? ???? ????????-???????????? ???????????????????? ???????? ??????????????, ??????????????, ?????? ?????????? ????????, ????% ???????????????? ???? ???? ???????? ???? ????????. As Adrian Parlow highlights, AI has no value until it hits a critical level of accuracy. At Lynxius, we automate optimization to help teams reach that "X" faster—unlocking the full power of AI. ?? Let’s make AI more accurate, reliable, and scalable. Learn more at www.lynxius.ai. #AI #AIOptimization #GenerativeAI #LegalTech #Lynxius
An interesting trend with new AI products is they have basically zero utility until they reach a certain degree of accuracy. In other words, the usefulness is roughly binary. Up until point X, the effort required to monitor and check the AI's work exceeds the effort to do it manually. People often fall into the trap of thinking that a 50% solution delivers 50% of the value. In fact, a 50% solution is usually worthless. Where X lies on the scale of usefulness depends on the application, the organization and the user. Some people just have a burning need and are more tolerant of errors. Others need error rates approaching zero. In legal tech, the bar for accuracy is very high. And most products have not yet hit it. Any work that will be sent to a client or court is extremely intolerant of errors. 70% or even 80% will generally not cut it for document drafting or due diligence, for example. Besides just increasing accuracy, the biggest lever that builders can pull is to make the AI's work easier to check. Better redlines, AI explanations, citing sources. These things all help tremendously. The flip side is that once you've hit X, it's immediately obvious and you get to witness some pretty magical customer experiences.