Computers cannot have human like AI until they can construct accurate internal models of the world where they can stimulate (plan) different actions and their results successfully. And this is herculean task - modern computers still struggle even with basic signal processing tasks - it will take hundreds of years before they can inteprete and understand what they see and hear (and this requires partially working model of the real world in order to put things into proper contexts etc). Even for humans it takes several years for child to develop this level of intelligence.
Currently computers are still extremely primitive. They can just simulate internal model of themselves (virtual machines) which they could the use to plan how to repair or modify themselves [use AI and machine learning to try different actions and observe the changes in VM environment] - or use probability and statistical models to learn correlations and causalities in preprocessed datasets but everything else is beyond them.
Robots can use probabilistic models how different actions change the world and can then make non-deterministic actions (bayesian and other probability models) by choosing the response randomly from the probable good actions (and there is no one good solution to many problems).
This is how evolution works. Humans decide probabilistically how to react to the same stimulus and those that survive will then propagate those (best) probabilistic decision models to the offspring.
The amount of surveillance that is happening in internet is probably massive. All information in internet that passes through USA borders is captured by NSA to begin with and this is probably just the tip of the iceberg (echelon..).
It is likely that many big governments are doing large scale surveillance in internet and collecting data about individual's actions and the global state of the mind through internet (analysing forums, conversations, maybe emails in order to follow patterns in mental state of the population). It is interesting that most of the data traffic in internet is still unencrypted - probably because people in power want it that way.
LucasArts and LucasFilm was the best entertrainment when I was young: Indiana Jones films and games (Indiana Jones and fate of Atlantis), Monkey Island, TIE Fighter etc.
But they really kind of "died" after late 1990s. The new Star Wars and Indiana Jones films/games just didn't have the quality of the old times (or maybe I just became old).
In order to have an accurate progress bar, one should be able to predict how long time the overall process will take and this can be very complicated or totally impossible to predict. Additionally, most software is quite badly coded and based on simple boolean control-logic and more sophisticated techniques [complex mathematical algorithms] are not routinely developed or used. How I would do it:
Run test code to test operation speeds and create and use mathematical model (black box solutions like neural networks could be fine here) to predict correct progress. Create learning dataset [for neural network] running the algorithm in different computers. Similarly, measure real progress and time use in the same machine so that the next time progress bar is needed it is more accurate.
In other words, creating accurate progress bars just makes very simple problem very complex and difficult and there are typically much more important things to do (most software has bugs - some very serious) than trying to get progress bars work 100% correctly.
Still, significant improvement could be made if somebody just created generic, self-learning progress bar class that would get more accurate the more often it is being used [the coder would just call new bar("problem-code"), bar.start(), bar.progress(0.75), bar.finish() and the algorithm would self-learn how much real progress 75% typically means for this specific problem with given machine specs (cpuid etc)].
In a university where I studied, students and normal personel got username@domain.tld style email addresses as a default. One then needed to specially apply for first.last@domain.tld like addresses. If there were conflicts, first.middle.last@domain.tld email addresses were used. Rest of the cases were handled as special cases.
Yes, machine learning, data analysis, probabilistic processing and (causal) learning from data is where the future is. The basic programming and binary logic is still important but not be able to create real AI-like solutions. Still, the capabilities of hardware are very important too, as serious number crunching requires lots of processing power (unlike "normal" programs): distributed monte carlo sampling from complex probability models using 1024 threads and CPU-cores + TBs of memory is easily required to handle more complex models. Binary logic works somehow as a crude approximation in high dimensional spaces where most of the data is near edges (hypercube with side length 1 has volume V=1^D = 1, but if you take just 5% away from each edge, the center (values between 0 and 1) has only volume V = 1 - 0.9^D which is close to zero in high dimensional spaces. Bayesian inference is required to properly handle uncertainly better once the dimensionality of the problem is properly reduced using "boolean"-like methods etc.
But basic MCMC and bayesian inference starts to be somewhat outdated afaik and there are smarter methods. Smart mathematical (semiprobabilistic) algorithms and scientific computing rule the future of computing.
If you can find somebody else to do the job for a cheaper rate then it is alright and you can make profit.
That's how to the economy/companies work.
+ It is just ridiculous if you make work contract that you should actually work, all that matter is the results. There is no scam if the other part of the contract gets the results he or she wants.
While bottom-down approach (like evolution) may work. It is just a black-box model (somewhat similar to neural networks), which is not going to be very scientific, we cannot understand how it works or how to improve it, unlike bayesian models (which has flaws), or causal models (better).
In other words, we need new causal+bayesian probabilistic mathematics to process and form meaningful models from data - and it needs to be fitted to the modern physics. The current limitations of handling causality with bayesian probability may also hinder our ability to understand physics. Another interesting area in this regard is application of causal theorems to quantum physics and trying to form bayesian-causal-quantum theorems (but I'm not a physicist).
IMO, one could maybe try to introduce causality to bayesian models by creating causal probability models ("causal gaussian distribution etc") and then having a strong bayesian prior that prefers existence of causal structures in data (which typically exist in real world). This could be then be very good "heuristic" that matches to physics of the data (if you really want to be rigorous these "causal priors" should be derived from physics somehow to match real world data [how causality emerges from quantum chaos?]).
Another way technology could advance is that we will become more and more efficient at using energy. Instead of having huge Dyson sphere, a super-advanced alien race could exist only inside huge computer simulation meaning that each individual would take only small amount of memory and watts to "exist" (something like Matrix) and number of "real" individuals outside this simulation would be rather limited.
Do you really think wikipedia is unbiased currently?
Just read companies or their product's wikipedia pages or pages about schizophrenia (nobody has never measured any chemical imbalance in such "disease") or read pages about popular tourism destinations or english pages about muslisms or al-qaida or pages about "toxic" substances and "good" medicines.
Yes. But it depends whether you are doing REAL DEVELOPMENT WORK (real R&D) or just straight-forward coding or web-development (IT) which doesn't require much reasoning.
Viruses are like guns. Creating guns and bombs can be unethical and should be somehow regulated but it shouldn't be a (serious) crime.
I cracked some games and coded interesting 3d effects when I was 15-years old or something.. when you are less than 16/18-years old, you don't really think too seriously about the consequences.
It will be much easier to gene-engineer humans to better fit into specifications of space and spaceships than to create spaceships for the current form of human being for interstellar travel:
1) too high mass/much smaller size 2) need for oxygen and food (direct use of electricity/solar power as energy source?) 3) need to move? (just brains connected to spaceship computers?) 4) ability live in zero g, recover from radiation, handle low temperatures, ability to hibernate etc
This makes sense if you are considering only high-dimensional vectors/problems.
With D-dimensional cube (lenghts = 1), you have almost everything near sides (10% from an edge).
1.0''D - 0.9''D => 1 (so in the middle there is almost nothing when D is large)
=> boolean logic is good approximative solution for very high-dimensional problems but when the D is low (after preprocessing?) the values in the middle matter (use bayesian probabilistic methods).
There are only actions not approved by the psychiatrist and labelled as "mental illness". For example, people are telling they hear voices and are therefore LYING and therefore mentally-ill (in psychiatry the fact that patient complains about something IS the disease, psychiatrists don't believe any of the illnesses actually exist.)
It is like trying to find morality in physics, or saying one religion has more "truth" in it than some other.
Slashdot Mirror
Computers cannot have human like AI until they can construct accurate internal models of the world where they can stimulate (plan) different actions and their results successfully. And this is herculean task - modern computers still struggle even with basic signal processing tasks - it will take hundreds of years before they can inteprete and understand what they see and hear (and this requires partially working model of the real world in order to put things into proper contexts etc). Even for humans it takes several years for child to develop this level of intelligence.
Currently computers are still extremely primitive. They can just simulate internal model of themselves (virtual machines) which they could the use to plan how to repair or modify themselves [use AI and machine learning to try different actions and observe the changes in VM environment] - or use probability and statistical models to learn correlations and causalities in preprocessed datasets but everything else is beyond them.
Sounds like electroshock to me. And many psychiatric patients who are still alive from such treatments are not very happy with the results.
Robots can use probabilistic models how different actions change the world and can then make non-deterministic actions (bayesian and other probability models) by choosing the response randomly from the probable good actions (and there is no one good solution to many problems).
This is how evolution works. Humans decide probabilistically how to react to the same stimulus and those that survive will then propagate those (best) probabilistic decision models to the offspring.
The amount of surveillance that is happening in internet is probably massive. All information in internet that passes through USA borders is captured by NSA to begin with and this is probably just the tip of the iceberg (echelon..).
It is likely that many big governments are doing large scale surveillance in internet and collecting data about individual's actions and the global state of the mind through internet (analysing forums, conversations, maybe emails in order to follow patterns in mental state of the population). It is interesting that most of the data traffic in internet is still unencrypted - probably because people in power want it that way.
LucasArts and LucasFilm was the best entertrainment when I was young: Indiana Jones films and games (Indiana Jones and fate of Atlantis), Monkey Island, TIE Fighter etc.
But they really kind of "died" after late 1990s. The new Star Wars and Indiana Jones films/games just didn't have the quality of the old times (or maybe I just became old).
Some brain EEG measuring techniques might be able to detect this.
It seems unlikely that nobody couldn't predict its downfall (it had to be rather larger to be visible).
Another possible scenario is a retired spy satellite.
In order to have an accurate progress bar, one should be able to predict how long time the overall process will take and this can be very complicated or totally impossible to predict. Additionally, most software is quite badly coded and based on simple boolean control-logic and more sophisticated techniques [complex mathematical algorithms] are not routinely developed or used. How I would do it:
Run test code to test operation speeds and create and use mathematical model (black box solutions like neural networks could be fine here) to predict correct progress. Create learning dataset [for neural network] running the algorithm in different computers. Similarly, measure real progress and time use in the same machine so that the next time progress bar is needed it is more accurate.
In other words, creating accurate progress bars just makes very simple problem very complex and difficult and there are typically much more important things to do (most software has bugs - some very serious) than trying to get progress bars work 100% correctly.
Still, significant improvement could be made if somebody just created generic, self-learning progress bar class that would get more accurate the more often it is being used [the coder would just call new bar("problem-code"), bar.start(), bar.progress(0.75), bar.finish() and the algorithm would self-learn how much real progress 75% typically means for this specific problem with given machine specs (cpuid etc)].
Renoise is not open source but is quite a decent DAW and intuitively if you have used trackers.
US ISPs are money-hungry.
In Finland I pay 12 euros (16 usd) for having wireless 3G with speed 5 Mbps or more (ping 75ms) and I don't live in a big city.
In a university where I studied, students and normal personel got username@domain.tld style email addresses as a default. One then needed to specially apply for first.last@domain.tld like addresses. If there were conflicts, first.middle.last@domain.tld email addresses were used. Rest of the cases were handled as special cases.
Cannot access mega.co.nz from Finland.
Traceroute seems to get all the way to the target IP thought.
Yes, machine learning, data analysis, probabilistic processing and (causal) learning from data is where the future is. The basic programming and binary logic is still important but not be able to create real AI-like solutions. Still, the capabilities of hardware are very important too, as serious number crunching requires lots of processing power (unlike "normal" programs): distributed monte carlo sampling from complex probability models using 1024 threads and CPU-cores + TBs of memory is easily required to handle more complex models. Binary logic works somehow as a crude approximation in high dimensional spaces where most of the data is near edges (hypercube with side length 1 has volume V=1^D = 1, but if you take just 5% away from each edge, the center (values between 0 and 1) has only volume V = 1 - 0.9^D which is close to zero in high dimensional spaces. Bayesian inference is required to properly handle uncertainly better once the dimensionality of the problem is properly reduced using "boolean"-like methods etc.
But basic MCMC and bayesian inference starts to be somewhat outdated afaik and there are smarter methods. Smart mathematical (semiprobabilistic) algorithms and scientific computing rule the future of computing.
If you can find somebody else to do the job for a cheaper rate then it is alright and you can make profit.
That's how to the economy/companies work.
+ It is just ridiculous if you make work contract that you should actually work, all that matter is the results. There is no scam if the other part of the contract gets the results he or she wants.
While bottom-down approach (like evolution) may work. It is just a black-box model (somewhat similar to neural networks), which is not going to be very scientific, we cannot understand how it works or how to improve it, unlike bayesian models (which has flaws), or causal models (better).
In other words, we need new causal+bayesian probabilistic mathematics to process and form meaningful models from data - and it needs to be fitted to the modern physics. The current limitations of handling causality with bayesian probability may also hinder our ability to understand physics. Another interesting area in this regard is application of causal theorems to quantum physics and trying to form bayesian-causal-quantum theorems (but I'm not a physicist).
IMO, one could maybe try to introduce causality to bayesian models by creating causal probability models ("causal gaussian distribution etc") and then having a strong bayesian prior that prefers existence of causal structures in data (which typically exist in real world). This could be then be very good "heuristic" that matches to physics of the data (if you really want to be rigorous these "causal priors" should be derived from physics somehow to match real world data [how causality emerges from quantum chaos?]).
Another way technology could advance is that we will become more and more efficient at using energy. Instead of having huge Dyson sphere, a super-advanced alien race could exist only inside huge computer simulation meaning that each individual would take only small amount of memory and watts to "exist" (something like Matrix) and number of "real" individuals outside this simulation would be rather limited.
Do you really think wikipedia is unbiased currently?
Just read companies or their product's wikipedia pages or pages about schizophrenia (nobody has never measured any chemical imbalance in such "disease") or read pages about popular tourism destinations or english pages about muslisms or al-qaida or pages about "toxic" substances and "good" medicines.
Yes. But it depends whether you are doing REAL DEVELOPMENT WORK (real R&D) or just straight-forward coding or web-development (IT) which doesn't require much reasoning.
You need both education and experience.
Referencees
Viruses are like guns. Creating guns and bombs can be unethical and should be somehow regulated but it shouldn't be a (serious) crime.
I cracked some games and coded interesting 3d effects when I was 15-years old or something.. when you are less than 16/18-years old, you don't really think too seriously about the consequences.
It will be much easier to gene-engineer humans to better fit into specifications of space and spaceships than to create spaceships for the current form of human being for interstellar travel:
1) too high mass/much smaller size
2) need for oxygen and food (direct use of electricity/solar power as energy source?)
3) need to move? (just brains connected to spaceship computers?)
4) ability live in zero g, recover from radiation, handle low temperatures, ability to hibernate etc
This makes sense if you are considering only high-dimensional vectors/problems.
With D-dimensional cube (lenghts = 1), you have almost everything near sides (10% from an edge).
1.0''D - 0.9''D => 1 (so in the middle there is almost nothing when D is large)
=> boolean logic is good approximative solution for very high-dimensional problems but when the D is low (after preprocessing?) the values in the middle matter (use bayesian probabilistic methods).
There are only actions not approved by the psychiatrist and labelled as "mental illness". For example, people are telling they hear voices and are therefore LYING and therefore mentally-ill (in psychiatry the fact that patient complains about something IS the disease, psychiatrists don't believe any of the illnesses actually exist.)
It is like trying to find morality in physics, or saying one religion has more "truth" in it than some other.
This is not surprising at all really. Gzip and other compression utilities can be used to get upper bound for real/nonredundant information content.
<p>I'm not sure if above is public knowledge, but I have used it as a one additional feature for certain pattern recognition tasks for a while.</p>
It seems like a good start would stop calling all known facts of science "laws", a term that has some kind of meaning, in a juridical sense.
When and where science were given right to have "laws" and everyone else don't?