Ram P retweeted
Jun 12
@DeepBrainChain I am writing to follow up on three vulnerability reports I submitted in April 2026 via responsible disclosure. It has now been approximately 60 days with no acknowledgment or response on @BugRap_Team .
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Paul retweeted
In a world hungry for computing power, @DeepBrainChain is the bridge.
By connecting idle GPUs into a seamless, decentralized network, we’re ensuring that the next big AI breakthrough isn't slowed down by hardware shortages.
#DBC #GPUComputing #DePIN #Blockchain
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May 6
I’ve always said this—$DOT is meant to be used for software. There’s no reason it should be expensive just to build on @Polkadot, especially with JAM on the way. The real value comes from the software built on top.
If you look at other chains, it’s usually the native token that becomes the most expensive part, which ultimately makes the chain extractive.
Spin-off chains like @bittensor , @enjin , and @DeepBrainChain have all used Substrate to build their own ecosystems. So why should the core infrastructure be so expensive to build on? At that point, developers might as well use a standard Rust-based, non-blockchain stack.
There has to be leverage.
May 5
Polkadot just shipped sponsored transactions — apps can now cover fees so users don't need DOT to interact.
The UX win is real. Onboarding friction was killing adoption.
But this is the third "you don't need DOT" feature in 6 months:
→ Sufficient assets (no DOT for account existence)
→ Asset-pay fees via AMM (no DOT for tx fees)
→ Sponsored transactions (no DOT for any user interaction)
Each one removes a friction.
Each one also removes a DOT demand sink.
Honest question for the community:
If the strategy is to abstract DOT away from the user experience (which is the right UX call), where is the compensating value capture?
Why no burn from Treasury surplus, Coretime revenue, or parachain fees to balance the demand sinks being removed?
You can't have it both ways:
→ Either users need DOT, and adoption is harder
→ Or users don't need DOT, and the network burns/captures value somewhere else to offset
What do you think?
Should JAM include a mandatory burn mechanism — Coretime, Treasury, fees, anything — to offset the demand sinks UX removed?
Or is the current path (UX wins no compensating capture) actually the right call?
Genuinely curious how the ecosystem reads this.
#Polkadot #DOT #JAM #OpenGov
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Hey @DeepBrainChain, are you an active chain or a dead one? Because if you are active, shouldn't the safety of your protocol and your users be your top priority?
You listed your project on Bugrap.io for auditing, but right now, it looks like nothing more than a cheap publicity stunt.
Here is why: I recently found and submitted CRITICAL vulnerabilities on your chain. I waited patiently for almost a month with absolutely zero response. I initially gave your team the benefit of the doubt, assuming you were just swamped with work.
But then I checked your project's public history on Bugrap, and the reality became pretty clear. Out of 24 total reports on your board, the standard workflow (Created ➡️ Approved ➡️ Confirmed ➡️ Fixed ➡️ Rewarded) is completely dead.
Take a look at the timeline:
- The very last bug you actually Confirmed was way back on 2024-11-20—and even that report has zero updates for being "Fixed" or "Rewarded."
- You completely ignored 3 bugs submitted prior to that date.
- Everything submitted since then is stalled. A report from 2024-11-22 is stuck at "Approved." The most recent report from 2026-03-17? Also just sitting at "Approved" with no further action.
It heavily implies that your bug bounty program is just a facade for marketing.
⚠️ To DeepBrainChain Users:Please do not risk your hard-earned money. I have personally tested and verified these critical vulnerabilities on the network. My advice is to avoid risking your funds here until they prove they actually take their security seriously.
🛡️ To Fellow Web3 Security Researchers:Be very cautious before spending your time auditing this project. Given the complete lack of replies and stalled pipelines, it's entirely possible they are monitoring our submissions and silently fixing the bugs behind the scenes to avoid paying bounties. I can't be 100% certain of this, but the silent treatment speaks volumes.
Security is not a marketing tool. Do better.
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The era of AI needs a foundation that’s built to scale.
DeepBrainChain is providing the high-performance GPU power needed to fuel the next generation of artificial intelligence—
deepbrainchain.org/
#DBC #Web️
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Feb 10
Lost me arse on Ethereum killer NEO, and it's ecosystem Deepbrainchain, Trinity. Was all a scam.
Remember the big play was supposed to be Wanchain lol.
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Jan 13
HERE IS MY TIER LIST OF AI CRYPTO PROJECTS I AM FOLLOWING AND WAITING FOR GOOD ENTRY:
S Tier (The "Blue Chips" / Infrastructure Kings):
$TAO (@Bittensor)
$FET (@ASI_Alliance)
$RENDER (@rendernetwork)
$NEAR (@NEARProtocol)
$GRASS (@Grass )
$VIRTUAL (@virtuals_io)
A Tier (High Growth / Major Challengers):
$AKT (@Akashnet)
$IO (@ionet)
$OLAS (@autonolas)
$NOS (@nosana_ai)
$TRAC (@origin_trail)
B Tier (Niche Leaders / Strong Utility):
$AIOZ (@AIOZNetwork)
$RLC (@iEx_ec)
$PHA (@PhalaNetwork)
$GLM (@golemproject)
C Tier (High Risk / Legacy):
$COMAI (@communeaidotorg)
$MAN (@MatrixAINetwork)
$DBC (@DeepBrainChain)
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2026 marks the evolution of $DBC.
We are moving beyond a GPU network to become the Settlement & Payment Base Layer for the AI Agent economy.
The future of AI is autonomous, and that future needs a native currency. 🤖💳
Learn more: deepbrainchain.org/
#DeepBrainChain #AI #Web3 #DBC
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Happy New Year, DBC Community!
As we enter 2026, the era of decentralized AI computing is scaling faster than ever. Thank you for being the backbone of the DeepBrain Chain ecosystem.
Let’s continue building the world’s largest decentralized AI computing network together. The future is smart, decentralized, and powered by YOU!
#DeepBrainChain #DBC #AI #Web3 #HappyNewYear2026
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31 Dec 2025
The rapid expansion of AI and compute-intensive onchain applications has exposed the need for better access to scalable and affordable GPU infrastructure, a solution only possible through decentralization.
Beyond the growing number of decentralized GPU solutions, these projects are providing solutions across multiple layers, including hardware aggregation, orchestration, tokenization, and collateralization, all aimed at making compute more accessible and capital-efficient.
Here’s a list of more projects in the decentralized GPU ecosystem.
—
● Decentralized GPU Marketplaces & Compute Networks:
Platforms that connect GPU owners with users needing compute for AI, ML, or rendering tasks.
@ChainGPU - decentralized marketplace for GPU and AI compute resources
@AITECHio - decentralized GPU marketplace that bridges high-performance computing hardware and AI
@swan_chain - GPU marketplace that connects idle GPU owners with users who need computing resources
@plancknetwork - incentivized marketplace offering cost-effective access to enterprise-grade GPU power
@KaisarNetwork - building a P2P marketplace to allow individuals and data centers rent out idle GPU for AI/ML tasks
@DeepNodeAI - connects GPU owners to clients who need computational power for AI/ML tasks
@DeepBrainChain - cloud computing platform where owners of idle GPUs rent out their computational power
@gonka_ai - pools unused GPU power to provide access to high-end hardware for AI training and inference
@pictor_network - turns idle GPUs into a global network for 3D rendering and AI workloads
@edgenetwork - cloud computing provider that pools idle GPU power to provide computing resources for AI, rendering, and other high-performance applications
@SaladTech - distributed cloud platform that pools idle consumer GPUs from individual PC owners
@JANCTION_Global - acts as a distributed supercomputer by pooling idle GPU resources
@NeurochainAI - GPU compute DePIN and L1 that pools distributed GPUs for AI training and inference
@FARLabsAI - allows individuals and data centers can contribute their idle GPUs to a shared network
@runonflux_edge - decentralized cloud infrastructure provider that aggregates global GPU resources for AI/ML and rendering
@InfraX_ - connects providers of idle computing power with users who need it for intensive computational tasks
@NodeOpsHQ - aggregates idle GPU and CPU resources from independent providers
@GPUAI_Coin - computing protocol that transforms idle GPU resources into a scalable infrastructure layer
@ClusterProtocol - decentralized orchestration and coordination layer that connects GPU owners to AI devs
@oraichain - provides high-demand computational power for its AI ecosystem through GPU staking
@ritualnet - sovereign execution layer for AI that bridges GPU compute resources with blockchain apps
@OpenGradient - uses a Heterogeneous Agentic Compute Architecture to connect distributed GPUs, making them available for AI workloads like inference
—
● AI Cloud & Infrastructure Providers:
Projects offering on-demand GPU infrastructure and scalable AI compute environments.
@hyperbolic_labs - provides on-demand GPU infra and AI cloud services, so devs and researchers can run training, inference, and scalable compute at lower cost
@Gata_xyz - lets users access distributed GPU resources for AI training, inference, and deployment
@oceanprotocol - orchestration layer that connects idle GPU resources with AI devs via its Ocean Nodes framework
@ICN_Protocol - integrates storage, CPUs, and GPUs to support high-demand AI/ML workloads
—
● Tokenized GPU Assets & DeFi Integration:
Platforms bridging physical GPU infrastructure with tokenization, finance, and yield generation.
@Compute_Labs - tokenizes physical GPUs, allowing investors to gain exposure to industrial-grade GPUs and share in yields from AI compute workloads
@PinLinkAi - RWA-tokenized platform for fractionalized ownership and rental of physical GPU assets
@EMCProtocol - GPU resource aggregation platform that also enables the tokenization of physical GPU assets
@USDai_Official - DeFi protocol that allows AI companies to borrow funds using their physical GPU hardware as on-chain collateral
—
● ZK / Cryptography-Focused GPU Infrastructure:
Projects leveraging GPU compute for zero-knowledge proofs and cryptographic computation.
@SuccinctLabs - decentralized infrastructure layer that coordinates global GPU resources to generate ZK proofs
@brevis_zk - ZK Coprocessor that leverages GPU parallelization to bridge complex off-chain data processing with on-chain smart contracts
@thezkcloud - leverages the parallel processing power of GPUs to provide a cloud platform for generating ZKPs
@Ingo_zk - semiconductor company that utilizes GPUs for ZKP hardware acceleration
—
● Specialized Compute Layers & Protocol Infrastructure:
Networks focusing on orchestration, coordination, or protocol-level compute innovation.
@chutes_ai - serverless AI compute subnet under the Bittensor ecosystem for lending GPU computing power
@CTXCBlockchain - the Cortex Virtual Machine (CVM) leverages GPUs to execute complex AI models on-chain
@NetworkMeson - decentralized bandwidth and data transmission layer for Web3 and AI apps that rely on high-performance computing, including GPUs
—
These projects are turning fragmented GPU capacity into a flexible, on-demand compute layer.
Through marketplaces, orchestration layers, and specialized execution environments, they reduce friction in GPU access and enable applications that would otherwise be constrained by centralization.
3 Oct 2025
The race for AI dominance is fueling a surge in the demand for GPUs, and it’s no longer confined to the data centers of big tech companies.
While centralized data centers still work, they’re expensive and simply can’t keep pace with the demand for GPUs, leading to supply bottlenecks.
Decentralized GPU networks are changing the game by pooling idle compute resources from independent data centers, miners, and individuals, providing scalable, cheaper, and more accessible computing power for applications that need them.
A growing number of projects are tapping into the potential of decentralized GPUs, paving new paths across fields, from AI and machine learning to graphics rendering and scientific simulations
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