Symbiotic Machines - Technology III- Analysing Data to Extract Meaning // EIT Digital

Symbiotic Machines - Technology III- Analysing Data to Extract Meaning

An X-ray CT scan of the head of one of the volunteers, showing electrodes distributed over the brain’s temporal lobe, where sounds are processed. Decoding the electrical signals flowing in the brain to make meaning emerge is still elusive, although some progress has been made. Credit: Adeen Flinker, UC Berkeley

Although we often don’t think about it, a major part of our communication is based on the understanding of the context and in sophisticated analyses of the intention of the person initiating the communication or responding to it.

Our brain is “cabled” to look for meaning, in spite of the quality of the communication itself. For what I consider as an “illuminating” examples look at the sentence:

"Aoccdrnig to a rscheearch at Cmabrigde Uinervtisy, it deosn't mttaer in waht oredr the ltteers in a wrod are, the olny iprmoatnt tihng is taht the frist and lsat ltteers be at the rghit pclae. The rset can be a toatl mses and you can sitll raed it wouthit porbelm. Tihs is bcuseae the huamn mnid deos not raed ervey lteter by istlef, but the wrod as a wlohe."

A symbiotic life requires the understanding of the meaning of the communications, which in turns requires an understanding of the “why” the communication takes place and the expected outcome of it.

Think about the question: “Do you have a pen?”. Its actual meaning is not that you are eager to know if your friend has a pen, rather if he can lend one to you right now and you are actually needing a pen now, so an answer like: “I think there is one in that drawer” is a perfect answer to your question, whilst an answer like “Yes I have one” followed by your friend turning and going away without giving you the pen is not a satisfactory answer, although it is an appropriate one from a grammatical point of view.

Bacterias are living a symbiotic life with viruses and with us, our body has many more bacterial and viruses that our own cells, and we can live thanks to this symbioses. Now one can say that there is no meaning, nor understanding, nor finality in the communications taking place (at a chemical level) among our cells and our symbiotic bacteria, however that is not the case. 

The meaning and the goal of the communications have been ingrained in the context through millions of years of natural selection, that got rid of all inappropriate communications.  The problem we are facing in our innovation path, here in Symbiotic Machines as in any other areas is the pace of evolution and the fact that we do not want to accept failures as a way of progress (or at least reduce failure in numbers and effect to a minimum!).

The flood of data that is characterizing the new century has prompted action from researchers all over the world, with strong investment and back up from industry and it is now resulting in a leap in artificial intelligence, with new approaches to data analytics that leverage on the huge mass of data available.  Deep learning, data visualization, Emerging meaning are just a few tools applied in data analyses and more will become available in the coming years characterizing the next decade as one based on data rather than on atoms. The IEEE Big Data Initiative is part of this effort and can contribute to the area of Symbiotic Machines.

 

Author - Roberto Saracco

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