A Bright Future For Soft Computing

Interesting this article here: Rebirthing HAL.

I think I have been hearing the very same arguments since my first days -- and even earlier -- as a freshman at my former university.

Evolutionary algorithms, neural networks, and others bio-inspired approaches are just profound simplifications of real systems. Don't expect them, at least in the near future, to replicate what their real counterparts do.

Worse Is Better!

David Tow has written an instigating article on the role artificial intelligence (AI) methods are playing and will play concerning its use in e-business.

He outlines a set of major methods he believes will become a hotbed for e-commerce and web intelligence:

1. Evolutionary algorithms
2. Bayesian networks
3. Fuzzy logic
4. Swarm intelligence
5. Neural networks
6. Intelligent agents

Except for #4 and #6, I have seen so many enterprise applications of the remaining methods -- being pretty honest, not only enterprise ones, but a highly diversified spectrum of uses of those methods (#1, #2, #3, and #5).

But what David Tow argues is the increasing use of those methods in e-commerce and web intelligence. I think his arguments are well reasoned, since those kinds of endeavours are recent phenomena -- they arose after the Internet and the World Wide Web --, it is normal AI methods have not been widely applied in them so far.

His future trends prognostics are even more instigating:

"The enterprise of the future will increasingly depend on the wide range of rigorous artificial intelligence algorithms and methods outlined above, to drive its operations at all levels of management. 

Decision Engineering techniques are at the forefront of this revolution- while IBM has recently set up a new services unit focussed on applying predictive modelling to automate business decisions.  

These techniques will continue to be enhanced and packaged in different combinations, to provide immensely powerful problem solving capability as well as integrating with the global intelligence of the Web 4.0.  

Major decisions incorporating sophisticated levels of intelligent problem-solving will increasingly be applied autonomously and within real time constraints, in order to achieve the level of adaptability required to survive in an ever-changing and uncertain global environment.

I do not think traditional methods are sentenced to die out, just take a look at the operations research guys that have bred a shining research city on the hill since the early stages of that field around the 1930s and I do not consider they will suddenly vanish from the surface of this planet.

The author did not point an important issue: Better not always means better. The better definition here is not intented to slur other methods, but it embeds what an enthusiast of some research area thinks about his own field/research: Not so rarely, we can see researchers colourfully speaking when it comes to their own research. I consider that a sensible attitude, but hyper-hyped words do not help to solve problems in the real world and the real world, as an old saying states, is a cruel place that may tear into shreds any hype. The chills of the AI Winter can still be felt.

Other important point has to do with the user base a given method owns. Someone may have designed the best time complexity algorithm, the best neural network, the best fuzzy set tunning method, and so on, but if they do not have a significant user base, all those methods are useless -- they may serve as an interesting academic investigation endeavour, but not for application in the real world, since no one would be using them. The ultimate example that illustrates this is the so called worse is better approach:

[...] [S]omething can be "inferior" but still "better". For example, to a particular market or user, software that is limited but exceptionally simple to use may be "better" than software that is more comprehensive but harder to use.

I hope I am not slurring the work of anyone else out there, but the Elitist Simple Genetic Algorithm is, in my humble and insignificant opinion, a perfect example of worse is better in evolutionary computation.

No, I do not consider the elitist SGA a bad method. On the contrary: It is an amazing method devised by Professor John Holland and it has succeeded in so many fields -- thanks to the embedded knowledge its users have included in it and its simplicity. BUT, the elitist SGA, despite its drawbacks, is the most applied genetic algorithm (and evolutionary algorithm) until now, even though there are some new genetic-based techniques that are direct descendants of the SGA, such as EDAs (Estimation of Distribution Algorithms), that were made to overcome some drawbacks inherent to the SGA. Fifteen years after the publication of Baluja's seminal EDA paper, the SGA still is strong, well alive, and bigger than all of its offsprings. Worse is better! :)

Even the SGA siblings (evolution strategies, evolutionary programming and genetic programming) have not got the wide range SGA has. The SGA dominance and its offsprings struggle to obtain a bigger amount in the application market is, in my opinion, an example of worse is better. Would the SGA be an evolutionarily stable strategy? :)

So, I do not believe future problem solving will be strongly tied to artificial intelligence methods. At least not in a fatalistic manner as some believe. Those methods will play a role -- major or minor -- in different problem solving situations, but not to the point of relying 100% on them.

The Grad School

That's it!

Next year, I shall be applying for some interesting course in Grad School. Despite the current fad in Brazil concerning the New Wave Of Public Exams to be admitted into one of the three major public Brazilian services (municipality, state, or federal), I would not feel comfortable after five years studying to get my BA. degree on computer/computing engineering to work in something that has little to nothing to do with engineering at all.

I am still a little hesitating upon geophysics or bioinformatics, both of them are amazing fields, but I must take into account the local academic environment and establishment of one and other at my university. The geophysics MSc. is a well established programme and it holds a very good critical mass of geophysicits - in addition, they make big engineering projects (sincerely, those guys are much closer to big engineering than the engineers themselves here).

The bioinformatics MSc. is just in its beginning and, to be honest, I dislike some engineering professors involved in it (for example, once, one of those professors, during a professor meeting, ordered another one to shut his mouth, because the other guy did not have any projects that would bring money to the department, then he could not say his opinion. Veeeeery democratic, isn't it?).

I am aware that I should not "complain" about those engineering professors, but just being completely blind not to see they have little interest in building a local excellence, what the guys from geophysics have already made, and, in my humble opinion, those professors only want to get the money coming from government agencies sponsoring biotech academic projects - it is a new fad happening in Brazil's universities. The professors from the biological sciences center have big bioinformatics ambitions, even telling us that we should seek some way to start up a bioinformatics business of our own. However, when looking at the local bioinformatics business opportunities, we feel anything but unmotivated. The bioscience guys have contributed on interesting genome endevour, such as the gene sequencing of Xylella fastidiosa. I am still thinking if I get into the bioinformatics grad school or not.

One of the key factors that leads me toward geophysics is the fact that in Brazil there are big oil/petroleum companies, such as Petrobras. Bioinformatics is still an activity being mainly sponsored by the Federal Brazilian Government (EMBRAPA, MCT, etc.) and its private ventures are very few. Sure, while it may seem a fruitless bioinformatics field for someone, it could be, by the other hand, a business opportunity before the eyes of another person, a chance to start a business from scratch - I am well aware of those two facets. The main consideration living in my mind these days is that I must make a choice and this choice will affect, likely, my whole life. So, I need to do a sensible choice, what is not easy. There are so many stuffs to ponder.

Early this year, I went to visit the geosciences center and the professor which accepted to be my advisor, as long as I apply for geophysics, treated me in a very very good manner. I liked the way we talked to each other, I felt as though I was his friend since a long time. He invited me to enter his office, to take a sit, and explain my situation. He heard everything, taking heed of each word I said. Few engineering professors treated me like he did.

On the other hand, when visiting the guys responsible for the bioinformatics MSc. programme, I felt like a a being from another planet. The woman who talked to me, told me very inaccurate informations concerning the bioinfo grad programme. Being honest, I disliked the way we interacted. A little more and she would be treading the grounds of impoliteness. I did not get a nice first impression of it.

I feel that I will end up applying for geophysics. BUT, let's see what will happen in the near future and see what field will receive the laurels of evolutionary computation...


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Personal Observations Upon Brazilian Public Service Admission Exams:

It's interesting how lawyers are well paid in Brazilian public services. Often, their salary range from US$ 3000.00 to US$ 6500.00 per month! At Petrobras - one of the most well-paying Brazilian corporations -, an engineer holding just a BA. degree can earn US$ 2150.00 per month! The funniest stuff is that an engineer can agregate knowledge and innovation to a given product, what helps to increase the product's value, while a public service lawyer is only eating away the contributors' money and, at least when it comes to Brazil, they do not deliver a good job, since their profession at service public level is full of corruption, bribery, lobby, ill will, and etc. Of course, there are very good lawyers in Brazil, but the majority is working for the private sector.

That's Brazil!

P.S: I wonder what an American entrepreneur and/or American venture would think about devoting one's life to eat away the contributors money instead of start a new business. My bet: A waste of time and, sure, money! :)

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Auf Wiedersehen!

Hi, Friends! :)

So, the Genetic Argonaut blog will soon enter some kind of "stagnation" (but not in a local optimum, since this blog has self-adaptation mechanisms!), because I am planning to begin my final project at university, something that has to do with neural networks. Then, the update of this blog will be sporadically, but not so "frequent" as it has been so far.

However, after some months I will be back again! Just wait!

Auf Wiedersehen!

Marcelo