# Consensus Related Articles

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Tsinghua's Prediction 2 Years Ago Is Becoming Global Consensus: Meta and Two Other Major AI Institutions Have Reached the Same Conclusion

Summary: In a remarkable validation of Chinese AI research, Meta and METR have independently reached conclusions that align perfectly with the "Density Law" proposed by a Tsinghua University and FaceWall Intelligent team two years ago. Published in Nature Machine Intelligence in late 2025, the law states that the computational power required to achieve a specific level of AI performance halves every 3.5 months. This convergence was starkly evident in April 2026. METR reported that AI capabilities are doubling every 88.6 days, while Meta's new model, Muse Spark, demonstrated it could match the performance of a model from the previous year using less than one-tenth of the training compute. When plotted, the growth curves from all three sources—using different metrics (parameters, compute, task length)—show an almost identical exponential slope. The findings have profound implications: AI inference costs are collapsing faster than anticipated, powerful edge-computing AI is becoming rapidly feasible, and the industry's strategy of simply scaling model size is becoming economically inefficient. The Chinese team, which has been building its "MiniCPM" model series based on this law since 2024, is seen as having a significant two-year lead in practical engineering experience, marking a rare instance where Chinese researchers pioneered a fundamental predictive trend in AI.

marsbit04/13 12:14

Tsinghua's Prediction 2 Years Ago Is Becoming Global Consensus: Meta and Two Other Major AI Institutions Have Reached the Same Conclusion

marsbit04/13 12:14

A Detailed Explanation of Tempo Chain and MPP Machine Payments Protocol

The global payment system is undergoing structural transformation, driven by the explosive growth of stablecoins and the rise of the AI agent economy. This creates a pressing need for next-generation payment infrastructure. AI agents have five core payment requirements: autonomy, micro-payments, high frequency, interoperability, and atomic settlement. Tempo, a payment-native blockchain by Commonware, addresses these needs. It features the Simplex BFT pipelined consensus for sub-second finality, dedicated block space, a stablecoin-native gas mechanism, and the Machine Payments Protocol (MPP) for end-to-end autonomous payments. Its technical architecture is payment-optimized. Key innovations include: - **Simplex BFT Consensus:** A pipelined design reducing confirmation latency to one network round-trip (1Δ). - **BLS Aggregate Signatures:** Minimizes bandwidth and computational overhead. - **Parallel Transaction Execution:** Enabled by custom EIP-2718 transaction types and an expiring nonce system. - **Dedicated Payment Lanes:** Protocol-reserved block space to shield payments from network congestion. - **Stablecoin-Native Design:** Stablecoins are first-class citizens for gas and on-chain exchange. MPP, co-designed with Stripe, is an open standard like "OAuth for payments." It enables AI agents to pay autonomously via a standardized HTTP challenge-response flow. Its core innovation is a session mechanism for efficient, continuous resource consumption without per-action on-chain confirmations. MPP is payment-rail agnostic, supporting various networks like Tempo, Stripe, and Lightning. Application scenarios include cross-border corporate settlements, 24/7 tokenized deposit clearing, commercially viable micro-payments, and autonomous AI agent transactions. Compared to rivals like Circle's Arc and Stable, Tempo differentiates through its EVM compatibility and Stripe partnership. Versus general-purpose chains like Ethereum L2s and Solana, Tempo's advantage lies in its payment-semantic native design, not just superior performance. The success of autonomous AI payments hinges on resolving regulatory uncertainty around agent identity and compliance. Tempo's core contribution is rethinking payment infrastructure at the protocol level, focusing on precision in payment semantics, pluggable compliance, and agent authorization models.

marsbit04/07 13:31

A Detailed Explanation of Tempo Chain and MPP Machine Payments Protocol

marsbit04/07 13:31

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