Soyuz 11 was the only crewed mission to board the world’s first space station, Salyut 1. The crew, Georgy Dobrovolsky, Vladislav Volkov, and Viktor Patsayev, arrived at the space station on 7 June 1971 and departed on 29 June. The mission ended in disaster when the crew capsule depressurized during preparations for reentry, killing the three-man crew. The three crew members of Soyuz 11 are the only humans known to have died in space.
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Millions of space nerds reacted with joy Monday to a study showing the atmosphere of Venus contains phosphine, a chemical byproduct of biological life. But none would have been more thrilled or less surprised by the discovery than the late, great Carl Sagan — who said this day might come more than 50 years ago.
Now best remembered as the presenter of the most-viewed-ever PBS series Cosmos, the author of the book behind the movie Contact, and the guy who put gold disks of Earth music on NASA’s Voyager missions, Sagan actually got his start studying our closest two planets. He became an astronomer after being inspired as a kid by Edgar Rice Burroughs’ space fantasies, set on Mars and Venus.
‘Cosmos’ presenter Carl Sagan was one of the world’s top experts on Venus, and he saw first what scientists have just announced: possible life on Venus.
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.
Spiros Michalakis is the Caltech quantum physicist who served as the science advisor on Bill & Ted: Face The Music and he was kind enough to sit down and chat about quantum physics, the nature of time, and the brilliant minds behind Bill & Ted.
Elon Musk’s controversial ‘brain chip’ might be coming to us sooner than we first thought, with the technology entrepreneur promising a working demo by the end of this week.
The news comes a little over a month after Musk announced his latest start-up, Neuralink, was in the process of developing a brain-computer interface that allegedly has a life-changing range of benefits – including the ability to stream music straight into your brain.
Now, Neuralink, which has already received more than $158 million in funding, will be demonstrating a working device this coming Friday, August 28, at approximately 6.00pm ET (11.00pm BST).
“I don’t love the idea of being a house cat, but what’s the solution?” he said in 2016, just months before he founded Neuralink. “I think one of the solutions that seems maybe the best is to add an AI layer.”
We always wonder how that “Eureka Moment” turns up…but truth may lie in the “High and Mighty”.
Cracked.com’s new book is now on sale. What follows is one of the classic articles that appear in the book, along with 18 new articles that you can’t read anywhere else.
Any dreadlocked white guys finding this article after Googling “Drugs Rule” should know that we’ve given this list about drugs a rule. To make the cut, an accomplishment has to be considered great by people who could pass a field sobriety test. So no Grateful Dead music. We’re sure someone somewhere has enjoyed the Dead perfectly sober, just as there are probably non-Christians who listen to Christian Rock. But we’re just as sure that in the grand scheme of things, those people don’t count.
In fact, because we’re masochists, we gave ourselves a strict no music policy, leaving us with … well, not a whole lot actually. Turns out most great things were accomplished by people who just said no, at least immediately prior to accomplishing them. Except for these five.
