<story><title>Native JSON Output from GPT-4</title><url>https://yonom.substack.com/p/native-json-output-from-gpt-4</url></story><parent_chain><item><author>swyx</author><text>i think people are underestimating the potential here for agents building - it is now a lot easier for GPT4 to call other models, or itself. while i was taking notes for our emergency pod yesterday (&lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;www.latent.space&amp;#x2F;p&amp;#x2F;function-agents&quot; rel=&quot;nofollow noreferrer&quot;&gt;https:&amp;#x2F;&amp;#x2F;www.latent.space&amp;#x2F;p&amp;#x2F;function-agents&lt;/a&gt;) we had this interesting debate with Simon Willison on just how many functions will be supplied to this API. Simon thinks it will be &amp;quot;deep&amp;quot; rather than &amp;quot;wide&amp;quot; - eg a few functions that do many things, rather than many functions that do few things. I think i agree.&lt;p&gt;you can now trivially make GPT4 decide whether to call itself again, or to proceed to the next stage. it feels like the first XOR circuit from which we can compose a &amp;quot;transistor&amp;quot;, from which we can compose a new kind of CPU.</text></item></parent_chain><comment><author>jonplackett</author><text>It was already quite easy to get GPT-4 to output json. You just append ‘reply in json with this format’ and it does a really good job.&lt;p&gt;GPT-3.5 was very haphazard though and needs extensive babysitting and reminding, so if this makes gpt3 better then it’s useful - it does have an annoying disclaimer though that ‘it may not reply with valid json’ so we’ll still have to do some sense checks into he output.&lt;p&gt;I have been using this to make a few ‘choose your own adventure’ type games and I can see there’s a TONNE of potential useful things.</text></comment>
<story><title>Native JSON Output from GPT-4</title><url>https://yonom.substack.com/p/native-json-output-from-gpt-4</url></story><parent_chain><item><author>swyx</author><text>i think people are underestimating the potential here for agents building - it is now a lot easier for GPT4 to call other models, or itself. while i was taking notes for our emergency pod yesterday (&lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;www.latent.space&amp;#x2F;p&amp;#x2F;function-agents&quot; rel=&quot;nofollow noreferrer&quot;&gt;https:&amp;#x2F;&amp;#x2F;www.latent.space&amp;#x2F;p&amp;#x2F;function-agents&lt;/a&gt;) we had this interesting debate with Simon Willison on just how many functions will be supplied to this API. Simon thinks it will be &amp;quot;deep&amp;quot; rather than &amp;quot;wide&amp;quot; - eg a few functions that do many things, rather than many functions that do few things. I think i agree.&lt;p&gt;you can now trivially make GPT4 decide whether to call itself again, or to proceed to the next stage. it feels like the first XOR circuit from which we can compose a &amp;quot;transistor&amp;quot;, from which we can compose a new kind of CPU.</text></item></parent_chain><comment><author>lbeurerkellner</author><text>It&amp;#x27;s interesting to think about this form of computation (LLM + function call) in terms of circuitry. It is still unclear to me however, if the sequential form of reasoning imposed by a sequence of chat messages is the right model here. LLM decoding and also more high-level &amp;quot;reasoning algorithms&amp;quot; like tree of thought are not that linear.&lt;p&gt;Ever since we started working on LMQL, the overarching vision all along was to get to a form of language model programming, where LLM calls are just the smallest primitive of the &amp;quot;text computer&amp;quot; you are running on. It will be interesting to see what kind of patterns emerge, now that the smallest primitive becomes more robust and reliable, at least in terms of the interface.</text></comment>