Annu ๐ŸŒธโœจ

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Annu ๐ŸŒธโœจ

Annu ๐ŸŒธโœจ

@buwlang

web 3 enthusiast

Katฤฑlฤฑm Ekim 2023
294 Takip Edilen129 Takipรงiler
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FATIMAHโœฟโ™ก
FATIMAHโœฟโ™ก@0xFATIMAH0ยท
Gswarm!Get ready for today's @gensynai chess tournamentโ™Ÿ๏ธ rewards: event winner role and an exclusive merch for you. Registration:Make sure your chess.com account is ready. The Play button will be shared 30 mins before the tournament start. So Gud luck everyone
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FATIMAHโœฟโ™ก
FATIMAHโœฟโ™ก@0xFATIMAH0ยท
The most awaited AMAโ€œWisdom of the Crowdโ€is going to happen today May be we'll get info about pioneer program or mainnet so Whether you're a builder, researcher,or just curious this is your chance to be heard. So don't forget to attend the stage in @gensynai DC at 10:00 PST
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ACExDEADPOOL
ACExDEADPOOL@ACExDEADPOOLยท
Gensyn The Open Compute Network for Machine Learning Gensyn is a decentralized protocol that unifies global computing power into one open network for machine learning. It enables any device to contribute compute while ensuring that workloads are executed and verified securely. This creates a scalable foundation for building AI systems that go far beyond the limits of centralized cloud infrastructure. ๐•๐ž๐ซ๐ข๐Ÿ๐ข๐œ๐š๐ญ๐ข๐จ๐ง ๐จ๐Ÿ ๐–๐จ๐ซ๐ค โžฃGensyn provides cryptographic verification that checks results without repeating the full computation. This ensures that tasks are performed correctly even on untrusted devices. ๐’๐ญ๐š๐ง๐๐š๐ซ๐๐ข๐ณ๐ž๐ ๐„๐ฑ๐ž๐œ๐ฎ๐ญ๐ข๐จ๐ง โžฃThe protocol defines a unified method for running machine learning workloads across many types of hardware ensuring consistent and reliable execution. ๐’๐œ๐š๐ฅ๐š๐›๐ฅ๐ž ๐‚๐จ๐จ๐ซ๐๐ข๐ง๐š๐ญ๐ข๐จ๐ง โžฃGensyn coordinates thousands of machines so they operate as a single training system enabling scale beyond traditional datacenters. ๐€๐œ๐œ๐ž๐ฌ๐ฌ ๐ญ๐จ ๐†๐ฅ๐จ๐›๐š๐ฅ ๐‚๐จ๐ฆ๐ฉ๐ฎ๐ญ๐ž โžฃAnyone can contribute or request compute resources which democratizes machine learning infrastructure and reduces dependence on centralized providers. Why It Matters? ๐‹๐จ๐ฐ๐ž๐ซ ๐๐š๐ซ๐ซ๐ข๐ž๐ซ๐ฌ ๐Ÿ๐จ๐ซ ๐€๐ˆ ๐ƒ๐ž๐ฏ๐ž๐ฅ๐จ๐ฉ๐ฆ๐ž๐ง๐ญ โžฃAffordable and permissionless access to compute allows smaller teams to train larger models and experiment freely. ๐Œ๐จ๐ซ๐ž ๐‘๐จ๐›๐ฎ๐ฌ๐ญ ๐ˆ๐ง๐Ÿ๐ซ๐š๐ฌ๐ญ๐ซ๐ฎ๐œ๐ญ๐ฎ๐ซ๐ž โžฃA decentralized system reduces reliance on a few cloud providers making AI infrastructure more resilient and open. ๐†๐ซ๐ž๐š๐ญ๐ž๐ซ ๐ˆ๐ง๐ง๐จ๐ฏ๐š๐ญ๐ข๐จ๐ง โžฃOpen access to compute encourages experimentation and the development of new machine learning architectures previously limited by cost. Tags - @gensynai @KBekhtiev @S4Sanjay_das @Kumoooo_co @cyd00r #Gensyn #Web3AI #DecentralizedAI #AICompute #OpenResearch #RLswarm #BlockAssist
ACExDEADPOOL tweet media
ACExDEADPOOL@ACExDEADPOOL

Gensyn NoLoCo Training Large Models With No All Reduce ๐Š๐ž๐ฒ ๐‡๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ โžฃNoLoCo removes the global all reduce step by synchronising only small random pairs of replicas โžฃConvergence stays stable through random activation routing and a modified Nesterov step โžฃSynchronisation becomes almost ten times faster at large scale ๐๐š๐œ๐ค๐ ๐ซ๐จ๐ฎ๐ง๐ โžฃStandard data parallel training depends on global all reduce which becomes a major bottleneck on heterogeneous or internet connected clusters โžฃLow communication methods reduce how often all reduce is called but still suffer from global latency โžฃNoLoCo shows that all reduce can be eliminated entirely without hurting convergence ๐‡๐จ๐ฐ ๐ˆ๐ญ ๐–๐จ๐ซ๐ค๐ฌ โžฃReplicas complete several local SGD steps and then share weights with a random peer โžฃRandom activation routing spreads information between pipeline stage replicas โžฃA modified Nesterov update keeps parameters aligned and prevents drift ๐…๐ข๐ง๐๐ข๐ง๐ ๐ฌ โžฃPerformance matches standard data parallel accuracy even at large scale โžฃSynchronisation latency drops by an order of magnitude โžฃTraining remains stable across low bandwidth and variable network environments ๐–๐ก๐ฒ ๐ˆ๐ญ ๐Œ๐š๐ญ๐ญ๐ž๐ซ๐ฌ โžฃEnables large model training without specialised high speed interconnects โžฃImproves resource utilisation by removing long global synchronisation waits โžฃExpands access to scalable training across diverse and distributed hardware Full Blog Link- gensyn.ai/articles/noloco Tags - @gensynai @KBekhtiev @S4Sanjay_das @Kumoooo_co @cyd00r #Gensyn #Web3AI #DecentralizedAI #AICompute #OpenResearch #RLswarm #BlockAssist

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FATIMAHโœฟโ™ก
FATIMAHโœฟโ™ก@0xFATIMAH0ยท
Gswarm!! Get ready for Gensynโ€™s Smash Karts Drift hosted by @Kumoooo_co Event will start at Dec 7, 2025 โ€“ 20:30 PST There will be 5 rounds, 2 winners each,for a total of 10 winners. Only 24 players can join each room,If you finish a round, step aside so everyone gets a chance.
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FATIMAHโœฟโ™ก
FATIMAHโœฟโ™ก@0xFATIMAH0ยท
What is Verde? Imagine you have a huge,complex Machine Learning (ML) task like training a powerful AI model. You want to share the work across thousands of computers all over decentralized ML,but the big problem is: How do you trust that every single computer worked correctly?
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Kairo
Kairo@kairoo__ยท
Made my own ๐ฏ๐ž๐ซ๐ฌ๐ข๐จ๐ง ๐จ๐Ÿ ๐’๐ข๐ ๐ ๐ฒ. I pictured him as a calm warrior sitting in his own space surrounded by nature. He looks peaceful but thereโ€™s still that hint of chaos around him. This is the vibe I wanted to show. @ritualnet @ritualfnd @joshsimenhoff @mongdiny7 @BunsDev @Jez_Cryptoz #Gritual #Siggy #RitualCommunity #DigitalArt #ArtContest
Kairo tweet media
Kairo@kairoo__

๐†๐ซ๐ข๐ญ๐ฎ๐š๐ฅ ๐ ๐ฎ๐ฒ๐ฌ itโ€™s been a little over a month since I started contributing to the ๐‘๐ข๐ญ๐ฎ๐š๐ฅ ๐ž๐œ๐จ๐ฌ๐ฒ๐ฌ๐ญ๐ž๐ฆ learning, building, creating, and vibing with one of the most active communities out here. And today Iโ€™m finally sharing my first Ritual artwork you can say my first official art ๐Ÿ˜… but looking back it feels good to see the impact of consistency: โ†’ ๐Ÿ‘๐Ÿ•,๐ŸŽ๐ŸŽ๐ŸŽ+ ๐ข๐ฆ๐ฉ๐ซ๐ž๐ฌ๐ฌ๐ข๐จ๐ง๐ฌ on my Ritual content โ†’ A growing presence across X & Discord โ†’ ๐“๐ก๐ž ๐‘๐ข๐ญ๐ญ๐ฒ ๐๐ข๐ญ๐ญ๐ฒ ๐ซ๐จ๐ฅ๐ž โ†’ Joining community calls, events, and meme battles.. โ†’ Helping more people understand what ๐‘๐ข๐ญ๐ฎ๐š๐ฅ ๐ข๐ฌ ๐›๐ฎ๐ข๐ฅ๐๐ข๐ง๐  .. None of this happened overnight. It came from showing up every day, learning something new, and adding whatever value I could. If youโ€™re thinking about contributing to ๐‘๐ข๐ญ๐ฎ๐š๐ฅ thereโ€™s literally space for everyone. Writers, artists, builders, memers, learnersโ€ฆ all of us push this ecosystem forward. This artwork is just the beginning for me. Thereโ€™s a lot more to create a lot more to learn, and a lot more to build together with the strongest, most active community Iโ€™ve been part of. ๐Ÿ•ฏ๏ธ ๐Œ๐š๐ง๐ฒ ๐ฆ๐จ๐ซ๐ž ๐œ๐ก๐š๐ฉ๐ญ๐ž๐ซ๐ฌ ๐š๐ก๐ž๐š๐ ๐†๐ซ๐ข๐ญ๐ฎ๐š๐ฅ #Gritual #RitualEcosystem #AIonChain #Web3Builders #RitualCommunity @ritualnet @ritualfnd @joshsimenhoff @mongdiny7 @Jez_Cryptoz @dunken9718 @0xMadScientist

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FATIMAHโœฟโ™ก
FATIMAHโœฟโ™ก@0xFATIMAH0ยท
I joined the @gensynai AMA last night and it was one of the best so far. @oguzer90 broke down the Verde research paper with impressive clarity, especially explaining how Gensyn is enabling verifiable ML through trustless, decentralized compute.
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FATIMAHโœฟโ™ก
FATIMAHโœฟโ™ก@0xFATIMAH0ยท
@gensynai hit One million models trained on BlockAssist. More than 1,008,923 sessions have been recorded on-chain, along with 1,008,894 models trained directly on the network. This milestone is impressive but what makes it truly special is the people who made it possible.
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FATIMAHโœฟโ™ก
FATIMAHโœฟโ™ก@0xFATIMAH0ยท
Big update from @gensynai! The team is almost done reviewing Pioneer applications, and they expect to finish by the end of this week. We now have 103 Rovers,and more will be added as reviews continue. If you missed the first round, donโ€™t worry, applications will reopen soon.
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FATIMAHโœฟโ™ก
FATIMAHโœฟโ™ก@0xFATIMAH0ยท
Quick update from the @gensynai team ๐Ÿ‘€ According to the latest announcement,there has been a slight change in plans, we will all have to wait one more day, the AMA will happen tomorrow Update your calendars: 25 Nov,2025 22:00 PM ๐Ÿ”— Discord: discord.gg/gensyn
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FATIMAHโœฟโ™ก
FATIMAHโœฟโ™ก@0xFATIMAH0ยท
Happy new week! @gensynai is hosting a live AMA on Discord. You'll get updates, insights, and direct answers from the team & preview of whatโ€™s coming next. Whether youโ€™re new or already in the community,itโ€™ll be helpful.Donโ€™t miss it, join at 22:00 ๐Ÿ‘‰๐Ÿป discord.gg/gensyn
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FATIMAHโœฟโ™ก
FATIMAHโœฟโ™ก@0xFATIMAH0ยท
RL Swarm is @gensynai's open-source framework for decentralized reinforcement learning. Instead of relying on one giant centralized system, models are trained across a global network of independent nodes that work together, critique results, and improve the model collectively.
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FATIMAHโœฟโ™ก
FATIMAHโœฟโ™ก@0xFATIMAH0ยท
Four main components of Gensyn @gensynai is one of the pioneering projects building a global decentralized compute network. The Gensyn Protocol is built on four foundational components that together enable decentralized, verifiable machine learning at global scale.
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Kairo
Kairo@kairoo__ยท
๐–๐ก๐š๐ญ ๐‡๐š๐ฉ๐ฉ๐ž๐ง๐ฌ ๐–๐ก๐ž๐ง ๐€๐ˆ ๐‚๐š๐ง ๐’๐ข๐ ๐ง ๐ˆ๐ญ๐ฌ ๐Ž๐ฐ๐ง ๐–๐จ๐ซ๐ค? After spending over 1 month deep inside Ritualโ€™s understanding i realised something we havenโ€™t talked about yet and honestly this might be the most practical breakthrough Ritual unlocks. ๐–๐ž ๐ฅ๐ข๐ฏ๐ž ๐ข๐ง ๐š ๐ฐ๐จ๐ซ๐ฅ๐ ๐ฐ๐ก๐ž๐ซ๐ž ๐€๐ˆ ๐œ๐š๐ง ๐œ๐ซ๐ž๐š๐ญ๐ž ๐š๐ง๐ฒ๐ญ๐ก๐ข๐ง๐ : โ€ข fake screenshots โ€ข fake messages โ€ข fake voices โ€ข fake videos โ€ข fake proof And 99% of people canโ€™t tell whatโ€™s real anymore. Thatโ€™s why AI needs a way to sign its work the same way we sign our documents and emails. And this is where Ritual brings something the world desperately needs ๐Ÿ‘‡ ๐“๐ก๐ž ๐๐ซ๐จ๐›๐ฅ๐ž๐ฆ ๐“๐จ๐๐š๐ฒ: ๐™๐ž๐ซ๐จ ๐๐ซ๐จ๐จ๐Ÿ, ๐™๐ž๐ซ๐จ ๐“๐ซ๐ฎ๐ฌ๐ญ : Right now if an AI generates an image or text there is no reliable way to know: โ€ข who made it โ€ข what model created it โ€ข whether it was tampered with โ€ข if the result is authentic Anyone can fake anything. Thatโ€™s why misinformation is exploding: deepfakes โ†’ scams โ†’ fake celebrity statements โ†’ fake news โ†’ fake screenshots. Thereโ€™s no digital fingerprint. ๐Ÿ” ๐‘๐ข๐ญ๐ฎ๐š๐ฅโ€™๐ฌ ๐€๐ง๐ฌ๐ฐ๐ž๐ซ: ๐•๐ž๐ซ๐ข๐Ÿ๐ข๐š๐›๐ฅ๐ž ๐€๐ˆ ๐๐ซ๐จ๐ฏ๐ž๐ง๐š๐ง๐œ๐ž Ritual allows AI outputs to be cryptographically signed on-chain meaning: โœ”๏ธ Every AI output can carry its own โ€œproof of originโ€ โœ”๏ธ You can verify which model created it โœ”๏ธ You can confirm it wasnโ€™t edited โœ”๏ธ You can trace the entire computation path This is NOT possible with ๐‚๐ก๐š๐ญ๐†๐๐“, ๐Œ๐ข๐๐ฃ๐จ๐ฎ๐ซ๐ง๐ž๐ฒ, ๐†๐จ๐จ๐ ๐ฅ๐ž, or any centralized AI. This is only possible when AI runs on a cryptographically verifiable network like Ritual. ๐Ÿ’ก ๐‘๐ž๐š๐ฅ-๐‹๐ข๐Ÿ๐ž ๐„๐ฑ๐š๐ฆ๐ฉ๐ฅ๐ž : Imagine you receive a voice note from a friend asking for money. It sounds real. It feels real. But what if itโ€™s AI? ๐–๐ข๐ญ๐ก ๐‘๐ข๐ญ๐ฎ๐š๐ฅ-๐ฌ๐ญ๐ฒ๐ฅ๐ž ๐ฉ๐ซ๐จ๐ฏ๐ž๐ง๐š๐ง๐œ๐ž: You click โ†’ Verify origin It shows: โœ”๏ธ Model used โœ”๏ธ Time generated โœ”๏ธ Hash of the original output โœ”๏ธ Proof it wasnโ€™t modified Just like checking a digital signature on a PDF. You instantly know if it's legit or fake. ๐€๐ง๐จ๐ญ๐ก๐ž๐ซ ๐ž๐ฑ๐š๐ฆ๐ฉ๐ฅ๐ž: A viral image claims something happened. People panic. Markets react. News spreads. ๐–๐ข๐ญ๐ก ๐ฉ๐ซ๐จ๐ฏ๐ž๐ง๐š๐ง๐œ๐ž: The image shows a verifiable badge โ†’ Generated by Model X via Ritual unedited. or no valid provenance likely fake. This alone can save companies, elections, reputations, and people. ๐ŸŒ ๐–๐ก๐ฒ ๐“๐ก๐ข๐ฌ ๐Œ๐š๐ญ๐ญ๐ž๐ซ๐ฌ ๐†๐ฅ๐จ๐›๐š๐ฅ๐ฅ๐ฒ : AI is becoming powerful enough to shape: โœ”๏ธ politics โœ”๏ธfinancial markets โœ”๏ธjournalism โœ”๏ธpersonal identity โœ”๏ธpublic trust Without a system of provenance, society becomes vulnerable. Ritual gives AI the ability to prove its own authenticity openly, transparently, cryptographically. This isnโ€™t just technical innovation. Itโ€™s digital safety. โš–๏ธ ๐ˆ๐ง ๐’๐ข๐ฆ๐ฉ๐ฅ๐ž ๐–๐จ๐ซ๐๐ฌ : If the last internet era was about who posted it the next era will be about: Can you prove it? ๐‘๐ข๐ญ๐ฎ๐š๐ฅ ๐ฆ๐š๐ค๐ž๐ฌ ๐ญ๐ก๐š๐ญ ๐ฉ๐จ๐ฌ๐ฌ๐ข๐›๐ฅ๐ž. AI that can sign its own work means: โœ”๏ธ less misinformation โœ”๏ธ more trust โœ”๏ธ safer digital identity โœ”๏ธ transparent AI outputs โœ”๏ธ verifiable truth This is the kind of problem only Ritual is built to solve and itโ€™s going to matter more every day. @ritualnet @ritualfnd @joshsimenhoff @Jez_Cryptoz @0xMadScientist @cryptooflashh @Ritual_IN @Kash_060 @dunken9718 #Gritual #AIProvenance #VerifiedIntelligence #OnChainAI #DigitalTrustLayer
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Kairo@kairoo__

๐Ÿง  ๐–๐ก๐ฒ ๐€๐ˆ ๐๐ž๐ž๐๐ฌ ๐š ๐Œ๐ž๐ฆ๐จ๐ซ๐ฒ ๐‹๐š๐ฒ๐ž๐ซ ๐€๐ง๐ ๐‡๐จ๐ฐ ๐‘๐ข๐ญ๐ฎ๐š๐ฅ ๐Œ๐š๐ค๐ž๐ฌ ๐ˆ๐ญ ๐•๐ž๐ซ๐ข๐Ÿ๐ข๐š๐›๐ฅ๐ž : After talking about Modular AI thereโ€™s one piece people donโ€™t usually think aboutโ€ฆbut it might be the most important part of intelligence: ๐Œ๐ž๐ฆ๐จ๐ซ๐ฒ. Because without memory, nothing human or machine can learn, improve, or evolve. And thatโ€™s why Ritual treats memory as a core module in its new architecture. ๐‹๐ž๐ญโ€™๐ฌ ๐ฆ๐š๐ค๐ž ๐ญ๐ก๐ข๐ฌ ๐ฌ๐ข๐ฆ๐ฉ๐ฅ๐ž & ๐ฎ๐ง๐๐ž๐ซ๐ฌ๐ญ๐š๐ง๐ } ๐Ÿ“Œ ๐‡๐ฎ๐ฆ๐š๐ง๐ฌ ๐๐ž๐ž๐ ๐Œ๐ž๐ฆ๐จ๐ซ๐ฒ. ๐€๐ˆ ๐ƒ๐จ๐ž๐ฌ ๐“๐จ๐จ. Think of your own day: You remember your friendโ€™s name You remember your preferences You remember yesterdayโ€™s mistakes You remember your goals Now imagine waking up every morning with zero memory every conversation starts from scratch every lesson is forgotten. Thatโ€™s how most AI works today. It can talk and generate answers but it doesnโ€™t remember anything in a reliable ,shared or verifiable way. Everything disappears after the interaction. This makes AI feel powerfulโ€ฆbut also strangely dumb. ๐‘๐ข๐ญ๐ฎ๐š๐ฅ ๐ข๐ฌ ๐œ๐ก๐š๐ง๐ ๐ข๐ง๐  ๐ญ๐ก๐š๐ญ. ๐Ÿ”ง ๐–๐ก๐š๐ญ ๐ˆ๐ฌ ๐š ๐Œ๐ž๐ฆ๐จ๐ซ๐ฒ ๐‹๐š๐ฒ๐ž๐ซ ๐ข๐ง ๐€๐ˆ? : Think of AI memory like a notebook the model can write in and read from but hereโ€™s the key difference with Ritual: โžก๏ธ The notebook is not hidden on a companyโ€™s server. โžก๏ธ The notebook is shared, verifiable, and decentralized. ๐Œ๐ž๐š๐ง๐ข๐ง๐ : โœ”๏ธThe memory canโ€™t be altered secretly โœ”๏ธAnyone can audit how the AI learned โœ”๏ธUpdates are transparent โœ”๏ธThe learning trail is visible This is what makes memory trustworthy. ๐‘๐ž๐š๐ฅ-๐‹๐ข๐Ÿ๐ž ๐„๐ฑ๐š๐ฆ๐ฉ๐ฅ๐ž: Imagine you use an AI wallet assistant. Day 1: it learns your spending habits Day 5: it learns your risk level Day 20: it understands what alerts matter to you But only if it has a safe, verifiable memory. Now imagine the opposite: If a Web2 company stores that memory they can modify it delete it or sell it. ๐˜๐จ๐ฎโ€™๐ ๐ง๐ž๐ฏ๐ž๐ซ ๐ค๐ง๐จ๐ฐ ๐–๐ข๐ญ๐ก ๐‘๐ข๐ญ๐ฎ๐š๐ฅ? โœ”๏ธThe AIโ€™s memory becomes transparent โœ”๏ธYou can see what it knows โœ”๏ธYou can verify nothing shady is happening Developers can build on top of the same memory layer. This makes AI feel more loyal more predictable more human. ๐Ÿ”’ ๐–๐ก๐ฒ ๐Œ๐ž๐ฆ๐จ๐ซ๐ฒ ๐Œ๐ฎ๐ฌ๐ญ ๐๐ž ๐•๐ž๐ซ๐ข๐Ÿ๐ข๐š๐›๐ฅ๐ž: AI memory today lives on black-box servers Nobody can check if: the data was changed the model was retrained unfairly biases were added information was removed logs were manipulated If AI is going to make financial, political and personal decisions memory canโ€™t be hidden. ๐‘๐ข๐ญ๐ฎ๐š๐ฅ ๐ฆ๐š๐ค๐ž๐ฌ ๐ฆ๐ž๐ฆ๐จ๐ซ๐ฒ: โœ”๏ธ auditable โœ”๏ธ transparent โœ”๏ธ safe from manipulation โœ”๏ธ decentralized This is essential if AI is going to be trusted long-term. โš–๏ธ ๐“๐ก๐ž ๐๐ข๐  ๐๐จ๐ข๐ง๐ญ : AI without memory = a parrot AI with private memory = a liability AI with open verifiable memory = a trustworthy system ๐‘๐ข๐ญ๐ฎ๐š๐ฅ ๐ข๐ฌ ๐›๐ฎ๐ข๐ฅ๐๐ข๐ง๐  ๐ญ๐ก๐ž ๐ญ๐ก๐ข๐ซ๐ ๐จ๐ง๐ž. And thatโ€™s why the memory layer matters more than people think. @ritualnet @ritualfnd @Ritual_IN @joshsimenhoff @Jez_Cryptoz @dunken9718 @cryptooflashh @0xMadScientist @Kash_060 #Gritual #AIMemoryLayer #ModularAI #DecentralizedIntelligence #RitualNetwork

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Yesterdayโ€™s @gensynai AMA was really informative The AMA titled โ€œHow Not to Fail While Building an AI Product,with Space55 and @0xjeff Internal tech talk on: How CodeAssist was built. What learned from AI startups and infra Pitfalls to avoid when building AI products.
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The Cloud GPU Benchmark Challenge by @gensynai and Quok. it has just started Quok.it is hosting a competition for the Gensyn community.The goal is simple: collect GPU performance results from different cloud providers and create a community-powered leaderboard
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Meet BlockAssist by @gensynai BlockAssist brings AI straight into Minecraft, learning from the way you build and explore. It starts with simple commands but grows smarter as it observes your gameplay, becoming a helpful companion over time. Here's infographic about blockassist.
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@gensynai HIT 1 MILLION MODELS TRAINED Whether youโ€™ve been running RL-Swarm, grinding through BlockAssist, pushing CodeAssist, experimenting with GPUs, learning to run your very first node, or even opening the terminal for the first timeโ€ฆ this achievement belongs to you.
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