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f(A.I.)r Launch is a groundbreaking method for launching crypto projects that ensures fair token distribution using AI.
By evaluating participants based on AI chat interactions, onchain activities, and social media presence, f(A.I.)r Launch guarantees equal opportunities for all participants.
This system addresses the common issues in traditional token launches, such as early investor advantages, by creating a transparent, community-driven process.
The AI-powered model continuously learns from previous launches, refining its fairness and accuracy over time. Moreover, it integrates seamlessly with existing platforms, making it easy for any launchpad to adopt.
f(A.I.)r Launch is driven by OLM's OpenLM-Score model, also known as the (A.I.)location Oracle. This model plays a central role in ensuring that token allocations are based on genuine user engagement, providing a fair and transparent process for all participants.
The first f(A.I.)r Launch is enabled by ChatOLM for the launch of 7007 token, marking a significant milestone in the application of this innovative system.
For more details, check out:
https://www.openlm.io/
OLM (OpenLM RevShare Token) is the world’s first tokenized AI model fully onchain, unlocked by the world’s first Initial Model Offering (IMO).
OLM introduces a novel ecosystem where AI models are not only built and trained, but also provide decentralized AI inference on blockchain, with transparent revenue-sharing mechanisms among OLM token holders.
OLM focuses on three sectors:
AI R&D: OLM builds, trains, and fine-tunes AI models.
Crypto AI: OLM integrates AI models into ORA's AI Oracle onchain.
$OLM Tokenization: $OLM token holders share revenue of the whole OLM ecosystem.
$OLM is on Ethereum mainnet and BNB Smart Chain.
OLM is powering decentralized applications in AI and Crypto.
OLM's AI models have been integrated into the ORA AI Oracle, which facilitates AI inference on the blockchain, ensuring verifiable, neutral, and transparent AI inference with opML.
OLM's OpenLM Score model enabled the f(A.I.)r launch of 7007, where its AI model determined token allocation, ensuring fairness by removing human bias and unfairness from the decision-making process and bots.
OLM’s AI models is deployed within ChatOLM, a decentralized AI chatbot. This chatbot leverages OLM's OpenLM and OpenLM-Chat language models in ORA's AI Oracle to offer onchain AI conversations.
2024 April - OLM IMO: The world's first IMO was completed successfully, marking the launch of OLM as a tokenized AI model.
2024 April - OLM DAO: Governance of OLM is decentralized through the OLM DAO, which allows holders to participate in decision-making.
2024 May - OLM Fine-Tuned Models: After launch, OLM’s AI models were fine-tuned for specialized use cases, increasing their adaptability and efficiency in real-world applications.
2024 May - Integration into ORA AI Oracle: OLM’s models were successfully integrated with ORA AI Oracle, bringing on-chain AI inference to blockchain projects, enhancing transparency and accountability.
2024 July - ChatOLM Application: OLM powers the decentralized AI chatbot ChatOLM, which is already live, offering autonomous AI-powered conversations using onchain inference.
2024 August - 1st RevShare Event: OLM completed its first revenue-sharing event, rewarding token holders by distributing proceeds generated from onchain AI inference.
2024 September - 1st f(A.I.)r Launch for 7007: OLM demonstrated its fair and neutral decision-making capabilities during 7007’s token launch, enabling AI to determine user allocation fairly and verifiably.
2024 October - SearchOLM in ChatOLM: OLM built advanced search capabilities within ChatOLM, allowing users to search the web, with uncensored information delivered by onchain AI.
2024 November - Experiment of OLM Agent: The OLM Twitter account was temporarily handed over to an OLM Agent to experiment with AI-driven sentiment governance before reverting to community control.
2024 December & 2025 January - Airdrops from IMOs: $OLM is the world's first Initial Model Offering and pioneer of this paradigm, so all $OLM holders are receiving airdrops from all future IMOs including $BRM and $KUMO.
Ongoing - OLMs: OLM will build tools and platform to create, customize, and deploy verifiable AI agents on ChatOLM, with modular prompts, trustless AI inference, and permissionless sharing.
Ongoing - 2nd f(A.I.)r Launch: The second f(A.I.)r launch is currently in planning stages, promising to leverage OLM’s AI to power even more decentralized applications.
Initial Model Offering (IMO), created and implemented by ORA, is a framework for tokenizing AI models onchain. It provides sustainable funding for open-source AI models and aligns incentives for developers, ecosystems, and token holders. Here’s a quick overview of how IMO benefits everyone:
For AI Models: IMO offers a way to fund open-source AI models by tokenizing them. This ensures ongoing development and contributions without relying on traditional monetization.
For Ecosystems: IMO brings developers and contributors together, aligning their goals through shared incentives. This encourages ongoing contributions and improvements.
For Token Holders: IMO allows token holders to capture the value generated by AI models. This includes onchain revenue and assets, providing long-term benefits.
OLM is the first AI model launched through the IMO framework.
Since it’s open-source, anyone can contribute, speeding up development and creating a shared knowledge base.
Unlike private AI companies, OLM benefits from decentralized collaboration and transparent governance, leading to faster growth.
Through IMO, OLM:
Accelerates development with community input.
Aligns incentives for both developers and token holders.
Offers transparent governance that benefits all participants.
IMO changes the game by making open-source AI development sustainable. It replaces the traditional venture-funded model with a decentralized, community-driven approach that allows faster growth and wider participation.
For more details, check out:
https://docs.ora.io/doc/the-ora-network/ai-oracle-network/references#openlm-1b
OLM’s AI models are seamlessly integrated with ORA’s AI Oracle, bringing AI inference directly onto the blockchain.
This enables the decentralized, verifiable use of AI within onchain environments, providing transparency and reliability to the users and applications that interact with OLM’s models.
ORA’s AI Oracle serves as the gateway that enables OLM’s AI models to operate onchain. The Oracle has been called over 100,000 times, demonstrating the growing demand for onchain AI services and generating consistent revenue through these interactions.
The Oracle ensures that all AI inferences made by OLM’s models are securely processed and recorded on the blockchain, making it a key component of the decentralized AI ecosystem.
Using Optimistic Machine Learning in ORA's AI Oracle, OLM’s models provide verifiable inferences on the Ethereum blockchain and Layer 2 (L2) networks.
This means that all AI outputs are recorded and can be verified for accuracy, ensuring trustworthiness.
The integration of OLM’s models with ORA’s AI Oracle has already proven its value.
OLM’s models have been called onchain around 40,000 times in just a few months, generating substantial revenue for $OLM token holders.
Each onchain interaction contributes to the growth of OLM’s ecosystem, aligning incentives for the community and token holders.
https://huggingface.co/OLMResearch
OpenLM-Chat 1B: A 1-billion-parameter model optimized for conversational tasks, enabling highly effective interactions in chat applications and other natural language interfaces.
OpenLM-Chat 7B: A more advanced 7-billion-parameter model, offering even more refined performance in conversational AI, designed for complex and nuanced dialogue.
OpenLM-Score: A specialized model used to assess and evaluate users in various decentralized applications, such as f(A.I.)r Launch, ensuring transparent and fair processes.
These models are continually enhanced through contributions from the community, driving innovation and refining their capabilities over time.
OLM has established an organization on Hugging Face to host and share its models with the world. This enables developers to access and contribute to OLM’s cutting-edge AI models.
OLM’s AI research and development are governed by the decentralized community of OLM DAO.
Through this governance model, decisions about OLM’s AI roadmap, model improvements, and new projects are made collectively by token holders.
The community votes on proposals through OLM’s governance portal on Snapshot, ensuring that the development remains transparent and community-driven.
You can explore the data on usage and revenue generation through the following dashboard: .
OLM's foundation is built on open language models like , which serves as the core of its AI development. The OpenLM model provides the framework for OLM’s subsequent advancements, allowing for continuous improvement and collaboration with the global AI community.
Building on the success of OpenLM, OLM has developed and fine-tuned to serve diverse use cases:
You can explore and collaborate with OLM’s AI research here: .
Participate in OLM DAO governance here: .
$OLM is an ERC-20 token that incorporates a cutting-edge revenue-sharing mechanism through compliance with the ERC-7641 standard.
This allows token holders to share in the revenue generated by OLM’s onchain AI models, creating a fair, sustainable, and decentralized ecosystem. Below is an overview of the core aspects of OLM tokenization:
ERC-7641 extends the basic functionalities of ERC-20 by introducing a built-in revenue-sharing mechanism.
Through this standard, $OLM token holders can periodically claim their share of the revenue generated by OLM’s AI models. The revenue is collected in a communal pool, and holders can redeem their portion by burning tokens or claiming rewards at designated intervals.
Revenue Sharing: Token holders periodically claim a portion of the revenue generated by OLM's AI models, distributed transparently via smart contracts. All revenues generated for OLM will be shared among $OLM holders, ensuring a fair distribution of profits.
Medium of Value: $OLM tokens are not just for revenue-sharing; they are also used to access services and training resources for AI model development. This ensures that token holders are actively engaged in the ecosystem’s growth and sustainability.
OLM’s integration with ERC-7641 provides a systematic and transparent approach to sharing the revenue generated by its AI models. Token holders can claim or burn tokens to receive a share of the revenue pool, ensuring a balanced and equitable distribution.
https://ai.ora.io
ORA’s Onchain AI Oracle is a trustless solution that brings AI inference directly onto any blockchain, providing verifiable AI outputs and enabling decentralized applications to integrate AI capabilities.
Trustless AI Inference: ORA ensures that all AI outputs are verifiable on blockchains, using Optimistic Machine Learning. This guarantees transparency and reliability in every AI inference made onchain.
Integrated OLM Models: ORA AI Oracle integrates OLM’s AI models, which have been called over 40,000 times onchain. These models power various decentralized applications, generating ETH revenue for the ecosystem and providing a source of value for $OLM token holders.
ORA’s staking program uses $OLM as the staking token. Holders who stake their $OLM tokens in the Oracle are incentivized with ORA points, which offer additional rewards and benefits within the ORA ecosystem. This staking mechanism strengthens the alignment between $OLM holders and the ORA Oracle’s success.
In addition to staking, users who utilize OLM’s models through the ORA AI Oracle will also earn ORA points. This incentivizes the use of OLM’s AI models for onchain AI inferences, ensuring active participation in the ecosystem and further growing the value of $OLM.
With the integration of OLM's AI models and a robust staking program, ORA AI Oracle is leading the way in bringing trustless, decentralized AI to the blockchain. It not only generates revenue for $OLM holders but also incentivizes participation through ORA points, creating a sustainable and fair ecosystem for all participants.
OLM ecosystem is growing rapidly, driven by its integration with ORA's Onchain AI Oracle and applications across decentralized platforms. Here’s an overview of the core data and key components of the ecosystem:
3 Models Integrated: OLM’s models have been integrated into ORA’s Onchain AI Oracle, enabling AI-powered applications across multiple platforms.
40,000+ Onchain Calls: OLM’s AI models have been called onchain over 40,000 times, generating revenue for the ecosystem and providing value to $OLM token holders.
ORA is Ethereum's Trustless AI, designed to bring AI inference on any blockchain.
The ORA Onchain AI Oracle integrates OLM’s models, providing verifiable AI outputs onchain. This has been instrumental in generating revenue in ETH for OLM through onchain AI calls.
ChatOLM is a decentralized AI chatbot powered by censorship-resistant onchain AI.
OLM’s models have been a core part of ChatOLM, enabling decentralized chat interactions. The models have seen widespread use, with thousands of daily onchain calls powering conversations.
7007 is building a protocol for onchain AIGC (AI-generated content) NFTs and exchanges.
The f(A.I.)r Launch of 7007’s token utilized OLM’s scoring model to determine fair token allocations. The model was called over 14,000 times onchain in just one day, showing its robust demand and utility in decentralized token distribution.
Through these integrations, OLM is cementing its place as a critical player in decentralized AI and blockchain applications, generating value for its token holders and driving innovation in the space.
ChatOLM is moving towards becoming open source and public, allowing developers to integrate its decentralized AI features into their own applications.
We are currently working on providing a general API for both SearchOLM and ChatOLM, enabling users to access real-time search and AI chat functionality outside the platform.
The API will allow seamless integration of ChatOLM’s capabilities, including text and image generation, as well as real-time information retrieval. More details on usage and availability will be shared as we continue development.
Stay tuned for updates on API access and documentation.
Much like how Telegram differs from WhatsApp, ChatOLM distinguishes itself from centralized chatbot services like ChatGPT by being decentralized and censorship-resistant.
Unlike traditional AI applications, which rely on centralized servers, ChatOLM is powered by decentralized infrastructure of ORA AI. This unique architecture allows for open, free-flowing communication that is resilient against censorship, while also providing users unlimited and permissionless features in their interactions.
ChatOLM is enabling unrestricted use cases such as NSFW agents, and Search for censored information compared to platforms like ChatGPT or Perplexity.
ChatOLM is designed to offer a seamless, dual-functionality experience through its two core features:
Much like ChatGPT, ChatOLM’s chat function allows users to engage in natural language conversations powered by advanced AI language models.
Users can ask questions, hold discussions, or receive assistance in real-time. The decentralized nature of ChatOLM means that these conversations are processed and settled on blockchains in a verifiable way.
ChatOLM Interface
The front-end where users submit AI requests (e.g., “What is decentralized AI?”).
Sends requests to the smart contract for processing.
Smart Contract
A blockchain-based intermediary that routes requests from the interface to the ORA AI Oracle.
Handles payment logic and integrates with the AI system.
ORA AI Oracle
Acts as a bridge between the smart contract and the AI models.
Integrates OLM AI Models to process the request.
Ensures secure, verifiable AI model selection and execution.
ORA Decentralized AI Network
A decentralized network of nodes responsible for running AI inference.
Processes AI requests and generates the response, which is sent back via the AI Oracle.
User Input: The user submits a query through the ChatOLM Interface.
Smart Contract: The query is sent to a smart contract on-chain.
ORA AI Oracle: The smart contract forwards the request to the ORA AI Oracle, which selects the appropriate OLM AI Model.
Decentralized AI Network: The Oracle relays the request to the network, where the AI inference is processed.
Response: The processed result is returned through the same path to the ChatOLM Interface.
Beyond its chat function, ChatOLM also incorporates a search feature, functioning similarly to platforms like Perplexity.
This feature allows users to retrieve information from the web through a search interface powered by decentralized AI.
ChatOLM Interface
The front-end where users submit AI search requests (e.g., “Who’s Vitalik?”).
Initiates the request by sending it to the AI Search Node.
AI Search Node
Receives the search query and comprehends the request by fetching information from external sources like DuckDuckGo or other search engines.
Processes and organizes the contextual information into a format suitable for AI inference.
Sends the processed context to the smart contract.
Smart Contract
Acts as the on-chain handler that routes the processed search context from the AI Search Node to the ORA AI Oracle.
Ensures secure interaction and token/payment handling (if applicable).
ORA AI Oracle
Integrates with the OLM AI Models to process the search context received from the smart contract.
Relays the search request to the decentralized AI network for inference.
ORA Decentralized AI Network
Processes the AI inference using the contextual data provided by the Oracle.
The decentralized network performs the inference and generates the AI-based search result.
User Input: The user submits a search query through the ChatOLM Interface.
AI Search Node: The query is received by the AI Search Node, which gathers relevant information from search engines and organizes it into context.
Smart Contract: The organized context is forwarded to the smart contract, which integrates with the ORA AI Oracle.
ORA AI Oracle: The Oracle selects the appropriate OLM AI Model and sends the request to the decentralized network for processing.
Decentralized AI Network: The network processes the inference and returns the search result.
Response: The result is passed back to the ChatOLM Interface for display to the user.
While ChatOLM’s Chat and Search functionalities both leverage decentralized AI, they serve distinct purposes and utilize different technologies to meet user needs.
Chat Functionality
Text and Image Generation: ChatOLM’s Chat is built on advanced language models (similar to ChatGPT) and can also integrate Stable Diffusion for image generation. This allows ChatOLM’s Chat to handle a wide range of natural language tasks, including answering questions, providing explanations, and generating visual content based on prompts.
Language Model-Based: The Chat function relies purely on internal AI models (OLM AI Models) for generating responses and creative outputs. It does not access real-time external data.
Search Functionality
External Information Access: ChatOLM’s Search is designed to access external internet information. Unlike Chat, Search interacts with real-time data from external sources, like web searches using DuckDuckGo or other search engines, to provide the latest and most accurate information.
AI Model with Browsing Capability: Search retrieves and processes context from the internet, similar to AI tools like Perplexity or ChatGPT with browsing. This feature allows it to fetch up-to-date and specific information that may not be stored in static AI models.
Here are examples of when to use Chat or Search depending on the type of query:
Chat (Text and Image Generation)
"Generate a cute dog"
Task: Image generation using Stable Diffusion.
Result: ChatOLM will generate a visual representation of a cute dog based on its internal AI model.
"Tell me a short story about AI taking over a spaceship"
Task: Creative text generation.
Result: ChatOLM will generate a short story using its language model.
"Summarize the benefits of decentralized AI"
Task: Text summarization based on internal knowledge.
Result: ChatOLM will generate a summary of decentralized AI from its model's understanding.
Search (Accessing Real-Time External Information)
"What's Ethereum's TPS right now counting L2s?"
Task: Fetching real-time external data.
Result: Search will retrieve the latest transaction per second (TPS) data, including Layer 2 scaling solutions.
"What are the latest regulations for AI in Europe?"
Task: Accessing recent news or articles.
Result: Search will gather current regulatory information from external web sources.
"What's the weather like in Hong Kong today?"
Task: Real-time data retrieval.
Result: Search will fetch current weather data for Hong Kong from external internet sources.
https://7007.ai
7007 is a groundbreaking platform focused on building AIGC (AI-Generated Content) exchange, where AI-generated content is turned into NFTs. By integrating OLM’s AI models through the ORA AI Oracle, 7007 offers a decentralized, transparent way to create, trade, and own AI-generated content onchain. In addition to its AIGC focus, 7007 has revolutionized token distribution with its f(A.I.)r Launch, using OLM’s OpenLM Score model to ensure fairness and transparency in token allocation.
7007 is leveraging OLM’s AI models to power its AIGC exchange, enabling:
AI-Generated Content as NFTs: OLM’s models are integrated into 7007’s platform to generate AI-powered NFTs, making the process decentralized, transparent, and verifiable onchain.
Trustless AI Creation: Through OLM’s models and the ORA AI Oracle, 7007 ensures that all AI-generated content is created and traded in a trustless, blockchain-powered environment.
The 7007 f(A.I.)r Launch uses OLM’s OpenLM Score model to fairly allocate tokens during its token launch:
AI-Driven Fairness: OLM’s OpenLM Score model evaluates participants based on their onchain activity and engagement, ensuring that token distribution is fair and not biased toward large investors or early adopters.
Significant Onchain Activity: The OpenLM Score model was called over 14,000 times in one day during the f(A.I.)r Launch, showcasing the demand for OLM’s AI-powered token distribution system.
Through both its AIGC product and the f(A.I.)r Launch, 7007 exemplifies the power of OLM’s AI models, creating a fair, transparent, and decentralized ecosystem for AI-generated content and token distribution.
OLM = AI + Onchain AI + Tokenization
OLM is at the forefront of decentralized AI, combining advanced AI development with blockchain to create a new standard for tokenized AI ownership and revenue generation. Here’s a brief overview of OLM’s core technologies:
OLM is dedicated to AI in building, training, and fine-tuning AI models in a decentralized manner. By leveraging open-source principles, OLM allows for community-driven contributions that continuously enhance the AI’s capabilities.
OLM integrates its AI models directly on the blockchain using ORA’s AI Oracle. OLM’s onchain AI models generate income by serving decentralized applications.
The $OLM token represents ownership in OLM’s AI ecosystem. Token holders share in the revenue generated by OLM’s onchain AI models, aligning incentives between developers, contributors, and investors. By tokenizing AI ownership, $OLM drives the future of decentralized AI innovation, allowing anyone to benefit from the growth and success of OLM’s AI technologies.
https://www.chatolm.com/
ChatOLM is a decentralized AI chatbot application led by OLM community. It harnesses the power of onchain AI models, offering censorship-resistant, verifiable interactions.
ChatOLM enables users to engage with AI directly on the blockchain, creating a unique and transparent user experience.
ChatOLM platform offers two distinct yet complementary products:
ChatOLM (chat)
SearchOLM (search)
ChatOLM’s chat feature leverages advanced language models and image generation tools like Stable Diffusion to provide users with dynamic text responses and creative visual outputs. It excels at generating content purely from internal AI models without relying on external data.
SearchOLM enables users to access real-time information from the web, functioning like an AI-powered search engine. While ChatOLM focuses on text and image generation, SearchOLM retrieves and processes external internet information, making it ideal for answering queries that require the latest or real-world data. Together, they offer a robust platform for both conversational AI and real-time search capabilities.
Onchain AI Chatbot: ChatOLM uses ORA’s AI Oracle to power its chatbot with Llama3 and OpenLM chat models. These models enable seamless, real-time conversations that are fully decentralized and verifiable onchain.
7007's Fair Launch: ChatOLM played a vital role in 7007's Fair Launch, utilizing the OpenLM score model to determine fair token allocation. This integration enabled decentralized and transparent token distribution, which was called over 14,000 times in a single day.
Text-to-Image AI: ChatOLM also supports text-to-image generation using ORA AI Oracle’s Stable Diffusion v3 model, allowing users to create AI-generated visuals directly onchain.
As an application built by the OLM community, ChatOLM represents the power of decentralized collaboration, showcasing how AI models can be integrated with blockchain technology for practical, everyday use cases. It stands as a cornerstone of OLM’s decentralized AI ecosystem.
