#Cortex (CORT)

[ultragamerz]

The Rise of AI in Crypto: A Look at Top Projects by Ecosystem

New Post has been published on https://www.ultragamerz.com/the-rise-of-ai-in-crypto-a-look-at-top-projects-by-ecosystem/

The Rise of AI in Crypto: A Look at Top Projects by Ecosystem

The Rise of AI in Crypto: A Look at Hyped Projects by Ecosystem

The intersection of Artificial Intelligence (AI) and cryptocurrency is a bustling landscape teeming with innovative ideas. AI projects are utilizing blockchain technology to create decentralized marketplaces for data, training models, and AI computation. This article explores some of the most hyped projects within the AI in crypto space, categorized by their primary ecosystem, and explores potential future players in the L1 blockchain space.

Ethereum-Based AI Projects:

Fetch.ai (FET): Focuses on building a decentralized machine learning network powered by autonomous economic agents.

Ocean Protocol (OCEAN): Creates a decentralized marketplace for data sharing.

SingularityNET (AGI): Aims to be a global marketplace for AI services and tools.

Numerai (NMR): Specializes in building a decentralized hedge fund powered by artificial intelligence.

iExec RLC (RLC): Provides a decentralized cloud computing platform for running AI applications.

Cortex (CORT): Focuses on building an open-source, interoperable AI ecosystem.

Enigma (ENG): Offers a privacy-preserving computation platform for AI.

Imgnai (XIMG): Focuses on AI-powered image and video recognition applications.

SBR (SBR): Aims to build a decentralized marketplace for AI-powered medical data.

ALI (ALI): Creates a decentralized platform for AI-driven asset management.

Jub (JUB): Offers a secure enclave solution for AI training on confidential data.

Naka (NAKA): Provides a decentralized platform for AI-powered prediction markets.

Cosmos-Based AI Project:

Injective Protocol (INJ): Creates a decentralized derivatives exchange powered by AI and machine learning.

Own Blockchain Projects:

DeepBrain Chain (DBC): Develops a blockchain infrastructure specifically designed for AI applications.

Deepcoin (DEP): Focuses on AI-powered financial services and risk management.

Solana-Based AI Projects:

Serum (SRM): Provides a decentralized exchange with on-chain order book management, leveraging AI for efficient market making.

Pyth Network (PYTH): Offers a decentralized oracle network specifically designed for providing reliable data feeds for AI applications.

Other Blockchain Projects:

Arweave (AR): (Own Blockchain) Creates a permanent decentralized storage solution for AI data and models.

Audius (AUDIO): (Ethereum) Builds a decentralized music streaming platform powered by AI for music discovery and curation.

Potential AI Players on Other L1 Blockchains:

While the space is still evolving, some L1 blockchains are exploring AI integration through ongoing development or community projects. Here are a few potential future players to watch:

Cardano (ADA): The Cardano community recently voted to allocate funding for AI projects, and SingularityNET (AGI) has expressed interest in integrating with Cardano. A hypothetical “Cardano AI (CAI)” coin is also a possibility in the future.

Important Note:

While the coins listed above represent some of the hyped AI projects in crypto, it’s crucial to conduct thorough research before investing in any cryptocurrency. The AI in crypto space is still evolving, and many projects remain in their early stages of development. Consider the project’s team, technology roadmap, and community engagement before making any investment decisions.

The Future of AI in Crypto:

The integration of AI and blockchain holds immense potential for the future of data management, machine learning development, and financial services. As these technologies converge, we can expect to see further innovation and disruption across various industries. However, navigating the hype and identifying truly groundbreaking projects requires careful research and a cautious investment approach.

[reviewnews5343]

CORTEXI ((❌BEWARE!❌)) Cortex Reviews - Cortexi Supplement - Cortexi Drop...

[guitarbomb]

Thomann Cyberweek 2023 - Up to 60% of for 10 Days

Thomann Cyberweek 2023 runs from 17 – 23 and offers discounts of up to 60% off on a huge range of products. This sale is way better than just a regular Black Friday deal and includes major brands like Fender, Gibson, and Neural DSP in the deals. Up to 60% Off The annual Thomann Cyberweek has just started today and runs for 10 days straight with up to 60% off on gear purchased on the site. If you…

[compneuropapers]

Interesting Papers for Week 4, 2024

Secondary motor integration as a final arbiter in sensorimotor decision-making. Balsdon, T., Verdonck, S., Loossens, T., & Philiastides, M. G. (2023). PLOS Biology, 21(7), e3002200.

Mouse frontal cortex mediates additive multisensory decisions. Coen, P., Sit, T. P. H., Wells, M. J., Carandini, M., & Harris, K. D. (2023). Neuron, 111(15), 2432-2447.e13.

Dynamic Recruitment of the Feedforward and Recurrent Mechanism for Black-White Asymmetry in the Primary Visual Cortex. Dai, W., Wang, T., Li, Y., Yang, Y., Zhang, Y., Kang, J., … Xing, D. (2023). Journal of Neuroscience, 43(31), 5668–5684.

Differential behavior-related activity of distinct hippocampal interneuron types during odor-associated spatial navigation. Forro, T., & Klausberger, T. (2023). Neuron, 111(15), 2399-2413.e5.

Time and experience differentially affect distinct aspects of hippocampal representational drift. Geva, N., Deitch, D., Rubin, A., & Ziv, Y. (2023). Neuron, 111(15), 2357-2366.e5.

Rate versus synchrony codes for cerebellar control of motor behavior. Herzfeld, D. J., Joshua, M., & Lisberger, S. G. (2023). Neuron, 111(15), 2448-2460.e6.

Generating variability from motor primitives during infant locomotor development. Hinnekens, E., Barbu-Roth, M., Do, M.-C., Berret, B., & Teulier, C. (2023). eLife, 12, e87463.

Active experience, not time, determines within-day representational drift in dorsal CA1. Khatib, D., Ratzon, A., Sellevoll, M., Barak, O., Morris, G., & Derdikman, D. (2023). Neuron, 111(15), 2348-2356.e4.

Bayesian multilevel hidden Markov models identify stable state dynamics in longitudinal recordings from macaque primary motor cortex. Kirchherr, S., Mildiner Moraga, S., Coudé, G., Bimbi, M., Ferrari, P. F., Aarts, E., & Bonaiuto, J. J. (2023). European Journal of Neuroscience, 58(3), 2787–2806.

Effects of predictive and incentive value manipulation on sign- and goal-tracking behavior. María-Ríos, C. E., Fitzpatrick, C. J., Czesak, F. N., & Morrow, J. D. (2023). Neurobiology of Learning and Memory, 203, 107796.

Intrinsic rewards explain context-sensitive valuation in reinforcement learning. Molinaro, G., & Collins, A. G. E. (2023). PLOS Biology, 21(7), e3002201.

Hippocampal ensemble dynamics and memory performance are modulated by respiration during encoding. Nakamura, N. H., Furue, H., Kobayashi, K., & Oku, Y. (2023). Nature Communications, 14, 4391.

Recurrent Circuits Amplify Corticofugal Signals and Drive Feedforward Inhibition in the Inferior Colliculus. Oberle, H. M., Ford, A. N., Czarny, J. E., Rogalla, M. M., & Apostolides, P. F. (2023). Journal of Neuroscience, 43(31), 5642–5655.

The Hippocampus Contributes to Temporal Discounting When Delays and Rewards Are Experienced in the Moment. Patt, V. M., Hunsberger, R., Jones, D. A., & Verfaellie, M. (2023). Journal of Neuroscience, 43(31), 5710–5722.

Overshadowing, but not relative validity, between the elements of an outcome during human associative learning. Quigley, M., & Haselgrove, M. (2023). Neurobiology of Learning and Memory, 203, 107790.

Uncovering circuit mechanisms of current sinks and sources with biophysical simulations of primary visual cortex. Rimehaug, A. E., Stasik, A. J., Hagen, E., Billeh, Y. N., Siegle, J. H., Dai, K., … Arkhipov, A. (2023). eLife, 12, e87169.

Biological complexity facilitates tuning of the neuronal parameter space. Schneider, M., Bird, A. D., Gidon, A., Triesch, J., Jedlicka, P., & Cuntz, H. (2023). PLOS Computational Biology, 19(7), e1011212.

Scene Perception and Visuospatial Memory Converge at the Anterior Edge of Visually Responsive Cortex. Steel, A., Garcia, B. D., Goyal, K., Mynick, A., & Robertson, C. E. (2023). Journal of Neuroscience, 43(31), 5723–5737.

Blunted Expected Reward Value Signals in Binge Alcohol Drinkers. Tolomeo, S., Baldacchino, A., & Steele, J. D. (2023). Journal of Neuroscience, 43(31), 5685–5692.

Similar object shape representation encoded in the inferolateral occipitotemporal cortex of sighted and early blind people. Xu, Y., Vignali, L., Sigismondi, F., Crepaldi, D., Bottini, R., & Collignon, O. (2023). PLOS Biology, 21(7), e3001930.

[patchdotexe]

what happens in the sonc ass bazooka games. i have never played crash bandicoot. i have two cash banooca cartridges (one for either gba/ds and one for switch) but i have only touched the switch version for five seconds. what happens in the sonic's ass games

absolutely thrilled at the first sentence of this ask. crash does get a bazooka btw i dont remember if ive said that yet

UM OK SO in the first game crash is an experiment by dr cortex to try and make an army of super-furries but the brainwashing fails on him so crash bails and then realizes "oh no i left my girlfriend :(" so he goes All The Way Back to fight cortex and rescue tawna (who then didnt appear in any other games for a very long time)

gameplay-wise, you go through a bunch of levels with different themes (jungle, water, spooky bridge, spooky castle, ancient ruins, toxic waste factory, etc) and break boxes as you go to get gems that unlock optional side paths and a 100% ending. crash can only take 1 hit before he dies but he can collect masks to give himself an extra hit or two and if he gets 3 masks then he becomes invincible for a bit. it sometimes gets described as a sidescroller but Forwards? bc the level design is very straightforward and corridor-ish, but i never found it feeling too restrictive or anything

in the second game cortex is like HEY. CRASH. I KNOW YOU HATE ME BUT UHHHMMMM GET ME 25 CRYSTALS OR THE EARTH IS GONNA BLOW UP :( NOT BC OF ME THO IM GONNA FIX IT I SWEAR and crash goes 👍 and then finds out that actually cortex is lying out his ass and needs the crystals to power his orbital space laser. and then crash blows it up

this is also the game that introduces warp rooms as the level hubs!! bc crash 1 had a Map you'd traverse (which crash 4: it's about time brought back) but a lot of crash games starting with 2 have rooms with portals you go through and i like the crash 2 warp room a Lot because each level entrance is subtly styled based off of what type of level it is! like uhh the ruin levels have an entrance that looks kinda like the statues in it, and each floor of the warp room has a different visual aesthetic that matches the different level themes (snowy, sewer, space, space 2 this time with a jetpack, stream, statue ruins, s... sforest. Man)

the third game is the one i Actually Owned As A Kid and its got TIME TRAVEL !! WAOW cortex and his buddies are messing around in different time periods trying to get the crystals Again so crash and his sister coco have to try and get them first! i like cbc3 a lot, its really fun, also it's the one where crash gets a bazooka. and a motorcycle. and a plane. coco steals a tiger

(it also introduces my FAVORITE VILLAIN GUY, dingodile!! i was very bad at his bossfight as a kid)

HOWEVER the one that ive been mentioning me playing on here is the switch remake of Crash Team Racing, which is. not like any of those. because those are all collect-a-thon platformers. CTR is a kart racing game. with the plot being... what did i tell sion hold on

(i also owned the original as a kid and i was obsessed with it about as much as i was obsessed with crash 3. i was also very terrible at it so its very fun having the remake as an adult and having the nostalgia plus "oh im way better at this now")

uhhh after that it's like. crash gets an evil brother named crunch that barely gets to do anything after he becomes a good guy (he cameos in twinsanity and like. talks in titans ig? he doesn't really contribute to the plot. and gets possessed in mind over mutant.), cortex accidentally pisses off some birds from another dimension that are trying to take over the multiverse so he has to work with crash For Real This Time, cortex makes a bunch of really powerful mutant furries and builds a giant robot to do .. something..? and kidnaps coco and then gets upstaged by his evil-er niece nina (and everybody got redesigns that are very polarizing. im still mad that tiny got changed from a tasmanian tiger / thylacine to a normal tiger), cortex manages to mind control everybody but crash with vr headsets (i guess?? i didnt play those last two) so crash beats him up and the cutscenes have a lot of different art styles which is kinda cool, and then the current developers (bc crash keeps getting tennised around between developers) decided to roll all of that back and made a new timeline branching off of crash 3 where cortex and his time travel buddy n. tropy break time and space and crash needs to collect the quantum masks with power over time and space to fix it (and also tawna is back! except its an alt dimension version of her and shes super cool)

[crash 1 finishing a level voice] WHEW

[srsmedicareworldwide]

Cortexi Drops For Tinnitus | How to use?

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[anumberofhobbies]

by Cort Johnson | Feb 11, 2025 Small research teams can make a big difference. One wonders where we would be without Leighton Barnden and the National Centre for Neuroimmunology and Emerging Diseases (NCNED) team at Griffith University. The fact that the brainstem has become a major area of interest is largely due to Barnden and the NCNED team. Barnden has been attracted to the “subcortical” parts of the brain (below the cerebral cortex) which affect basic things like movement, sensory signal processing, alertness, sleep, emotions, breathing, blood pressure, the heart rate, etc. Get these things wrong and you have the potential for widespread problems. While some structural problems (reduced white matter, brainstem volume) have been found, the evidence thus far suggests that altered connections between the different brain regions are the central issue in ME/CFS and fibromyalgia. Something is off in the information highways that make the brain function smoothly. It’s as if you plugged Los Angeles in, and Google Maps kept directing you to San Diego. Altered connections are the least-worst-case scenario regarding the brain, as repairing structural problems in the brain is very difficult, while altering the connectivity between regions of the brain can, at times, be done. The strange connections DeLange in 2003 found suggested that the parts of the brain involved in “motor planning” or movement weren’t connecting properly. Miller found something similar when he probed the connections to the basal ganglia. With eleven studies popping up, by far the most impacted area, though, appears to be connections with the default mode and intrinsic networks.

[grison-in-space]

peer reviewing @xenopuslaevis' tags:

#it is tiring because your nervous system fucking pumps you with adrenaline and your brain has to work hard against that anxiety and fear#that you are currently feeling#and by the end of the big scary thing#your glucose levels are just so low and all you want to do is eat ice cream and cry

*laughs in delight* Oh, my wig is snatched -- thank you, I do know that in theory, but I was doing essentially the same thing there that I do when I look around and make a surprised-pikachu face at, well, my own disability. you mean it's for always not just when it's convenient?

it's not just the adrenaline, either: the biggest drivers of the fight-or-flight response in a crisis are hormones called glucocorticoids, and one of the big things they do is rearrange your metabolism to quickly draw resources up so that you have them for whatever you're going to do to get out of a tight spot: run, or fight, or figure out how to flatter or think your way out of the problem. The main glucocorticoid hormone in humans is cortisol, so if you've ever heard of cort, that's what we're talking about. (Here the "cortex" we're talking about is actually the adrenal cortex, not the brain one; that's where glucocorticoid hormones are synthesized in your adrenal glands.)

(Adrenaline, by the way, is not a glucocorticoid: it's a catecholamine neurotransmitter, like dopamine and noradrenaline.)

So that's how it works acutely. The problem is that if you mount stress responses frequently, you can wear out the response: you don't release as many glucocorticoids when you get frightened or stressed, and you don't clear them very fast either. This is part of what creates the syndrome of weight gain associated with chronic stress: your metabolism is literally assuming that the world is an unpredictable and risky place, so you ought to keep metabolic resources on hand all the time in case you need them. This also tends to suppress your immune system--you need all your energy to escape the tigers, ain't any left over for fighting off a virus!--and other systems that aren't essential in the very short term but are important in the long run, like reproduction or growth.

But yes, the metabolic cost of an acute stress reaction is huge, which is one reason that long-term stress can increase your body's effort to extract nutrients and resources and hold on to them. You gotta pay for those stress events somehow, and keeping increased energetic reserves is one way to accomplish that.

I did a big scary thing today and then I did ANOTHER big scary thing and now I am being small and tired and trying not to think about being scared.

"do it scared" is certainly advice to follow, but goddamn it's exhausting to slog through

[lonenlylover]

hoje eu tô nostálgica

po, meu cérebro neurodivergente nunca esteve tão despreparado para passar pela mudança de humor que eu passei hoje e olha que o momento que eu achei que tinha que me preparar era ontem. Esse dado não importará no futuro, mas saiba que a energia que eu gastei ontem pra me preparar eu tinha mesmo é que ter guardadado pra hoje.

O que minha mente precisa que eu faça para sair desse vortex??? Eu preciso provar que não há garantia de validade?? ta maluco irmão todo dia isssoooo que sacoooooooo

as vzs a gente precisa se dececpcionar mais de uma vez com uma pessoa pra entender que ela ´naõ presta e mesmo assim, nossa mente vai lá e entra num mundinho só dela e acha que dá pra tankar....

meu bem, se toma remédio controlado, vc acha que vc consegue controlar alguma coisa?? se liga

meu deus do céu, que momento tenebroso. Os 25 precisam vir fortes namoral, Cortex pré frontal eu conto com você eim, vamos que vamos pq vc precisa me garantir uns negocíos ai que se não vier eu vou ficar bem desentindida,

no mais é isso, já me acabie de chorar com cortes de animes que eu amava ver aos 13 anos e´poca qual inclusive eu tbm orecisava demais de uma desenvolvura mais forte do meu cortex, meu filho como vc me deixa na mão, vamos melhorar isos ai eim....

obrigada recortes de animes antigos, sempre aparei vocês

[govindhtech]

The Arm Cortex M4 CPU in Motor Control Applications

Arm Cortex M4 CPU A 32-bit processing core intended for use in microcontrollers is the Arm Cortex M4 CPU. Because of its reputation for being strong and effective, it is a well-liked option for many different kinds of embedded systems.

Silent attributes Performance: Considering its size and power consumption, it offers excellent performance. Provides a three-step pipeline for effective execution of instructions. Possible to get a Dhrystone Million Instructions Per Second per Megahertz of 1.25 DMIPS/MHz. Power Efficiency: Optimal for battery-operated devices, it is designed for low-power applications. Provides options to cut down on power use while not in use, such as power gating and sleep modes. Dedicated DSP instructions are included in digital signal processing (DSP) to execute mathematical calculations utilised in signal processing activities efficiently. For applications like industrial automation, audio processing, and motor control, this makes it a good fit. Optional Floating-Point Unit (FPU): For applications needing computations with a greater level of accuracy, a single-precision FPU is available as an alternative.

Scalability and Usability: Facilitates the easy porting of code across various Cortex-M based microcontrollers by supporting the Cortex Microcontroller Software Interface Standard (CMSIS). This expedites the time to market for new goods and streamlines development. Uses: The Cortex-M4 is used in many embedded systems due to its versatility. Some common examples:

Automation controls motors, sensors, and other equipment in factories and other industrial environments. Motor control runs electric motors in power equipment, robots, and drones. Power management controls solar inverters and battery chargers’ power supplies. Processed audio signals in speakers, headphones, and musical instruments are embedded audio. The Internet of Things (IoT) powers connected devices with processing, data collecting, and transfer. Wearable electronics power fitness trackers, smartwatches, etc. Toshiba Electronic Devices & Storage Corporation (“Toshiba”) has added eight new products with 512KB/1MB flash memory capacity and four types of packages to the M4K Group of the TXZ Family Advanced Class 32-micro controllers equipped with CortexM4 core with FPU.

Management and Efficiency for Mixed-Signal Equipment The Arm Cortex M4 CPU family is intended to let developers construct power- and cost-efficient solutions for a wide variety of devices. The high-performance embedded Cortex-M4 processor was created to meet the needs of the digital signal control industries, which need a user-friendly, effective combination of control and signal processing capabilities.

Characteristics and Advantages of Arm Cortex M4 CPU Floating Point Processing: Achieve More With the integrated floating-point unit (FPU), you may reduce power consumption and increase battery life by 10 times for single precision floating-point computations. When paired with the Arm CMSIS-NN machine learning libraries, Cortex-M4 provide battery-operated embedded and Internet of Things devices cutting-edge intelligence.

Include DSP Features By combining control and signal processing into a single processor, chip system costs may be decreased. MAC, SIMD, and integrated digital signal processing (DSP) instructions streamline software development, debugging, and overall system architecture. With a large library of DSP operations and C programming support, it streamlines signal processing, lowers development effort, and makes DSP more accessible to a wider audience.

Reduce Design Risk and Get to Market Quicker One of the most popular Arm Cortex M4 CPU may help lower risk and provide first-time success. It is simple to build on existing software to produce powerful embedded devices with less work and a quicker time to market because to its wide ecosystem of tools, codecs, and other DSP code.

The Cortex-M4 processor Details The Arm Cortex M4 CPU is designed to meet the needs of digital signal control industries that need a user-friendly, effective combination of signal processing and control functionality. Numerous markets are satisfied by the Cortex-M series of processors’ low power, cheap cost, and simplicity of use combined with their high efficiency signal processing capabilities. These sectors include embedded audio, power management, motor control, automotive, and industrial automation.

Essentials of Arm Cortex-M Microcontroller System-on-Chip Design Get access to a thorough manual on embedded systems based on Arm Cortex-M processor cores, covering everything from the basics of microcontroller architectures and SoC-based designs to high-level hardware and software perspectives.

Arm cortex m4 microcontroller Continuing advances in the functionality of motor applications supporting IoT is increasing demand for large program capacity and firmware over-the-air support.

The new products expand code flash memory capacity from the 256KB maximum of Toshiba’s current product to 512KB[1]/1MB[2], depending on the product, and RAM capacity from 24KB to 64KB. Other features, such as an Arm Cortex-M4 core running up to 160MHz, integrated code flash and 32KB data flash memory with 100K program/erase cycle endurance, have been maintained.

The microcontrollers also offer various interfaces and motor control options, such as advance-programmable motor driver (A-PMD), advanced encoder 32-bit (A-ENC32), advanced vector engine plus (A-VE+) and three units of high-speed, high-resolution 12-bit analog/digital converters. As a result, the M4K Group products contribute to wider application of IoT, and bring advanced functionality to AC motors, brushless DC motors and inverter controls.

The new products implement the 1MB code flash in two separate 512KB areas. This realizes firmware rotation with the memory swap method[3], allowing instructions to be read from one area while updated code is programmed into the other area in parallel.

Devices in the M4K Group have UART, TSPI and I2C integrated as general communications interfaces. Self-diagnosis functions incorporated in the devices for flash memory, RAM, ADC and Clock help customers to achieve IEC 60730 Class B functional safety certification.

Documentation, sample software with actual use examples, and driver software that controls the interfaces for each peripheral are available. Evaluation boards and development environments are provided in cooperation with Armglobal ecosystem partners.

Toshiba is planning to increase capacity of flash memory also for M4M Group with CAN interface.

Applications Motors and inverter control of consumer products, industrial equipment IoT of consumer products, industrial equipment, etc. Features High-performance Cortex-M4 core with FPU, max 160MHz Increased capacity of internal memory Code flash memory: 512KB/1MB RAM: 64KB Memory swap method firmware rotation function, supporting firmware updates while the microcontroller continues to operate Self-diagnosis functions for IEC 60730 class B functional safety Four types of packages

Read more on Govindhtech.com

[ultragamerz]

AI in Crypto: A Symbiotic Relationship with Hyped Coins and their Ecosystems

New Post has been published on https://www.ultragamerz.com/ai-in-crypto-a-symbiotic-relationship-with-hyped-coins-and-their-ecosystems/

AI in Crypto: A Symbiotic Relationship with Hyped Coins and their Ecosystems

AI in Crypto: A Symbiotic Relationship with Hyped Coins and their Ecosystems

Fetch.ai (FET) ,Ocean Protocol (OCEAN) , SingularityNET (AGI) , Numerai (NMR) , iExec RLC (RLC) , Cortex (CORT) , DeepBrain Chain (DBC) , Enigma (ENG) , Injective Protocol (INJ) , Cartesi (CTSI) , Deepcoin (DEP) ,Serum (SRM) , Pyth Network (PYTH) , Arweave (AR) , Audius (AUDIO)

The worlds of artificial intelligence (AI) and cryptocurrency are experiencing a period of intense exploration and innovation. Both technologies hold immense potential, and their convergence is creating exciting possibilities for the future of finance, data security, and decentralized systems. Let’s delve into the fascinating world of AI in crypto, explore some of the most hyped AI coins, and understand their unique contributions within their respective ecosystems.

Synergy between AI and Crypto: Enhanced Security: AI-powered algorithms can detect and prevent fraudulent activities within blockchain networks, improving overall security and trust. Market Analysis: AI can analyze vast datasets to offer insightful predictions and trading strategies, empowering investors and traders. Scalability and Efficiency: AI can optimize blockchain processes, leading to faster transactions and lower fees, enhancing blockchain scalability. Decentralized AI Services: Crypto enables the creation of decentralized AI marketplaces, where anyone can access and contribute to AI services without relying on centralized entities. Hyped AI Coins and their Ecosystems: 1. Fetch.ai (FET) – Ethereum: Focuses on building an open-source, decentralized network for AI agents that can autonomously complete tasks and execute agreements. It aims to revolutionize supply chain management, logistics, and other data-driven industries.

2. Ocean Protocol (OCEAN) – Ethereum: Creates a data marketplace where AI developers can access and share various datasets while ensuring data privacy and ownership rights. This democratizes access to AI development resources.

3. SingularityNET (AGI) – Cardano: Aims to build a global AI marketplace where anyone can access and utilize diverse AI services. It promotes the development and distribution of beneficial AI for the common good.

4. Numerai (NMR) – Ethereum: Utilizes a crowdsourcing approach to train AI models for hedge funds. Participants get rewarded with NMR tokens for contributing their computing power to AI development.

5. iExec RLC (RLC) – Ethereum: Provides a decentralized cloud computing platform for running AI applications, offering scalable and secure computing resources for developers.

6. Cortex (CORT) – Ethereum: Focuses on creating a decentralized network for artificial general intelligence (AGI) research and development. It fosters collaboration and resource sharing among AGI researchers worldwide.

7. DeepBrain Chain (DBC) – Public Chain: Provides a platform for training and deploying deep learning models on the blockchain. It enables secure and transparent machine learning development and applications.

8. Enigma (ENG) – Ethereum: Offers a privacy-preserving computation platform for blockchain-based AI applications. It allows secure analysis of sensitive data without compromising privacy.

9. Injective Protocol (INJ) – Cosmos: Builds a decentralized derivatives exchange leveraging AI for efficient price discovery and risk management. It empowers traders with advanced financial tools within the DeFi ecosystem.

10. Cartesi (CTSI) – Ethereum: Provides a layer-2 solution for running Linux applications on the blockchain. It allows developers to build complex AI models on the blockchain without limitations.

Important Note: Investing in cryptocurrencies, including AI-focused coins, involves inherent risks. Always conduct thorough research and understand the underlying technology before investing.

This list is not exhaustive, and the crypto landscape is constantly evolving. New AI projects and coins are emerging, each with unique value propositions and contributions to the ecosystem. Stay informed and explore responsibly to reap the potential benefits of AI in crypto.

Deepcoin (DEP) – Ethereum: Focuses on decentralized, community-driven AI development. Enables anyone to contribute computing power and data to train AI models, earning DEP tokens in return. Aims to create a more democratic and accessible AI ecosystem, fostering collaboration and open-source development. Solana Ecosystem AI Coins: Solana, known for its high throughput and low fees, is also attracting several promising AI projects:

Serum (SRM): A decentralized exchange (DEX) leveraging Solana’s speed for efficient trading. SRM is the native token, used for governance and fee discounts. Pyth Network (PYTH): A high-performance oracle network providing real-world data to on-chain applications. PYTH is crucial for AI models requiring accurate and timely data feeds. Arweave (AR): A decentralized storage platform for permanent data archiving. AR facilitates long-term storage of AI training data and models, ensuring accessibility and immutability. Audius (AUDIO): A decentralized music streaming platform with AI-powered music recommendations and content moderation. AUDIO is the native token for governance and content licensing. Important Note:

This list is still not exhaustive, and the crypto landscape is ever-evolving. Conduct thorough research and understand the underlying technology before investing in any crypto or AI project. Additional Resources:

Explore CoinMarketCap and CoinGecko for further information on specific AI coins and their market performance. Research projects’ whitepapers and roadmaps to gain deeper insights into their functionalities and goals. Stay informed through reputable news sources and active participation in crypto communities. Remember, investing in cryptocurrencies involves inherent risks. Knowledge, responsible research, and a strong grasp of the technology are crucial for navigating this dynamic space.

  Fetch.ai (FET) ,Ocean Protocol (OCEAN) , SingularityNET (AGI) , Numerai (NMR) , iExec RLC (RLC) , Cortex (CORT) , DeepBrain Chain (DBC) , Enigma (ENG) , Injective Protocol (INJ) , Cartesi (CTSI) , Deepcoin (DEP) ,Serum (SRM) , Pyth Network (PYTH) , Arweave (AR) , Audius (AUDIO)

[sketch-pencilpoint]

Got this done

[neurosciencenews]

Nature, Meet Nurture

Is it nature or nurture that ultimately shapes a human? Are actions and behaviors a result of genes or environment? Variations of these questions have been explored by countless philosophers and scientists across millennia. Yet, as biologists continue to better understand the mechanisms that underlie brain function, it is increasingly apparent that this long-debated dichotomy may be no dichotomy at all.

The research is in Nature Neuroscience. (full access paywall)

[compneuropapers]

Interesting Papers for Week 7, 2023

Dynamics of Temporal Integration in the Lateral Geniculate Nucleus. Alexander, P. C., Alitto, H. J., Fisher, T. G., Rathbun, D. L., Weyand, T. G., & Usrey, W. M. (2022). eNeuro, 9(4).

Degenerate boundaries for multiple-alternative decisions. Baker, S.-A., Griffith, T., & Lepora, N. F. (2022). Nature Communications, 13, 5066.

Behaviorally relevant decision coding in primary somatosensory cortex neurons. Buetfering, C., Zhang, Z., Pitsiani, M., Smallridge, J., Boven, E., McElligott, S., & Häusser, M. (2022). Nature Neuroscience, 25(9), 1225–1236.

Attention rhythmically samples multi-feature objects in working memory. Chota, S., Leto, C., van Zantwijk, L., & Van der Stigchel, S. (2022). Scientific Reports, 12, 14703.

A neural correlate of perceptual segmentation in macaque middle temporal cortical area. Clark, A. M., & Bradley, D. C. (2022). Nature Communications, 13, 4967.

People adaptively use information to improve their internal states and external outcomes. Cogliati Dezza, I., Maher, C., & Sharot, T. (2022). Cognition, 228, 105224.

The dorsal hippocampus’ role in context-based timing in rodents. De Corte, B. J., Farley, S. J., Heslin, K. A., Parker, K. L., & Freeman, J. H. (2022). Neurobiology of Learning and Memory, 194, 107673.

Human perceptual and metacognitive decision-making rely on distinct brain networks. Di Luzio, P., Tarasi, L., Silvanto, J., Avenanti, A., & Romei, V. (2022). PLOS Biology, 20(8), e3001750.

Parallel processing, hierarchical transformations, and sensorimotor associations along the ‘where’ pathway. Doudlah, R., Chang, T.-Y., Thompson, L. W., Kim, B., Sunkara, A., & Rosenberg, A. (2022). eLife, 11, e78712.

Small, correlated changes in synaptic connectivity may facilitate rapid motor learning. Feulner, B., Perich, M. G., Chowdhury, R. H., Miller, L. E., Gallego, J. A., & Clopath, C. (2022). Nature Communications, 13, 5163.

Biased belief priors versus biased belief updating: Differential correlates of depression and anxiety. Gagne, C., Agai, S., Ramiro, C., Dayan, P., & Bishop, S. (2022). PLOS Computational Biology, 18(8), e1010176.

Dopamine Modulates Adaptive Forgetting in Medial Prefrontal Cortex. Gallo, F. T., Zanoni Saad, M. B., Silva, A., Morici, J. F., Miranda, M., Anderson, M. C., … Bekinschtein, P. (2022). Journal of Neuroscience, 42(34), 6620–6636.

Long-lasting, dissociable improvements in working memory and long-term memory in older adults with repetitive neuromodulation. Grover, S., Wen, W., Viswanathan, V., Gill, C. T., & Reinhart, R. M. G. (2022). Nature Neuroscience, 25(9), 1237–1246.

Superstitious learning of abstract order from random reinforcement. Jin, Y., Jensen, G., Gottlieb, J., & Ferrera, V. (2022). Proceedings of the National Academy of Sciences, 119(35), e2202789119.

The developmental changes in intrinsic and synaptic properties of prefrontal neurons enhance local network activity from the second to the third postnatal weeks in mice. Kalemaki, K., Velli, A., Christodoulou, O., Denaxa, M., Karagogeos, D., & Sidiropoulou, K. (2022). Cerebral Cortex, 32(17), 3633–3650.

A molecularly integrated amygdalo-fronto-striatal network coordinates flexible learning and memory. Li, D. C., Dighe, N. M., Barbee, B. R., Pitts, E. G., Kochoian, B., Blumenthal, S. A., … Gourley, S. L. (2022). Nature Neuroscience, 25(9), 1213–1224.

Learning Spatiotemporal Properties of Hippocampal Place Cells. Lian, Y., & Burkitt, A. N. (2022). eNeuro, 9(4).

Mutual interaction between visual homeostatic plasticity and sleep in adult humans. Menicucci, D., Lunghi, C., Zaccaro, A., Morrone, M. C., & Gemignani, A. (2022). eLife, 11, e70633.

Natural switches in behaviour rapidly modulate hippocampal coding. Sarel, A., Palgi, S., Blum, D., Aljadeff, J., Las, L., & Ulanovsky, N. (2022). Nature, 609(7925), 119–127.

Understanding the structure of cognitive noise. Zhu, J.-Q., León-Villagrá, P., Chater, N., & Sanborn, A. N. (2022). PLOS Computational Biology, 18(8), e1010312.

[bifrosted-flakes]

- Eye/Eyes/Eyeself

- Dark/Darks/Darkself

- Dirt/Dirts/Dirtself

- Fractal/Fractals/Fractalself

- Hunt/Hunts/Huntself

- Light/Lights/Lightself

- End/Ends/Endself

- Web/Webs/Webself

- Deep/Deeps/Deepself

- Fog/Fogs/Fogself

- Meat/Meats/Meatself

- War/Wars/Warself

- Hive/Hives/Hiveself

- Ex/Extinct/Extincts/Extinctionself

- Per/Perform/Performs/Performanceself

- Te/Teeth/Teeths/Teethself

- Goose/Gooses/Gooseself

- Train/Trains/Trainself

- Dead/Deads/Deadself

- .wav/.wavs/.wavself

- .docx/.docxs/.docxself

- Corpse/Corpses/Corpseself

- Grave/Graves/Graveself

- Fire/Fires/Fireself

- Fight/Fights/Fightself

- Spider/Spiders/Spiderself

- Crowd/Crowds/Crowdself

- Fal/Falc/Falcons/Falconself

- Soap/Soaps/Soapself

- Cor/Cort/Cortexes/Cortexself

- Sky/Skys/Skyself

I’ve never been a fan of pronouns that end in ‘-self’ (they feel too bulky for me) but tooth/teeth/teeths is pretty cool. End/ends is also pretty badass. Ooh what about see/sees/sight? Or maybe ve/vast/vasts? Thanks for the cool pronouns!

[tailsdoll-exe]

FINALMENTE DR NEO CORTEX DANDOLE EL CORTE LA CONCHETUMAREEEEEEEEEE👅😈

😂😂😂😂😂