Progress in understanding expert performance is limited by the scarcity of quantitative data on long-term knowledge acquisition and deployment. Here we use the Rubik's Cube as a cognitive model system existing at the intersection of puzzle solving, skill learning, expert knowledge, cultural transmission, and group theory. By studying competitive cube communities, we find evidence for universality in the collective learning of the Rubik's Cube in both sighted and blindfolded conditions: expert performance follows exponential progress curves whose parameters reflect the delayed acquisition of algorithms that shorten solution paths. Blindfold solves form a distinct problem class from sighted solves and are constrained not only by expert knowledge but also by the skill improvements required to overcome short-term memory bottlenecks, a constraint shared with blindfold chess. Cognitive artifacts such as the Rubik's Cube help solvers navigate an otherwise enormous mathematical state space. In doing so, they sustain collective intelligence by integrating communal knowledge stores with individual expertise and skill, illustrating how expertise can, in practice, continue to deepen over the course of a single lifetime.

Our brain may not be as capable of rewiring following an amputation as we thought, which could have serious implications for how we treat a common complication called phantom limb pain. A part of the brain called the somatosensory cortex receives and processes sensory information across the body, such as touch and temperature. Some studies suggest the areas of the cortex are mapped to different parts of the body, so a different area will light up if you burn your hand versus your toe, for instance. It has also been suggested that the somatosensory cortex reorganises itself in the case of an amputation or severed nerve. For example, in a study of macaques whose arm nerves had been severed, neurons in the somatosensory cortex that normally respond to stimulation of the hand were instead activated by touching the face.

Large Language Models (LLMs) are deep neural networks that, through training on huge amounts of text, learn to accurately predict the next word (or token) in a text. It has been surprising to many that next-token prediction has lead to impressive abilities, such as learning of syntax, code generation, writing in any style, and factual recall. It has been claimed in the LLM literature that, as the number of network parameters and amount of training data is scaled up, certain capabilities arise suddenly and unexpectedly, a phenomenon that these writers term "emergence". For example, Wei et al. [1] write, "we define emergent abilities of large language models as abilities that are not present in smaller-scale models but are present in large-scale models; thus they cannot be predicted by simply extrapolating the performance improvements on smaller-scale models." And in a recent review of emergent abilities in LLMs Berti et al. [2] survey around 100 papers the majority of which equate emergence with the discontinuous appearance of abilities with increasing data or model size.

In March of 2021, the Santa Fe Institute hosted a workshop as part of its Foundations of Intelligence in Natural and Artificial Systems project. This project seeks to advance the field of artificial intelligence by promoting interdisciplinary research on the nature of intelligence. During the workshop, speakers from diverse disciplines gathered to develop a taxonomy of intelligence, articulating their own understanding of intelligence and how their research has furthered that understanding. In this report, we summarize the insights offered by each speaker and identify the themes that emerged during the talks and subsequent discussions.

As progress accelerates towards AGI, the number of people who realize the significance of each new breakthrough decreases. This is the AGI Significance Paradox. There is a very old metaphor that you can boil a frog in water without it jumping out when you gradually increase the temperature. The fable goes that the frog does not have the internal models to recognize that there is a change in the water temperature. A cold-blooded creature like the frog is thought to have its temperature regulated only by the external environment.

What does the future look like for humans and machines? Elon Musk would argue that it involves wiring brains directly up to computers – but neuroscientists tell Inverse that's easier said than done. On August 28, Musk and his team unveiled the latest updates from secretive firm Neuralink with a demo featuring pigs implanted with their brain chip device. These chips are called Links, and they measure 0.9 inches wide by 0.3 inches tall. They connect to the brain via wires, and provide a battery life of 12 hours per charge, after which the user would need to wirelessly charge again.

In 1933, dismayed at the Nazification of Germany, the philosopher wrote "The Triumph of Stupidity," attributing the rise of Adolf Hitler to the organized fervor of stupid and brutal people--two qualities, he noted, that "usually go together." He went on to make one of his most famous observations, that the "fundamental cause of the trouble is that in the modern world the stupid are cocksure while the intelligent are full of doubt." Russell's quip prefigured the scientific discovery of a cognitive bias--the Dunning–Kruger effect--that has been so resonant that it has penetrated popular culture, inspiring, for example, an opera song (from Harvard's annual Ig Nobel Award Ceremony): "Some people's own incompetence somehow gives them a stupid sense that anything they do is first rate. No surprise, then, that psychologist Joyce Ehrlinger prefaced a 2008 paper she wrote with David Dunning and Justin Kruger, among others, with Russell's comment--the one he later made in his 1951 book, New ...

Once you're called a "genius," what's left? No, getting called a "genius" is the final accolade, the last laudatory label for anyone. At least that's how several members of Mensa, an organization of those who've scored in the 98th percentile on an IQ test, see it. "I don't look at myself as a genius," LaRae Bakerink, a business consultant and a Mensa member, said. "I think that's because I see things other people have done, things they have created, discovered, or invented, and I look at those people in awe, because that's not a capability I have."

Once you're called a "genius," what's left? No, getting called a "genius" is the final accolade, the last laudatory label for anyone. At least that's how several members of Mensa, an organization of those who've scored in the 98th percentile on an IQ test, see it. "I don't look at myself as a genius," LaRae Bakerink, a business consultant and a Mensa member, said. "I think that's because I see things other people have done, things they have created, discovered, or invented, and I look at those people in awe, because that's not a capability I have."

Thomas Reardon puts a terrycloth stretch band with microchips and electrodes woven into the fabric--a steampunk version of jewelry--on each of his forearms. "This demo is a mind fuck," says Reardon, who prefers to be called by his surname only. He sits down at a computer keyboard, fires up his monitor, and begins typing. After a few lines of text, he pushes the keyboard away, exposing the white surface of a conference table in the midtown Manhattan headquarters of his startup. Only this time he is typing on…nothing. Yet the result is the same: The words he taps out appear on the monitor. Steven Levy is Backchannel's founder and Editor in Chief.