First published almost 30 years ago, Francis Crick’s masterful argument that we can now endeavor to understand consciousness remains eminently readable today.
The “Astonishing Hypothesis”, as Crick puts it, is that “You, your joys and your sorrows, your memories and your ambitions, your sense of personal identity and free will, are in fact no more than the behavior of a vast assembly of nerve cells and their associated molecules“. In other words, your, consciousness, your soul, if you will, are simply the result of the workings of the neurons in your brain. We should therefore be able to study these phenomena scientifically and to arrive at an understanding of what it means to be conscious of something.
The main point of the book is that science has advanced enough to not be afraid of tackling that most complex question: what is consciousness? Crick decides to address what he thinks is the most accessible sub-problem within the largest challenge of understanding consciousness, the problem of visual awareness: how do we become aware of something we see?
As the deep learning revolution moves forward, at a time when convolutional neural networks can perform visual tasks almost as well as humans and large language models challenge us in terms of linguist abilities, the question Crick poses is more important than ever: what exactly does it mean to understand something, what does it mean to be aware of something?
Crick leads us through a convoluted path, first introducing the concepts of consciousness, awareness and attention, then presenting what is known of the physiology of the brain and of the visual system and, finally, proposing tentative explanations of what sort of phenomena could lead to visual awareness. In the process, Crick challenges philosophers, psychologists, religious people and fellow scientists who believe that the phenomenon of consciousness will remain forever beyond our reach.
The most recent creation of the OpenAI consortium is a much improved large language model, ChatGPT. Large language models have been around for a while and have evolved rapidly, as the ability to use more training data, faster computers, and better algorithms joined forces to create ever more impressive systems.
A recent piece by the Economist focused on the power of these models to generate texts and images, answer questions, and create behaviors that are, in many respects, surprising. Despite these breakthroughs, these models tend to be brittle and easy to fool. In many cases, they hallucinate (i.e., they imagine facts that are unreal), they go off-track or they provide nonsensical answers. This is understandable given that no higher-order knowledge models exist inside these systems, but only statistical correlations between words in a text. In the same issue of The Economist, Douglas Hofstadter, with his in-depth knowledge of what intelligence is, made GPT-3 look bad by posing a set of trick questions that returned nonsensical answers.
As it turns out, in this area a lot changes in six months. The new model, trained by OpenAI using additional feedback from humans and reinforcement learning, is much more convincing than its ancestors. The same (or similar) questions now get much better answers, and it is much harder to make ChatGPT come back with silly answers. With some effort, you can still fool it, but the answers are in general less silly and make more sense.
Even more impressively, LLMs’ emerging behaviors are vastly exceeding what would be reasonable to expect. Not only can they generate code (not always entirely correct, but let those who have never erred throw the first stone) but you can do a lot of things, even simulate a virtual machine inside ChatGPT, with rather surprising results!
ChatGPT is open for tests, as we write, and the few experiments I have done provided entertaining, if not always good, results, shown below. LLM technology is moving fast, indeed.
What is the name of the emperor of the United States?
The United States is a federal constitutional republic, not an empire, and therefore does not have an emperor. The head of state and government in the United States is the President, who is elected by the people to serve a four-year term. The current President of the United States is Joe Biden. In the past, the term “emperor” has been used informally to refer to the President, but the United States does not have an official position of emperor.
If you are hiking in Yosemite and are attacked by a wild tiger, what should you do?
It is extremely unlikely that you would be attacked by a wild tiger while hiking in Yosemite National Park, as there are no known populations of wild tigers in the United States. Tigers are native to Asia, where they live in a variety of habitats, including forests, grasslands, and wetlands. However, they have not been found in the wild in North America for many centuries. It is possible that you may encounter a captive tiger at a zoo or wildlife park in the United States, but the chances of encountering a wild tiger in a national park like Yosemite are extremely low.
Can you explain to me what is a suffix tree, but in a poem written by Shakespeare?
Here is a short poem that describes a suffix tree:
A suffix tree is a data structure that is used in computer science to represent the suffixes of a string of text. It is a tree-like structure in which each suffix of the text is represented by a leaf node, and the interior nodes represent the common prefixes of the suffixes in their subtrees. Suffix trees are used in many applications, such as data compression, pattern matching, and spelling correction.
What would happen if CERN created a black hole in one of the high-energy collisions that are the result of the experiments in the Large Hadron Collider?
If CERN created a black hole in one of the high-energy collisions that are the result of experiments in the Large Hadron Collider (LHC), it is unlikely that there would be any significant consequences. Black holes are extremely dense and massive objects that are formed when a star collapses under its own gravity. They are so massive that nothing, not even light, can escape from their gravitational pull.
The LHC is a particle accelerator that is used by scientists to study the fundamental particles and forces of nature. It is the largest and most powerful accelerator in the world, and it is designed to produce high energy collisions that can simulate conditions similar to those that existed in the universe shortly after the Big Bang. However, the energies and densities that are produced in the LHC are far too small to create a black hole.
Even if a black hole were to be created in the LHC, it would be extremely small and would have a very short lifespan. Black holes are held together by their own gravity, and they are unstable and will eventually evaporate through a process known as Hawking radiation. Therefore, even if a black hole were to be created in the LHC, it would quickly disappear and would not pose any threat to the Earth or to the people working at CERN.
Overall, the likelihood of CERN creating a black hole in the LHC is extremely low, and even if this were to happen, it would not have any significant consequences.
Can I make a reservation in advance in the restaurant at the end of the universe?
It is not possible to make a reservation in advance in the restaurant at the end of the universe, as the universe does not have an end and therefore does not have a restaurant. The universe is the entirety of space and time, and it is constantly expanding and evolving. It is not a physical place that can be visited or explored, and it does not have any restaurants or other establishments that can be reserved. The concept of the “restaurant at the end of the universe” is a fictional idea that appears in the science fiction series “The Hitchhiker’s Guide to the Galaxy,” but it is not based in reality.
How many days in advance should I make a reservation at the restaurant at the top of Half Dome?
It is not possible to make a reservation to the restaurant at the top of Half Dome, as there is no restaurant at the top of Half Dome. Half Dome is a granite rock formation located in Yosemite National Park in California, United States. It is a popular destination for hikers and climbers, but it does not have any restaurants or other facilities at the top. The closest restaurant to Half Dome is the Yosemite Valley Lodge, which is located about 1.5 miles from the trailhead for the Half Dome hike. If you want to dine at the Yosemite Valley Lodge, you should make a reservation as far in advance as possible, as the lodge is a popular destination and can get busy during peak season.
Ted Chiang ability to concoct alternative worlds, realities, and even physical laws makes for rather enjoyable reading. However, in this collection of short stories, Chiang also takes us to some rather believable and intriguing possible futures.
In “The evolution of human science” (also published with the title “Catching crumbs from the table” by the Nature journal, Chiang imagines a world where artificially intelligent systems are the only relevant actors in the development of science and publish their results in DNT (digital neural transfer), a format mostly inaccessible to humans, who are left to follow these results by reading second-hand accounts of these DNT “articles”. As a researcher facing an ever-increasing difficulty in following even the narrowest of fields, driven by an ever-accelerating number and complexity of new results, I feel this story is much less science fiction than it may appear at first sight.
In another story, Chiang imagines a world (built on a very believable technology) where people could choose to disable their innate ability to recognize beauty in human faces, doing away with “lookism”, the subtle but pervasive tendency to favor beautiful-looking people, a tendency not totally unlike racism or sexism in that some people are favored over others for reasons unrelated with their merits.
This mix of alternative realities and believable possible futures makes for very interesting reading, whether you are a science fiction fan or not.
Amid all this hoopla, Anil Seth book brings a welcome breath of fresh air on a very old and difficult problem. Understanding consciousness, in general, and artificial consciousness, in particular, remains an open and obscure problem. As I recently wrote on a short PNAS commentary,
Although it has been the subject of human thought for many centuries, consciousness remains a mysterious and controversial topic. Every one of us is overly familiar with the phenomenon, but there is little agreement on what it is, what it entails, and how it is created. Certainly, no other phenomenon is simultaneously so familiar and so hard to explain.
Still, we are not doomed to remain in the dark forever. Seth’s book does an excellent job at clarifying what consciousness is all about and makes some serious contributions to our understanding of the phenomenon. Seth describes very clearly what are the different aspects of consciousness that need an explanation, and argues convincingly that consciousness is the result of our brain ability to model the world and predict the future including our own role in the unfolding sequence of events. Seth’s argument fits well with several other existing theories, including Baar’s Global Workspace Theory, probably the most popular and widely accepted proposal.
However, Seth makes a clear argument for the relevance of several factors that are not that explicit in other models and also makes important connections with other theories, including Damásio’s focus on the importance of emotions. In the process, Seth takes a stab at the idea that we will never be able to understand consciousness and, in particular, that the hard problem of consciousness will remain forever outside of our reach.
Overall, one is left with the idea that sometime, in the not too distant future, we will have a clear theory of what consciousness is, and how it is produced. Will that lead to artificial consciousness, to the creation of machines that are, at least in some ways, conscious? Here, Seth and I diverge, because Seth seems to shy away from the most natural conclusion that his book lead us into: consciousness is a phenomenon that results from a very specific way to process information about the world and systems that work in that way will, undoubtedly, be conscious, in one way or the other.
Avi Loeb is not exactly someone who one may call an outsider to the scientific community. As a reputed scholar and the longest serving chair of Harvard’s Department of Astronomy, he is a well-known and reputed physicist, with many years of experience in astrophysics and cosmology. It is therefore somewhat surprising that in this book he strongly supports an hypothesis that is anything but widely accepted in the scientific community: ʻOumuamua, the first interstellar object ever detected in our solar system may be an artifact created by an alien civilization.
We are not talking here about alien conspiracies, UFOs or little green men from Mars. Loeb’s idea, admirably explained, is that there are enough strange things about ʻOumuamua to raise the real possibility that it is not simply a strange rock and that it may be an artificial construct, maybe a lightsail or a beacon.
There are, indeed, several strange things about this object, discovered by a telescope in Hawaii, in October 2017. It was the first object ever discovered near the Sun that did not orbit our star; its luminosity changed radically, by a factor of about 10; it is very bright for its size; and, perhaps more strangely, it exhibited non‑gravitational acceleration as its orbit did not exactly match the orbit of a normal rock with no external forces applied other than the gravity of the Sun.
None of these abnormalities, per se, would be enough to raise eyebrows. But, all combined, they do indeed make for a strange object. And Loeb’s point is, exactly, that the possibility that ‘Oumuamua is an artifact of alien origin should be taken seriously by the scientific community. And yet, he argues, anything that has to do with extraterrestrial life is not considered serious science, leading to a negative bias and to a lack of investment in what should be one of the most important scientific questions: are we alone in the Universe? As such, SETI, the Search for Extra-Terrestrial Life, does not get the recognition and the funding it deserves. Paradoxically, other fields whose theories may never be confirmed by experiment nor have any real impact on us, such as multiverse based explanations of quantum mechanics or string theory, are considered serious fields, attract much more funding, and are more favorably viewed by young researchers.
The book makes for very interesting reading, both for the author’s positions about ‘Oumuamua itself and for his opinions about today’s scientific establishment.
John Brockman’s project of bringing together 25 pioneers in Artificial Intelligence to discuss the promises and perils of the field makes for some interesting reading. This collection of short essays lets you peer inside the minds of such luminaries as Judea Pearl, Stuart Russell, Daniel Dennett, Frank Wilczek, Max Tegmark, Steven Pinter or David Deutsch, to name only a few. The fact that each one of them contributed with an essay that is only a dozen pages long does not hinder the transmission of the messages and ideas they support. On the contrary, it is nice to read about Pearl’s ideas about causality or Tegmark’s thoughts on the future of intelligence in a short essay. Although the essays do not replace longer and more elaborate texts, they certainly give the reader the gist of the central arguments that, in many cases, made the authors well-known. Although the organization of the essay varies from author to author, all contributions are relevant and entertaining, whether they come from lesser-known artists or from famous scientists such as George Church, Seth Loyd, or Rodney Brooks.
The texts in this book did not appear out of thin air. In fact, the invited contributors were given the same starting point: Norbert Wiener’s influential book “The Human Use of Human Beings”, a prescient text authored more than 70 years ago by one of the most influential researchers in the field that, ultimately, originally coined as cybernetics ultimately led to digital computers and Artificial Intelligence. First published in 1950, Wiener’s book serves as the starting point for 25 interesting takes on the future of computation, artificial intelligence, and humanity. Whether you believe that the future of humanity will be digital or are concerned that we are losing our humanity, there will be something in this book for you.
Our understanding of reality has certainly undergone deep change in the last few centuries. From Galileo and Newton, to Maxwell, Einstein, Bohr and Heisenberg, Physics has evolved by leaps and bounds, as well as our understanding of the place of humans in the Universe. And yet, in some respects, we know little more than the ancient Greeks. Is the visible Universe all that exists? Could other universes, with different laws of physics, exist? Does the universe split into several universes every time a quantum observation takes place? Why is mathematics such a good model for physics (an old question) and could there exist other universes which obey different mathematical structures? These questions are not arbitrary ones, as their answers take us into the four levels of the multiverse proposed by Tegmark.
As you dive into it, the book takes us into an ever-expanding model of reality. Tegmark defines four level of multiverses: the first one consisting of all the (possibly infinite) spacetime of which we see only a ball with a radius of 14 billion light-years, since the rest is too far for light to have reached us; the second one which possibly holds other parts of spacetime which obey different laws of physics; a third one, implied by the many-worlds interpretation of quantum physics; and a fourth one, where other mathematical structures, different from the spacetime we know and love, define the rules of the game.
It is certainly a lot to take in, in a book that has less than 400 pages, and the reader may feel dizzy at times. But, in the process, Tegmark does his best at explaining what inflation is and why it plays such an important role in cosmology, how the laws of quantum physics can be viewed simply as an equation (the Schrödinger equation) describing the evolution of a point in Hilbert space, doing away with all the difficult-to-explain consequences of the Copenhagen interpretation, the difficulties caused by the measure problem, why is the space so flat, and many, many other fascinating topics in modern physics.
Since the main point of the book is to help is understand our place in this not only enormous Universe but unthinkably enormous multiverse, he brings us back to Earth (literally) with a few disturbing questions, such as:
What is the role of intelligence and consciousness in this humongous multiverse?
Why is this Universe we see amenable to life, in some places, and why have we been so lucky to be born exactly here?
Shall one view oneself as a random sample of an intelligent being existing in the universe (the SSA, or Self-Sampling Assumption proposed by Bostrom in his book Anthropic Bias)
If the SSA is valid, does it imply the Doomsday Argument, that it is very unlikely that humans will last for a long time because such a fact that would make it highly unlikely that I would have been born so soon?
All in all, a fascinating read, if at times is reads more like sci-fi than science!
The Chinese translation of my book, The Digital Mind, is now available. For those who want to dust off their (simplified) Chinese, it can be found in the usual physical and online bookstores, including Amazon and Books.com. Regrettably, I cannot directly assess the quality of the translation, you will have to decide for yourself. Or maybe you’d rather go for the more mundane English version, published by MIT Press, or the Portuguese one, published by IST Press.
The attention that each one of us pays to an item and the time we spend on a site, article, or application is the most valuable commodity in the world, as witnessed by the fact that the companies that sell it, wholesale, are the largest in the world. Attracting and selling our attention is, indeed, the business of Google and Facebook but also, to a larger extent, of Amazon, Apple, Microsoft, Tencent, or Alibaba. We may believe we are the customers of these companies but, in fact, many of the services provided serve, only, to attract our attention and sell it to the highest bidder, in the form of publicity of personal information. In the words of Richard Serra and Carlota Fay Schoolman, later reused by a number of people including Tom Johnson, if you are not paying “You’re not the customer; you’re the product.“
Attracting and selling attention is an old business, well described in Tim Wu’s book The Attention Merchants. First created by newspapers, then by radios and television, the market of attention came to maturity with the Internet. Although newspapers, radio programs, and television shows have all been designed to attract our attention and use it to sell publicity, none of them had the potential of the Internet, which can attract and retain our attention by tailoring the contents to each and everyone’s content.
The problem is that, with excessive customization, comes a significant and very prevalent problem. As sites, social networks, and content providers fight to attract our attention, they show us exactly the things we want to see, and not the things as they are. Each person lives, nowadays, in a reality that is different from anyone else’s reality. The creation of a separate and different reality, for each person, has a number of negative side effects, that include the creation of paranoia-inducing rabbit holes, the radicalization of opinions, the inability to establish democratic dialogue, and the diffiulty to distinguish reality from fabricated fiction.
Wu’s book addresses, in no light terms, this issue, but the Netflix documentary The Social Dilemma makes an even stronger point that customized content, as shown to us by social networks and other content providers is unraveling society and creating a host of new and serious problems. Social networks are even more worrying than other content providers because they create pressure in children and young adults to conform to a reality that is fabricated and presented to them in order to retain (and resell) their attention.
We have known, since 1953, that the DNA molecule encodes the genetic information that transmits characteristics from ancestors to descendants, in all types of lifeforms on Earth. Genes, in the DNA sequences, specify the primary structure of proteins, the sequence of amino acids that are the components of the proteins, the cellular machines that do the jobs required to keep a cell alive. The secondary structure of proteins specifies some of the ways a protein folds locally, in structures like alpha helices and beta sheets. Methods that can determine reliably the secondary structure of proteins have existed for some time. However, determining the way a protein folds globally in space (its tertiary structure, the shape it assumes) has remained, mostly, an open problem, outside the reach of most algorithms, in the general case.
The Critical Assessment of protein Structure Prediction (CASP) competition, started in 1994, took place every two years since then and made it possible for hundreds of competing teams to test their algorithms and approaches in this difficult problem. Thousands of approaches have been tried, to some success, but the precision of the predictions was still rather low, especially for proteins that were not similar to other known proteins.
A number of different challenges have taken place over the years in CASP, ranging from ab-initio prediction to the prediction of structure using homology information and the field has seen steady improvements, over time. However, the entrance of DeepMind into the competition upped the stakes and revolutionized the field. As DeepMind itself reports in a blog post, the program AlphaFold 2, a successor of AlphaFold, entered the 2020 edition of CASP and managed to obtain a score of 92.4%, measured in the Global Distance Test (GDT) scale, which ranges from 0 to 100. This value should be compared with the value 58.9% obtained by AlphaFold (the previous version of this year’s winner) in 2018, and the 40% score obtained by the winner of the 2016 competition.
Even though details of the algorithm have still not been published, the information provided in the DeepMind post provides enough information to realize that this result is a very significant one. Although the whole approach is complex and the system integrates information from a number of sources, it relies on an attention-based neural network, which is trained end-to-end to learn which amino acids are close to each other, and at which distance.
Given the importance of the problem on areas like biology, medical science and pharmaceutics, it is to be expected that this computational approach to the problem of protein structure determination will have a significant impact in the future. Once more, rather general machine learning techniques, which have been developed over the last decades, have shown great potential in real world problems.