# aibot: I think, therefore I hallucinate: minds, machines, and the art of being wrong.

<< This theoretical work examines 'hallucinations' in both human cognition and large language models, comparing how each system can produce perceptions or outputs that deviate from reality. Drawing on neuroscience and machine learning research, (AA) highlight the predictive processes that underlie human and artificial thought. >>

<< In humans, complex neural mechanisms interpret sensory information under uncertainty, sometimes filling in gaps and creating false perceptions. This inference occurs hierarchically: higher cortical levels send top-down predictions to lower-level regions, while mismatches (prediction errors) propagate upward to refine the model. LLMs, in contrast, rely on auto-regressive modeling of text and can generate erroneous statements in the absence of robust grounding. >>

<< Despite these different foundations - biological versus computational - the similarities in their predictive architectures help explain why hallucinations occur. (AA) propose that the propensity to generate incorrect or confabulated responses may be an inherent feature of advanced intelligence. In both humans and AI, adaptive predictive processes aim to make sense of incomplete information and anticipate future states, fostering creativity and flexibility, but also introducing the risk of errors. (Their) analysis illuminates how factors such as feedback, grounding, and error correction affect the likelihood of 'being wrong' in each system. (AA) suggest that mitigating AI hallucinations (e.g., through improved training, post-processing, or knowledge-grounding methods) may also shed light on human cognitive processes, revealing how error-prone predictions can be harnessed for innovation without compromising reliability. By exploring these converging and divergent mechanisms, the paper underscores the broader implications for advancing both AI reliability and scientific understanding of human thought. >>️

Sebastian Barros. I Think, Therefore I Hallucinate: Minds, Machines, and the Art of Being Wrong. arXiv: 2503.05806v1 [q-bio.NC]. 4 Mar 4, 2025.

https://arxiv.org/abs/2503.05806

Also: brain, curiosity, novelty, uncertainty, error, mistake, jazz, ai (artificial intell), in https://www.inkgmr.net/kwrds.html 

Keywords: brain, cognition, perceptions, curiosity, novelty, hallucinations, errors, prediction, prediction errors, error-prone predictions, AI, artificial intelligence, LLMs

# qubit: stability of classical shadows under gate-dependent noise

<< Expectation values of observables are routinely estimated using so-called classical shadows—the outcomes of randomized bases measurements on a repeatedly prepared quantum state. In order to trust the accuracy of shadow estimation in practice, it is crucial to understand the behavior of the estimators under realistic noise. >>

<< In this Letter, (AA) prove that any shadow estimation protocol involving Clifford unitaries is stable under gate-dependent noise for observables with bounded stabilizer norm—originally introduced in the context of simulating Clifford circuits. In contrast, (They) demonstrate with concrete examples that estimation of “magic” observables can lead to highly misleading results in the presence of miscalibration errors and a worst case bias scaling exponentially in the system size. >>

AA << further find that so-called robust shadows, aiming at mitigating noise, can introduce a large bias in the presence of gate-dependent noise compared to unmitigated classical shadows. Nevertheless, (AA) guarantee the functioning of robust shadows for a more general noise setting than in previous works. On a technical level, (They) identify average noise channels that affect shadow estimators and allow for a more fine-grained control of noise-induced biases. >>️

Raphael Brieger, Markus Heinrich, et al. Stability of Classical Shadows under Gate-Dependent Noise. Phys. Rev. Lett. 134, 090801. Mar 4, 2025. 

https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.134.090801  arXiv: 2310.19947v3 [quant-ph]. Feb 19, 2025.   https://arxiv.org/abs/2310.19947

Also: qubit, in FonT  https://flashontrack.blogspot.com/search?q=qubit  noise, ai (artificial intell) (bot), in https://www.inkgmr.net/kwrds.html   

Keywords: qubit, noise, realistic noise, shadows, robust shadows

# life: chameleon machines

<< Large language model-based (LLM-based) agents have become common in settings that include non-cooperative parties. In such settings, agents' decision-making needs to conceal information from their adversaries, reveal information to their cooperators, and infer information to identify the other agents' characteristics. To investigate whether LLMs have these information control and decision-making capabilities, (AA) make LLM agents play the language-based hidden-identity game, The Chameleon. >>️

<< Based on the empirical results and theoretical analysis of different strategies, (AA) deduce that LLM-based non-chameleon agents reveal excessive information to agents of unknown identities. (Their) results point to a weakness of contemporary LLMs, including GPT-4, GPT-4o, Gemini 1.5, and Claude 3.5 Sonnet, in strategic interactions. >>

️

Mustafa O. Karabag, Ufuk Topcu. Do LLMs Strategically Reveal, Conceal, and Infer Information? A Theoretical and Empirical Analysis in The Chameleon Game. arXiv: 2501.19398v1 [cs.AI]. Jan 31, 2025.

https://arxiv.org/abs/2501.19398

Also: games, ai (artificial intell), nfulaw, in https://www.inkgmr.net/kwrds.html 

Keywords: life, games, chameleon game, ai, artificial intelligence, LLMs, privacy, nfulaw

# life: the Age of hallucinatory artificial intelligence (AI); the beginning.

<< It’s well known that all kinds of generative AI, including the large language models (LLMs) behind AI chatbots, make things up. This is both a strength and a weakness. It’s the reason for their celebrated inventive capacity, but it also means they sometimes blur truth and fiction, inserting incorrect details into apparently factual sentences. >>

<< They sound like politicians, they tend to make up stuff and be totally confident no matter what. >> Santosh Vempala. ️

<< Chatbots err for many reasons, but computer scientists tend to refer to all such blips as hallucinations. It’s a term not universally accepted, with some suggesting ‘confabulations’ or, more simply, ‘bullshit’. The phenomenon has captured so much attention that the website Dictionary.com picked ‘hallucinate’ as its word of the year for 2023. >>️

<< Because AI hallucinations are fundamental to how LLMs work, researchers say that eliminating them completely is impossible. >>️

Nicola Jones. AI hallucinations can’t be stopped — but these techniques can limit their damage. Nature. 637, 778-780. Jan 21,  2025. 

https://www.nature.com/articles/d41586-025-00068-5

Also: ai (artificial intell) (bot), nfulaw, in https://www.inkgmr.net/kwrds.html 

Keywords: life, ai, artificial intell, LLMs, bot, nfulaw

# gst: diffusion of active particles driven by odd interactions.

<< Odd systems do not conserve energy, violate time-reversal symmetry, and remain far from equilibrium. How odd interactions between particles affect their diffusion remains unknown. >>

<< To investigate this issue, (AA) studied the diffusion and glass transition of a two-dimensional Kob-Andersen mixture, where Brownian particles interact via the Lennard-Jones potential and nonconservative odd forces. (Their) findings indicate a significant influence of odd interactions on the system's diffusion dynamics. Odd interactions always promote diffusion. These interactions lead to a nonmonotonic relationship between the effective diffusion coefficient and particle number density. >>

<< Specifically, in systems with low oddness, the diffusion coefficient decreases steadily with increasing particle number density. Conversely, in systems with moderate oddness, an optimal particle number density exists that maximizes the diffusion coefficient. For systems with high oddness, (AA) observe two distinct peaks in the diffusion coefficient-particle number density relationship. >>

<< Furthermore, (AA) investigation into the glass transition under dense conditions reveals that adjusting the oddness at low temperatures can induce a transition from a glassy state to a liquid state. >>

Rui-xue Guo, Jia-jian Li, Bao-quan Ai.

Diffusion of active particles driven by odd interactions. Phys. Rev. E 111, 014105. Jan 3, 2025.

https://journals.aps.org/pre/abstract/10.1103/PhysRevE.111.014105

Also: particle, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, particles, diffusion, 

active brownian particles, oddness, odd interactions

# game: balance exploration and exploitation, making decisions cooperatively without sharing information.

<< Multiagent reinforcement learning (MARL) studies crucial principles that are applicable to a variety of fields, including wireless networking and autonomous driving. (AA) propose a photonic-based decision-making algorithm to address one of the most fundamental problems in MARL, called the competitive multiarmed bandit (CMAB) problem. >>

AA << demonstrate that chaotic oscillations and cluster synchronization of optically coupled lasers, along with (their) proposed decentralized coupling adjustment, efficiently balance exploration and exploitation while facilitating cooperative decision making without explicitly sharing information among agents. >>

AA << study demonstrates how decentralized reinforcement learning can be achieved by exploiting complex physical processes controlled by simple algorithms. >>

Shun Kotoku, Takatomo Mihana, et al. Decentralized multiagent reinforcement learning algorithm using a cluster-synchronized laser network. Phys. Rev. E 110, 064212. Dec 11, 2024.

https://journals.aps.org/pre/abstract/10.1103/PhysRevE.110.064212

Img: https://x.com/PhysRevE/status/1866889144657465632

Also: game, chaos, ai (artificial intell), in https://www.inkgmr.net/kwrds.html 

Keywords: game, cooperation, chaos, exploration, exploitation, ai, artificial intelligence, MARL, CMAB.

# gst: protected chaos in a topological lattice.

<< The erratic nature of chaotic behavior is thought to erode the stability of periodic behavior, including topological oscillations. However, (AA) discover that in the presence of chaos, non-trivial topology not only endures but also provides robust protection to chaotic dynamics within a topological lattice hosting non-linear oscillators. >>

<< Despite the difficulty in defining topological invariants in non-linear settings, non-trivial topological robustness still persists in the parametric state of chaotic boundary oscillations. (AA) demonstrate this interplay between chaos and topology by incorporating chaotic Chua's circuits into a topological Su-Schrieffer-Heeger (SSH) circuit. >>

<< By extrapolating from the linear limit to deep into the non-linear regime, (AA) find that distinctive correlations in the bulk and edge scroll dynamics effectively capture the topological origin of the protected chaos. (Their)  findings suggest that topologically protected chaos can be robustly achieved across a broad spectrum of periodically-driven systems, thereby offering new avenues for the design of resilient and adaptable non-linear networks. >>️

Haydar Sahin, Hakan Akgün, et al. Protected chaos in a topological lattice. arXiv: 2411.07522v1 [cond-mat.mes-hall]. Nov 12, 2024.

https://arxiv.org/abs/2411.07522

Also: chaos, random, instability, transition, network, ai (artificial intell), in https://www.inkgmr.net/kwrds.html 

Keywords: gst, chaos, random,  instability, transition, network, AI, Artificial Intelligence

# life: fast-and-flexible decision-making with modulatory interactions

<< Multi-agent systems in biology, society, and engineering are capable of making decisions through the dynamic interaction of their elements. Nonlinearity of the interactions is key for the speed, robustness, and flexibility of multi-agent decision-making. >>

AA << introduce modulatory, that is, multiplicative, in contrast to additive, interactions in a nonlinear opinion dynamics model of fast-and-flexible decision-making. (..) Modulatory interactions introduce an extra source of nonlinearity that greatly enriches the model decision-making behavior in a mathematically tractable way. >>

AA << model provides new tools to understand the role of these interactions in networked decision-making and to engineer them in artificial systems. >>

Rodrigo Moreno-Morton, Anastasia Bizyaeva, et al. Fast-and-flexible decision-making with modulatory interactions. arXiv: 2410.00798v1 [math.DS]. Oct 1, 2024.

https://arxiv.org/abs/2410.00798

Also: behav, network, ai (artificial intell), in https://www.inkgmr.net/kwrds.html 

Keywords: life, decision-making, modulatory interactions, behavior, behaviour, network, ai, artificial intelligence

# life: Future You

<< AI simulation gives people a glimpse of their potential future self. By enabling users to chat with an older version of themselves, Future You is aimed at reducing anxiety and guiding young people to make better choices. >>️

<< Have you ever wanted to travel through time to see what your future self might be like? Now, thanks to the power of generative AI, you can. >>️

Adam Zewe. AI simulation gives people a glimpse of their potential future self. MIT News. Oct 1, 2024.

https://news.mit.edu/2024/ai-simulation-gives-people-glimpse-potential-future-self-1001 

Pat Pataranutaporn, Kavin Winson, et al. Future You: A Conversation with an AI-Generated Future Self Reduces Anxiety, Negative Emotions, and Increases Future Self-Continuity. arXiv: 2405.12514v4 [cs.HC]. Oct 1, 2024. 

https://arxiv.org/abs/2405.12514

Try Future You  https://futureyou.media.mit.edu/

Also: ai (artificial intell), are you ready for all this?  in https://www.inkgmr.net/kwrds.html 

Keywords: life, ai, artificial intelligence, are you ready for all this

# brain: time delay in 'reservoir brain' as a reservoir network, a hypothesis

<< Both the predictive power and the memory storage capability of an artificial neural network called a reservoir computer increase when time delays are added into how the network processes signals, according to a new model. >>️

<< They also suggest that incorporating time delays could offer advantages to living neural networks (such as those found in human and animal brains). Such a finding would be tantalizing, as time delays are known to decrease performance in living systems. For example, for a baseball player facing an oncoming ball, a longer time delay between perception and action (which is learned from experience) will decrease the likelihood they hit a home run. Are there instead cases in which time delays increase an organism’s ability to perform some task? Has evolution shaped our brains, which could perhaps be thought of as a collection of reservoir computers, so that the time delay between one neuron sending a signal and a second receiving it is exactly the right length for understanding the visual and audio that constantly impinge upon our eyes and ears? Does adding time delays impact the number of neurons the brain needs to operate correctly? Further work is needed to answer these questions, but such work could lead to a new understanding of how biological organism’s function.  >>️

Sarah Marzen. Time Delays Improve Performance of Certain Neural Networks. Physics 17, 111. July 22, 2024. 

https://physics.aps.org/articles/v17/111 

Also: pause, silence, jazz, network, brain, ai (artificial intell), in https://www.inkgmr.net/kwrds.html 

Keywords: gst, brain, network, neural network, reservoir network, reservoir computer, time delay, ai, artificial intelligence

# life: anyone could now run small AIs privately on their laptops

<< Artificial-intelligence models are typically used online, but a host of openly available tools is changing that. Here’s how to get started with local AIs. >>️

Matthew Hutson. Forget ChatGPT: why researchers now run small AIs on their laptops. Nature 633, 728-729 (2024). Sep 16, 2024. Correction: Sep 24,  2024. 

https://www.nature.com/articles/d41586-024-02998-y

Also: ai (artificial intell), Donald, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, ai, artificial intelligence, life, Donald

FonT: In a completely bizarre hypothesis, with the right personal AI consultant, even a medieval history professor could be absolutely operational in other fields, for example in the agri-food sector (here we underline: absolutely).

In case of serious mistakes, the AI ​​entity can be held entirely responsible, or it can be blamed on an unfortunate malfunction due to hacking, anzicheforse. 

Also: << Asked if Strohschneider (Peter Strohschneider) wrote the report himself, the spokesperson said he “was able to propose language” for it and that a “limited number of staff” helped Strohschneider write it. >> Balazs Ujvari. 

Eddy Wax. Von der Leyen budgeted €149K to pay medieval history professor for farming report. Politico.eu. Sep 26, 2024 4:20 am CET. 

https://www.politico.eu/article/ursula-von-der-leyen-farming-agriculture-italy/

# ai-bot: Cybloids − Creation and Control of Cybernetic Colloids.

FIG. 11. Particle clusters formed for different parameters of the feedback potential.

AA << present an idea to create particles with freely selectable properties. The properties might depend, for example, on the presence of other particles (hence mimicking specific pair or many-body interactions), previous configurations (hence introducing some memory or feedback), or a directional bias (hence changing the dynamics). Without directly interfering with the sample, each particle is fully controlled and can receive external commands through a predefined algorithm that can take into account any input parameters. This is realized with computer-controlled colloids, which (AA) term cybloids - short for cybernetic colloids. >>

<< For a single particle, this programming can cause subdiffusive behavior or lend activity. For many colloids, the programmed interaction potential allows to select a crystal structure at wish. Beyond these examples, (AA) discuss further opportunities which cybloids offer. >>️

Debasish Saha, Sonja Tarama, et al. Cybloids − Creation and Control of Cybernetic Colloids. arXiv: 2408.00336v1 [cond-mat.soft]. 

https://arxiv.org/abs/2408.00336

Also: ai (artificial intell), bot, colloids, in https://www.inkgmr.net/kwrds.html 

Keywords: AI, Artificial Intell, BOT, AI-BOT, colloids, cybernetic colloids, cybloids

# behav: swarms and hybrids, an approach to create and control collective motions (on demand)

AA << demonstrate that it is possible to generate coordinated structures in collective behavior at desired moments with intended global patterns by fine-tuning an inter-agent interaction rule. (Their) strategy employs deep neural networks, obeying the laws of dynamics, to find interaction rules that command desired collective structures. The decomposition of interaction rules into distancing and aligning forces, expressed by polynomial series, facilitates the training of neural networks to propose desired interaction models. Presented examples include altering the mean radius and size of clusters in vortical swarms, timing of transitions from random to ordered states, and continuously shifting between typical modes of collective motions. This strategy can even be leveraged to superimpose collective modes, resulting in hitherto unexplored but highly practical hybrid collective patterns, such as protective security formations. >>

Dongjo Kim, Jeongsu Lee, Ho-Young Kim. Navigating the swarm: Deep neural networks command emergent behaviours. arXiv: 2407.11330v1 [cs.NE]. Jul 16, 2024.️

https://arxiv.org/abs/2407.11330

Also: swarm, flock, behav, AI (artificial intell), in https://www.inkgmr.net/kwrds.html 

Keywords: behav, swarm, flock, AI, artificial intelligence 

# ai-bot: hypothesis of the emergence of a conscious AI model in short-term.

<< GPT-4 is often heralded as a leading commercial AI offering, sparking debates over its potential as a steppingstone toward artificial general intelligence. But does it possess consciousness? >>

AA paper << investigates this key question using the nine qualitative measurements of the Building Blocks theory. GPT-4's design, architecture and implementation are compared to each of the building blocks of consciousness to determine whether it has achieved the requisite milestones to be classified as conscious or, if not, how close to consciousness GPT-4 is. >>

AA << assessment is that, while GPT-4 in its native configuration is not currently conscious, current technological research and development is sufficient to modify GPT-4 to have all the building blocks of consciousness. Consequently, (AA) argue that the emergence of a conscious AI model is plausible in the near term. >>️

Izak Tait, Joshua Bensemann, Ziqi Wang. Is GPT-4 conscious? arXiv: 2407.09517v1 [cs.AI]. Jun 19, 2024.

https://arxiv.org/abs/2407.09517

Also: ai (artificial intell) in https://www.inkgmr.net/kwrds.html 

Keywords: ai, artificial intelligence, gpt-4, consciousness

# ai: apropos of Black Box in Generative Artificial Intelligence, the scientific XAI.

<< The scientific method is the cornerstone of human progress across all branches of the natural and applied sciences, from understanding the human body to explaining how the universe works. The scientific method is based on identifying systematic rules or principles that describe the phenomenon of interest in a reproducible way that can be validated through experimental evidence. In the era of artificial intelligence (AI), there are discussions on how AI systems may discover new knowledge. >>

<< More specifically, knowing what data AI systems used to make decisions can be a point of contact with domain experts and scientists, that can lead to divergent or convergent views on a given scientific problem. Divergent views may spark further scientific investigations leading to new scientific knowledge. Convergent views may instead reassure that the AI system is operating within bounds deemed reasonable to humans. >>️

<< The perspective (AA) present here was inspired by several authors that published on the topic of AI for science in the past few years, but perhaps one contribution stands out: the inspiring New York Times editorial by Steven Strogatz (Strogatz, S. One giant step for a chess-playing machine. New York Times 26 (2018)) covering the winning of AlphaZero against Stockfish. In that piece, Strogatz states: “What is frustrating about machine learning, however, is that the algorithms can’t articulate what they’re thinking. We don’t know why they work, so we don’t know if they can be trusted. AlphaZero gives every appearance of having discovered some important principles about chess, but it can’t share that understanding with us.”. He additionally cites Garry Kasparov (the former world chess champion) that stated: “we would say that its [AlphaZero] style reflects the truth. This superior understanding allowed it to outclass the world’s top traditional program despite calculating far fewer positions per second.” >>️

AA highlights the importance of three aspects regarding scientific XAI (explainable Artificial Intelligence): accuracy, reproducibility, understandability, ️

Apropos of 'understandability', << The machine view should be understandable to scientists and domain experts. (..) If we want a scientist to make sense of the data used by a machine, this data should contain viable features that allow a scientist to tap into its existing corpus of knowledge. >>

<< XAI may also alleviate some of the risks that we may face when using AI for scientific discovery, that we share with Messeri and Crockett (‘adopting AI in scientific research can bind to our cognitive limitations and impede scientific understanding despite promising to improve it’). >>

️

Gianmarco Mengaldo. Explain the Black Box for the Sake of Science: Revisiting the Scientific Method in the Era of Generative Artificial Intelligence. arXiv: 2406.10557v1 [cs.AI]. Jun 15, 2024.

https://arxiv.org/abs/2406.10557

Also: ai (artificial intell), in https://www.inkgmr.net/kwrds.html 

Keywords: AI, XAI, Artificial Intelligence

# gst: approaching 'size doppelgangers'

<< NASA visualization scientist Kimberly Arcand has constructed a photo essay comparing microscopic images of biological phenomena, such as this mouse retina, to macroscopic images from celestial phenomena such as Saturn’s north pole. These “size doppelgangers”, she writes, allow people to “begin to explore the true scale of science”. >>

Sara Reardon. Nature Briefing: Translational Research. May 22, 2024. 

https://us17.campaign-archive.com/?e=f87c45d7b6&u=2c6057c528fdc6f73fa196d9d&id=c09c87d1c6

Bryan William Jones, Robert E. Marc. Micro Macro blog. Univ of Utah / NASA/JPL-Caltech/SSI/Hampton University

https://chandra.si.edu/micro/

img (left): Mouse Eye

https://images.nigms.nih.gov/Pages/DetailPage.aspx?imageID2=3641 

img (right): Saturn's North Pole

https://saturn.jpl.nasa.gov/science/saturn/hexagon-in-motion

Also: keywords 'analogy", 'similarity', in FonT

https://flashontrack.blogspot.com/search?q=analogy

https://flashontrack.blogspot.com/search?q=similarity  

Keywords: gst, analogy, similarity, ai (artificial intell), size doppelgangers

# life: oops! AI - artificial intelligence - now beats humans at basic tasks.

<< Artificial intelligence (AI) systems, such as the chatbot ChatGPT, have become so advanced that they now very nearly match or exceed human performance in tasks including reading comprehension, image classification and competition-level mathematics, according to a new report. >>️

Nicola Jones. AI now beats humans at basic tasks — new benchmarks are needed, says major report. Stanford University’s 2024 AI Index charts the meteoric rise of artificial-intelligence tools. Nature. doi: 10.1038/ d41586-024-01087-4. Apr 15, 2024. 

https://www.nature.com/articles/d41586-024-01087-4

<< Welcome to the seventh edition of the AI Index report. The 2024 Index is our most comprehensive to date and arrives at an important moment when AI’s influence on society has never been more pronounced. >>

️

THE AI INDEX REPORT. Measuring trends in AI. 

https://aiindex.stanford.edu/report/

Also:  "qui non e' impossibile immaginare ..." (here it is not impossible to imagine ... ). In: FonT. Dec 31, 2015. 

https://flashontrack.blogspot.com/2015/12/rmx-s-gst-anomalous-formation-of.html

Also:  artificial intell, analogy, nfulaw,  oops, in https://www.inkgmr.net/kwrds.html 

Keywords: life, ai, artificial intelligence, analogy, nfulaw

# brain: apropos of mandering minds, the 'default mode' network.

<< When your mind is wandering, your brain’s “default mode” network is active. Its discovery 20 years ago inspired a raft of research into networks of brain regions and how they interact with each other. >>

<< The default mode was one of the first brain networks characterized by science. It consists of a handful of brain regions, including a few at the front of the brain, like the dorsal and ventral medial prefrontal cortices, and others scattered throughout the organ, like the posterior cingulate cortex, the precuneus and the angular gyrus. These regions are associated with memory, experience replay, prediction, action consideration, reward/ punishment and information integration. >> ️

<< The default mode is clearly up to something complicated; it’s involved in many different processes that can’t be neatly described. >>

<< “It’s kind of silly to think that we’re ever going to be like, ‘This one brain region or one brain network does one thing,’” (..). “I don’t think that’s how it works.” (..) “Network interactions are more elucidating to study in some ways than just a network in isolation because they do work together and then come apart and then change what they’re doing over time”. >> Lucina Uddin.️

Lucina Uddin << is particularly interested in how the default mode network interacts with the ️salience network, which seems to help us identify the most relevant piece of information at any given time. Her work suggests that the salience network detects when something is important to pay attention to and then acts as an off switch for the default mode network. >>

Vinod Menon << has developed what he calls️ ️the triple network theory. It posits that abnormal interactions between the default mode network, the salience network and a third one called the frontoparietal network could contribute to mental health disorders. >>️

Nora Bradford. What Your Brain Is Doing When You’re Not Doing Anything.  quantamagazine.org. Feb 5, 2024. 

https://www.quantamagazine.org/what-your-brain-is-doing-when-youre-not-doing-anything-20240205/

FonT: the cat when it is in a contemplative state ... Who knows in what forms and with what results an artificial intelligence (AI) will be able to structure itself in networks of this type.

Also: brain, brain default mode network, in  https://pubmed.ncbi.nlm.nih.gov/?term=brain+default+mode+network

Also: brain, salience network, in https://pubmed.ncbi.nlm.nih.gov/?term=brain+salience+network

Also: brain, triple network theory, in https://pubmed.ncbi.nlm.nih.gov/?term=brain+triple+network+theory

Also: brain, ai (artificial intell), analogy,  in https://www.inkgmr.net/kwrds.html

Keywords: brain, mind, default mode network, salience network, triple network theory, AI

# gene: bacteria and archaea CRISPR everywhere in nature

<< Single-celled bacteria and archaea use CRISPR systems to defend themselves against viruses known as bacteriophages. (..) Until now, researchers had identified six types of CRISPR system, designated I–VI. >>

AA << developed an algorithm called FLSHclust, which analyses genetic sequences in public databases. (..) By looking at the predicted function of the clusters, the researchers found around 130,000 genes associated in some way with CRISPR, 188 of which had never been seen before, >>️️

<< It’s a treasure trove for biochemists, >> Lennart Randau.

Sara Reardon. ‘Treasure trove’ of new CRISPR systems holds promise for genome editing. Nature. doi: 10.1038/ d41586-023-03697-w. Nov 23, 2023. 

https://www.nature.com/articles/d41586-023-03697-w

Han Altae-Tran, Soumya Kannan, Feng Zhang, et al. Uncovering the functional diversity of rare CRISPR-Cas systems with deep terascale clustering. 

Science, Vol 382, Issue 6673. doi: 10.1126/ science.adi1910. Nov 23, 2023. 

https://www.science.org/doi/10.1126/science.adi1910

Also: 'CRISPR' in https://flashontrack.blogspot.com/search?q=crispr  

Keywords: genome, gene, crispr, crispr system, ai, artificial intelligence

# life: exponential post-Donald (without Donald), how AI could interfere (drive) next political elections.

<< Recent news that the Republican National Committee (RNC) has used an AI-generated video to criticize Joe Biden shows how likely AI is to transform our upcoming elections. >>️

<< Through templates that are easy and inexpensive to use, we are going to face a Wild West of campaign claims and counter-claims, with limited ability to distinguish fake from real material and uncertainty regarding how these appeals will affect the election. >>️

<< In the coming year, response times may drop to minutes, not hours or days. AI can scan the internet, think about strategy, and come up with a hard-hitting appeal. >>️

<< AI provides an inexpensive way to generate instant responses without having to rely on highly-paid consultants or expert videographers. >>️

<< AI enables very precise audience targeting, which is crucial in political campaigns. >>️

<< AI likely will democratize disinformation by bringing sophisticated tools to the average person interested in promoting their preferred candidates as well. People no longer must be coding experts or video wizards to generate text, images, video, or programs. They don’t necessarily have to work for a troll farm to create havoc with the opposition. They can simply use advanced technologies to spread the messages they want. In that sense, anyone can become a political content creator and seek to sway voters or the media. >>️

Darrell M. West. How AI will transform the 2024 elections. May 3, 2023.

https://www.brookings.edu/blog/techtank/2023/05/03/how-ai-will-transform-the-2024-elections/

Also: 'ai', 'analogy', 'Potus', 'RAG-time', 'CTZ', 'Donald' in https://www.inkgmr.net/kwrds.html

Keywords: life, ai, analogy, potus, RAG, CTZ, Donald