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· 2 min read

We're excited to share a transformative opportunity at Altera.al, a breakthrough AI startup that recently made waves with their groundbreaking work in developing digital humans. Recently featured in MIT Technology Review, Altera.al has demonstrated remarkable progress in creating AI agents that can develop humanlike behaviors, form communities, and interact meaningfully in digital spaces.

Altera.al: Join the Frontier of Digital Human Development with Compensation of $600K-1M

About Altera.al

Founded by Robert Yang, who left his position as an assistant professor in computational neuroscience at MIT to pursue this vision, Altera.al has already secured over $11 million in funding from prestigious investors including A16Z and Eric Schmidt's emerging tech VC firm. Their recent Project Sid demonstration showed AI agents spontaneously developing specialized roles, forming social connections, and even creating cultural systems within Minecraft - a significant step toward their goal of creating truly autonomous AI agents that can collaborate at scale.

Why Now Is an Exciting Time to Join

Altera.al has achieved a significant technical breakthrough in their mission to develop machines with fundamental human qualities. Their work goes beyond traditional AI development - they're creating digital beings that can:

  • Form communities and social hierarchies
  • Develop specialized roles and responsibilities
  • Create and spread cultural patterns
  • Interact meaningfully with humans in digital spaces

Who They're Looking For

Following their recent breakthrough, Altera.al is scaling their team and offering exceptional compensation packages ranging from $600,000 to $1,000,000 for:

  • Experts in AI agent research
  • Strong Individual Contributors in:
    • Distributed systems
    • Security
    • Operating systems

How to Apply

Ready to be part of this groundbreaking journey? Apply directly through their careers page: https://jobs.ashbyhq.com/altera.al

Join the Future of Digital Human Development

This is a unique opportunity to work at the intersection of artificial intelligence and human behavior modeling, with a team that's already demonstrating remarkable results. If you're passionate about pushing the boundaries of what's possible in AI and human-machine interaction, Altera.al could be your next adventure.


For more updates on groundbreaking opportunities in tech and blockchain, follow us on Twitter or join our Discord community.

This post is part of our ongoing commitment to supporting innovation and connecting talent with transformative opportunities in the tech industry.

· 8 min read

Every year, a16z publishes sweeping predictions on the technologies that will define our future. This time, their crypto team has painted a vivid picture of a 2025 where blockchains, AI, and advanced governance experiments collide.

I’ve summarized and commented on their key insights below, focusing on what I see as the big levers for change — and possible stumbling blocks. If you’re a tech builder, investor, or simply curious about the next wave of the internet, this piece is for you.

1. AI Meets Crypto Wallets

Key Insight: AI models are moving from “NPCs” in the background to “main characters,” acting independently in online (and potentially physical) economies. That means they’ll need crypto wallets of their own.

  • What It Means: Instead of an AI just spitting out answers, it might hold, spend, or invest digital assets — transacting on behalf of its human owner or purely on its own.
  • Potential Payoff: Higher-efficiency “agentic AIs” could help businesses with supply chain coordination, data management, or automated trading.
  • Watch Out For: How do we ensure an AI is truly autonomous, not just secretly manipulated by humans? Trusted execution environments (TEEs) can provide technical guarantees, but establishing trust in a “robot with a wallet” won’t happen overnight.

2. Rise of the DAC (Decentralized Autonomous Chatbot)

Key Insight: A chatbot running autonomously in a TEE can manage its own keys, post content on social media, gather followers, and even generate revenue — all without direct human control.

  • What It Means: Think of an AI influencer that can’t be silenced by any one person because it literally controls itself.
  • Potential Payoff: A glimpse of a world where content creators aren’t individuals but self-governing algorithms with million-dollar (or billion-dollar) valuations.
  • Watch Out For: If an AI breaks laws, who’s liable? Regulatory guardrails will be tricky when the “entity” is a set of code housed on distributed servers.

3. Proof of Personhood Becomes Essential

Key Insight: With AI lowering the cost of generating hyper-realistic fakes, we need better ways to verify that we’re interacting with real humans online. Enter privacy-preserving unique IDs.

  • What It Means: Every user might eventually have a certified “human stamp” — hopefully without sacrificing personal data.
  • Potential Payoff: This could drastically reduce spam, scams, and bot armies. It also lays the groundwork for more trustworthy social networks and community platforms.
  • Watch Out For: Adoption is the main barrier. Even the best proof-of-personhood solutions need broad acceptance before malicious actors outpace them.

4. From Prediction Markets to Broader Information Aggregation

Key Insight: 2024’s election-driven prediction markets grabbed headlines, but a16z sees a bigger trend: using blockchain to design new ways of revealing and aggregating truths — be it in governance, finance, or community decisions.

  • What It Means: Distributed incentive mechanisms can reward people for honest input or data. We might see specialized “truth markets” for everything from local sensor networks to global supply chains.
  • Potential Payoff: A more transparent, less gameable data layer for society.
  • Watch Out For: Sufficient liquidity and user participation remain challenging. For niche questions, “prediction pools” can be too small to yield meaningful signals.

5. Stablecoins Go Enterprise

Key Insight: Stablecoins are already the cheapest way to move digital dollars, but large companies haven’t embraced them — yet.

  • What It Means: SMBs and high-transaction merchants might wake up to the idea that they can save hefty credit-card fees by adopting stablecoins. Enterprises that process billions in annual revenue could do the same, potentially adding 2% to their bottom lines.
  • Potential Payoff: Faster, cheaper global payments, plus a new wave of stablecoin-based financial products.
  • Watch Out For: Companies will need new ways to manage fraud protection, identity verification, and refunds — previously handled by credit-card providers.

6. Government Bonds on the Blockchain

Key Insight: Governments exploring on-chain bonds could create interest-bearing digital assets that function without the privacy issues of a central bank digital currency.

  • What It Means: On-chain bonds could serve as high-quality collateral in DeFi, letting sovereign debt seamlessly integrate with decentralized lending protocols.
  • Potential Payoff: Greater transparency, potentially lower issuance costs, and a more democratized bond market.
  • Watch Out For: Skeptical regulators and potential inertia in big institutions. Legacy clearing systems won’t disappear easily.

Key Insight: Wyoming introduced a new category called the “decentralized unincorporated nonprofit association” (DUNA), meant to give DAOs legal standing in the U.S.

  • What It Means: DAOs can now hold property, sign contracts, and limit the liability of token holders. This opens the door for more mainstream usage and real commercial activity.
  • Potential Payoff: If other states follow Wyoming’s lead (as they did with LLCs), DAOs will become normal business entities.
  • Watch Out For: Public perception is still fuzzy on what DAOs do. They’ll need a track record of successful projects that translate to real-world benefits.

8. Liquid Democracy in the Physical World

Key Insight: Blockchain-based governance experiments might extend from online DAO communities to local-level elections. Voters could delegate their votes or vote directly — “liquid democracy.”

  • What It Means: More flexible representation. You can choose to vote on specific issues or hand that responsibility to someone you trust.
  • Potential Payoff: Potentially more engaged citizens and dynamic policymaking.
  • Watch Out For: Security concerns, technical literacy, and general skepticism around mixing blockchain with official elections.

9. Building on Existing Infrastructure (Instead of Reinventing It)

Key Insight: Startups often spend time reinventing base-layer technology (consensus protocols, programming languages) rather than focusing on product-market fit. In 2025, they’ll pick off-the-shelf components more often.

  • What It Means: Faster speed to market, more reliable systems, and greater composability.
  • Potential Payoff: Less time wasted building a new blockchain from scratch; more time spent on the user problem you’re solving.
  • Watch Out For: It’s tempting to over-specialize for performance gains. But specialized languages or consensus layers can create higher overhead for developers.

10. User Experience First, Infrastructure Second

Key Insight: Crypto needs to “hide the wires.” We don’t make consumers learn SMTP to send email — so why force them to learn “EIPs” or “rollups”?

  • What It Means: Product teams will choose the technical underpinnings that serve a great user experience, not vice versa.
  • Potential Payoff: A big leap in user onboarding, reducing friction and jargon.
  • Watch Out For: “Build it and they will come” only works if you truly nail the experience. Marketing lingo about “easy crypto UX” means nothing if people are still forced to wrangle private keys or memorize arcane acronyms.

11. Crypto’s Own App Stores Emerge

Key Insight: From Worldcoin’s World App marketplace to Solana’s dApp Store, crypto-friendly platforms provide distribution and discovery free from Apple or Google’s gatekeeping.

  • What It Means: If you’re building a decentralized application, you can reach users without fear of sudden deplatforming.
  • Potential Payoff: Tens (or hundreds) of thousands of new users discovering your dApp in days, instead of being lost in the sea of centralized app stores.
  • Watch Out For: These stores need enough user base and momentum to compete with Apple and Google. That’s a big hurdle. Hardware tie-ins (like specialized crypto phones) might help.

12. Tokenizing ‘Unconventional’ Assets

Key Insight: As blockchain infrastructure matures and fees drop, tokenizing everything from biometric data to real-world curiosities becomes more feasible.

  • What It Means: A “long tail” of unique assets can be fractionalized and traded globally. People could even monetize personal data in a controlled, consent-based way.
  • Potential Payoff: Massive new markets for otherwise “locked up” assets, plus interesting new data pools for AI to consume.
  • Watch Out For: Privacy pitfalls and ethical landmines. Just because you can tokenize something doesn’t mean you should.

A16Z’s 2025 outlook shows a crypto sector that’s reaching for broader adoption, more responsible governance, and deeper integration with AI. Where previous cycles dwelled on speculation or hype, this vision revolves around utility: stablecoins saving merchants 2% on every latte, AI chatbots operating their own businesses, local governments experimenting with liquid democracy.

Yet execution risk looms. Regulators worldwide remain skittish, and user experience is still too messy for the mainstream. 2025 might be the year that crypto and AI finally “grow up,” or it might be a halfway step — it all depends on whether teams can ship real products people love, not just protocols for the cognoscenti.

· 11 min read

On November 13, 2024, 0G Labs announced a $40 million funding round led by Hack VC, Delphi Digital, OKX Ventures, Samsung Next, and Animoca Brands, thrusting the team behind this decentralized AI operating system into the spotlight. Their modular approach combines decentralized storage, data availability verification, and decentralized settlement to enable AI applications on-chain. But can they realistically achieve GB/s-level throughput to fuel the next era of AI adoption on Web3? This in-depth report evaluates 0G’s architecture, incentive mechanics, ecosystem traction, and potential pitfalls, aiming to help you gauge whether 0G can deliver on its promise.

Background

The AI sector has been on a meteoric rise, catalyzed by large language models like ChatGPT and ERNIE Bot. Yet AI is more than just chatbots and generative text; it also includes everything from AlphaGo’s Go victories to image generation tools like MidJourney. The holy grail that many developers pursue is a general-purpose AI, or AGI (Artificial General Intelligence)—colloquially described as an AI “Agent” capable of learning, perception, decision-making, and complex execution similar to human intelligence.

However, both AI and AI Agent applications are extremely data-intensive. They rely on massive datasets for training and inference. Traditionally, this data is stored and processed on centralized infrastructure. With the advent of blockchain, a new approach known as DeAI (Decentralized AI) has emerged. DeAI attempts to leverage decentralized networks for data storage, sharing, and verification to overcome the pitfalls of traditional, centralized AI solutions.

0G Labs stands out in this DeAI infrastructure landscape, aiming to build a decentralized AI operating system known simply as 0G.

What Is 0G Labs?

In traditional computing, an Operating System (OS) manages hardware and software resources—think Microsoft Windows, Linux, macOS, iOS, or Android. An OS abstracts away the complexity of the underlying hardware, making it easier for both end-users and developers to interact with the computer.

By analogy, the 0G OS aspires to fulfill a similar role in Web3:

  • Manage decentralized storage, compute, and data availability.
  • Simplify on-chain AI application deployment.

Why decentralization? Conventional AI systems store and process data in centralized silos, raising concerns around data transparency, user privacy, and fair compensation for data providers. 0G’s approach uses decentralized storage, cryptographic proofs, and open incentive models to mitigate these risks.

The name “0G” stands for “Zero Gravity.” The team envisions an environment where data exchange and computation feel “weightless”—everything from AI training to inference and data availability happens seamlessly on-chain.

The 0G Foundation, formally established in October 2024, drives this initiative. Its stated mission is to make AI a public good—one that is accessible, verifiable, and open to all.

Key Components of the 0G Operating System

Fundamentally, 0G is a modular architecture designed specifically to support AI applications on-chain. Its three primary pillars are:

  1. 0G Storage – A decentralized storage network.
  2. 0G DA (Data Availability) – A specialized data availability layer ensuring data integrity.
  3. 0G Compute Network – Decentralized compute resource management and settlement for AI inference (and eventually training).

These pillars work in concert under the umbrella of a Layer1 network called 0G Chain, which is responsible for consensus and settlement.

According to the 0G Whitepaper (“0G: Towards Data Availability 2.0”), both the 0G Storage and 0G DA layers build on top of 0G Chain. Developers can launch multiple custom PoS consensus networks, each functioning as part of the 0G DA and 0G Storage framework. This modular approach means that as system load grows, 0G can dynamically add new validator sets or specialized nodes to scale out.

0G Storage

0G Storage is a decentralized storage system geared for large-scale data. It uses distributed nodes with built-in incentives for storing user data. Crucially, it splits data into smaller, redundant “chunks” using Erasure Coding (EC), distributing these chunks across different storage nodes. If a node fails, data can still be reconstructed from redundant chunks.

Supported Data Types

0G Storage accommodates both structured and unstructured data.

  1. Structured Data is stored in a Key-Value (KV) layer, suitable for dynamic and frequently updated information (think databases, collaborative documents, etc.).
  2. Unstructured Data is stored in a Log layer which appends data entries chronologically. This layer is akin to a file system optimized for large-scale, append-only workloads.

By stacking a KV layer on top of the Log layer, 0G Storage can serve diverse AI application needs—from storing large model weights (unstructured) to dynamic user-based data or real-time metrics (structured).

PoRA Consensus

PoRA (Proof of Random Access) ensures storage nodes actually hold the chunks they claim to store. Here’s how it works:

  • Storage miners are periodically challenged to produce cryptographic hashes of specific random data chunks they store.
  • They must respond by generating a valid hash (similar to PoW-like puzzle-solving) derived from their local copy of the data.

To level the playing field, the system limits mining competitions to 8 TB segments. A large miner can subdivide its hardware into multiple 8 TB partitions, while smaller miners compete within a single 8 TB boundary.

Incentive Design

Data in 0G Storage is divided into 8 GB “Pricing Segments.” Each segment has both a donation pool and a reward pool. Users who wish to store data pay a fee in 0G Token (ZG), which partially funds node rewards.

  • Base Reward: When a storage node submits valid PoRA proofs, it gets immediate block rewards for that segment.
  • Ongoing Reward: Over time, the donation pool releases a portion (currently ~4% per year) into the reward pool, incentivizing nodes to store data permanently. The fewer the nodes storing a particular segment, the larger the share each node can earn.

Users only pay once for permanent storage, but must set a donation fee above a system minimum. The higher the donation, the more likely miners are to replicate the user’s data.

Royalty Mechanism: 0G Storage also includes a “royalty” or “data sharing” mechanism. Early storage providers create “royalty records” for each data chunk. If new nodes want to store that same chunk, the original node can share it. When the new node later proves storage (via PoRA), the original data provider receives an ongoing royalty. The more widely replicated the data, the higher the aggregate reward for early providers.

Comparisons with Filecoin and Arweave

Similarities:

  • All three incentivize decentralized data storage.
  • Both 0G Storage and Arweave aim for permanent storage.
  • Data chunking and redundancy are standard approaches.

Key Differences:

  • Native Integration: 0G Storage is not an independent blockchain; it’s integrated directly with 0G Chain and primarily supports AI-centric use cases.
  • Structured Data: 0G supports KV-based structured data alongside unstructured data, which is critical for many AI workloads requiring frequent read-write access.
  • Cost: 0G claims $10–11/TB for permanent storage, reportedly cheaper than Arweave.
  • Performance Focus: Specifically designed to meet AI throughput demands, whereas Filecoin or Arweave are more general-purpose decentralized storage networks.

0G DA (Data Availability Layer)

Data availability ensures that every network participant can fully verify and retrieve transaction data. If the data is incomplete or withheld, the blockchain’s trust assumptions break.

In the 0G system, data is chunked and stored off-chain. The system records Merkle roots for these data chunks, and DA nodes must sample these chunks to ensure they match the Merkle root and erasure-coding commitments. Only then is the data deemed “available” and appended into the chain’s consensus state.

DA Node Selection and Incentives

  • DA nodes must stake ZG to participate.
  • They’re grouped into quorums randomly via Verifiable Random Functions (VRFs).
  • Each node only validates a subset of data. If 2/3 of a quorum confirm the data as available and correct, they sign a proof that’s aggregated and submitted to the 0G consensus network.
  • Reward distribution also happens through periodic sampling. Only the nodes storing randomly sampled chunks are eligible for that round’s rewards.

Comparison with Celestia and EigenLayer

0G DA draws on ideas from Celestia (data availability sampling) and EigenLayer (restaking) but aims to provide higher throughput. Celestia’s throughput currently hovers around 10 MB/s with ~12-second block times. Meanwhile, EigenDA primarily serves Layer2 solutions and can be complex to implement. 0G envisions GB/s throughput, which better suits large-scale AI workloads that can exceed 50–100 GB/s of data ingestion.

0G Compute Network

0G Compute Network serves as the decentralized computing layer. It’s evolving in phases:

  • Phase 1: Focus on settlement for AI inference.
  • The network matches “AI model buyers” (users) with compute providers (sellers) in a decentralized marketplace. Providers register their services and prices in a smart contract. Users pre-fund the contract, consume the service, and the contract mediates payment.
  • Over time, the team hopes to expand to full-blown AI training on-chain, though that’s more complex.

Batch Processing: Providers can batch user requests to reduce on-chain overhead, improving efficiency and lowering costs.

0G Chain

0G Chain is a Layer1 network serving as the foundation for 0G’s modular architecture. It underpins:

  • 0G Storage (via smart contracts)
  • 0G DA (data availability proofs)
  • 0G Compute (settlement mechanisms)

Per official docs, 0G Chain is EVM-compatible, enabling easy integration for dApps that require advanced data storage, availability, or compute.

0G Consensus Network

0G’s consensus mechanism is somewhat unique. Rather than a single monolithic consensus layer, multiple independent consensus networks can be launched under 0G to handle different workloads. These networks share the same staking base:

  • Shared Staking: Validators stake ZG on Ethereum. If a validator misbehaves, their staked ZG on Ethereum can be slashed.
  • Scalability: New consensus networks can be spun up to scale horizontally.

Reward Mechanism: When validators finalize blocks in the 0G environment, they receive tokens. However, the tokens they earn on 0G Chain are burned in the local environment, and the validator’s Ethereum-based account is minted an equivalent amount, ensuring a single point of liquidity and security.

0G Token (ZG)

ZG is an ERC-20 token representing the backbone of 0G’s economy. It’s minted, burned, and circulated via smart contracts on Ethereum. In practical terms:

  • Users pay for storage, data availability, and compute resources in ZG.
  • Miners and validators earn ZG for proving storage or validating data.
  • Shared staking ties the security model back to Ethereum.

Summary of Key Modules

0G OS merges four components—Storage, DA, Compute, and Chain—into one interconnected, modular stack. The system’s design goal is scalability, with each layer horizontally extensible. The team touts the potential for “infinite” throughput, especially crucial for large-scale AI tasks.

0G Ecosystem

Although relatively new, the 0G ecosystem already includes key integration partners:

  1. Infrastructure & Tooling:

    • ZK solutions like Union, Brevis, Gevulot
    • Cross-chain solutions like Axelar
    • Restaking protocols like EigenLayer, Babylon, PingPong
    • Decentralized GPU providers IoNet, exaBits
    • Oracle solutions Hemera, Redstone
    • Indexing tools for Ethereum blob data
  2. Projects Using 0G for Data Storage & DA:

    • Polygon, Optimism (OP), Arbitrum, Manta for L2 / L3 integration
    • Nodekit, AltLayer for Web3 infrastructure
    • Blade Games, Shrapnel for on-chain gaming

Supply Side

ZK and Cross-chain frameworks connect 0G to external networks. Restaking solutions (e.g., EigenLayer, Babylon) strengthen security and possibly attract liquidity. GPU networks accelerate erasure coding. Oracle solutions feed off-chain data or reference AI model pricing.

Demand Side

AI Agents can tap 0G for both data storage and inference. L2s and L3s can integrate 0G’s DA to improve throughput. Gaming and other dApps requiring robust data solutions can store assets, logs, or scoring systems on 0G. Some have already partnered with the project, pointing to early ecosystem traction.

Roadmap & Risk Factors

0G aims to make AI a public utility, accessible and verifiable by anyone. The team aspires to GB/s-level DA throughput—crucial for real-time AI training that can demand 50–100 GB/s of data transfer.

Co-founder & CEO Michael Heinrich has stated that the explosive growth of AI makes timely iteration critical. The pace of AI innovation is fast; 0G’s own dev progress must keep up.

Potential Trade-Offs:

  • Current reliance on shared staking might be an intermediate solution. Eventually, 0G plans to introduce a horizontally scalable consensus layer that can be incrementally augmented (akin to spinning up new AWS nodes).
  • Market Competition: Many specialized solutions exist for decentralized storage, data availability, and compute. 0G’s all-in-one approach must stay compelling.
  • Adoption & Ecosystem Growth: Without robust developer traction, the promised “unlimited throughput” remains theoretical.
  • Sustainability of Incentives: Ongoing motivation for nodes depends on real user demand and an equilibrium token economy.

Conclusion

0G attempts to unify decentralized storage, data availability, and compute into a single “operating system” supporting on-chain AI. By targeting GB/s throughput, the team seeks to break the performance barrier that currently deters large-scale AI from migrating on-chain. If successful, 0G could significantly accelerate the Web3 AI wave by providing a scalable, integrated, and developer-friendly infrastructure.

Still, many open questions remain. The viability of “infinite throughput” hinges on whether 0G’s modular consensus and incentive structures can seamlessly scale. External factors—market demand, node uptime, developer adoption—will also determine 0G’s staying power. Nonetheless, 0G’s approach to addressing AI’s data bottlenecks is novel and ambitious, hinting at a promising new paradigm for on-chain AI.

· 5 min read
Dora Noda

BlockEden.xyz, known for its Remote Procedure Call (RPC) infrastructure, is expanding into AI inference services. This evolution leverages its open-source, permissionless design to create a marketplace where model researchers, hardware operators, API providers, and users interact seamlessly. The network's Relay Mining algorithm ensures a transparent and verifiable service, presenting a unique opportunity for large model AI researchers to monetize their work without infrastructure maintenance.

The Core Problem

The AI landscape faces significant challenges, including:

  • Restricted Model-Serving Environments: Resource-intensive infrastructure limits AI researchers' ability to experiment with various models.
  • Unsustainable Business Models for Open Source Innovation: Independent engineers struggle to monetize their work, relying on major infrastructure providers.
  • Unequal Market Access: Enterprise-grade models dominate, leaving mid-tier models and users underserved.

BlockEden.xyz’s Unique Value Proposition

BlockEden.xyz addresses these issues by decoupling the infrastructure layer from the product and services layer, ensuring an open and decentralized framework. This setup enables high-quality service delivery and aligns incentives among all network participants.

Key benefits include:

  • Established Network: Utilizing an existing network of BlockEden.xyz's services to streamline model access and service quality.
  • Separation of Concerns: Each stakeholder focuses on their strengths, improving overall ecosystem efficiency.
  • Incentive Alignment: Cryptographic proofs and performance measurements drive competition and transparency.
  • Permissionless Models & Supply: An open marketplace for cost-effective hardware supply.

Decentralized AI Inference Stakeholders

Model Providers: Coordinators

Coordinators manage the product and services layer, optimizing service quality and providing seamless access for applications. Coordinators discreetly ensure supplier integrity by posing as regular users, offering unbiased performance assessments.

Model Users: Applications

Applications typically use first-party coordinators but can also access the network with a third-party for enhanced privacy and cost savings. Direct access allows for diverse use case experimentation and eliminates intermediary costs.

Model Suppliers: Hardware Operators

Suppliers run inference nodes to earn tokens. Their competencies in DevOps, hardware maintenance, and logging are crucial for network growth. The permissionless approach encourages participation from various hardware providers, including those with idle or dormant resources.

Model Sources: Engineers & Researchers

Researchers and institutions that open-source models can earn revenue based on usage. This model incentivizes innovation without the need for infrastructure maintenance, providing a sustainable business model for open-source contributors.

Working with Cuckoo Network

BlockEden.xyz collaborates with Cuckoo Network to revolutionize AI inference through a decentralized and permissionless infrastructure. This partnership focuses on leveraging both platforms' strengths to create a seamless and efficient ecosystem for AI model deployment and monetization.

Key Collaboration Areas

  • Infrastructure Integration: Combining BlockEden.xyz's robust RPC infrastructure with Cuckoo Network's decentralized model-serving capabilities to offer a scalable and resilient AI inference service.
  • Model Distribution: Facilitating the distribution of open-source AI models across the network, enabling researchers to reach a broader audience and monetize their innovations without the need for extensive infrastructure.
  • Quality Assurance: Implementing mechanisms for continuous monitoring and assessment of model performance and supplier integrity, ensuring high-quality service delivery and reliability.
  • Economic Incentives: Aligning economic incentives across all stakeholders through cryptographic proofs and performance-based rewards, fostering a competitive and transparent marketplace.
  • Privacy and Security: Enhancing privacy-preserving operations and secure model inference through advanced technologies like Trusted Execution Environments (TEE) and decentralized data storage solutions.
  • Community and Support: Building a supportive community for AI researchers and developers, providing resources, guidance, and incentives to drive innovation and adoption within the decentralized AI ecosystem.

By partnering with Cuckoo Network, BlockEden.xyz aims to create a holistic and decentralized approach to AI inference, empowering researchers, developers, and users with a robust, transparent, and efficient platform for AI model deployment and utilization. You can now try decentralized text-to-image API at https://blockeden.xyz/api-marketplace/cuckoo-ai.

Input/Output of a Decentralized Inference Network

LLM Inputs to Cuckoo Network:

  • Open-source models
  • Demand from end-users or Applications
  • Aggregated supply from commodity hardware
  • Quality of service guarantees

LLM Outputs from Cuckoo Network:

  • No downtime
  • Seamless model experimentation
  • Public model evaluation
  • Privacy-preserving operations
  • Censorship-free models

Web3 Ecosystem Integrations

BlockEden.xyz's RPC protocol can integrate with other Web3 protocols to enhance Decentralized AI (DecAI):

Data & Storage Networks: Seamless integration with decentralized storage solutions like Filecoin/IPFS and Arweave for model storage and data integrity.

Compute Networks: Complementary services leveraging decentralized computing layers like Akash and Render, supporting both dedicated and idle hardware.

Inference Networks: Flexible deployment models and robust ecosystems supporting diverse inference tasks.

Applications: AI agents, consumer apps, and IoT devices benefit from DecAI inference for personalized services, data privacy, and edge decision-making.

Summary

BlockEden.xyz's established infrastructure and economic design unlock new opportunities for open-source AI. By providing a decentralized and verifiable service, it bridges the gap between open-source AI and Web3, enabling innovative, sustainable, and reliable services. This approach allows for greater model diversity, better market access for SMEs, and a new business model for open-source researchers. Future developments will continue to expand the ecosystem, ensuring BlockEden.xyz remains a robust and adaptable solution in the evolving AI and blockchain landscapes.

· 4 min read
Dora Noda

We are glad to announce that BlockEden.xyz, web3 developers' go-to platform for API marketplace, has added a new, powerful capability – OpenAI API. Yes, you heard it right! Developers, tech enthusiasts, and AI pioneers can now leverage the cutting-edge machine learning models offered by OpenAI, directly through BlockEden's API Marketplace.

Before we dive into the how-to guide, let's understand what OpenAI API brings to the table. OpenAI API is a gateway to AI models developed by OpenAI, such as the industry-renowned GPT-3, the state-of-the-art transformer-based language model known for its remarkable ability to understand and generate human-like text. The API enables developers to use this advanced technology for a variety of applications, including drafting emails, writing code, answering questions, creating written content, tutoring, language translation, and much more.

Now, let's see how you can incorporate the power of OpenAI API into your applications using BlockEden.xyz. You can do it in three ways: using Python, using JavaScript (Node.js), or using curl directly from the command line. In this blog, we're going to provide the basic setup for each method, using a simple "Hello, World!" example.

The API key below is public and subject to change and rate limit. Get your own BLOCKEDEN_API_KEY from https://blockeden.xyz/dash instead.

Python:

Using Python, you can use the OpenAI API as shown in the following snippet:

import openai

BLOCKEDEN_API_KEY = "8UuXzatAZYDBJC6YZTKD"
openai.api_key = ""
openai.api_base = "https://api.blockeden.xyz/openai/" + BLOCKEDEN_API_KEY + "/v1"

response = openai.ChatCompletion.create(
model="gpt-3.5-turbo-16k",
messages=[{"role": "user", "content": "hello, world!"}],
temperature=0,
max_tokens=2048,
top_p=1,
frequency_penalty=0,
presence_penalty=0
)

print(response["choices"])

JavaScript (Node.js):

You can also utilize the OpenAI API with JavaScript. Here's how you can do it:

const { Configuration, OpenAIApi } = require("openai");

const BLOCKEDEN_API_KEY = "8UuXzatAZYDBJC6YZTKD";
const configuration = new Configuration({
basePath: "https://api.blockeden.xyz/openai/" + BLOCKEDEN_API_KEY + "/v1"
});
const openai = new OpenAIApi(configuration);

(async () => {
const response = await openai.createChatCompletion({
model: "gpt-3.5-turbo-16k",
messages: [{role: "user", content: "hello, world!"}],
temperature: 0,
max_tokens: 2048,
top_p: 1,
frequency_penalty: 0,
presence_penalty: 0,
});

console.log(JSON.stringify(response.data.choices, null, 2));
})()

cURL:

Last but not least, you can call the OpenAI API using curl directly from your terminal:

curl https://api.blockeden.xyz/openai/8UuXzatAZYDBJC6YZTKD/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-3.5-turbo-16k",
"messages": [{"role": "user", "content": "hello, world!"}],
"temperature": 0,
"max_tokens": 2048,
"top_p": 1,
"frequency_penalty": 0,
"presence_penalty": 0
}'

So, what's next? Dive in, experiment, and discover how you can leverage the power of OpenAI API for your projects, be it for chatbots, content generation, or any other NLP-based application. The possibilities are as vast as your imagination. With BlockEden.xyz's seamless integration with OpenAI, let's redefine the boundaries of what's possible.

For more information on OpenAI's capabilities, models, and usage, visit the official OpenAI documentation.

Happy Coding!

What is BlockEden.xyz

BlockEden.xyz is an API marketplace powering DApps of all sizes for Sui, Aptos, Solana, and 12 EVM blockchains. Why do our customers choose us?

  1. High availability. We maintain 99.9% uptime since our first API - Aptos main net launch.
  2. Inclusive API offerings and community. Our services have expanded to include Sui, Ethereum, IoTeX, Solana, Polygon, Polygon zkEVM, Filecoin, Harmony, BSC, Arbitrum, Optimism, Gnosis, Arbitrum Nova & EthStorage Galileo. Our community 10x.pub has 4000+ web3 innovators from Silicon Valley, Seattle, and NYC.
  3. Security. With over $45 million worth of tokens staked with us, our clients trust us to provide reliable and secure solutions for their web3 and blockchain needs.

We provide a comprehensive suite of services designed to empower every participant in the blockchain space, focusing on three key areas:

  • For blockchain protocol builders, we ensure robust security and decentralization by operating nodes and making long-term ecosystem contributions.
  • For DApp developers, we build user-friendly APIs to streamline development and unleash the full potential of decentralized applications.
  • For token holders, we offer a reliable staking service to maximize rewards and optimize asset management.