GPT, Use your Tools!
“The right tool makes the job easy, son.” -My dad, Shlomo Avni
I had been joining my dad for the odd job around the house (not as much as I’d like anymore), and this phrase comes up again and again.
“Use your tools!” -Emily Bache
These both stuck with me since I heard them.
I’ve been fortunate to work with Emily and to hear her tell this to us developers many a time. And she’s right. Using tools and becoming proficient at it offloads effort, freeing up resources for better things. And yes, many tools have been tuned for a narrow use case, and are just ‘perfect’ for the job.
Knowhow Loss
Some tools might worry you.
“If I rely on this tool, I will lose the knowhow and skill required to get the job done without it.”
A valid concern. We become dependent on our tools.
An examle that comes to mind is navigation.
Learning is Required
Using a tool is a skill in and of itself, we have to learn it.
GPT
Large Language Models (LLMs) are much like brains.
- Context / focus
- Short term memory
- Knowledge with far from perfect retrieval capabilities
- They’re slow, when compared to other software
- Can learn
LLM’s primary tool, you might say, is word generation. It is the main mechanism by which they interact with the world.
Word generation on its own, goes a long way, but we get to experience its limits very often.
Example: ‘1283645 * 1763520931313 = ?’
A simple math problem. However, simply generating words is obviously not the way to go here. LLMs are not endowed with built-in calculators, they’re just neural nets.
See one experiment with ChatGPT here.
Good tools are reliable, predictable controllable tend to be specialized GPT is much like a brain it’s very shares same characteristics with the human brain it can learn unpredictable, stochastic generative makes things up perceptive I found (and many others) that some practices are useful for better cognitive performance.