Ok. Yet another post which digresses from core style of Pluggd.in. But then that’s the fun part of it! For over decades now we are a part of a society which breathes on technology and even survives by it. Be it over the internet or mobile network or just about anything else. Awesome online bookstores, location-aware stuff, powerful social networks, multi-touch technology and what not. From terminal based access to Lynx browsers to IE/Netscape to emails to IM’s to Mozilla’s & Chrome’s and Facebooks & Twitters we have witnessed evolution of technology from a completely off-line distribution model to now almost a completely online one.
But all this is about past, and let’s not talk about it.
Talk of the town today is real time internet & social media. In fact social media is such a f**ked term over the internet these days that I really don’t feel like using it. But it”s a living present that one could confirm with every Tom, Dick and Harry on Twitter who is busy selling the social media opportunity to the industry. Whatever, let’s not get into that either.
Let’s extrapolate into the future.
Step back and look at last 100 years in development of Computer Science, Electronics and other traditional Technology first. It all started with simple calculators (Wilhelm Schickard), Charles Babbage, Lady Ada Lovelace and then branched out in to specific fields of research which have been sought after & contributed upon by some of the best brains of our society. A branch of science driven by logic.
Through it came basic internet (disruptive in all respects, as we are witnessing it) which has now progressed into real-time internet where Twitters and other services around the world help humans gain insight, knowledge, trends and information in a ‘decisive fashion’ along the real-time-line of our existence.
So what is next?
Paradigm of Machine Intelligence:
Is it not the turn for Artificial intelligence, Genetic algorithms, and Neural networks to take over? Or it is. These fields of research too have been under continuous development by the best human brains across the world and numerous abstractions have already been successfully delivered by passing generations of computer scientists. For roughly fifty odd years or so. Now what if such an ensemble of layered knowledge of simulated intelligence goes out in the open over the internet for a prolong period of time? Does this sound like a tipping point where mass usage of simulated intelligence in technology would take over the regular solutions available?
Entrepreneurship is an indicator:
Rising entrepreneurship in the field of AI is a strong indication of where the subject is headed. Adapting different use-cases of machine intelligence, there are several quaint startups that offer great value already. For example we have Siri – the first intelligence based Mobile app, Gestures from SixthSense Technologies, Minority report act from Oblong Industries and even in Biotechnology there is Genetic 2.0 which talks about “beginning a parallel genetic code with 256 blank four-letter codons that can be assigned to amino acids instead of the available 64 triplet combination that exists in our lifeforms today “. So new, stronger life forms it talks about.
Another awesome example of Genetic Algorithms is that of work by a brilliant musician-cum-emeritus professor from University of California – David Cope – who created EMMY (derived from Experiments in Musical Intelligence) a computer application which composes and plays operatic music. As good as original Mozart or Bach. Having developed an application which qualified the Turing test with indistinguishable musical ability, Prof. Cope confirms that any creative pursuit of man-kind is just a recombination of something “heard” or “lifted” from elsewhere. Call it plagiarism. He even reverse-engineered centuries of music to its roots & forebears to prove his finds. “Nobody’s original,” Cope says. “We are what we eat, and in music, we are what we hear. What we do is look through history and listen to music. Everybody copies from everybody. The skill is in how large a fragment you choose to copy and how elegantly you can put them together.”
Let’s murder the Captcha now, for example.
The test of “humanness” on internet hangs by a thin thread of binary files. There is anti-circumvention clause of the Digital Millennium Copyright Act (DMCA) in the United States to prevent mass scale circumvention of Captcha and an exemplary case of injunction against a violating company too. All major commercial services such as Facebook, Google & Twitter rely on Captcha & Phonetic test for humans.
But technically speaking how unstoppable is it to programmatically parse the binaries that allows the bots to create bot accounts without any human intervention? If one looks at the pace of on-going research in Voice Recognition or Image recognition it seems pretty reasonable to assume that Captchas are soon gonna have to die and something more “undoable” by machines will have to be put in place. Evolution yet again, until the next wave of upgrade!
Well more than the defeat of Captchas or of Voice Binaries is a concern that of applying the Genetics Paradigm to human generated passwords which too are more-often-than-not simply composed. Passwords are easily predictable piece of data for all practical purposes and technically speaking I am not talking about social engineering. Composing passwords is not as much complex or original an activity as is composing music. And when music itself can be genetically attributed to cut-copy-paste syndrome to the aboriginal sounds of animals, birds and other objects how easy it’d be to work out cracks for passwords using genetic algorithms?
Genetics is more than Computer Science
Evolution applies to Nature. So does it apply to industry, businesses, technology, governance, communication and our children too. Let’s hypothesize a Neural Network and open it over the internet to simply tell us a ‘Yes’ or ‘No’ before buying a particular scrip on the Tokyo’s stock exchange! And now if this neural network is trained with data-sets of masses (applying the social media paradigm here) and its corresponding result-sets – frequently called as intelligence of the crowd/market (one can compound training with real-time data inputs also) – then how powerful would such a neural network be? Will it give an answer with impeccable accuracy as to how the scrip’s gonna perform on the stock exchange? Theoretically yes, coz it will have infinite sample size of training over social nature of internet and time, right?
Code named ‘Awareness’
Human brain is claimed to be the only object in the world which is aware of itself. It is powerful, it can think, decide, learn, store, process, collaborate and get tired too. In fact most of evolutionary physical limitations of the human body (as compared to animals) can be attributed to the available alternative of using a powerful brain in our defense. Brain too evolves naturally and slowly over generations & generations of people. But for technology, the realm of evolution is much faster. Our society pulls out best brains competitively and puts them on projects of intelligence. These best brains contribute philosophy over philosophy over philosophy and build on the capabilities of the machines. Now when this process is opened to crowd-sourcing, developer community, open-source paradigm and other contributory concepts what we might eventually end-up with is “accelerated evolution”. Until one day we would have another object which is aware of itself. Or at least more intelligent than a single human brain.
Now the question is: how far is such day?