Blog and Research
Trusting Trust in the Age of AI
While resources are heavily invested in improving frontier models and optimizing prompts, the true challenge lies in how AI systems retrieve and rank information. Chaos Labs identifies the greatest risk in AI-generated misinformation infiltrating the data pipeline. If AI agents are unknowingly trained on manipulated or sybilled content, it becomes nearly impossible to trust their outputs. This vulnerability is exacerbated by unreliable document ranking systems, which prioritize popularity and commercial interests over accuracy. The Dead Internet Theory, which warns of a future where human-created content is drowned out by machine-generated noise, serves as a chilling reminder of what’s at stake if these systems are not carefully safeguarded.
Omer Goldberg
|AI-Driven Chaos and the Rise of Oracles: The Future of Trust
We’re expanding the definition of an Oracle. At its core, an Oracle is more than a protocol to source and deliver high-integrity, reliable, authentic, and secure data between networks. It adds a crucial truth-seeking layer of verification and filtering. Oracles don’t just deliver data—they ensure it’s trustworthy. Using truth-seeking algorithms, Oracles will filter out misinformation and manipulated data, safeguarding the applications and networks they serve.
Omer Goldberg
|Edge Proofs: AI-Powered Prediction Market Oracles
Edge Proofs Oracles ensure verifiable data provenance, integrity, and authenticity, enabling blockchain applications to trust the external data they rely on. This capability is crucial for Prediction Market Oracles, a specialized subset of proof oracles designed to bring off-chain data on-chain in a secure and trusted manner, ensuring accurate verification of real-world outcomes like elections.
Omer Goldberg
|Oracle Risk and Security Standards: Data Freshness, Accuracy and Latency (Pt. 5)
Data Freshness, Accuracy, and Latency are fundamental attributes that determine an Oracle's effectiveness and security. Data freshness ensures that the information provided reflects real-time market conditions. Accuracy measures how closely the Oracle's price reflects the true market consensus at any given time. Latency refers to the time delay between market price movements and when the Oracle updates its price feed.
Omer Goldberg
|Introducing Edge: The Next Generation Oracle Protocol
At Chaos Labs, we've always believed that robust risk management and reliable data are the foundations of a thriving DeFi ecosystem. With Edge, we're putting that belief into action, providing a solution that doesn't just report prices but actively contributes to the security and efficiency of on-chain finance.
Omer Goldberg
|dYdX Chain: End of Season 6 Launch Incentive Analysis
Chaos Labs is pleased to provide a comprehensive review of the sixth trading season on the dYdX Chain. This analysis encompasses all facets of exchange performance, emphasizing the impact of the Launch Incentive Program.
Gearbox LT Methodology
This methodology proposes a framework to derive liquidation thresholds (LT) and liquidation bonuses (LB) specifically for LSTs and LRTs on Gearbox, which are assets closely related to ETH. These tokens are fundamentally priced on Gearbox based on their intrinsic value as receipt tokens representing underlying staked or restaked ETH, when withdrawals are enabled. However, during periods of significant market volatility, LSTs and LRTs may temporarily deviate from their fundamental ETH value in the open market due to factors such as liquidity constraints, market sentiment, and liquidation events.
Oracle Risk and Security Standards: Data Replicability (Pt. 4)
Data replicability is the capacity for third parties to independently recreate an Oracle’s reported prices. This requires transparency into two key components of the Oracle’s system: its data inputs and its aggregation methodology.
Omer Goldberg
|Chaos Labs Secures $55M in Series A Funding
We're excited to announce our $55M Series A led by Haun Ventures to accelerate the development of our advanced risk management platform.
Omer Goldberg
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