Lifeboat Foundation

Except someone—or, rather, something— can hear: your car. Hearing your angry words, aggressive tone, and raised voice, and seeing your furrowed brow, the onboard computer goes into “soothe” mode, as it’s been programmed to do when it detects that you’re angry. It plays relaxing music at just the right volume, releases a puff of light lavender-scented essential oil, and maybe even says some meditative quotes to calm you down.

What do you think—creepy? Helpful? Awesome? Weird? Would you actually calm down, or get even more angry that a car is telling you what to do?

Continue reading “Cars Will Soon Be Able to Sense and React to Your Emotions” »

Video of them testing their prototype lightsaber.

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— 300 interviews with the people who shape our world, in 40 countries and on 12 platforms.

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Circa 2016

Scientists from a Belgian university have built a solar-powered machine that can turn urine into drinkable water. They deployed it at a 10-day music and theater festival in central Ghent, Belgium. The experiment was a success as the scientists were able to recover a 1,000 litres of unconsumed water, which will be used to make Belgian beer, from the urine of several partygoers.

CERN’s Timepix particle detectors, developed by the Medipix2 Collaboration, help unravel the secret of a long-lost painting by the great Renaissance master, Raphael. 500 years ago, the Italian painter Raphael passed away, leaving behind him many works of art, paintings, frescoes, and engravings.

CERNs Timepix particle detectors, developed by the Medipix2 Collaboration, help unravel the secret of a long-lost painting by the great Renaissance master, Raphael.

500 years ago, the Italian painter Raphael passed away, leaving behind him many works of art, paintings, frescoes, and engravings. Like his contemporaries Michelangelo and Leonardo da Vinci, Raphael’s work made the joy of imitators and the greed of counterfeiters, who bequeathed us many copies, pastiches, and forgeries of the great master of the Renaissance.

Continue reading “CERN Timepix Technology Helps Rediscover Lost Painting by the Great Renaissance Master, Raphael” »

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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Circa 2019

Watch Mitchie Brusco land the first 1260 in skateboard history in the Skateboard Big Air final, Saturday at X Games Minneapolis 2019.

Continue reading “MITCHIE BRUSCO: First-ever Big Air 1260 | World of X Games” »

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.

Continue reading “Carl Sagan predicted life on Venus in 1967. We may be close to proving him right” »

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.

Continue reading “Joscha Bach — GPT-3: Is AI Deepfaking Understanding?” »