A very interesting new book by Nick Bostrom, Superintelligence, addresses the questions that will be raised by the appearance of Artificial Intelligence (AI) Systems that are vastly smarter than humans.
So far, researchers have concentrated their efforts on the development of artificial intelligence systems that are as intelligent as humans, the so called strong AI. This is a tall order and it may yet take many years until we reach that point.
However, as Nick Bostrom points out in this book, there is no reason to believe that, once developed, strong AI systems would remain approximately as intelligent as humans. Once an AI system with human-level intelligence comes into existence, it will certainly be able to improve itself rapidly past that level.
As Irving John Good, a statistician that worked with Alan Turing at Bletchley Park, pointed out, a smarter than human machine is probably the last invention man will ever need to create. After that, such a machine can invent all sorts of new technologies, including the ones related with AI.
Nick Bostrom describes in a very clear and convincing way how a superintelligence may develop out of research in AI and neurosciences, using a number of different paths that may include whole brain emulation, strong artificial intelligence or highly connected communities of human brains.
A recent article in Venture Beat points out that top management jobs, up to the level of CEO, may soon be taken over by robots.
There has been an ongoing discussion about which jobs are safer from being taken over by computers. Many candidates have been put forward, like lawyer, doctor, manager or driver. The fast developments of Artificial Intelligence have made these predictions look ridiculous, usually just a few years after their are issued.
The fact of the matter is that we have no idea which jobs will be safer from being taken over by computers.
Relevant to the case in point, what do CEOs do? According to Venture Beat, they ” allocate resources, build the culture, oversee and deliver the company’s performance, be the face of the company, and juggle with everyday compromises. For most CEOs, developing objective, data-driven decisions is advantageous for the success of the company.”
Clearly, many of these tasks require analytical minds and data analysis capabilities which are, by now, more likely to be mastered by artificially intelligent agents than by humans.
It seems to be safe to say that more creative jobs will be safer, for a longer time, from being done by computers. The difficulty lies in defining what, exactly, is creativity. And, once that is done, computers will be able to have it, too…
The news comes from IEEE, the normally subdued and reliable Institute of Electrical and Electronics Engineers, and not from the National Enquirer or The Globe!
In the future, humans may find it more satisfying to enter into long-term romantic relationships with robots than with other humans.
According to Senior IEEE Member Kevin Curran, robots can be expected “to never nag, to always respond positively, focus on what you want to talk about, be responsive to your moods, and ultimately act as the perfect partner.”
Movies like Ex Machina or Her have explored this situation that, for most of us, looks far-fetched and unbelievable. Still, it is true that human-like feelings can be very easily attributed to intelligent systems that are programmed to reply in the right way, as the emotional attachment some owners feel for their Rumba vacuum cleaners.
Image courtesy of IEEE.
Woody Allen’s famous quote on immortality “I don’t want to achieve immortality through my work; I want to achieve immortality through not dying. I don’t want to live on in the hearts of my countrymen; I want to live on in my apartment.” has a different meaning for Dmitry Itskov. He aims to achieve immortality both through his work and through not dying.
Dmitry Itskov is a Russian entrepreneur and billionaire, best known for creating the 2045 initiative, which aims to achieve cybernetic immortality by the year 2045.
Cited in a recent BBC article, Dmitry Itskov promises that “Within the next 30 years, I am going to make sure that we can all live forever.”
The idea sounds preposterous, but there is no doubt he is not deranged and is serious about it. It is indeed a breathtaking ambition, to achieve mind uploading by the year 2045, but could it actually be done?
The scientific director of the 2045 initiative, Randal Koene, a neuroscientist, who has done work on diverse aspects of brain modeling, believes the task is extremely difficult but not impossible, at least in theory. In a number of videos and presentations available in YouTube, he explains how existing technologies could be used, in principle, to reach this goal.
The question remains: will it ever become possible and, if so, when?
Image by Nevit Dilmen, via Wikimedia Commons
Go-playing program AlphaGo, developed by Google’s DeepMind, has secured victory against 18-time world champion Lee Sedol. AlphaGo won the first three games of a five game match played in Seoul, thus securing the match.
Gordon Moore, scientist and chairman of Intel, first noticed that the number of transistors that can be placed inexpensively on an integrated circuit increased exponentially over time, doubling approximately every two years. This corresponds to an exponential increase on the number of transistors per chip that led to an increase by a factor of more than 1,000,000 in 40 years. Moore’s law has fueled the enormous developments in computer technology that have revolutionized technology and society in the last decades.
A long standing question is for how long will Moore’s law hold, since no exponential growth can last forever. The Technology Quarterly section of this week edition of the Economist, summarized in this short article, analyzes this question in depth.
The conclusions are that, while the rate of increase of the number of transistors in a chip will become smaller and smaller, advances in other technologies, such as software and cloud computing, will cover the slack, providing us with increases in computational power that will not deviate much from what Moore’s law would have predicted.
Image of computer scientist and businessman Gordon Moore. The image is a screenshot from the Scientists You Must Know video, created by the Chemical Heritage Foundation, in which he briefly discusses Moore’s Law
AlphaGo, the Go playing program developed by Google’s DeepMind, scored its first victory in the match against Lee Sedol.
This win comes in the heels of AlphaGo victory over Fan Hui, the reigning 3-times European Champion, but it has a deeper meaning, since Lee Sedol is one of the two top Go players in the world, together with Lee Changho. Go is viewed as one of the more difficult games to be mastered by computer, given the high branching factor and the inherent difficulty of position evaluation. It has been believed that computers would not master this game for many decades to come.
Ongoing coverage of the match is available in the AlphaGo website and the matches will be livestreamed on DeepMind’s YouTube channel.
AlphaGo used deep neural networks trained by a combination of supervised learning from professional games and reinforcement learning from games it played with itself. Two different networks are used, one to evaluate board positions and another one to select moves. These networks are then used inside a special purpose search algorithm.
The image shows the final position in the game, courtesy of Google’s DeepMind.
A new book by Pedro Domingos, The Master Algorithm, describes how machine learning algorithms will become more and more essential in the development of technology. Machine learning techniques already enable many systems to behave intelligently, and are at the source of many fascinating new developments, including self-driving cars, speech recognition, automated trading systems, intelligent digital assistants, like Siri or Cortana, and many, many, other technologies.
Mastering machine learning is essential to anyone interested in the development of digital technologies, and this book represents the ideal stepping stone towards more technical works.
Domingos provides an excellent, non-technical, introduction to this essential area, describing what he calls the five tribes of machine learning: the symbolists, the connectionists, the evolutionaries, the Bayesians, and the analogizers. He argues that the algorithms of each of these tribes can, and will one day, be combined into one master algorithm, the mother of all learning algorithms.
There are many excellent reviews and pieces on the book, including GoodReads, Times Higher Education and KDNuggets. Now available at Amazon, your corner bookstore or at a FNAC near you.
Recent news about OpenWorm, a project that aims at recreating in a computer the behaviour of a complete animal, the roundworm Caenorhabditis elegans. The OpenWorm project aims at constructing a complete model of this worm, not only of the 302 neurons and the 95 muscle cells, but also of the remaining thousand cells in each worm (more exactly, 959 somatic cell plus about 2000 germ cells in the hermaphrodite sex and 1031 cells in the males).
The one millimeter long worm C. elegans has a long history in science, as one of the animals more extensively used as a model for the study of simple multicellular organisms. It was the first animal to have its genome sequenced, in 1998.
But well before that, in 1963, Sydney Brenner proposed it as a model organism for the investigation of neural development in animals. In an effort that lasted for more than twelve years, the complete structure of the brain of C. elegans was reverse engineered, leading to a diagram of the wiring of each neuron in this simple brain. The effort of reverse engineering the worm brain included slicing, very thinly, several worm brains, obtaining roughly 8000 photos of the slices using an electron microscope and connecting, mostly by hand, each neuron section of each slice to the corresponding neuron section in the neighbor slices. The complete wiring diagram of the 302 neurons and the roughly 7000 synapses, which constitute the brain of this simple creature, was described in minute detail in a 340 pages article, published in 1986, entitled The Structure of the Nervous System of the Nematode Caenorhabditis elegans, with a running head The Mind of a Worm.
In 2008, IEEE Spectrum, the flagship publication of the Institute for Electrical and Electronic Engineers, the major professional association of this area, dedicated a full issue to the question of the singularity. This issue received an award for the best single oopic magazine issue of that year.
In this special report, which is as actual today as it was in 2008, a number of scientists, visionaries and engineers give their opinion on whether a singularity will or will not exist. The issue covers topics related with the singularity, such as robotics, consciousness and quantum phenomena and artificial intelligence. A must read for anyone interested in the topic, one of the best unbiased assessments of whether the singularity will or will exist.