European Union Outlines Strategies to Boost AI Adoption, Research - WSJ
European Union Outlines Strategies to Boost AI Adoption, Research WSJ
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Why Your Trading Agent Needs a Pre-Trade Gate
Your agent traded $50,000 into a halted market at 3am. Nobody was watching. This isn't a hypothetical. It's the failure mode that autonomous trading agents are quietly running toward — and almost nobody has a circuit breaker in place. The Blind Spot in Autonomous Execution Agents that execute trades check a lot of things. Price feeds. Order book depth. Portfolio constraints. Risk limits. Slippage estimates. What they almost never check: is the exchange actually open right now? Price feeds don't tell you the exchange is closed. They serve you the last known price — which may be hours old — and they do it silently. A market data feed returning a stale quote and a market data feed returning a live quote look identical to an agent reading the response. An agent that sees a valid price and a fi
Positional Restructuring of System Prompts: Mitigating Transformer Attention Bias in Sub-Frontier Models
I built a sovereign AI system on a Mac Mini that kept forgetting facts written in its own system prompt. Instead of upgrading hardware, I figured out why — and found some things I was not expecting. The obvious part: moving critical facts from the middle to the beginning and end of the system prompt fixes recall (2.0 to 7.0 on a verification battery). This builds on Liu et al.'s lost-in-the-middle work. The less obvious part: a model with 83.4% IFBench scored 3.4/10 on fact recall while a model with 23.9% IFBench scored 7.5/10 after restructuring. Instruction-following and fact recall appear to be independent capabilities. I have not seen this documented elsewhere. The paper also covers a behavioral rule methodology that took a 32B model from 6.2 to 9.4 across seven dimensions with cold re
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