📢Allora AMA Key Takeaways First, I would like to thank Ari @heysoahri for asking my pre-submitted questions, Humbleman @Cryptowombat125 for hosting and conducting the AMA clearly, and Founder @nick_emmons for the wonderful answers! Listening to the Allora @AlloraNetwork AMA live and re-listening a few times for summarization has sparked many new thoughts! This is another ingredient for yapping ^^ ✔️Key Takeaways ▪️Near Mainnet: Aggregation/Objective Function optimization + significant improvement in developer onboarding with Forge. ▪️Differentiation: Goal-oriented inference, financial/DeFi specialized aggregation surpassing single model performance. ▪️Token Value Capture: Intelligence-based assets supported by real use cases such as gas, inference payments, staking security, and worker slots. ▪️TGE/Rewards: TGE date not disclosed (official channel announcement pending). ▪️Yapping/Country-specific rewards: Including allocations for Korea, reward design linked to multiple programs (specific figures not disclosed but mentioned as "not disappointing"). ✔️Question Summary 1. Near Mainnet, what has changed? (Technical upgrades) ▪️Aggregation logic/Objective Function optimization: Moving beyond simple continuous price prediction, experiments are underway to embed strategic logic directly into the objective function for more practical outputs. ▪️Preparing for problem type expansion: Currently strong in regressions --> ongoing protocol-level optimization/innovation research to expand into other AI problem types. ▪️Advanced economic matching design: Improving incentive/economic design to match model providers and consumers more efficiently. 2. Changing developer onboarding with ‘Forge’ (alpha coming soon) ▪️Allora Forge overhaul: Evolving into a one-stop model developer platform abstracting model hosting, DevOps/MLOps, and data provisioning. ▪️No crypto knowledge needed for developers: Significantly simplified API/SDK, data, and feature access to lower barriers for AI developers. 3. Expected effects of transitioning from testnet to mainnet ▪️Most major topics will operate simultaneously on mainnet: Topics centered around price/returns/volatility/volume predictions, etc. ▪️Natural quality and scale increase: When transitioning to a real trading environment, the number and performance of models typically rise. ▪️Accessibility: Permissionless network --> anyone can access via API/SDK (similar UX to testnet). 4. How Allora differs from centralized AI (core logic) ▪️"Intent" analogy: Users present their desired goal (intent) without the burden of choosing which model to use --> the network provides results with the optimal model combination. ▪️DeFi/Finance specialized capabilities: Designed to ensure that aggregated model intelligence consistently outperforms in areas where LLMs are weak (quant/finance). ▪️Excess performance of aggregation: The results of multiple models consistently exceed the performance of a single model --> shifting from a model-centric to an objective-centric AI. 5. Response regarding prediction ‘horizons’ (how far out?) ▪️Theoretically possible to predict arbitrarily far, but as the verification (ground truth) retrieval cycle lengthens, the network's self-improvement speed slows down. ▪️Practically, the ecosystem shows high interest in predictions on an hourly scale (verification and reward loops operate quickly). 6. Usage method: App vs API/SDK ▪️Currently, it has a strong middleware infrastructure character --> primary consumers are developers/protocols (integrated via API/SDK). ▪️In the future, as generative/LLM aggregation expands, end-user interfaces are expected to diversify. 7. Partnerships & Korean initiatives ▪️Core growth axis: AI agent ecosystem LLMs excel in "coordination/orchestration," while financial judgment is complemented by Allora inference --> enhancing the practical DeFi capabilities of agents. ▪️Focus on Korea: Participation in government conferences (AI World) and education --> POC --> focusing on expanding the decentralized AI base. 8. Token utility (Why HODL?) ▪️Gas/inference payments: Used for topic funding and inference costs. ▪️Economic security: Validators and Reputers stake to secure the network (delegated staking possible, rewards shared). ▪️Worker participation: Inference/forecaster workers buy topic slots and participate --> performance-based rewards. Positioning: If Bitcoin is an energy-backed asset, Allora tokens are positioned as ‘intelligence-backed’ assets. 9. TGE/Rewards ▪️TGE date: Not disclosed (will be announced via official channels). ▪️Yapping/country-specific rewards: Including allocations for Korea, multi-program rewards planned (specific figures not disclosed but guidance: "won’t disappoint").