The platform’s core goal is to create a decentralized, low-cost, and scalable global supercomputer infrastructure by aggregating idle GPU and device power worldwide. This structure enables AI developers and content creators to access affordable computing power while individual users can earn income by sharing the unused capacity of their devices.

What is Neurolov (NLOV) Aiming For?

One of the most important elements distinguishing Neurolov from similar projects is its “browser-based compute platform” approach. Users can include their desktop computers, laptops, tablets, or mobile devices in the network, while those demanding computing can access GPU power without any software or hardware investment.

This structure offers a significant advantage, especially for individual developers, small teams, and startups struggling to enter AI development processes due to high hardware costs. It creates a more flexible and cost-effective alternative compared to traditional cloud providers.

Distributed GPU Network with Neurolov (NLOV)

At the center of the Neurolov protocol is the unification of globally distributed GPUs and devices under a peer-to-peer (P2P) network. This network has a hybrid structure that includes individual devices beyond data centers.

The main computing resources in the network are:

• GPU clusters
• Individual GPUs
• Laptops and desktop computers
• Mobile devices
• Enterprise data centers and bulk GPU providers

These resources serve a wide range of use cases such as artificial intelligence training, inference, content creation, gaming, agent infrastructures, and research.

Dual-Engine System: SWARM and NLOV

The economic and technical structure of Neurolov is shaped around two main components: SWARM and NLOV.

SWARM Engine

SWARM is a gamified resource allocation mechanism that distributes computing tasks within the network. Devices solve tasks, contribute to the network’s operation, and are rewarded based on their performance. This structure aims to increase the network’s sustainability and efficiency.

NLOV Token Mechanism

The $NLOV token forms the economic backbone of the platform. Computing demand, AI model usage, and in-network transactions are performed with NLOV. As usage increases, token burn and staking mechanisms activate, bringing the supply-demand balance to a dynamic structure.

This system aims to establish a direct link between platform usage and token economy.

Federated Learning and Data Privacy

Neurolov adopts a federated learning approach in parallel with its decentralized structure. With this model, data is processed on different devices without being collected in a single central point. Thus:

• User data is protected without leaving the device
• Privacy and data security are increased
• Collaborative model development becomes possible

This structure provides a significant advantage, especially for AI projects working with sensitive data.

Products and Services

GPU Compute

One of Neurolov’s core services is the GPU rental infrastructure. Users can instantly rent the GPU power they need for AI training and inference processes. This model offers high-performance computing without expensive hardware investments.

AI Model Production

Text, image, audio, code, and video production can be done through the platform. This structure, which minimizes technical knowledge requirements, facilitates AI integration for creators and businesses.

Swarm Network

Users who include their devices in the network can earn $NLOV by sharing their idle processing power. This mechanism expands the network’s total computing capacity as the number of participants increases.

AI Agents

Neurolov supports the development of autonomous AI agents for decentralized applications. These agents can be used in Web3 projects for automation, data analysis, and intelligent decision-making processes.

Neurolov (NLOV) Roadmap

Neurolov’s near-term roadmap focuses on the platform’s token economy and governance structure.

Q1 2026 – Token Generation Event and Global Access

• $NLOV Token Generation Event (TGE)
• Activation of the on-chain governance system
• Feature development through community votes
• Listings on centralized and decentralized exchanges
• Creation of liquidity pools

These steps target the platform’s transition to a fully community-focused structure.

Neurolov (NLOV) Tokenomics

$NLOV sits at the center of all transactions and incentive mechanisms in the Neurolov ecosystem. The platform’s active operation aims to shape token demand directly through usage.

Basic Information

• Total Supply: 500,000,000 NLOV
• Ticker: $NLOV
• Blockchain: Solana

Token Distribution (Allocation)

• Seed Investors: 1%
• Pre-Sale Investors: 10%
• IDO: 2%
• Private Investment Round: 17%
• Team and Development: 12%
• Ecosystem and Rewards: 20%
• Community and Marketing: 12%
• Liquidity: 10%
• Foundation Treasury: 8%
• Burn: 8%

This distribution offers a structure that balances both early investors and long-term ecosystem growth.

Neurolov (NLOV) Team

The Neurolov team consists of individuals with deep experience in artificial intelligence, marketing, strategy, and Web3 fields. The project’s vision is not limited to technical infrastructure but aims to build a globally adoptable AI compute network.

Dhruv Panchal – Founder & CEO Panchal, the founder and CEO of Neurolov, has developed AI solutions for global brands and participated in projects reaching over 50,000 people in more than 40 countries. He signed a $13 million AI agreement with the Gujarat Government and is a humanitarian aid and innovation leader recognized by the United Nations.

Jesse Guglielmo – Strategy Head Guglielmo, contributing to the strategy side of the project, served as CMO at Binance Labs-backed Bracket. With over 20 years of marketing experience, Guglielmo has managed GTM processes generating over $50 million in revenue in fintech, consumer technologies, and Web3 fields.

Claire Cawthon – Marketing Head Claire Cawthon, prominent on the marketing side, serves as CMO at ForceField and advisor at Kinetic Capital. She has worked with over 280 Web3 projects, including Ethereum and Solana, and managed annual marketing budgets exceeding $145 million.

Official Links

• Website
• X (Twitter)
• Whitepaper

Also, you can freely share your thoughts and comments about the topic in the comment section. Additionally, please follow us on our Telegram, YouTube, and Twitter channels for the latest news and updates.

The post What is Neurolov (NLOV)? appeared first on Coin Engineer.

What Is Janction (JCT)?

One of the biggest bottlenecks in today’s AI landscape is access to high-performance GPU resources and the efficient use of those resources.

Centralized cloud providers are expensive, limited in accessibility, and often come with privacy concerns. This is exactly where Janction (JCT) comes in: the world’s first Layer-2 blockchain network offering verifiable, synergistic, and scalable AI services. Through smart contracts, Janction automates machine learning workflows and brings together essential components such as AI models, GPU computing power, data streams, and labeling into a unified ecosystem.

The core purpose of Janction is to establish a globally distributed GPU marketplace, enabling users to access the computing power they need at low cost. This allows GPU owners to earn revenue, while developers gain affordable access to AI compute capacity.

Key Features of Janction

1. Distributed GPU Pool

Janction aggregates GPUs with varying hardware specifications into vGPU units and brings them together in a single pool.
This pool is automatically managed with:

• Load balancing

• Task parallelization

• Resource verification

• Pricing and usage metrics

2. GPU Marketplace

Users can:

• Rent GPUs

• Lease out their GPU resources

• Select cost-efficient options for their workloads

This structure offers an effective solution for both individual users and institutional AI companies.

3. Layer-2 Solution for AI Workloads

Janction is built on a Layer-2 architecture that ensures AI tasks are:

• Verifiable

• Scalable

• Synchronized

Transactions executed on Layer-2 are later recorded on the main chain and rewarded through a transparent Proof of Contribution mechanism.

Proof of Contribution

Janction uses an advanced evaluation model to measure contributions from both data providers and GPU providers.
This model uses factors such as:

• Individual data value

• Shapley value method

• Usage frequency

• Participant reputation score

This mechanism aims to ensure fair rewards for developers and resource providers across the system.

AI Services Janction Aims to Provide

AI Image Generation

• Create images from text inputs

• Useful for advertising, design, and social media

Speech–Text Conversions

• TTS: Text-to-speech

• STT: Speech-to-text

• Ideal for podcasts, subtitles, customer service, etc.

Video Processing

• Super-resolution

• Noise reduction

• Color enhancement

• Slow motion & frame enhancement

Object Detection and Image Analysis

• Security applications

• Industrial quality control

• Autonomous driving sensor data

Private LLM

Users can run their own private LLM models on Janction, benefiting from:

• Data privacy

• Regulatory compliance

• Enterprise-grade AI solutions

Janction Architecture

The network consists of three main layers:

1. Blockchain Layer

• Transaction records

• Data availability

• Reward distribution

• On-chain data ingestion

2. Distributed Resource Pooling

• vGPUs

• Task routing

• API-based AI microservices

• Horizontally scalable GPU clusters

3. GPU Marketplace

• Resource tracking

• Price comparison

• Renting & revenue model

• User rating (reputation system)

Roles in the Janction Ecosystem

• GPU Provider: Supplies GPU resources and earns revenue

• Aggregator: Discovers, manages, and distributes GPU resources

• User: Rents GPUs and processes AI workloads

• Node Operators: Participate in verification and balancing processes

Janction Partnerships

Janction expands its ecosystem and strengthens its infrastructure through strategic partnerships with leading Web3 projects such as Arichain, DMC-Dao, AltLayer, TEN, Humanode, Etarn, and Chainlink. These collaborations provide the platform with multi-layered technological support in areas such as data verification, secure identity infrastructure, Layer-2 scaling solutions, AI-focused execution layers, and reliable oracle integrations.

This partner network forms a powerful technological backbone that brings Janction’s DePIN- and AI-focused vision into real-world applications.

Janction Team – HARA

HARA, one of the key figures behind Janction, stands out as a versatile executive combining financial expertise with technology leadership. As the CFO of Jasmy, he leads the vision of “IoT-based data democracy,” while as the CEO of Janction, he develops the decentralized GPU pool powered by an EVM-compatible Layer-2 architecture. With a background at KPMG, CPA certification, and extensive IPO and corporate consulting experience, HARA provides the project with strong leadership in both financial transparency and sustainable growth strategies.

Official Links

• Website
• X (Twitter)
• Whitepaper

You can also freely share your thoughts and comments about the topic in the comment section. Additionally, don’t forget to follow us on our Telegram, YouTube, and Twitter channels for the latest news and updates.

The post What Is Janction (JCT)? appeared first on Coin Engineer.

The main goal of Nosana is to make GPU access for AI more affordable and accessible. This allows companies to avoid expensive hardware investments while individual users can earn passive income by renting out idle hardware (gaming PCs, mining rigs, or even MacBooks). 

Unlike traditional cloud computing services, Nosana reduces dependence on large tech companies and offers a community-driven, flexible solution. 

Team & Founders 

Nosana was founded by Jesse Eisses and Sjoerd Dijkstra, experienced developers and engineers specialized in decentralized AI solutions. The founders aim to democratize access to GPU hardware, enabling everyone to leverage AI capabilities without high costs or barriers. 

Project Concept 

The core idea behind Nosana is to utilize unused GPUs to build a global computing network. Initially launched as a decentralized solution for software development processes (CI/CD), the project pivoted toward AI inference workloads when it realized that the industry alone could not meet the required scale. 

The platform addresses GPU scarcity while also reducing e-waste and operational costs. The ultimate vision is for projects to operate without dependence on centralized companies, relying instead on community-driven decentralized infrastructure. 

Key Advantages 

• Minimal latency: Nosana network reduces waiting times and accelerates testing processes. 
• Early bug detection: Faster tests allow errors to be found early in the development cycle. 
• Rapid evaluation of changes: Code modifications are tested instantly. 
• Consistency and agility: Increases flexibility in development workflows. 
• Faster test execution: Tests complete in a significantly shorter time. 

Investors & Partnerships 

Nosana received a grant from the Solana Foundation, providing credibility and early-stage funding. Integration goals with machine learning protocols like PyTorch and HuggingFace indicate potential partnerships and strengthen its position in the ecosystem. As a decentralized project, Nosana focuses on community and foundation support rather than traditional venture capital. 

How It Works 

Nosana is built on the Solana blockchain, providing high throughput and low transaction fees for AI workloads. 

• GPU Owners (Servers): Rent out unused GPU capacity on the Nosana network, earning NOS tokens. 
• AI Users (Clients): Rent GPU power from the network for AI projects in exchange for NOS tokens. 
• Decentralized Network: Secured by Solana’s Proof of History (PoH) and Proof of Stake (PoS) mechanisms, ensuring transparency and high security. 
• The platform provides GPU owners with passive income while offering AI users cost-effective, scalable, and flexible GPU access. 

Governance 

NOS token plays a role in governance and economic incentives. Users can stake tokens to earn rewards and participate in platform decisions. Official documents detail programs such as staking, vesting/pools, and node registration. 

Roadmap 

Nosana’s roadmap is divided into five phases to expand the platform and ecosystem: 

• Genesis (v0.1 – H1 2024): Alpha and beta stages, end-to-end testing, early adopters onboarded. 
• Galactica (v1.0 – H1 2025): Mainnet launch, network scaling, and user base expansion. 
• Triangulum (v1.X – H2 2025): Integration with PyTorch, HuggingFace, and TensorFlow. 
• Whirlpool (v1.X – H1 2026): Support for a wider range of GPUs including AMD, Intel, and Apple Silicon. 
• Sombrero (v1.X – H2 2026): Enterprise support with fiat payments and invoicing features. 

NOS Token 

NOS is the native utility token of the Nosana ecosystem. Its main use cases: 

• Network Fees: Payment for GPU usage on the network. 
• Staking: Contribute to network security and earn rewards. 
• Governance: Vote on resource allocation and platform decisions. 

Token Details 

• Total Supply: 100,000,000 NOS 
• Max Supply: Not specified 
• Circulating Supply: 48,190,000 NOS 

Token Allocation 

• Company: 25% (25,000,000) — 36-month vesting; 10% unlocked initially. 
• Team: 20% (20,000,000) — 48-month linear vesting. 
• Mining: 20% (20,000,000) — nodes; 24-month linear capped distribution. 
• Backers (Investors): 17% (17,000,000) — 9-month vesting; 10% unlocked initially. 
• Liquidity: 10% (10,000,000) — trading/accessible at launch. 
• Airdrop: 5% (5,000,000) — incentivized testnet programs. 
• Public Sale: 3% (3,000,000) 

Features 

• Decentralized & community-driven 
• Cost-effective GPU access 
• Flexible pay-as-you-go model 
• Passive income for hardware owners 
• Solana integration for fast and low-cost transactions 

Ecosystem 

• Tools & Integrations: CLI, SDK, dashboards, wallet integration (Phantom, Solflare), node management, pools & rewards. 
• Developer-Friendly: PyTorch/HuggingFace/TensorFlow connectors, SDKs, sample codes. 
• Use Cases: AI inference, CI/CD workloads initially; expanded ML/AI scenarios later. 

Official Links 

• Website
• Twitter
• Telegram
• Discord

You can also freely share your thoughts and comments about the topic in the comment section. Additionally, don’t forget to follow us on our Telegram, YouTube, and Twitter channels for the latest news and updates.

The post Nosana (NOS) Overview: Decentralized GPU & AI Solutions appeared first on Coin Engineer.

What Is DecentralGPT (DGC)?

DecentralGPT is a decentralized AI network supporting open-source large language models. It aims to build a secure, privacy-preserving, democratic, and transparent General Artificial Intelligence (AGI) network. Distributed nodes collectively perform data processing and model inference, reducing dependence on a single computational center and increasing system resilience against attacks. Its open-source nature fosters collaboration within the global developer community, driving rapid technological advancement. DecentralGPT overcomes the limitations of traditional AI models, offering a more secure, equitable, and open AI future.

AIGC Industry and AGI Outlook

Market Value of the AIGC Industry

The AI-Generated Content (AIGC) industry, encompassing the automated creation of text, images, videos, and music, is a rapidly growing field. Revolutionizing sectors like media, advertising, entertainment, and education, AIGC provides efficient solutions for content production, personalized marketing, and user engagement.

• Media and News: For instance, The New York Times uses AIGC technology to automatically generate sports news and financial bulletins, enabling faster content updates compared to manual processes and dynamically adjusting reports based on reader feedback. Data shows that media companies using AIGC experience a 40% reduction in content production time and a 30% increase in audience engagement.
• Advertising: A leading online retailer utilized AIGC to create personalized ads, achieving a 20% increase in click-through rates and a significant improvement in advertising ROI. AIGC boosts campaign click-through rates by 20-30% and enhances cost-effectiveness by 50% compared to traditional methods.
• Educational Technology: Online education platforms leverage AIGC to produce personalized learning materials and interactive experiences, improving student learning efficiency by an average of 35%. Institutions adopting AIGC report a 40% increase in student engagement and a 50% rise in satisfaction.

Future Market Growth

Recent market research predicts the AIGC industry will reach a trillion-dollar market size within the next decade. Key drivers include:

• Technological Innovation: Next-generation language models like GPT and BERT enable near-human-quality text and image generation.
• Enterprise Demand: Digital transformation fuels demand for fast, personalized content production. By 2025, at least 60% of global large enterprises are expected to adopt AIGC technology.
• Cost Reduction: AIGC can reduce content production costs by up to 70%, particularly for large-scale needs.
• Emerging Markets: As internet access and technology adoption grow in regions like Asia and Africa, AIGC demand is projected to exceed 35% annual growth.

DecentralGPT’s Role in AGI

DecentralGPT accelerates AGI development through its decentralized network. Distributed computing resources lower operational costs and enhance data security. Localized data processing protects sensitive information (e.g., medical or financial data). Additionally, it democratizes technology by providing equal access to global developers, fostering innovation.

Core Features of DecentralGPT

• Decentralized Architecture: Globally distributed nodes independently execute AI model inference tasks, reducing reliance on a single data center and enhancing system resilience.
• Multi-Model Support and Open Source: Supports various open-source large language models, increasing transparency and accessibility.
• Privacy and Security: Data encryption at local nodes minimizes privacy breach risks.
• Democratic Access: Users and developers in both developed and developing countries can equally benefit from the platform.
• Efficiency and Cost Reduction: Global distributed resources boost processing speed and lower centralized system costs.
• Technological Innovation: Open-source support encourages global collaboration and rapid technological advancement.
• Social Equity: Broadens access to advanced AI technologies, bridging the technology gap.
• Environmentally Friendly: Distributed nodes reduce environmental impact through renewable energy use and shorter data transmission distances.
• Data Sovereignty: Users gain greater control over their data through localized processing and strict governance policies.

DecentralGPT Technical Architecture

User Interface

Users interact with DecentralGPT through client node interfaces, which collect queries, data inputs, or administrative commands, encrypt them, and send them to distributed GPU nodes.

Distributed Coordinator

The client node also functions as a distributed coordinator, querying the status of GPU nodes across the network for task allocation and load balancing. It processes encrypted requests, selects suitable GPU nodes, and assigns tasks via a random blockchain machine.

Distributed Computing Nodes

• Node Structure: Each node is equipped with GPUs capable of performing AI model inference independently or collectively.
• Operating System and Software: Nodes run on Ubuntu or similar systems, with software and libraries to support AI model execution.
• P2P Network: Nodes connect via a peer-to-peer (P2P) network, enhancing data sharing and network reliability.

Data Storage and Sharing

• IPFS Technology: The Interplanetary File System (IPFS) is used for distributed data storage and sharing.
• Web3 Storage: User data is encrypted and accessible end-to-end with private keys.
• File Storage and Access: All data is securely stored and accessed through a distributed storage network.

Distributed GPU Machines

GPU nodes perform high-speed AI model inference, forming a global distributed computing network.

Core Functions of DecentralGPT

• Natural Language Understanding and Generation: Handles tasks like answering questions, writing articles, and generating code.
• Multi-Language Support: Geographically distributed nodes optimize processing for local languages.
• Personalized User Experience: Provides tailored responses based on user history.
• Seamless Integration and Scalability: Offers open APIs for easy integration and global scalability.
• Enhanced Privacy and Security: Local encryption and advanced security protocols ensure data protection.
• Customizable Interface: Businesses and developers can tailor interfaces and functions to specific needs.

Distributed GPU Mining Mechanism

DecentralGPT employs a distributed GPU mining mechanism to support network vitality and model development.

• Total Supply: 1 trillion tokens in the first four years, followed by 50 billion annually.
• Mining Conditions: Requires long-lease GPU machines pledging DBC tokens on the DBC network.
• Reward Distribution: Every 600 blocks (approximately 1 hour), 5,707,763 DGC is distributed based on a miner’s computing power share.
• Reward Allocation: Model developers receive 30%, GPU miners receive 70%.
• Halving: Rewards halve every four years for 100 years.
• Automatic Burning: 100% of user payments are burned, reducing token supply.

DecentralGPT (DGC) Tokenomics Model

DGC is the economic unit of the DecentralGPT platform. In the first four years, 1 trillion tokens are issued, with 60% on BNB Chain and 40% on DBC EVM Chain. All user-paid DGC tokens are 100% burned.

Token Allocation:

• Team: 10%
• Seed Round: 10%
• A Round: 5%
• Node Operation: 10%
• Airdrop: 5%
• Mining (GPU): 20%
• Liquidity: 5%
• Foundation: 10%
• Ecosystem & Marketing: 14.5%
• Staking Reward: 6%
• Mining Race: 4.5%

Roadmap

• 2025 Q1: Growth marketing, DGC public sale, foundational AI agent API, long-term memory optimization.
• 2025 Q2: Community growth, Canvas support, diverse document formats, learning, and summarization.
• 2025 Q3-Q4: AI agent growth, node clusters in Europe and Africa, LLM computer interface control (70% accuracy), real-time voice and video calls.
• 2026 Q1-Q2: AI agent infrastructure, 90% accurate interface control, virtual avatar support.
• 2026 Q3-Q4: Virtual avatars in video calls, preliminary AGI with support for all input/output modalities.

Strategic Partners and Investors

DecentralGPT is backed by prominent partners and investors, including Bybit, OKX, Deep Brain Chain, IO.NET, Aethir, DePIN X, AGICRYPTO, Cherry Ventures, and BTR CAPITAL.

DecentralGPT Team

• Vitalli: CEO, Blockchain Marketing Expert, FinTech Manager
• Harry: Chief Scientist & CTO, Stanford Post-Doc, AI Team Leader
• Joshua Vizer: Strategy Director, Product Strategy, Community Growth
• Ze: Marketing Director, UPenn Ventures Club Analyst
• Jeff: Business Director, Serial Entrepreneur, Wall Street Investment Banking
• Anwar: Tech Advisor, Columbia University Faculty, ETH Hackathon Judge

Official Links

• Website
• X (Twitter)
• Whitepaper

You can also freely share your thoughts and comments about the topic in the comment section. Additionally, don’t forget to follow us on our Telegram, YouTube, and Twitter channels for the latest news and updates.

The post What Is DecentralGPT (DGC)? appeared first on Coin Engineer.

Features of NeuralAI

• AI-Powered 3D Model Generation: NeuralAI creates 3D models using text and visual inputs. Users can quickly start projects and obtain detailed 3D models that can be exported in industry-standard formats.
• Fast Iteration: NeuralAI helps developers increase the speed of 3D model creation, enabling more experimentation and helping them find the best results for their vision. The only limit is the developer’s imagination.
• Biττensor Subnet: NeuralAI is working on making 3D asset creation more efficient on the Biττensor subnet. This network offers a resource expansion cycle where 3D asset creators (miners) earn rewards.
• GPU Leasing and Mining: In collaboration with AKASH Network, NeuralAI provides ready-to-use templates for GPU leasing and TAO mining. This offers developers a cost-effective solution for additional processing power.
• GPU Streaming (Research Ongoing): NeuralAI aims to stream high-quality GPU power from local devices using cloud computing. This technology allows players to experience enhanced graphics and smooth gaming experiences without hardware upgrades.

NeuralAI Marketplace and 3D Assets

NeuralAI offers a marketplace where 3D assets can be freely traded. Users can share their created 3D assets with other developers and earn revenue. The marketplace, different from traditional asset exchange platforms, supports features such as NFT tokenization, on-demand 3D model generation, and much more.

You Might Be Interested In: Elon Musk Shared, That Memecoin Flew: Up 500%!

Revenue Strategy: NeuralAI Marketplace takes a 5% transaction fee. Half of this fee is distributed to $NEURAL token holders, while the other half is reinvested into the NeuralAI ecosystem.

$NEURAL Token

$NEURAL is the cryptocurrency token of the NeuralAI platform and operates on the Ethereum blockchain. This token acts as a key for accessing services on the platform.

• Staking: $NEURAL token holders can stake their tokens and earn revenue from the platform. These income sources can come from TAO mining, Bittensor mainnet emissions, and premium features.
• Discounted Prices: $NEURAL token holders will receive discounts on future premium services and enterprise solutions.

NeuralAI Tokenomics

• Total Supply: 10 million $NEURAL tokens
• Tax: 4% tax on buys and sells (2% for development, 2% for marketing)
• Distribution:
  • Liquidity Pool: 7,000,000 NEURAL (70%) – Initial liquidity injection and investor funds will be re-locked.
  • Team and Advisors: 500,000 NEURAL (5%) – 3-month lock, 24-month linear vesting.
  • Research and Development: 500,000 NEURAL (5%) – 6-month linear vesting.
  • Marketing and CEX Listings: 1,000,000 NEURAL (10%) – Multi-sig, used as needed.
  • KOL and Strategic Pre-Sale: 1,000,000 NEURAL (10%) – 50% TGE, 1M Cliff, 3M Linear Vesting.

NeuralAI offers great potential for accelerating and reducing the cost of 3D model production, providing immense value for game developers and other creative industries. The $NEURAL token is a key element of the platform’s economic structure, offering various ways to reward users.

You can also freely share your thoughts and comments about the topic in the comment section. Additionally, don’t forget to follow us on our Telegram, YouTube, and Twitter channels for the latest news and updates.

The post What is NeuralAI (NEURAL)? appeared first on Coin Engineer.

Court Ruling and Legal Process On December 11, the Supreme Court issued a brief order, rejecting Nvidia’s appeal without providing a reason. This decision upheld the Ninth Circuit’s ruling, which reversed a lower court decision from March 2021 that had initially dismissed the case.

Nvidia was aiming to overturn the Ninth Circuit Court of Appeals ruling from August 2023, which revived a lawsuit filed by Nvidia shareholders in 2018. The lawsuit claims that Nvidia hid over $1 billion in GPU sales to crypto miners and that CEO Jensen Huang downplayed the volume of these sales.

A spokesperson for Nvidia told:  “We would have preferred a decision affirming the trial court’s dismissal of the case, but we are fully prepared to continue our defense. Consistent and predictable standards in securities litigation are essential to protecting shareholders and ensuring a strong economy, and we remain committed to supporting them.”

You Might Be Interested In: Elon Musk Talks About the Name of a New Memecoin!

Shareholder Claims and Evidence The lawsuit argues that a significant portion of Nvidia’s GPU sales was driven by sales to crypto miners. It points to the decline in sales at the end of 2018, when the crypto market collapsed, causing Nvidia’s stock price to drop nearly 30% in just two days.

In October, the Department of Justice and the Securities and Exchange Commission (SEC) supported the case, stating that Nvidia’s argument was based on false information. The agencies highlighted the shareholders’ case, which includes evidence such as statements from former Nvidia executives and a Bank of Canada report alleging that Nvidia understated its cryptocurrency revenue by $1.35 billion.

Nvidia’s Previous SEC Payment In 2022, Nvidia paid $5.5 million to the SEC to settle charges related to its insufficient disclosure of the impact of crypto mining on its gaming business. The company neither admitted nor denied the SEC’s findings, but this payment raised concerns about Nvidia’s past transparency issues.

You can also freely share your thoughts and comments about the topic in the comment section. Additionally, don’t forget to follow us on our Telegram, YouTube, and Twitter channels for the latest news and updates.

The post Nvidia’s Crypto Mining Lawsuit Rekindled! appeared first on Coin Engineer.

Impact on Crypto Mining and Blockchain

Nvidia’s growth is also influencing the cryptocurrency space, particularly through its GPU products. The demand for Hopper and Blackwell chips is improving blockchain network optimization and crypto mining efficiency. GPUs continue to play a vital role in mining and staking due to their high processing power.

Nvidia’s Role in the Crypto Ecosystem

• GPU Prices and Supply: Nvidia’s growth could push GPU prices higher, impacting crypto miners, especially smaller ones.
• Proof of Work: Despite Ethereum’s shift to Proof of Stake, Nvidia’s GPUs remain essential for Proof of Work networks.
• Next-Gen Blockchain: Nvidia’s AI solutions could enhance technologies like Zero-Knowledge rollups, promoting scalability in blockchain.

Nvidia’s expansion in AI and data centers is likely to accelerate the adoption of blockchain technology, enabling stronger network infrastructures and creating opportunities in Ethereum Layer 2 projects, ZK technologies, and AI-driven crypto solutions.

You can also freely share your thoughts and comments about the topic in the comment section. Additionally, don’t forget to follow us on our Telegram, YouTube, and Twitter channels for the latest news and updates.

The post Nvidia Reports $35.1 Billion Revenue, Driven by AI and Data Centers appeared first on Coin Engineer.

The CISO of Io.net, Husky.io responded immediately by locking down the network with patches and improvements. Due to the powerful permission layers of their GPUs, the real hardware of the GPUs survived the attack.

Between 07:27:43 and 07:29:05 AM PST on April 25, write operations increased within the GPU metadata API to trigger the breach detection and the alarm activation.

The security measures included making it more complex to inject SQL queries into the APIs and helping to document illegal attempts better. To complement the problems of universal authorization tokens, a user-specific authentication solution was promptly deployed using Auth0 with OKTA.

Furthermore, the anticipated reduction in supply force participants was aggravated by the fact that this security patch update happened at the time when one of the reward program snapshots occurred. As legitimate GPUs did not restart and update, they were unable to use the uptime API, resulting in a drastic drop in the number of active GPU connections from 600,000 to 10,000.

In response to these issues, we initiated Ignition Rewards Season 2 in May to stimulate the participation of the supply side. The supply chain collaboration regarding device upgrades, reboots, and reconnections is a continuous process.

Io.net API Vulnerability Exposed

The problem with the intruder was flaws in the proof-of-work (PoW) method used to detect fake GPUs. Attacking tactics intensified as a result of all aggressive security measures that were applied even before the incident, thus proving the need for continuous security research and advancement.

To present the content in input/output Explorer, the attackers exploited a vulnerability in an API. Therefore, in the process, user IDs were exposed upon device ID searches. Data had been dumped into the database by some malicious attackers a few weeks before the incident.

The attackers managed to get into the ‘worker-API,’ which allowed them to alter device metadata without needing user-level authentication by using a valid universal authentication token.

For early threat detection and neutralization, Husky.io emphasized continuous full assessment and penetration testing of public endpoints. Despite hurdles, we continue to rebuild network connectivity and stimulate supply-side participation in order for the platform to remain operational and deliver hundreds of thousands of compute hours per month.

Io.net wanted to integrate Apple silicon chip technology in March to enhance its AI and ML offerings.

The post Io.net Faces Cyberattack: Security Breach Impacts GPU Network appeared first on Coin Engineer.