The AI battle is heating up as Google’s Sparrow chatbot gears up to take on OpenAI’s ChatGPT. Will Sparrow be the one to reach AGI? Don’t miss out on this exciting competition!
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Through the issue of mental representation addressed in the previous article, it is possible to get a first idea about the theoretical discontinuity between traditional cognitive science and more recent approaches gathered under the umbrella of so-called 4E Cognition. In fact, in many cases those latter reflect — directly or in a collateral way — the attempt to overcome the problem of representation in human cognition, even thought, as we’re going to say, this doesn’t entail a unite consensus at all.
4E Cognition has not to be seen as a specific and well-defined theoretical system, rather, it is a term referring to all those works (hypothesis, theories, experiments, etc.) which deviate from the traditional representational-computational model of cognition (see part 1), taking a dynamic and enactive approach, namely, conceiving cognition as embodied, embedded, enactive and extended (that’s why 4E). In a nutshell, mental states and cognitive processes would be: embodied when they are partly constituted by bodily processes; embedded when there is an essential causal dependence between such states and processes and the environment; enacted when the actions of the subject can partly constitute these states and processes; and extended when objects or processes in the environment can partly constitute those states and processes [4].
Here you can find a quick conversational introduction to 4E cognition made by professor Shaun Gallagher:
Please join the Project on Nuclear Issues for a book launch event, featuring “The Fragile Balance of Terror: Deterrence in the Nuclear Age.”
In The Fragile Balance of Terror, edited by Vipin Narang and Scott Sagan, the foremost experts on nuclear policy and strategy offer insight into an era rife with more nuclear powers. Some of these new powers suffer domestic instability, others are led by pathological personalist dictators, and many are situated in highly unstable regions of the world—a volatile mix of variables. The increasing fragility of deterrence in the twenty-first century is created by a confluence of forces: military technologies that create vulnerable arsenals, a novel information ecosystem that rapidly transmits both information and misinformation, nuclear rivalries that include three or more nuclear powers, and dictatorial decision making that encourages rash choices. The nuclear threats posed by India, Pakistan, Iran, and North Korea are thus fraught with danger.
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The AI, called ProGen, works in a similar way to AIs that can generate text. ProGen learned how to generate new proteins by learning the grammar of how amino acids combine to form 280 million existing proteins. Instead of the researchers choosing a topic for the AI to write about, they could specify a group of similar proteins for it to focus on. In this case, they chose a group of proteins with antimicrobial activity.
The researchers programmed checks into the AI’s process so it wouldn’t produce amino acid “gibberish”, but they also tested a sample of the AI-proposed molecules in real cells. Of the 100 molecules they physically created, 66 participated in chemical reactions similar to those of natural proteins that destroy bacteria in egg whites and saliva. This suggested that these new proteins could also kill bacteria.
The researchers selected the five proteins with the most intense reactions and added them to a sample of Escherichia coli bacteria. Two of the proteins destroyed the bacteria.
Bryan Johnson releases his rejuvenation protocol:
Blueprint is a public science experiment to determine whether it’s possible to stay the same biological age. This requires slowing down aging processes as much as possible and then reversing the aging that has happened. Currently my speed of aging is .76 (DunedinPACE). That means for every 365 days each year, I age 277 days. My goal is to remain the same age biologically for every 365 days that pass.
I openly share (for free!) my diet, exercise and other protocols so that others can benefit and try to improve upon what I’m doing. I also openly share my health data as data is better than human opinion at guiding decision making. You can find everything here: https://blueprint.bryanjohnson.co/
Posted in futurism
Ji didn’t only stick with it; in the fall semester, she ran rehearsals and organized concerts as co-director. She also served as president and is now an historian going into her final undergraduate semester.
Pursuing interdisciplinary interests
Whether exploring poetry, scientific research, or challenging historical norms to make student life at MIT more inclusive, Ji is deliberate about doing things her own way.
Twelve-hour (12 h) ultradian rhythms are a well-known phenomenon in coastal marine organisms. While 12 h cycles are observed in human behavior and physiology, no study has measured 12 h rhythms in the human brain. Here, we identify 12 h rhythms in transcripts that either peak at sleep/wake transitions (approximately 9 AM/PM) or static times (approximately 3 PM/AM) in the dorsolateral prefrontal cortex, a region involved in cognition. Subjects with schizophrenia (SZ) lose 12 h rhythms in genes associated with the unfolded protein response and neuronal structural maintenance. Moreover, genes involved in mitochondrial function and protein translation, which normally peak at sleep/wake transitions, peak instead at static times in SZ, suggesting suboptimal timing of these essential processes.
You can grasp a hand. You can also grasp a concept. One is literal. One is metaphorical. Our brains know the difference, but would we be able to understand the latter without the former?
Previous studies have suggested that our understanding of metaphors may be rooted in our bodily experience. Some functional MRI, o fMRI, brain imaging studies have indicated, for example, that when you hear a metaphor such as “she had a rough day,” regions of the brain associated with tactile experience are activated. If you hear, “he’s so sweet,” areas associated with taste are activated. And when you hear action verbs used in a metaphorical context, like “grasp a concept,” regions involved in motor perception and planning are activated.
A study by University of Arizona researcher Vicky Lai, published in the journal Brain Research, builds on this research by looking at when, exactly, different regions of the brain are activated in metaphor comprehension and what that tells us about the way we understand language.
Starting with the emergence of quantum mechanics, the world of physics has been divided between classical and quantum physics. Classical physics deals with the motions of objects we typically see every day in the macroscopic world, while quantum physics explains the exotic behaviors of elementary particles in the microscopic world.
Many solids or liquids are composed of particles interacting with one another at close distances, which sometimes results in the rise of “quasiparticles.” Quasiparticles are long-lived excitations that behave effectively as weakly interacting particles. The idea of quasiparticles was introduced by the Soviet physicist Lev Landau in 1941, and ever since has been highly fruitful in quantum matter research. Some examples of quasiparticles include Bogoliubov quasiparticles (i.e. “broken Cooper pairs”) in superconductivity, excitons in semiconductors, and phonons.
Examining emergent collective phenomena in terms of quasiparticles provided insight into a wide variety of physical settings, most notably in superconductivity and superfluidity, and recently in the famous example of Dirac quasiparticles in graphene. But so far, the observation and use of quasiparticles have been limited to quantum physics: in classical condensed matter, the collision rate is typically much too high to allow long-lived particle-like excitations.
Tech giants from Google to Amazon and Alibaba —not to mention nation-states vying for technological supremacy—are racing to dominate this space. The global quantum-computing industry is projected to grow from $412 million in 2020 to $8.6 billion in 2027, according to an International Data Corp. analysis.
Whereas traditional computers rely on binary “bits”—switches either on or off, denoted as 1s and 0s—to process information, the “qubits” that underpin quantum computing are tiny subatomic particles that can exist in some percentage of both states simultaneously, rather like a coin spinning in midair. This leap from dual to multivariate processing exponentially boosts computing power. Complex problems that currently take the most powerful supercomputer several years could potentially be solved in seconds. Future quantum computers could open hitherto unfathomable frontiers in mathematics and science, helping to solve existential challenges like climate change and food security. A flurry of recent breakthroughs and government investment means we now sit on the cusp of a quantum revolution. “I believe we will do more in the next five years in quantum innovation than we did in the last 30,” says Gambetta.
But any disrupter comes with risks, and quantum has become a national-security migraine. Its problem-solving capacity will soon render all existing cryptography obsolete, jeopardizing communications, financial transactions, and even military defenses. “People describe quantum as a new space race,” says Dan O’Shea, operations manager for Inside Quantum Technology, an industry publication. In October, U.S. President Joe Biden toured IBM’s quantum data center in Poughkeepsie, N.Y., calling quantum “vital to our economy and equally important to our national security.” In this new era of great-power competition, China and the U.S. are particularly hell-bent on conquering the technology lest they lose vital ground. “This technology is going to be the next industrial revolution,” says Tony Uttley, president and COO for Quantinuum, a Colorado-based firm that offers commercial quantum applications. “It’s like the beginning of the internet, or the beginning of classical computing.”
