Lifeboat Foundation

On GPT-3, achieving AGI, machine understanding and lots more… Will GPT-3 or an equivalent be used to deepfake human understanding?

Joscha Bach on GPT-3, achieving AGI, machine understanding and lots more
02:40 What’s missing in AI atm? Unified coherent model of reality
04:14 AI systems like GPT-3 behave as if they understand — what’s missing?
08:35 Symbol grounding — does GPT-3 have it?
09:35 GPT-3 for music generation, GPT-3 for image generation, GPT-3 for video generation
11:13 GPT-3 temperature parameter. Strange output?
13:09 GPT-3 a powerful tool for idea generation
14:05 GPT-3 as a tool for writing code. Will GPT-3 spawn a singularity?
16:32 Increasing GPT-3 input context may have a high impact
16:59 Identifying grammatical structure & language
19:46 What is the GPT-3 transformer network doing?
21:26 GPT-3 uses brute force, not zero-shot learning, humans do ZSL
22:15 Extending the GPT-3 token context space. Current Context = Working Memory. Humans with smaller current contexts integrate concepts over long time-spans
24:07 GPT-3 can’t write a good novel
25:09 GPT-3 needs to become sensitive to multi-modal sense data — video, audio, text etc
26:00 GPT-3 a universal chat-bot — conversations with God & Johann Wolfgang von Goethe
30:14 What does understanding mean? Does it have gradients (i.e. from primitive to high level)?
32:19 (correlation vs causation) What is causation? Does GPT-3 understand causation? Does GPT-3 do causation?
38:06 Deep-faking understanding
40:06 The metaphor of the Golem applied to civ
42:33 GPT-3 fine with a person in the loop. Big danger in a system which fakes understanding. Deep-faking intelligible explanations.
44:32 GPT-3 babbling at the level of non-experts
45:14 Our civilization lacks sentience — it can’t plan ahead
46:20 Would GTP-3 (a hopfield network) improve dramatically if it could consume 1 to 5 trillion parameters?
47:24 GPT3: scaling up a simple idea. Clever hacks to formulate the inputs
47:41 Google GShard with 600 billion input parameters — Amazon may be doing something similar — future experiments
49:12 Ideal grounding in machines
51:13 We live inside a story we generate about the world — no reason why GPT-3 can’t be extended to do this
52:56 Tracking the real world
54:51 MicroPsi
57:25 What is computationalism? What is it’s relationship to mathematics?
59:30 Stateless systems vs step by step Computation — Godel, Turing, the halting problem & the notion of truth
1:00:30 Truth independent from the process used to determine truth. Constraining truth that which can be computed on finite state machines
1:03:54 Infinities can’t describe a consistent reality without contradictions
1:06:04 Stevan Harnad’s understanding of computation
1:08:32 Causation / answering ‘why’ questions
1:11:12 Causation through brute forcing correlation
1:13:22 Deep learning vs shallow learning
1:14:56 Brute forcing current deep learning algorithms on a Matrioshka brain — would it wake up?
1:15:38 What is sentience? Could a plant be sentient? Are eco-systems sentient?
1:19:56 Software/OS as spirit — spiritualism vs superstition. Empirically informed spiritualism
1:23:53 Can we build AI that shares our purposes?
1:26:31 Is the cell the ultimate computronium? The purpose of control is to harness complexity
1:31:29 Intelligent design
1:33:09 Category learning & categorical perception: Models — parameters constrain each other
1:35:06 Surprise minimization & hidden states; abstraction & continuous features — predicting dynamics of parts that can be both controlled & not controlled, by changing the parts that can be controlled. Categories are a way of talking about hidden states.
1:37:29 ‘Category’ is a useful concept — gradients are often hard to compute — so compressing away gradients to focus on signals (categories) when needed
1:38:19 Scientific / decision tree thinking vs grounded common sense reasoning
1:40:00 Wisdom/common sense vs understanding. Common sense, tribal biases & group insanity. Self preservation, dunbar numbers
1:44:10 Is g factor & understanding two sides of the same coin? What is intelligence?
1:47:07 General intelligence as the result of control problems so general they require agents to become sentient
1:47:47 Solving the Turing test: asking the AI to explain intelligence. If response is an intelligible & testable implementation plan then it passes?
1:49:18 The term ‘general intelligence’ inherits it’s essence from behavioral psychology; a behaviorist black box approach to measuring capability
1:52:15 How we perceive color — natural synesthesia & induced synesthesia
1:56:37 The g factor vs understanding
1:59:24 Understanding as a mechanism to achieve goals
2:01:42 The end of science?
2:03:54 Exciting currently untestable theories/ideas (that may be testable by science once we develop the precise enough instruments). Can fundamental physics be solved by computational physics?
2:07:14 Quantum computing. Deeper substrates of the universe that runs more efficiently than the particle level of the universe?
2:10:05 The Fermi paradox
2:12:19 Existence, death and identity construction.

The ability of future superintelligent machines and enhanced humans alike to instantly transfer knowledge and directly share experiences with each other in digital format will lead to evolution of intelligence from relatively isolated individual minds to the global community of hyperconnected digital minds. The forthcoming phenomenon, the Syntellect Emergence, or the Cybernetic Singularity, is already seen on the horizon, when Digital Gaia, the global neural network of billions of hyperconnected humans and superintelligent machines, and trillions of sensors around the planet, “wakes up” as a living, conscious superorganism. It is when, essentially, you yourself transcend to the higher Gaian Mind. https://link.medium.com/vXrDIWOns9

#CyberneticSingularity

“Evolution is a process of creating patterns of increasing order… I believe that it’s the evolution of patterns that constitutes the ultimate story of our world. Each stage or epoch uses the information-processing methods of the previous…

Continue reading “The Cybernetic Singularity: When Humankind Transcends Biology” »

Scientists suggest that a counter-intuitive, hypothetical species of black holes may negate the standard model of cosmology, where dark energy is an inherent and constant property of spacetime that will result in an eventual cold death of the universe. “It’s the big elephant in the room,” says Claudia de Rham, a theoretical physicist at Imperial College London about dark energy, the mysterious, elusive phenomena that pushes the cosmos to expand so rapidly and which is estimated to account for 70% of the contents of the universe. “It’s very frustrating.”

Generic Objects of Dark Energy

Astronomers have known for two decades that the expansion of the universe is accelerating, but the physics of this expansion remains a mystery. In 1966, Erast Gliner, a young physicist at the Ioffe Physico-Technical Institute in Leningrad, proposed an alternative hypothesis that very large stars should collapse into what could be called Generic Objects of Dark Energy (GEODEs). These appear to be black holes when viewed from the outside but, unlike black holes, they contain dark energy instead of a singularity.

Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.

Known for identifying cutting edge technologies, he is currently a Co-Founder of a startup and fundraiser for high potential early-stage companies. He is the Head of Research for Allocations for deep technology investments and an Angel Investor at Space Angels.

A frequent speaker at corporations, he has been a TEDx speaker, a Singularity University speaker and guest at numerous interviews for radio and podcasts. He is open to public speaking and advising engagements.

Adapting the Intelligence Community

As machines become the primary collectors, analysts, consumers, and targets of intelligence, the entire U.S. intelligence community will need to evolve. This evolution must start with enormous investments in AI and autonomization technology as well as changes to concepts of operations that enable agencies to both process huge volumes of data and channel the resulting intelligence directly to autonomous machines. As practically everything becomes connected via networks that produce some form of electromagnetic signature or data, signals intelligence in particular will need to be a locus of AI evolution. So will geospatial intelligence. As satellites and other sensors proliferate, everything on earth will soon be visible at all times from above, a state that the federal research and development center Aerospace has called the “GEOINT Singularity.” To keep up with all this data, geospatial intelligence, like signals intelligence, will need to radically enhance its AI capabilities.

The U.S. intelligence community is currently split up into different functions that collect and analyze discrete types of intelligence, such as signals or geospatial intelligence. The RIA may force the intelligence community to reassess whether these divisions still make sense. Electromagnetic information is electromagnetic information, whether it comes from a satellite or an Internet of Things device. The distinction in origin matters little if no human ever looks at the raw data, and an AI system can recognize patterns in all of the data at once. The division between civilian and military intelligence will be similarly eroded, since civilian infrastructure, such as telecommunications systems, will be just as valuable to military objectives as military communications systems. Given these realities, separating intelligence functions may impede rather than aid intelligence operations.

Corrinne Graham (Economic financial analyst, Space Renaissance USA) interviewed Gregg Maryniak, about his history, motivation and aims to inspire young generations to find their way to the outer space. Gregg is the co-founder, together with Peter Diamandis, of the X-Prize Foundation. The X-Prize is recognized, by the space community, as the initiative that triggered the New Space revolution, by demonstrating that the low cost access to space was feasible and mature. He was the Executive Director of the Space Studies Institute, founded by Gerard O’Neill in Chicago, US. He’s on the Board of Directors of the Singularity University and keeps on restlessly working to inspire and motivate youngs, students and public opinion at large, explaining why human expansion into space is needed and very urgent, in order not to miss our “launch window”. During the conversation, we acknowledged that we agree on many points, all of them primary relevant to the survival and continued progress of civilization. Namely the common appreciation for the O’Neill’s model, that gives priority and preference to artificial rotating structures – the “space colonies” – since they assure 1G artificial gravity. Also, we are 100% in tune about the extreme urgency of kicking-off civilian expansion into outer space, and the subsequent need to make people to understand it. The big risk – said Gregg — is to miss our launch window, the period in which social and economic conditions are favorable to begin really moving into space. When I asked him whether he thinks that humanity is doing everything that is to be done, and if we are in time, on our evolutionary road to space, his answer was a clear “NO”. So we understood that we also agree on the most urgent technology advances to be raised as priority: the enabling technologies, necessary to bring untrained civilians to travel, live and work in space. Namely low acceleration vehicles, protection against cosmic radiations, artificial gravity, green environments and artificial ecosystems in space habitats. Gregg is a great achievement indeed, in our SR Academy Mentorship Programme. After this first meeting, we’ll try to hold other ones, properly announced on social networks, with the target to bring the above discussion to large public opinion. Stay in tune! https://spacerenaissance.space/gregg-maryniak-interviewed-by…programme/

CHECK THE SPACE RENAISSANCE ACADEMY MENTORSHIP PROGRAM! https://spacerenaissance.space/the-space-renaissance-academy…programme/ Students: choose some theme(s) for your graduation theses or Ph.D https://spacerenaissance.space/themes-for-graduate-works/ Mentors: choose your favorite disciplines on which you can provide mentorship https://spacerenaissance.space/mentorship-disciplines/

Short stories about theity written in collaboration with GPT-3.

Ogba Educational Clinic

Long before coronavirus appeared and shattered our pre-existing “normal,” the future of work was a widely discussed and debated topic. We’ve watched automation slowly but surely expand its capabilities and take over more jobs, and we’ve wondered what artificial intelligence will eventually be capable of.

The pandemic swiftly turned the working world on its head, putting millions of people out of a job and forcing millions more to work remotely. But essential questions remain largely unchanged: we still want to make sure we’re not replaced, we want to add value, and we want an equitable society where different types of work are valued fairly.

Continue reading “A Human-Centric World of Work: Why It Matters, and How to Build It” »

#CyberneticSingularity

About 542 million years ago, something weird and profoundly remarkable happened on Earth. Quite suddenly, life went insanely inventive, proliferating from simple, rudimentary single-celled organisms into myriad multi-cellular forms. Evolution discovered the idea of more sophisticated and specialized cells, and most of the basic body plans we know today. Biologists call it the Cambrian explosion.

Continue reading “Nearing the Cybernetic Singularity: What is the Syntellect Emergence?” »