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AI is an important tool, but often it struggles to find a home and a solution to fix. Many articles point to the power of AI, but also the ability of AI solution providers to identify and solve problems with AI and deliver value.In ones view a reason for this is simple, it’s the problem of GenAI. By its definition its General, Gen AI LLMs are collections of General data and information. The problem with General AI is when you apply it to specific problems the information and data bought back is not always as accurate as one would hope, to solve a specific problem. Taking an arrogant stance, if it were then AI would have given us a cure for cancer. It has as not yet done this, but is being used to cut the time to find cures down significantly.You get around this problem by creating domain specific AI. AI that relies on a number of factors least of all LLMs, that contribute to the creation of domain specific Language models. You create models that contain the secret sauce gathered from domains, contain domain specific knowledge collected specifically to solve specific problems. Just like trying to find a cure for cancer, you won’t find all you need in LLMs, it is complimented by the knowledge, skills and experience of domain experts. Its the Six Sigma problem; to improve process performance you first need to understand the process, measure it and corelate what goes in with what comes out to get a meaningful response.One believes that domain specific LLMs, when attributed with domain knowledge, skills and experience tied with Gen AI enhances AIs ability to solve complex problems such as those we have to solve in Cybersecurity, risk management and audit. But these occur when you combine LLMs, Domain models and professional knowledge.@Thaddeus Dziekanowski Brian D. McCarthy Faisal Khan Dan MilesVeritas GRC#cybersecurity #cyberriskmanagement #artificalintelligence
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