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Thank you for posting, @Thaddeus Dziekanowski. What is important is not that AI is being adopted in everyday life, or the record investments being made in AI, which, in part, have fuelled the adoption of AI. But the rate of performance improvements in AI, over such a short period of time. Driven by data consumption, that maybe an indicator of model performance.
Models will continue to consume more data, but model performance is consolidating between the big AI players such as Google, DeepSeek, Open AI and xAI vie for market share. The challenge is what happens when Ai consumes the generally available data? That is the information that all models have access to is the data we all type into internet-enabled platforms. But that’s rapidly running out. For AI to break out, it needs to acquire domain-specific knowledge, that is, the data held within specific domains of expertise such as cybersecurity, compliance, and audit. Data that is used to solve complex problems is not pumped into the internet, but held by professionals.
AI can tell me how to boil an egg, but it can’t tell you if you comply with cyber regulations; it has to consume domain-specific data to do that.
Domain-specific AI is the next stop.
Brian D. McCarthy
@Parava Security Solutions
#cybersecurity #ai
https://lnkd.in/eweJBRCp
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