0. Intro to ORA

ORA is Ethereum’s trustless AI that enables AI and any-size compute on blockchains.

ORA breaks down the limitations of smart contracts by offering AI, richer data sources and arbitrary compute so developers can innovate freely.

ORA’s work has been trusted by Compound, Ethereum Foundation, Uniswap, Optimism, and beyond.

1. ORA’s Onchain AI

ORA makes Onchain AI reality. ORA contributes a suite of cutting-edge research and products to the field of onchain AI. The products include zkML, opML, and opp/ai.

a) zkML: Zero-knowledge Machine Learning

zkML is a cryptographic approach to onchain machine learning.

ORA is at the forefront of zkML. Moreover, ORA invented the world’s first zkML library: Keras2Circom.

According to benchmark, research supported by Ethereum Foundation, Keras2Circom is outperforming other zkML frameworks.

Also, Keras2Circom is production-ready, and battle-tested with rich ecosystem.

Read more here, and check out Keras2Circom library on GitHub.

b) opML: Optimistic Machine Learning

opML is a cost-efficient and highly efficient machine learning framework to enable onchain machine learning now.

ORA is the inventor and creator of opML, in terms of both academic research and open-source implementation.

zkML can generate cryptographic proof for ML computations that can be succinct enough to be verified on-chain. However, current computing power cannot practically generate proofs efficiently and affordably, especially for large AI models.

Contrary to zkML, opML can efficiently bring large models like Grok’s 314 billion parameter model on-chain, reducing overhead costs by over 1,000,000x.

Learn more in our paper: https://arxiv.org/abs/2401.17555.

c) opp/ai: Optimistic Privacy-Preserving AI

opp/ai, Optimistic Privacy-Preserving AI, integrates zkML for privacy with opML for efficiency.

opp/ai is a hybrid model tailored for onchain AI.

ORA is the inventor of opp/ai.

Compared to pure zkML, opp/ai performs far better while maintaining the same privacy feature of zkML.

Read more here and learn more in our paper: https://arxiv.org/abs/2402.15006.

2. ORA Onchain AI Oracle (OAO)

a) Introduction

ORA’s Onchain AI Oracle (OAO) is ORA’s verifiable and decentralized AI oracle.

OAO enables anyone to use onchain AI inference on any blockchain.

OAO uses opML to create a verifiable proof for ML computations that can feasibly be verified on the blockchain. This opens up new possibilities for AI in blockchain.

b) OAO on Ethereum and Optimism

OAO has been running, based on opML, on Ethereum and Optimism to generate verifiable AI inferences.

Last month, ORA OAO was deployed on Ethereum mainnet.

And recently, in collaboration with Optimism, ORA OAO is integrated on Optimism mainnet.

Read more on the announcement of OAO deployment on Ethereum and the one on Optimism.

c) Build with OAO

As a developer, you can check out the following resources to build AI-powered onchain applications:

1. OAO Repo: OAO.
2. OAO Doc: AI Oracle.
3. Video Tutorial on Building with OAO: How to interact and build with OAO.
4. Ideas to Build with OAO for Inspiration: So You Wanna Build with Onchain AI.
5. ORA Ecosystem Projects for Reference: awesome-ora.

3. ORA Initial Model Offering (IMO)

In this age of AI, ORA introduced a new mechanism, IMO (Initial Model Offering).

a) Introduction

TL;DR: IMO tokenizes AI model onchain.

1. For AI models, IMO enables sustainable funding for open-source AI models.
2. For ecosystems, IMO helps align values and incentives for distribution and ongoing contribution.
3. For token holders, IMO lets anyone capture the value of AI models onchain, from sources including onchain revenue and inference assets (eg. ERC-7007).

Many open-sourced AI models face the challenge in monetizing their contributions, leading to a lack of motivation for contributors and organizations alike. As a result, the AI industry is currently led by closed-source, for-profit companies. The winning formula for open-source AI models is the need to gather more funding and build in public.

With IMO, we can win the fight for open-source AI. IMO can enable the sustainability of the open-source AI model’s ecosystem by fostering long-term benefits and encouraging engagement and funding to the open-source AI community. The win is when we have better open-source models than proprietary models.

IMO tokenizes the ownership of open-source AI models, sharing its profit to the token holders.

b) Core Components of IMO

IMO is permissionless, so anyone and any community can carry out an IMO for their AI model.

In IMO, there are two core components:

1. Onchain AI Model with Verifiability
2. Revenue Sharing of Onchain Usage

For Onchain AI, we need tokens to be tied to right AI model and inference. ORA is enabling it with the previously mentioned ORA OAO, the world’s first AI Oracle for any AI model.

For Revenue Sharing of Onchain Usage, ORA introduced ERC-7641: Intrinsic RevShare Token for fair revenue-sharing as basis of IMO. IMO tokens are not AI meme coin, but represent a share of an AI model. Holders benefit from AI model’s revenue from OAO and inference asset like ERC-7007: Verifiable AI-Generated Content Token.

c) Summary of IMO

IMO is permissionless, so anyone and any community can carry out an IMO for their AI model.

IMO tokenizes specific AI models, which gives:

1. The community the ability to efficiently fundraise for open-source.
2. Contributors incentives to continue improving a globally accessible model.
3. Token holders revenue opportunities from the use of the model onchain.

A meaningful IMO requires Onchain AI and a Revenue Sharing mechanism of IMO token:

1. Onchain AI can be achieved by ORA OAO.
2. Revenue comes from model usage in ORA OAO and inference asset such as ERC-7007 co-authored by ORA.
3. Revenue sharing mechanism can be enforced by ERC-7641 authored by ORA.

Read more about IMO here and here.

Watch ORA’s announcement of IMO at ETHDenver.

Watch IMO Explained in 60 Seconds.

4. OpenLM IMO: World’s First IMO

$OLM on Mainnet: 0xe5018913F2fdf33971864804dDB5fcA25C539032LP Address on Mainnet: 0xB57CFe32dbF5227d9c9A03eF3D2E9E53cb4524B0

a) Introduction to OpenLM

OpenLM is a performative language modeling (LM) repository, aimed to facilitate research on medium sized LMs.

OpenLM is open, performative, and decentralized AI, as opposed to closed, centralized, licensed LLM’s funded and overseen by duplicitous Big Tech oligarchs.

OpenLM is an open-source model under MIT-license created by a decentralized team. Their contributions will be recognized by this donation, which will also help incentivize and facilitate r&d on open-source LMs that are accessible to any one.

b) OpenLM IMO

On April 10, we announced the world’s first IMO: OpenLM IMO.

OpenLM IMO tokenizes OpenLM’s open source model.

Like Prometheus stealing fire for civilization, ORA demonstrates the benefits an IMO unlocks for open-source AI communities with this first IMO of OpenLM

$OLM is not ORA’s token. It is a tokenization of the OpenLM model on Ethereum with ownership shared among OpenLM contributors and community. Nevertheless, ORA’s onchain AI oracle enables tokenization of ai models.

IMO will be a cornerstone of OpenLM’s journey, providing funding and incentives to nurture sustainable ecosystem, democratize access, & propel continuous development.

IMO for OpenLM is poised to revolutionize landscape of LLM with power of open-source software & community.

Read more about OpenLM IMO here.

c) OpenLM IMO Event

The world’s first IMO of OpenLM IMO was a smashing success.

All 500 million tokens were sold for 150 ETH (about 0.5 million USD). This occurred in 5 minutes. This is a testimony to high demand in the face of low supply. $OLM continues to change hands on decentralized exchanges of Uniswap.

Unfortunately, the great majority of people who tried to purchase $OLM at the start of the sale did not have their transactions successfully processed because demand far exceeded the limited supply.

This was the first IMO and there will be more to come. Future IMO’s will have different parameters that enable more valued people and wallets to get involved.

d) Roadmap of OpenLM IMO

The goal of IMO is to foster open-source communities and grow ecosystems. OpenLM IMO provides the open-source community of OpenLM with more resources.

This is the flagship demonstration of IMO as a technology. This is the start of a movement towards a more sustainable, competitive and open-source AI future.

The following is the roadmap to enable OpenLM IMO’s success.

1. OAO Integration

To enable revenue sharing of $OLM, ORA will integrate OpenLM AI model into Onchain AI Oracle. By this, onchain revenue can be generated from each time users interact with OpenLM model, tracked by OAO.

1. OpenLM Ecosystem Expansion

For AI models, IMO enables sustainable funding for open-source AI models. With this effort of OpenLM IMO, various projects can use OpenLM to contribute to the $OLM’s revenue pool.

1. Donation to OpenLM Community

As previously announced and planned, 10% of $OLM IMO tokens go to existing and future OpenLM contributors.

We are finalizing all the details for the support to open and decentralized AI community.

1. Revenue Sharing Events

OpenLM RevShare Token ($OLM) has the following features:

1. Revenue Sharing: Part of the revenue from OAO or other sources will be distributed to the revenue-sharing pool of $OLM tokens. Token holders can claim revenue every 90 days after the snapshot.
2. Burn: Part of the revenue from OAO or other sources will be distributed to the burning pool of $OLM tokens. Token holders can burn their tokens as a buyback mechanism. The burning mechanism will support the “floor price” of OpenLM tokens.

About ORA

ORA is Ethereum’s trustless AI that enables AI and any-size compute on blockchains.

ORA breaks down the limitations of smart contracts by offering AI, richer data sources and arbitrary compute so developers can innovate freely.

ORA’s work has been trusted by Compound, Ethereum Foundation, Uniswap, Optimism and beyond.

www.ora.io | x.com/oraprotocol | discord.gg/MgyYbW9dQj

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1. This article is reprinted from [Mirror]. All copyrights belong to the original author [Ed Roman, Managing Partner at Hack VC]. If there are objections to this reprint, please contact the Gate Learn team, and they will handle it promptly.
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