🏗️Risks & Barriers
Risk and barriers we need to consider, along with mitigation and solutions, and innovative designs by on issues faced by similar companies like Pyth, API3, The Graph, Chainlink, Covalent, and others.
Major Risks
Data accuracy and reliability: AI-enhanced oracles rely on data quality and accuracy. Inaccurate or biased data can lead to incorrect decisions, affecting the network's credibility and trust.
Scalability and performance: As the network grows, it may face scalability issues, leading to decreased performance, increased latency, or even network congestion.
Interoperability: Integrating with other blockchain platforms, applications, or services might be challenging due to differences in protocols, data formats, or APIs.
AI bias and ethics: AI models can be biased or perpetuate existing biases. Ensure that your AI models are designed with fairness, transparency, and ethics in mind.
Node and user incentives: Decentralized networks rely on node and user incentives to maintain participation. Ensure that your network provides sufficient incentives for nodes and users to participate and contribute.
Major Barriers:
Adoption and user acquisition: Convincing users to adopt your decentralized oracle and indexer network might be challenging, especially if they're accustomed to centralized alternatives.
Network effects: As mentioned earlier, achieving critical mass is crucial for a decentralized network. Overcoming this barrier will require significant marketing and outreach efforts.
Technical complexity: Decentralized networks can be complex and difficult to understand, especially for non-technical users. You'll need to develop user-friendly interfaces and documentation to facilitate adoption.
Scalability and performance: As the network grows, it may face scalability issues, which can be challenging to overcome without significant investments in infrastructure and development.
Regulatory hurdles: Navigating regulatory requirements and obtaining necessary licenses or approvals can be time-consuming and costly.
Competition from centralized alternatives: Centralized oracle and indexer services might offer more convenient, user-friendly, or cost-effective solutions, making it challenging for decentralized networks to compete.
Lack of standardization: The lack of standardization in the oracle and indexer space can make it difficult to integrate with other blockchain platforms, applications, or services.
Limited developer resources: Attracting and retaining skilled developers to work on your decentralized network can be challenging, especially in a competitive job market
To mitigate these risks and barriers, Torram will focus on:
Developing a robust and secure network architecture.
Ensuring data accuracy and reliability through AI-enhanced oracles and slow rollout of AI-enhanced products after significant testing.
Building a strong developer community and angel user base through education, marketing, and outreach.
Fostering partnerships and collaborations with other blockchain platforms, applications, or services primarily in the bitcoin L1 and L2 ecosystem
Investing in scalability and performance improvements, possibly integrating L2 sidechains
Developing user-friendly interfaces and documentation to facilitate developer adoption.
Attracting and retaining skilled developers through competitive compensation and a positive work environment.
Torram is looking at the issues faced by API3, Pyth, The Graph, and Covalent with regards to issues each project faced garnering adoption from traditional and web2 markets.
We are considering implementing the following technological breakthroughs from other web3 projects including
off-chain data signing for APIs
decentralized indexing and AI enhanced subquery abilities
AI enhanced Airnode development (light web API wrappers) for specific intents without sandbox-capabilities for efficiency with self optimization abilities via generative/autonomous AI agents, and one day AGI or Artificial General Intelligence.
These are just a few innovative approaches we look to consider optimizing for the barriers and issues others have face.
For example, lack of APIs due to lack of integrations brought about a chicken-and-egg problem to proactively try to identify which APIs would be most in demand. Now with the use of predictive AI capabilities, looking through developer networks, social listening, and marketplace crawling (Honeycomb API Marketplace as an example), will allow us to predict needs before they arise to solve some of these challenges as it relates to institutional DeFi activity on bitcoin blockchain.
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