In Scientists were, for the first time, able to show that 800,000 living brain cells trapped in a petri dish can be taught how to play the videogame Pong.
Algorithms have helped mathematicians perform fundamental operations for thousands of years. The ancient Egyptians created an algorithm to multiply two numbers without requiring a multiplication table, and Greek mathematician Euclid described an algorithm to compute the greatest common divisor, which is still in use today.
During the Islamic Golden Age, Persian mathematician Muhammad ibn Musa al-Khwarizmi designed new algorithms to solve linear and quadratic equations. In fact, al-Khwarizmi’s name, translated into Latin as Algoritmi, led to the term algorithm. But, despite the familiarity with algorithms today – used throughout society from classroom algebra to cutting edge scientific research – the process of discovering new algorithms is incredibly difficult, and an example of the amazing reasoning abilities of the human mind.
In our paper, published today in Nature, we introduce AlphaTensor, the first artificial intelligence (AI) system for discovering novel, efficient, and provably correct algorithms for fundamental tasks such as matrix multiplication. This sheds light on a 50-year-old open question in mathematics about finding the fastest way to multiply two matrices.
“The idea was to build a society like we have for all the other disciplines in medicine,” says Evelyne Bischof, a professor of medicine at Shanghai University of Medicine and Health Sciences and the inaugural vice president of the society. She has previously spearheaded educational efforts with Zhavoronkov and others, co-developing a formal course on longevity medicine for doctors. At the ARDD meeting, Bischof announced their course had just received continuing medical education (CME) accreditation from the American Medical Association.
“Longevity medicine is crystallizing as a discipline,” says Andrea Maier, an internal medicine specialist and geriatrician at National University of Singapore who is serving as the society’s inaugural president. One thing that’s not yet clear, several experts told me, is whether longevity will come to be established as a sub-discipline of geriatrics or internal medicine or whether it will become a separate medical specialty unto itself.
“Whichever way it goes,” Maier says, “it’s happening.”
This metaverse meme video is about wojak who grows old in a metaverse. From the moment he is still a child and has his first school day, he already lives through his vr glasses. His school is in the metaverse, as well as his friends. Years later, he starts doubting about how “normal” living meta actually is. Didn’t people maybe have a better life back when there was no metaverse? When you did stuff offline? Who knows…
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You may not realize it, but each time you recall a memory—like your first time riding a bike or walking into your high school prom—your brain changes the memory ever so slightly. It’s almost like adding an Instagram filter, with details being filled in and information being updated or lost with each recall.
“We’re inadvertently applying filters to our past experiences,” says Steve Ramirez, a Boston University neuroscientist. Even though a filtered memory is different from the original, you can tell what that basic picture is, for the most part, he says.
“Memory is less of a video recording of the past, and more reconstructive,” says Ramirez, a BU College of Arts & Sciences assistant professor of psychological and brain sciences. The malleable nature of memory is both a blessing and curse: It’s bad if we remember false details, but it’s good that our brains have the natural ability to mold and update memories to make them less potent, especially if it is something scary or traumatic.
https://www.youtube.com/watch?v=NsWOZ4IAHNU
If there is one thing science fiction movies and comics have taught us, it’s that humans have no.
limitations, and we will one day be able to open a portal that transverses into another dimension. What if I tell you that day is closer to us than ever? This is the latest discovery made.
by scientists and is by far the biggest of the century.
Will we finally get to find out if we are the only beings in the cosmos? What technology have.
scientists designed capable of making interstellar teleportation possible? How and where will.
the portals take us?
Join us as we explore how scientists have finally found a way to open a portal to another.
dimension.
Disclaimer Fair Use:
1. The videos have no negative impact on the original works.
2. The videos we make are used for educational purposes.
3. The videos are transformative in nature.
4. We use only the audio component and tiny pieces of video footage, only if it’s necessary.
Set to be one of the largest, if not the largest, investment opportunity in the decades to come, longevity is a rapidly accelerating field; the Longevity Investors Conference targets the global investor community, bringing together institutional investors and top class experts for networking and exploration of relevant insights into the field, as well as expert education and investment opportunities.
Longevity. Technology: It’s not long to wait, now until the Longevity Investors Conference, which takes place later this month in Gstadt, Switzerland. The speaker list is full of longevity pioneers and visionaries, and we have been lucky enough to be given the opportunity to ask them some of our burning longevity questions.
Longevity. Technology readers can get their exclusive invitation to the leading investors-only longevity conference HERE.
Strenuous cognitive work leads to an accumulation of glutamate in the prefrontal cortex, according to new research published in the journal Current Biology. The new findings suggest that mental fatigue is a neuropsychological mechanism that helps to avert the build up of potentially toxic byproducts of prolonged cognitive activity.
“Nobody knows what mental fatigue is, how it is generated and why we feel it,” said study author Antonius Wiehler, a member of the Motivation, Brain and Behavior Lab at Pitié Salpêtrière Hospital in Paris. “It has remained a mystery despite more than a century of scientific research. Machines can do cognitive tasks continuously without fatigue, the brain is different and we wanted to understand how and why. Mental fatigue has important consequences: for economic decisions, for management at work, for education at school, for clinical cure, etc.”
The researchers were particularly interested in the role of glutamate, an excitatory neurotransmitter that is involved in a variety of cognitive functions, including learning and memory. In addition, glutamate plays a role in controlling the strength of synaptic connections. Too much or too little glutamate can lead to neuronal dysfunction, so it is critical that this neurotransmitter is tightly regulated.
Started out as an interview ended up being a discussion between Hugo de Garis and (off camera) Adam Ford + Michel de Haan.
00:11 The concept of understanding under-recognised as an important aspect of developing AI
00:44 Re-framing perspectives on AI — the Chinese Room argument — and how can consciousness or understanding arise from billions of seemingly discreet neurons firing? (Should there be a binding problem of understanding similar to the binding problem of consciousness?)
04:23 Is there a difference between generality in intelligence and understanding? (and extentionally between AGI and artificial understanding?)
05:08 Ah Ha! moments — where the penny drops — what’s going on when this happens?
07:48 Is there an ideal form of understanding? Coherence & debugging — ah ha moments.
10:18 Webs of knowledge — contextual understanding.
12:16 Early childhood development — concept formation and navigation.
13:11 The intuitive ability for concept navigation isn’t complete.
Is the concept of understanding a catch all?
14:29 Is it possible to develop AGI that doesn’t understand? Is generality and understanding the same thing?
17:32 Why is understanding (the nature of) understanding important?
Is understanding reductive? Can it be broken down?
19:52 What would be the most basic primitive understanding be?
22:11 If (strong) AI is important, and understanding is required to build (strong) AI, what sorts of things should we be doing to make sense of understanding?
Approaches — engineering, and copy the brain.
24:34 Is common sense the same thing as understanding? How are they different?
26:24 What concepts do we take for granted around the world — which when strong AI comes about will dissolve into illusions, and then tell us how they actually work under the hood?
27:40 Compression and understanding.
29:51 Knowledge, Gettier problems and justified true belief. Is knowledge different from understanding and if so how?
31:07 A hierarchy of intel — data, information, knowledge, understanding, wisdom.
33:37 What is wisdom? Experience can help situate knowledge in a web of understanding — is this wisdom? Is the ostensible appearance of wisdom necessarily wisdom? Think pulp remashings of existing wisdom in the form of trashy self-help literature.
35:38 Is understanding mapping knowledge into a useful framework? Or is it making accurate / novel predictions?
36:00 Is understanding like high resolution carbon copy like models that accurately reflect true nature or a mechanical process?
37:04 Does understanding come in gradients of topologies? Is there degrees or is it just on or off?
38:37 What comes first — understanding or generality?
40:47 Minsky’s ‘Society of Mind’
42:46 Is vitalism alive in well in the AI field? Do people actually think there are ghosts in the machines?
48:15 Anthropomorphism in AI literature.
50:48 Deism — James Gates and error correction in super-symmetry.
52:16 Why are the laws of nature so mathematical? Why is there so much symmetry in physics? Is this confusing the map with the territory?
52:35 The Drake equation, and the concept of the Artilect — does this make Deism plausible? What about the Fermi Paradox?
55:06 Hyperintelligence is tiny — the transcention hypothesis — therefore civs go tiny — an explanation for the fermi paradox.
56:36 Why would *all* civs go tiny? Why not go tall, wide and tiny? What about selection pressures that seem to necessitate cosmic land grabs?
01:01:52 The Great Filter and the The Fermi Paradox.
01:02:14 Is it possible for an AGI to have a deep command of knowledge across a wide variety of topics/categories without understanding being an internal dynamic? Is the turing test good enough to test for understanding? What kinds of behavioral tests could reliably test for understanding? (Of course without the luxury of peering under the hood)
01:03:09 Does AlphaGo understand Go, or DeepBlue understand chess? Revisiting the Chinese Room argument.
01:04:23 More on behavioral tests for AI understanding.
01:06:00 Zombie machines — David Chalmers Zombie argument.
01:07:26 Complex enough algorithms — is there a critical point of complexity beyond which general intelligence likely emerges? Or understanding emerges?
01:08:11 Revisiting behavioral ‘turing’ tests for understanding.
01:13:05 Shape sorters and reverse shape sorters.
01:14:03 Would slightly changing the rules of Go confuse AlphaGo (after it had been trained)? Need for adaptivity — understanding concept boundaries, predicting where they occur, and the ability to mine outwards from these boundaries…
01:15:11 Neural nets and adaptivity.
01:16:41 AlphaGo documentary — worth a watch. Progresses in AI challenges human dignity which is a concern, but the DeepMind and the AlphaGo documentary seemed to be respectful. Can we manage a transition from human labor to full on automation while preserving human dignity?
Filmed in the dandenong ranges in victoria, australia.
Many thanks for watching!
https://youtube.com/watch?v=R0NP5eMY7Q8
Quantum algorithms: An algorithm is a sequence of steps that leads to the solution of a problem. In order to execute these steps on a device, one must use specific instruction sets that the device is designed to do so.
Quantum computing introduces different instruction sets that are based on a completely different idea of execution when compared with classical computing. The aim of quantum algorithms is to use quantum effects like superposition and entanglement to get the solution faster.
