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When I’m asked to check a box to confirm I’m not a robot, I don’t give it a second thought, of course I’m not a robot.
On the other hand, when my keyboard guesses the next word I’m about to text, I start to doubt myself.
Just thinking out loud about building something to help me typing with more confidence and sound natural.
Food for thought: https://fortune-com.cdn.ampproject.org/c/s/fortune.com/2023/06/13/chatgpt-like-human-language-robots-linguistics-artificial-intelligence/amp
If you’re a non-engineer experimenting with prompt engineering, here’s the deal: understanding how LLMs actually work isn’t just a nice-to-have, it’s non-negotiable.
Take the Chain of Thought technique as an example. Using it after the model has already decided is like trying to screw in a bolt with a hammer, it’s just not going to work. At that point, the model isn’t “thinking” or “deliberating” anymore. It’s already locked in its answer and might just be scrambling to justify something wrong.
Sounds obvious, right? But tons of articles and tools (looking at you, Langchain) get this wrong. They miss the timing and end up using models to evaluate their own responses in ways that don’t make sense, leading to garbage conclusions.
If you want to build better AI solutions, get the basics down. Knowing how LLMs tick will save you headaches, lead to smarter results, and happier users.
Are Jonathan Haidt and Zach Rausch obsessed with looking for data to prove their point of view that social media is destroying women’s mental health all over the world, or are they right?
I’ve been following them for a while, and their research is quite interesting.
Artificially intelligent machines are all perception, no sensation; they’ll never be sentient so long as they only process information.
If we don’t understand what sentience is for, we’re likely to see it everywhere. Conversely, once we perceive its practical value, we’ll acknowledge its rarity.
Consciousness evolved to make us feel that life is worth living, a rare perception in this world.
https://www.newyorker.com/news/annals-of-inquiry/nicholas-humphreys-beautiful-theory-of-mind
I was always bothered by the extensive list of issues reported by the Core Web Vitals Assessment, but after getting some unique insights and successful results from friends, we decided to dig deeper and make our platform compliant with Google’s recommendations.
So far, so good!
