April 2nd, 2025 Effect AI Community Call

Near-Complete Product Build: The team is close to releasing the first version (“version zero”) of the new Effect platform. The core functionality is nearly complete.
Beta Testing Timeline:
- Internal Testing: A small, internal group will begin testing the platform in the next few weeks to check functionality and gather initial feedback.
- Wider Beta Access: After internal tests, a broader group of whitelisted or pre-registered users will be invited. Exact dates are not yet finalized, but the team is targeting roughly a month to complete internal testing.

Torus-Powered Login: Effect is integrating a system that uses Torus (Web3Auth) to create decentralized private keys in the background, allowing users to log in with social accounts (Google, Discord, Twitter, etc.).
Simplified Worker Experience:
- No wallet is needed initially to start doing tasks. Workers can earn Effect tokens without handling wallets or keys directly.
- Once workers are ready to withdraw earnings, they will set up or connect a crypto wallet to claim payouts.
Rationale: The goal is to remove crypto-related barriers for non-technical workers while preserving decentralization in the background.

Reward Mechanisms: The team plans to implement measures that link earnings to task completion and accuracy. Users who simply join and do not fulfill tasks (or submit poor work) will be filtered out over time.
Monitoring & Feedback Loops: At first, the network will monitor task quality and worker performance closely (e.g., a whitelisted pool of testers) and iterate on quality-control algorithms as the platform scales.

Human-Only Edge Cases: The conversation highlighted that large language models can handle many traditional microtasks, so Effect aims to focus on tasks that truly require human insight (e.g., subjective evaluations, nuanced labeling, or specialized tasks that LLMs struggle with).
Future-Forward Use Cases:
- Benchmarking and comparing LLMs.
- Content moderation, specialized translations, fine-tuning voice/transcription models (e.g., Whisper).
- Potential “human-in-the-loop” solutions for AI agents (such as those built through “MCP servers”), where humans provide final approval or oversight for non-deterministic AI actions.

New Full-Time Team Member: Miguel, a long-time community member and translator/validator, has joined the Effect team. He will work across development, community relations, and marketing.
Returning and New Workers: The upcoming platform will be open to both new and old workers. Although some old EOS-based credentials may not carry over directly, active community members from the past will have priority access to beta testing.
Support & Documentation: A new support system and better onboarding flow (including guides and how-tos) will accompany the beta release.

Roadmap & White Paper: Both are being updated to reflect the new protocol architecture and the broader vision of Effect as it shifts focus to human tasks that complement AI. The team wants these documents to be comprehensive and relevant to the latest trends in AI, so they are still in progress.
Marketing Approach: Full-scale marketing efforts will ramp up after the platform is running smoothly and the user experience is tested. The team plans to showcase how Effect stands out in the rapidly changing AI landscape by focusing on tasks that genuinely require human input.
1. Next Steps
  1. Complete Internal Testing: Finalize features like social login, worker assignment, and support ticketing.
  2. Whitelisted Beta: Invite pre-registered and selected community members to try tasks, provide feedback, and report bugs.
  3. Refined Roadmap & White Paper: Publish details on long-term plans, protocol design, and vision for human-AI collaboration.
  4. Roll Out Marketing: Once version zero is stable, begin broader outreach to attract more workers and potential AI-focused clients.

Last updated 3 months ago

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