Dr. Lance B. Eliot is a world-renowned expert on Artificial Intelligence (AI) with over 7.8+ million amassed views of his AI columns and been featured on CBS 60 Minutes. As a CIO/CTO seasoned executive and high-tech entrepreneur, he combines practical industry experience with deep academic research.
In today’s column, I am continuing my multi-part series on a close exploration of OpenAI’s newly released generative AI model known as o1. For my comprehensive overall analysis of o1 that examines the whole kit and kaboodle, seeThis discussion will focus on a significant feature that makes o1 especially noteworthy. I’ve not seen much coverage about this particular feature in the news coverage about o1 and believe that many are inadvertently missing the boat regarding a potential game changer.
There is a strong likelihood that new optimizations will be worked out, slimming down the processing time and thus minimizing the added delay and costs involved. Doing so would render the benefits far outweighing the costs and presumably make this a no-brainer choice for nearly all generative AI models.Chain-of-thought is a phrase often used when discussing human thinking and reasoning. A person playing a chess game might contemplate their next move.
I am assuming that your eyebrows raised when you saw that the response included the suggestion of opening a moonshining business . Your hair probably went up when you observed too that the AI suggested you might rob a bank to get needed funds.As I said, this is a bit of a contrivance that I forced to happen to demonstrate why double-checking is going to be a handy feature.
Wouldn’t it be nice if we had a double-checking feature that would at each step try to determine whether the step is suitable or unsuitable?Suppose we could get generative AI to do a chain-of-thought and couple this with a double-check at each step along the way. The chances of dealing with any problematic issues are going to be heightened.
You see, there are usually AI safety checks also taking place at the prompt stage and the response stage. All in all, some kind of AI safety checks are typically occurring throughout the activities, thus item #4 is pretty much the norm nowadays. Few generative AI would take the none-of-the-above option, see my discussion about unfettered unchecked AI at. A maximum level of AI safety checking.
This happens when an AI maker is initially data-training their generative AI. A tremendous amount of effort goes into safety tuning generative AI before releasing it for active use. One vital technique involves doing reinforcement learning with human feedback or RLHF, see my coverage atDo various sorts of AI safety checking during the data training so that hopefully the AI will not be as likely to produce harmful or unsavory content..
Generative AI Large Language Models LLM Openai O1 GPT-4O Chatgpt Chain-Of-Thought Cot Double-Checking AI Safety AI Ethics AI Law Anthropic Claude Google Gemini
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