Building an AI That Learns Like an Analyst
Most AI-driven security tools lean on retrieval-augmented generation: pull relevant precedent, drop it into the context window, let the model reason over it. It works, but it has a cost problem and a consistency problem. The more data you feed a large language model to improve its answer, the more expensive that answer gets — and the more room there is for the model to produce inconsistent results, independent of hallucination. Torq built its "SOC brain" to get around that tradeoff. On the latest episode of the TechSpective Podcast, I sat down with Torq Co-Founder and CTO Leonid Belkind to…
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