The development and new possibilities that artificial intelligence offers us every day never cease to surprise us. Among the most relevant today for Gray matter We can highlight the creation of algorithms capable of tracking neuroimages and genetic and physiological data of numerous individuals from which to extract biological markers capable of correctly predicting the course of neurological and mental diseases. like Alzheimer's. Without a doubt, it is something that can help conceive or perfect treatments to combat neurodegeneration or its progress.
A different type of this development is the already very popular ChatGPT (Chat Generative Pre-trained Transformer), a large computer consulting room that we can access today for free to ask for things that were previously unthinkable, such as writing a report on a legal case, asking us write a journalistic article on a certain topic or solve a complex problem, even of an emotional nature, providing a variety of solutions. Since I am allergic to pollen, I just asked my ChatGPT where I should go on vacation to avoid suffering from that allergy and his answer is absolutely correct.
But, as is often the case with important advances in science, artificial intelligence is not exempt from criticism. In the particular case of ChatGPT, which already has more than one hundred million users around the world, its creator, the company OpenAI, receives criticism ranging from the copying of information on the Internet and its statistical rather than cognitive treatment to the invention of data or facts and also to malicious uses of technology, which, in turn, immerses ChatGPT in the moral conflict that great scientific and technological advances almost always provoke.
New, more powerful versions of the gadgets developed so far (for example, a ChatGPT-turbo), are in the making, so it would seem that artificial intelligence is called to replace or even surpass many human activities, including, especially, those related to ingenuity and creativity. Its possibilities today are as extraordinary as they are unpredictable and continue to challenge the biological and inherent possibilities of its creator, who is none other than the human brain.
This challenge leads us to the question of this article and to consider, likewise, that everything that involves developing simulations of the functioning of the brain can also be a way of knowing more and better about it. But, to begin with, we encounter the obstacle that we still do not know all the functional secrets of the human brain, an organ that contains the impressive number of 85,000 million neurons interconnected in a very complex way by some 1,014 synapses, so intelligence artificial intelligence, its algorithms and learning programs (machine learning) will always be trying to reproduce or simulate something that we only know to a limited extent.
It is true that we are now in possession of and can learn much from the abundance of anatomical, physiological and genetic data, as well as the structural connectome of the human brain, i.e. the way your neurons connect. But, even if we were able to simulate all this data in a complex artificial intelligence program we could still be far from guaranteeing a true reproduction of what the human brain does or can do.
This is why Viren Jain, a Californian specialist in computing and cognitive science, a leader in the study of brain connectivity, that is, the connection between neurons, considers a recent article in Nature Whether, indeed, a learning machine can be used to build models that simulate the activity of brains, or whether we can train artificial intelligence programs on connectomes and other data to reproduce the same activity of neurons that we would expect to find in biological systems, or also if a system like the human brain can be understood when mathematics or a computer apparently reproduces its behavior.
Viren Jain also believes that, although the main problem faced by multiple studies such as the already abandoned European Human Brain Project Despite the limited knowledge of detailed anatomical and functional maps of the brain, it remains very difficult to assess to what extent artificially developed simulation systems could accurately capture what happens in biological systems. An added problem would be the way in which an artificial intelligent device would have to be expressed in order for us to consider it accurately comparable to the human brain.
On the other hand, it is not even clear that we will be able to artificially construct something as complex as the human brain, an organ also endowed with emerging functional capacities, such as phenomenological consciousness, the nature of which we still do not know. The hypothesis of functional integration of scientists such as Giulio Tononi or Christof Koch It assumes that consciousness arises spontaneously from complex systems such as the human brain, that is, that it comes to us, so to speak, as standard at birth. This means that, if artificial intelligence were one day capable of building a system as complex as our brain, its superior emergent capabilities could also arise spontaneously from that system, even if we still do not understand its true nature, that is, the way in which made possible.
The topic, surely, will not fail to raise the exciting and centuries-old debate of whether the intelligence of an artificial system could equal, let alone surpass, that of its own creator. Today, it does not seem possible.
Gray matter It is a space that tries to explain, in an accessible way, how the brain creates the mind and controls behavior. The senses, motivations and feelings, sleep, learning and memory, language and consciousness, as well as their main disorders, will be analyzed in the conviction that knowing how they work is equivalent to knowing ourselves better and increasing our well-being and relationships with other people.
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