Showing posts with label Ben Goertzel. Show all posts
Showing posts with label Ben Goertzel. Show all posts

AI - Technological Singularity

 




The emergence of technologies that could fundamentally change humans' role in society, challenge human epistemic agency and ontological status, and trigger unprecedented and unforeseen developments in all aspects of life, whether biological, social, cultural, or technological, is referred to as the Technological Singularity.

The Singularity of Technology is most often connected with artificial intelligence, particularly artificial general intelligence (AGI).

As a result, it's frequently depicted as an intelligence explosion that's pushing advancements in fields like biotechnology, nanotechnology, and information technologies, as well as inventing new innovations.

The Technological Singularity is sometimes referred to as the Singularity, however it should not be confused with a mathematical singularity, since it has only a passing similarity.

This singularity, on the other hand, is a loosely defined term that may be interpreted in a variety of ways, each highlighting distinct elements of the technological advances.

The thoughts and writings of John von Neumann (1903–1957), Irving John Good (1916–2009), and Vernor Vinge (1944–) are commonly connected with the Technological Singularity notion, which dates back to the second half of the twentieth century.

Several universities, as well as governmental and corporate research institutes, have financed current Technological Singularity research in order to better understand the future of technology and society.

Despite the fact that it is the topic of profound philosophical and technical arguments, the Technological Singularity remains a hypothesis, a guess, and a pretty open hypothetical idea.

While numerous scholars think that the Technological Singularity is unavoidable, the date of its occurrence is continuously pushed back.

Nonetheless, many studies agree that the issue is not whether or whether the Technological Singularity will occur, but rather when and how it will occur.

Ray Kurzweil proposed a more exact timeline for the emergence of the Technological Singularity in the mid-twentieth century.

Others have sought to give a date to this event, but there are no well-founded grounds in support of any such proposal.

Furthermore, without applicable measures or signs, mankind would have no way of knowing when the Technological Singularity has occurred.

The history of artificial intelligence's unmet promises exemplifies the dangers of attempting to predict the future of technology.

The themes of superintelligence, acceleration, and discontinuity are often used to describe the Technological Singularity.

The term "superintelligence" refers to a quantitative jump in artificial systems' cognitive abilities, putting them much beyond the capabilities of typical human cognition (as measured by standard IQ tests).

Superintelligence, on the other hand, may not be restricted to AI and computer technology.

Through genetic engineering, biological computing systems, or hybrid artificial–natural systems, it may manifest in human agents.

Superintelligence, according to some academics, has boundless intellectual capabilities.

The curvature of the time curve for the advent of certain key events is referred to as acceleration.

Stone tools, the pottery wheel, the steam engine, electricity, atomic power, computers, and the internet are all examples of technological advancement portrayed as a curve across time emphasizing the discovery of major innovations.

Moore's law, which is more precisely an observation that has been viewed as a law, represents the increase in computer capacity.

"Every two years, the number of transistors in a dense integrated circuit doubles," it says.

People think that the emergence of key technical advances and new technological and scientific paradigms will follow a super-exponential curve in the event of the Technological Singularity.

One prediction regarding the Technological Singularity, for example, is that superintelligent systems would be able to self-improve (and self-replicate) in previously unimaginable ways at an unprecedented pace, pushing the technological development curve far beyond what has ever been witnessed.

The Technological Singularity discontinuity is referred to as an event horizon, and it is similar to a physical idea linked with black holes.

The analogy to this physical phenomena, on the other hand, should be used with care rather than being used to credit the physical world's regularity and predictability to technological singularity.

The limit of our knowledge about physical occurrences beyond a specific point in time is defined by an event horizon (also known as a prediction horizon).

It signifies that there is no way of knowing what will happen beyond the event horizon.

The discontinuity or event horizon in the context of technological singularity suggests that the technologies that precipitate technological singularity would cause disruptive changes in all areas of human life, developments about which experts cannot even conjecture.

The end of humanity and the end of human civilization are often related with technological singularity.

According to some research, social order will collapse, people will cease to be major actors, and epistemic agency and primacy would be lost.

Humans, it seems, will not be required by superintelligent systems.

These systems will be able to self-replicate, develop, and build their own living places, and humans will be seen as either barriers or unimportant, outdated things, similar to how humans now consider lesser species.

One such situation is represented by Nick Bostrom's Paperclip Maximizer.

AI is included as a possible danger to humanity's existence in the Global Catastrophic Risks Survey, with a reasonably high likelihood of human extinction, placing it on par with global pandemics, nuclear war, and global nanotech catastrophes.

However, the AI-related apocalyptic scenario is not a foregone conclusion of the Technological Singularity.

In other more utopian scenarios, technology singularity would usher in a new period of endless bliss by opening up new opportunities for humanity's infinite expansion.

Another element of technological singularity that requires serious consideration is how the arrival of superintelligence may imply the emergence of superethical capabilities in an all-knowing ethical agent.

Nobody knows, however, what superethical abilities might entail.

The fundamental problem, however, is that superintelligent entities' higher intellectual abilities do not ensure a high degree of ethical probity, or even any level of ethical probity.

As a result, having a superintelligent machine with almost infinite (but not quite) capacities but no ethics seems to be dangerous to say the least.

A sizable number of scholars are skeptical about the development of the Technological Singularity, notably of superintelligence.

They rule out the possibility of developing artificial systems with superhuman cognitive abilities, either on philosophical or scientific grounds.

Some contend that while artificial intelligence is often at the heart of technological singularity claims, achieving human-level intelligence in artificial systems is impossible, and hence superintelligence, and thus the Technological Singularity, is a dream.

Such barriers, however, do not exclude the development of superhuman brains via the genetic modification of regular people, paving the door for transhumans, human-machine hybrids, and superhuman agents.

More scholars question the validity of the notion of the Technological Singularity, pointing out that such forecasts about future civilizations are based on speculation and guesswork.

Others argue that the promises of unrestrained technological advancement and limitless intellectual capacities made by the Technological Singularity legend are unfounded, since physical and informational processing resources are plainly limited in the cosmos, particularly on Earth.

Any promises of self-replicating, self-improving artificial agents capable of super-exponential technological advancement are false, since such systems will lack the creativity, will, and incentive to drive their own evolution.

Meanwhile, social opponents point out that superintelligence's boundless technological advancement would not alleviate issues like overpopulation, environmental degradation, poverty, and unparalleled inequality.

Indeed, the widespread unemployment projected as a consequence of AI-assisted mass automation of labor, barring significant segments of the population from contributing to society, would result in unparalleled social upheaval, delaying the development of new technologies.

As a result, rather than speeding up, political or societal pressures will stifle technological advancement.

While technological singularity cannot be ruled out on logical grounds, the technical hurdles that it faces, even if limited to those that can presently be determined, are considerable.

Nobody expects the technological singularity to happen with today's computers and other technology, but proponents of the concept consider these obstacles as "technical challenges to be overcome" rather than possible show-stoppers.

However, there is a large list of technological issues to be overcome, and Murray Shanahan's The Technological Singularity (2015) gives a fair overview of some of them.

There are also some significant nontechnical issues, such as the problem of superintelligent system training, the ontology of artificial or machine consciousness and self-aware artificial systems, the embodiment of artificial minds or vicarious embodiment processes, and the rights granted to superintelligent systems, as well as their role in society and any limitations placed on their actions, if this is even possible.

These issues are currently confined to the realms of technological and philosophical discussion.


~ Jai Krishna Ponnappan

Find Jai on Twitter | LinkedIn | Instagram


You may also want to read more about Artificial Intelligence here.



See also: 


Bostrom, Nick; de Garis, Hugo; Diamandis, Peter; Digital Immortality; Goertzel, Ben; Kurzweil, Ray; Moravec, Hans; Post-Scarcity, AI and; Superintelligence.


References And Further Reading


Bostrom, Nick. 2014. Superintelligence: Path, Dangers, Strategies. Oxford, UK: Oxford University Press.

Chalmers, David. 2010. “The Singularity: A Philosophical Analysis.” Journal of Consciousness Studies 17: 7–65.

Eden, Amnon H. 2016. The Singularity Controversy. Sapience Project. Technical Report STR 2016-1. January 2016.

Eden, Amnon H., Eric Steinhart, David Pearce, and James H. Moor. 2012. “Singularity Hypotheses: An Overview.” In Singularity Hypotheses: A Scientific and Philosophical Assessment, edited by Amnon H. Eden, James H. Moor, Johnny H. Søraker, and Eric Steinhart, 1–12. Heidelberg, Germany: Springer.

Good, I. J. 1966. “Speculations Concerning the First Ultraintelligent Machine.” Advances in Computers 6: 31–88.

Kurzweil, Ray. 2005. The Singularity Is Near: When Humans Transcend Biology. New York: Viking.

Sandberg, Anders, and Nick Bostrom. 2008. Global Catastrophic Risks Survey. Technical Report #2008/1. Oxford University, Future of Humanity Institute.

Shanahan, Murray. 2015. The Technological Singularity. Cambridge, MA: The MIT Press.

Ulam, Stanislaw. 1958. “Tribute to John von Neumann.” Bulletin of the American Mathematical Society 64, no. 3, pt. 2 (May): 1–49.

Vinge, Vernor. 1993. “The Coming Technological Singularity: How to Survive in the Post-Human Era.” In Vision 21: Interdisciplinary Science and Engineering in the Era of Cyberspace, 11–22. Cleveland, OH: NASA Lewis Research Center.


AI - What Is Superintelligence AI? Is Artificial Superintelligence Possible?

 


 

In its most common use, the phrase "superintelligence" refers to any degree of intelligence that at least equals, if not always exceeds, human intellect, in a broad sense.


Though computer intelligence has long outperformed natural human cognitive capacity in specific tasks—for example, a calculator's ability to swiftly interpret algorithms—these are not often considered examples of superintelligence in the strict sense due to their limited functional range.


In this sense, superintelligence would necessitate, in addition to artificial mastery of specific theoretical tasks, some kind of additional mastery of what has traditionally been referred to as practical intelligence: a generalized sense of how to subsume particulars into universal categories that are in some way worthwhile.


To this day, no such generalized superintelligence has manifested, and hence all discussions of superintelligence remain speculative to some degree.


Whereas traditional theories of superintelligence have been limited to theoretical metaphysics and theology, recent advancements in computer science and biotechnology have opened up the prospect of superintelligence being materialized.

Although the timing of such evolution is hotly discussed, a rising body of evidence implies that material superintelligence is both possible and likely.


If this hypothesis is proved right, it will very certainly be the result of advances in one of two major areas of AI research


  1. Bioengineering 
  2. Computer science





The former involves efforts to not only map out and manipulate the human DNA, but also to exactly copy the human brain electronically through full brain emulation, also known as mind uploading.


The first of these bioengineering efforts is not new, with eugenics programs reaching back to the seventeenth century at the very least.

Despite the major ethical and legal issues that always emerge as a result of such efforts, the discovery of DNA in the twentieth century, together with advances in genome mapping, has rekindled interest in eugenics.

Much of this study is aimed at gaining a better understanding of the human brain's genetic composition in order to manipulate DNA code in the direction of superhuman intelligence.



Uploading is a somewhat different, but still biologically based, approach to superintelligence that aims to map out neural networks in order to successfully transfer human intelligence onto computer interfaces.


  • The brains of insects and tiny animals are micro-dissected and then scanned for thorough computer analysis in this relatively new area of study.
  • The underlying premise of whole brain emulation is that if the brain's structure is better known and mapped, it may be able to copy it with or without organic brain tissue.



Despite the fast growth of both genetic mapping and whole brain emulation, both techniques have significant limits, making it less likely that any of these biological approaches will be the first to attain superintelligence.





The genetic alteration of the human genome, for example, is constrained by generational constraints.

Even if it were now feasible to artificially boost cognitive functioning by modifying the DNA of a human embryo (which is still a long way off), it would take an entire generation for the changed embryo to evolve into a fully fledged, superintelligent human person.

This would also imply that there are no legal or moral barriers to manipulating the human DNA, which is far from the fact.

Even the comparatively minor genetic manipulation of human embryos carried done by a Chinese physician as recently as November 2018 sparked international outrage (Ramzy and Wee 2019).



Whole brain emulation, on the other hand, is still a long way off, owing to biotechnology's limits.


Given the current medical technology, the extreme levels of accuracy necessary at every step of the uploading process are impossible to achieve.

Science and technology currently lack the capacity to dissect and scan human brain tissue with sufficient precision to produce full brain simulation results.

Furthermore, even if such first steps are feasible, researchers would face significant challenges in analyzing and digitally replicating the human brain using cutting-edge computer technology.




Many analysts believe that such constraints will be overcome, although the timeline for such realizations is unknown.



Apart from biotechnology, the area of AI, which is strictly defined as any type of nonorganic (particularly computer-based) intelligence, is the second major path to superintelligence.

Of course, the work of creating a superintelligent AI from the ground up is complicated by a number of elements, not all of which are purely logistical in nature, such as processing speed, hardware/software design, finance, and so on.

In addition to such practical challenges, there is a significant philosophical issue: human programmers are unable to know, and so cannot program, that which is superior to their own intelligence.





Much contemporary research on computer learning and interest in the notion of a seed AI is motivated in part by this worry.


Any machine capable of changing reactions to stimuli based on an examination of how well it performs in relation to a predetermined objective is defined as the latter.

Importantly, the concept of a seed AI entails not only the capacity to change its replies by extending its base of content knowledge (stored information), but also the ability to change the structure of its programming to better fit a specific job (Bostrom 2017, 29).

Indeed, it is this latter capability that would give a seed AI what Nick Bostrom refers to as "recursive self-improvement," or the ability to evolve iteratively (Bostrom 2017, 29).

This would eliminate the requirement for programmers to have an a priori vision of super intelligence since the seed AI would constantly enhance its own programming, with each more intelligent iteration writing a superior version of itself (beyond the human level).

Such a machine would undoubtedly cast doubt on the conventional philosophical assumption that robots are incapable of self-awareness.

This perspective's proponents may be traced all the way back to Descartes, but they also include more current thinkers like John Haugeland and John Searle.



Machine intelligence, in this perspective, is defined as the successful correlation of inputs with outputs according to a predefined program.




As a result, robots differ from humans in type, the latter being characterized only by conscious self-awareness.

Humans are supposed to comprehend the activities they execute, but robots are thought to carry out functions mindlessly—that is, without knowing how they work.

Should it be able to construct a successful seed AI, this core idea would be forced to be challenged.

The seed AI would demonstrate a level of self-awareness and autonomy not readily explained by the Cartesian philosophical paradigm by upgrading its own programming in ways that surprise and defy the forecasts of its human programmers.

Indeed, although it is still speculative (for the time being), the increasingly possible result of superintelligent AI poses a slew of moral and legal dilemmas that have sparked a lot of philosophical discussion in this subject.

The main worries are about the human species' security in the case of what Bostrom refers to as a "intelligence explosion"—that is, the creation of a seed AI followed by a possibly exponential growth in intellect (Bostrom 2017).



One of the key problems is the inherently unexpected character of such a result.


Humans will not be able to totally foresee how superintelligent AI would act due to the autonomy entailed by superintelligence in a definitional sense.

Even in the few cases of specialized superintelligence that humans have been able to construct and study so far—for example, robots that have surpassed humans in strategic games like chess and Go—human forecasts for AI have shown to be very unreliable.

For many critics, such unpredictability is a significant indicator that, should more generic types of superintelligent AI emerge, humans would swiftly lose their capacity to manage them (Kissinger 2018).





Of all, such a loss of control does not automatically imply an adversarial relationship between humans and superintelligence.


Indeed, although most of the literature on superintelligence portrays this relationship as adversarial, some new work claims that this perspective reveals a prejudice against machines that is particularly prevalent in Western cultures (Knight 2014).

Nonetheless, there are compelling grounds to believe that superintelligent AI would at the very least consider human goals as incompatible with their own, and may even regard humans as existential dangers.

For example, computer scientist Steve Omohundro has claimed that even a relatively basic kind of superintelligent AI like a chess bot would have motive to want the extinction of humanity as a whole—and may be able to build the tools to do it (Omohundro 2014).

Similarly, Bostrom has claimed that a superintelligence explosion would most certainly result in, if not the extinction of the human race, then at the very least a gloomy future (Bostrom 2017).

Whatever the benefits of such theories, the great uncertainty entailed by superintelligence is obvious.

If there is one point of agreement in this large and diverse literature, it is that if AI research is to continue, the global community must take great care to protect its interests.





Hardened determinists who claim that technological advancement is so tightly connected to inflexible market forces that it is simply impossible to change its pace or direction in any major manner may find this statement contentious.


According to this determinist viewpoint, if AI can deliver cost-cutting solutions for industry and commerce (as it has already started to do), its growth will proceed into the realm of superintelligence, regardless of any unexpected negative repercussions.

Many skeptics argue that growing societal awareness of the potential risks of AI, as well as thorough political monitoring of its development, are necessary counterpoints to such viewpoints.


Bostrom highlights various examples of effective worldwide cooperation in science and technology as crucial precedents that challenge the determinist approach, including CERN, the Human Genome Project, and the International Space Station (Bostrom 2017, 253).

To this, one may add examples from the worldwide environmental movement, which began in the 1960s and 1970s and has imposed significant restrictions on pollution committed in the name of uncontrolled capitalism (Feenberg 2006).



Given the speculative nature of superintelligence research, it is hard to predict what the future holds.

However, if superintelligence poses an existential danger to human existence, caution would dictate that a worldwide collaborative strategy rather than a free market approach to AI be used.



~ Jai Krishna Ponnappan

Find Jai on Twitter | LinkedIn | Instagram


You may also want to read more about Artificial Intelligence here.



See also: 


Berserkers; Bostrom, Nick; de Garis, Hugo; General and Narrow AI; Goertzel, Ben; Kurzweil, Ray; Moravec, Hans; Musk, Elon; Technological Singularity; Yudkowsky, Eliezer.



References & Further Reading:


  • Bostrom, Nick. 2017. Superintelligence: Paths, Dangers, Strategies. Oxford, UK: Oxford University Press.
  • Feenberg, Andrew. 2006. “Environmentalism and the Politics of Technology.” In Questioning Technology, 45–73. New York: Routledge.
  • Kissinger, Henry. 2018. “How the Enlightenment Ends.” The Atlantic, June 2018. https://www.theatlantic.com/magazine/archive/2018/06/henry-kissinger-ai-could-mean-the-end-of-human-history/559124/.
  • Knight, Heather. 2014. How Humans Respond to Robots: Building Public Policy Through Good Design. Washington, DC: The Project on Civilian Robotics. Brookings Institution.
  • Omohundro, Steve. 2014. “Autonomous Technology and the Greater Human Good.” Journal of Experimental & Theoretical Artificial Intelligence 26, no. 3: 303–15.
  • Ramzy, Austin, and Sui-Lee Wee. 2019. “Scientist Who Edited Babies’ Genes Is Likely to Face Charges in China.” The New York Times, January 21, 2019



Artificial Intelligence - Who Is Ben Goertzel (1966–)?


Ben Goertzel is the founder and CEO of SingularityNET, a blockchain AI company, as well as the chairman of Novamente LLC, a research professor at Xiamen University's Fujian Key Lab for Brain-Like Intelligent Systems, the chief scientist of Mozi Health and Hanson Robotics in Shenzhen, China, and the chair of the OpenCog Foundation, Humanity+, and Artificial General Intelligence Society conference series. 

Goertzel has long wanted to create a good artificial general intelligence and use it in bioinformatics, finance, gaming, and robotics.

He claims that, despite AI's current popularity, it is currently superior than specialists in a number of domains.

Goertzel divides AI advancement into three stages, each of which represents a step toward a global brain (Goertzel 2002, 2): • the intelligent Internet • the full-fledged Singularity Goertzel presented a lecture titled "Decentralized AI: The Power and the Necessity" at TEDxBerkeley in 2019.

He examines artificial intelligence in its present form as well as its future in this discussion.

"The relevance of decentralized control in leading AI to the next stages, the strength of decentralized AI," he emphasizes (Goertzel 2019a).

In the evolution of artificial intelligence, Goertzel distinguishes three types: artificial narrow intelligence, artificial broad intelligence, and artificial superintelligence.

Artificial narrow intelligence refers to machines that can "address extremely specific issues... better than humans" (Goertzel 2019a).

In certain restricted activities, such as chess and Go, this kind of AI has outperformed a human.

Ray Kurzweil, an American futurologist and inventor, coined the phrase "narrow AI." Artificial general intelligence (AGI) refers to intelligent computers that can "generate knowledge" in a variety of fields and have "humanlike autonomy." By 2029, according to Goertzel, this kind of AI will have reached the same level of intellect as humans.

Artificial superintelligence (ASI) is based on both narrow and broad AI, but it can also reprogram itself.



By 2045, he claims, this kind of AI will be smarter than the finest human brains in terms of "scientific innovation, general knowledge, and social abilities" (Goertzel 2019a).

According to Goertzel, Facebook, Google, and a number of colleges and companies are all actively working on AGI.

According to Goertzel, the shift from AI to AGI will occur within the next five to thirty years.

Goertzel is also interested in artificial intelligence-assisted life extension.

He thinks that artificial intelligence's exponential advancement will lead to technologies that will increase human life span and health eternally.

He predicts that by 2045, a singularity featuring a drastic increase in "human health span" would have occurred (Goertzel 2012).

Vernor Vinge popularized the term "singularity" in his 1993 article "The Coming Technological Singularity." Ray Kurzweil coined the phrase in his 2005 book The Singularity is Near.

The Technological Singularity, according to both writers, is the merging of machine and human intellect as a result of a fast development in new technologies, particularly robots and AI.

The thought of an impending singularity excites Goertzel.

SingularityNET is his major current initiative, which entails the construction of a worldwide network of artificial intelligence researchers interested in developing, sharing, and monetizing AI technology, software, and services.

By developing a decentralized protocol that enables a full stack AI solution, Goertzel has made a significant contribution to this endeavor.

SingularityNET, as a decentralized marketplace, provides a variety of AI technologies, including text generation, AI Opinion, iAnswer, Emotion Recognition, Market Trends, OpenCog Pattern Miner, and its own cryptocurrency, AGI token.

SingularityNET is presently cooperating with Domino's Pizza in Malaysia and Singapore (Khan 2019).



Domino's is interested in leveraging SingularityNET technologies to design a marketing plan, with the goal of providing the finest products and services to its consumers via the use of unique algorithms.

Domino's thinks that by incorporating the AGI ecosystem into their operations, they will be able to provide value and service in the food delivery market.

Goertzel has reacted to scientist Stephen Hawking's challenge, which claimed that AI might lead to the extinction of human civilization.

Given the current situation, artificial super intelligence's mental state will be based on past AI generations, thus "selling, spying, murdering, and gambling are the key aims and values in the mind of the first super intelligence," according to Goertzel (Goertzel 2019b).

He acknowledges that if humans desire compassionate AI, they must first improve their own treatment of one another.

With four years, Goertzel worked for Hanson Robotics in Hong Kong.

He collaborated with Sophia, Einstein, and Han, three well-known robots.

"Great platforms for experimenting with AI algorithms, including cognitive architectures like OpenCog that aim at human-level AI," he added of the robots (Goertzel 2018).

Goertzel argues that essential human values may be retained for future generations in Sophia-like robot creatures after the Technological Singularity.

Decentralized networks like SingularityNET and OpenCog, according to Goertzel, provide "AIs with human-like values," reducing AI hazards to humanity (Goertzel 2018).

Because human values are complicated in nature, Goertzel feels that encoding them as a rule list is wasteful.

Brain-computer interfacing (BCI) and emotional interfacing are two ways Goertzel offers.

Humans will become "cyborgs," with their brains physically linked to computational-intelligence modules, and the machine components of the cyborgs will be able to read the moral-value-evaluation structures of the human mind directly from the biological components of the cyborgs (Goertzel 2018).

Goertzel uses Elon Musk's Neuralink as an example.

Because it entails invasive trials with human brains and a lot of unknowns, Goertzel doubts that this strategy will succeed.

"Emotional and spiritual connections between people and AIs, rather than Ethernet cables or Wifi signals, are used to link human and AI brains," according to the second method (Goertzel 2018).

To practice human values, he proposes that AIs participate in emotional and social connection with humans via face expression detection and mirroring, eye contact, and voice-based emotion recognition.

To that end, Goertzel collaborated with SingularityNET, Hanson AI, and Lia Inc on the "Loving AI" research project, which aims to assist artificial intelligences speak and form intimate connections with humans.

A funny video of actor Will Smith on a date with Sophia the Robot is presently available on the Loving AI website.

Sophia can already make sixty facial expressions and understand human language and emotions, according to the video of the date.

When linked to a network like SingularityNET, humanoid robots like Sophia obtain "ethical insights and breakthroughs...

via language," according to Goertzel (Goertzel 2018).

Then, through a shared internet "mindcloud," robots and AIs may share what they've learnt.

Goertzel is also the chair of the Artificial General Intelligence Society's Conference Series on Artificial General Intelligence, which has been conducted yearly since 2008.

The Journal of Artificial General Intelligence is a peer-reviewed open-access academic periodical published by the organization. Goertzel is the editor of the conference proceedings series.


Jai Krishna Ponnappan


You may also want to read more about Artificial Intelligence here.


See also: 

General and Narrow AI; Superintelligence; Technological Singularity.


Further Reading:


Goertzel, Ben. 2002. Creating Internet Intelligence: Wild Computing, Distributed Digital Consciousness, and the Emerging Global Brain. New York: Springer.

Goertzel, Ben. 2012. “Radically Expanding the Human Health Span.” TEDxHKUST. https://www.youtube.com/watch?v=IMUbRPvcB54.

Goertzel, Ben. 2017. “Sophia and SingularityNET: Q&A.” H+ Magazine, November 5, 2017. https://hplusmagazine.com/2017/11/05/sophia-singularitynet-qa/.

Goertzel, Ben. 2018. “Emotionally Savvy Robots: Key to a Human-Friendly Singularity.” https://www.hansonrobotics.com/emotionally-savvy-robots-key-to-a-human-friendly-singularity/.

Goertzel, Ben. 2019a. “Decentralized AI: The Power and the Necessity.” TEDxBerkeley, March 9, 2019. https://www.youtube.com/watch?v=r4manxX5U-0.

Goertzel, Ben. 2019b. “Will Artificial Intelligence Kill Us?” July 31, 2019. https://www.youtube.com/watch?v=TDClKEORtko.

Goertzel, Ben, and Stephan Vladimir Bugaj. 2006. The Path to Posthumanity: 21st Century Technology and Its Radical Implications for Mind, Society, and Reality. Bethesda, MD: Academica Press.

Khan, Arif. 2019. “SingularityNET and Domino’s Pizza Announce a Strategic Partnership.” https://blog.singularitynet.io/singularitynet-and-dominos-pizza-announce-a-strategic-partnership-cbbe21f80fc7.

Vinge, Vernor. 1993. “The Coming Technological Singularity: How to Survive in the Post-Human Era.” In Vision 21: Interdisciplinary Science and Engineering in the Era of Cyberspace, 11–22. NASA: Lewis Research Center





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