How does it write code so well? Because code is a programming language with syntax and rules, like any language. So while math is a logic and formula-based operation, is not necessarily handled well by AI. Because it is based on a language model, it calculates probability of the next correct answer in a cascading linear fashion. This may seem ironic but generative AI is not good at math. The more published examples available, the higher the theoretical accuracy and confidence of the response. If there’s a large body of examples for how a particular programming problem is solved, this is readily retrieved. What is AI good at? What is it NOT good at?ĪI excels at problems that require deterministic solutions, such as programming code, scripting languages, query languages, etc.
Similar to general guidance but a deeper dive on any giving topic, or a search for topical references These can be easily tested as to whether they correct or not.Īdvice that is highly available via search engines but well-summarized and curated by AI Specific to cybersecurity and IT, these tools are assistants or helpers in getting: This amounts to a very handy tool for retrieval of information using complex requests. Generative AI, as an analogy for the human brain, would be the frontal lobe, where language and communication are controlled. We’re talking about generative AI, which uses large language models and machine learning to generate a host of outputs like: answers to questions, images based on seed parameters, or complete essays on a given topic. This article provides a framework for how AI can fit into the toolkit of the modern cybersecurity professional. Once the initial excitement of OpenAI’s ChatGPT subsided, it became apparent that these tools in their current form are extremely useful and powerful assistants to the daily tasks of anyone in a technical role, much like search engines, but…different.
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