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To anyone who has worked with LLMs extensively, this is obvious. Single prompts can only get you so far (surprisingly far actually, but then they fall over qui

To anyone who has worked with LLMs extensively, this is obvious. Single prompts can only get you so far (surprisingly far actually, but then they fall over quickly). This is actually the reason I built my own chat client (~2 years ago), because I wanted to “fork” and “prune” the context easily; using the hosted interfaces was too opaque. In the age of (working) tool-use, this starts to resemble agents calling sub-agents, partially to better abstract, but mostly to avoid context pollution.

nomel 1y ago
Did you release your client? I've really wanted something like this, from the beginning. I thought it would also be neat to merge contexts, by maybe mixing summarizations of key points at the merge point, but never tried.
Zopieux 1y ago
I find it hilarious that this is how the original GPT3 UI worked, if you remember, and we're now discussing of reinventing the wheel. A big textarea, you plug in your prompt, click generate, the completions are added in-line in a different color. You could edit any part, or just append, and click generate again. 90% of contemporary AI engineering these days is reinventing well understood concepts "but for LLMs", or in this case, workarounds for the self-inflicted chat-bubble UI. aistudio makes this slightly less terrible with its edit button on everything, but still not ideal.
- surrTurr 1y ago
  The original GPT-3 was trained very differently than modern models like GPT-4. For example, the conversational structure of an assistant and user is now built into the models, whereas earlier versions were simply text completion models. It's surprising that many people view the current AI and large language model advancements as a significant boost in raw intelligence. Instead, it appears to be driven by clever techniques (such as "thinking") and agents built on top of a foundation of simple text completion. Notably, the core text completion component itself hasn’t seen meaningful gains in efficiency or raw intelligence recently...

nomel 1y ago

Did you release your client? I've really wanted something like this, from the beginning. I thought it would also be neat to merge contexts, by maybe mixing summarizations of key points at the merge point, but never tried.

Zopieux 1y ago

I find it hilarious that this is how the original GPT3 UI worked, if you remember, and we're now discussing of reinventing the wheel. A big textarea, you plug in your prompt, click generate, the completions are added in-line in a different color. You could edit any part, or just append, and click generate again. 90% of contemporary AI engineering these days is reinventing well understood concepts "but for LLMs", or in this case, workarounds for the self-inflicted chat-bubble UI. aistudio makes this slightly less terrible with its edit button on everything, but still not ideal.

surrTurr 1y ago
The original GPT-3 was trained very differently than modern models like GPT-4. For example, the conversational structure of an assistant and user is now built into the models, whereas earlier versions were simply text completion models. It's surprising that many people view the current AI and large language model advancements as a significant boost in raw intelligence. Instead, it appears to be driven by clever techniques (such as "thinking") and agents built on top of a foundation of simple text completion. Notably, the core text completion component itself hasn’t seen meaningful gains in efficiency or raw intelligence recently...