One of the most common criticisms of generative AI tools is that they often “hallucinate,” or make up information, making them somewhat unreliable for certain high-stakes tasks. To help you combat hallucinations, we recommend you try out the following tips in your own use of generative AI. You might find that you get better, more reliable outputs as a result.
Now that AI has entered the mainstream, more businesses are implementing these tools into their daily operations. Tasks like drafting emails, brainstorming for a new project, or debugging code have all been made easier. Here’s the secret to making the most out of AI: you get out what you put in. What do we mean by this? Let’s find out.
Artificial intelligence is all the rage these days. In fact, most businesses are using it for a multitude of things. With everyone all-aboard the AI train, it’s easy to confuse the computational power and speed AI offers to be infallible. Unfortunately, AI can get things going sideways if you aren’t careful. When it does go wrong, the consequences can be more than just an inconvenience. Here’s a look at some of the most critical ways AI can go wrong:
Pop culture has given us a vivid, if often terrifying, impression of artificial intelligence. When we hear AI, many still picture calculated malice: a HAL 9000, a Skynet, or an Ultron. The real potential of AI is far more productive, it’s less about calculating world domination and more about becoming your organization’s most helpful collaborator. Think of it as a JARVIS for your executive team or an R2-D2 for your operational staff: a powerful tool that assists your team in generating ideas, solving complex problems, and completing high-volume tasks. Critically, maximizing this potential doesn’t require new hardware; it requires sharpening the very soft skills we already value in our top performers: curiosity, empathy, and resilience.
Did you know that during World War II, Allied codebreakers didn’t just crack the German Enigma code with pure math? They also used clever tricks, like baiting the Germans into sending predictable messages, to expose the machine’s inner workings. History proves this approach worked then, and (unfortunately) continues to work now. This art of manipulating a system to reveal its secrets has found a new, high-tech home in the world of artificial intelligence. It’s called prompt hacking, and it’s essentially a form of digital social engineering aimed directly at the AI models businesses are starting to rely on.