending it isn't over and get to work in building quality, honesty and stability.Tech boom is over. Over and out.
Bitcoin is the pioneer, though. We now have other mechanisms which are more economical with energy than PoW and there are cryptocurrencies such as Ethereum Classic which have much more capabilities than Bitcoin does. I think that technologically Bitcoin is pretty lame compared to it's alternatives but I respect Bitcoin for being the pioneer. The pioneer is always inferior to whatever is built upon the lessons it taught the world.TBH i don't really see a use for bitcoin other than as an alternative market or risky asset for your portfolio. I used to think it was cool as a decentralised financial system with a baked in monetary policy but I don't anymore. I hate mining it's stupid - brute force computing. What bitcoin did prove is that digital signatures are reliable for proving ownership so that's all we really need and can delete our blockchains.
People who stepped aboard the Bitcoin train do not need another ride.We will never see returns like we did in the past. It's not going to make random people filthy rich via buy-and-hold strategies.
That's the thing. Once it's too big, there will be powers that try to keep from collapsing. Personally I think that once the Central Bank has their tokens ready (another type of digital coin), then climate change policies will prevent mining by making it illegal; while maybe still allowing existing bitcoins to be exchanged to these tokens.Could be. When do you expect the pyramid to collapse?
I disagree. Deep-learned matrices can be sold, and keep being useful. Examples: People that apply for a loan fill in a form, and there's a matrix that is used that detects people that are not going to pay back. This data is then given to a human, that will decide if the loan is granted, or not. Or more close to home, Having this door that only allows your cat in, but not other cats by using a Computer Vision Matrix that has learned to detect your cat. Of course, the door problem can also be solved by using an RFID in the necklace of the cat.The other thing that similarly sucks up all available processing power is deep learning.
So you can keep going to concerts and enjoy the music next to the giant speakers. Still, you will lose your earrings because MIT did nothing to solve that. And asking around for "Hey, have you seen Golden Earrings" gives so many false positives... everybody has seen them, but I can't find them.MIT Scientists Develop New Regenerative Drug That Reverses Hearing Loss
MIT spinout Frequency Therapeutics’ drug candidate stimulates the growth of hair cells in the inner ear. The biotechnology company Frequency Therapeutics is seeking to reverse hearing loss — not with hearing aids or implants, but with a new kind of regenerative therapy. The company uses small molweb.archive.org
So you can keep going to concerts and enjoy the music next to the giant speakers.
I thought that already happened ? Mining was banned in some jurisdictions and then miners migrated en masse somewhere else, then causing mining to be banned there to prevent blackouts... It's not banned everywhere yet, of course, and some countries have even adopted cryptocurrencies. I don't know, too big to fail sounds too contradictory with anarchist utopias to apply. What do I know ?That's the thing. Once it's too big, there will be powers that try to keep from collapsing. Personally I think that once the Central Bank has their tokens ready (another type of digital coin), then climate change policies will prevent mining by making it illegal; while maybe still allowing existing bitcoins to be exchanged to these tokens.
I guess I don't need to tell you about Dutch child care programs, do I ? And there're issues on privacy in model matrices, which make them more difficult to sell that it might seem.I disagree. Deep-learned matrices can be sold, and keep being useful. Examples: People that apply for a loan fill in a form, and there's a matrix that is used that detects people that are not going to pay back. This data is then given to a human, that will decide if the loan is granted, or not.
Deep Learning is very fragile. It's not useless, it's just way oversold. And it's dangerous because then people get faulty systems and think they work. People love to believe in magic, and deep learning is intrinsically difficult to explain to users. So you get police patrols stopping driverless cars, mothers killing themselves because an automated system fined them for more money than they ever earned, or drugs being available without noone quite knowing why they work. I once even read a mathemathician complaining that nowadays with theorem solvers colleagues were applying results without properly checking all (nonsensical, but required) constraints and piling wrong results over wrong results from that. And if a mathematician can get it wrong, an engineer can be fooled, a marketing manager can be sure it's so great and an end user can't be arsed to understand what they're using. And someone gets to pick the pieces.I agree on that Deep Learning is not a panacea. But Imagine cars getting better and better at driving because all the feedback they give each other. And then humans are too afraid to drive because the machines just drive bumper to bumper because that's more efficient use of the road.
So you can keep going to concerts and enjoy the music next to the giant speakers. Still, you will lose your earrings because MIT did nothing to solve that. And asking around for "Hey, have you seen Golden Earrings" gives so many false positives... everybody has seen them, but I can't find them.
Regression analysis to the umpteenth degree. My father has never used a computer and gets this.intrinsically difficult to explain to users
You can only explain it because you have oversimplified the problem. You invest only looking at profits (and in some timeframe too). Deep learning is applied to everything from art to justice, handwaving its implications away.Regression analysis to the umpteenth degree. My father has never used a computer and gets this.
Imagine you are a trading company that has a stock trading algorithm (bot) that uses reinforcement learning to continuously improve it's performance. It's making good money but you can't understand exactly how it works so it makes you nervous. Now imagine it starts making more money than all your other algorithms. You internalize your nervousness and use it exclusively. Now imagine it's not imaginary and happening all around us.