Good read, but I have to disagree with the fact that skill and taste are correlated. It's true that learning skill gives you a more nuanced view of the craft that refines your skill. But software is not only for those who have skill in it, but for everybody. Lots of amazing engineers have an awful taste (really, really awful) in everything that is not their immediate field of knowledge or interest, with the aggravation that their skill makes them arrogant.
On the contrary, a lower barrier for skill could bring people from other disciplines with excellent taste to make beautiful, even if technical imperfect, pieces of craft.
I clearly didn't express myself correctly, sorry. What I want to say is that one can develop taste with skill in one craft, like software engineering, while having awful taste in others, which is needed for many apps. This means that people with taste in other areas can now create nice software using their taste in other areas
We were messing around at work last week building an AI agent that was supposed to only respond with JSON data. GPT and Sonnet more or less what we wanted, but Gemma insisted on giving us a Python code snippet.
Whom's messenger? You didn't point us to anyone's research.
I just don't see how sampling tokens constrained to a grammar can be worse than rejection-sampling whole answers against the same grammar. The latter needs to follow the same constraints naturally to not get rejected, and both can iterate in natural language before starting their structured answer.
Under a fair comparison, I'd expect the former to provide answers at least just as good while being more efficient. Possibly better if top-whatever selection happened after the grammar constraint.
I will die on this hill and I have a bunch of other Arxiv links from better peer reviewed sources than yours to back my claim up (i.e. NeurIPS caliber papers with more citations than yours claiming it does harm the outputs)
Any actual impact of structured/constrained generation on the outputs is a SAMPLER problem, and you can fix what little impact may exist with things like https://arxiv.org/abs/2410.01103
How can advertising and marketing become more profitable from this? It's a genuine question, but I don't see how making advertising and marketing easier for everybody and hence flooding the already flooded market would result in increased productivity.
By significantly reducing the cost of creating the advertisements. Want to air a commercial? You no longer have to have actors, sets, designers, costumes, etc. just ask AI to make you a commercial and describe what you want it to look like.
Consider all the labor and capital spent across all the advertising real estate in the world. Commercial, online ads, billboards, labeling. The inputs to make all these things are now greatly reduced. To increase productivity, it doesn't matter that the market is flooded, just that it's much easier to make these things.
No need, it was much more comfortable to stay in known sectors such as banking, industry or tourism. Now there is a real need so I'm positive things will change.
On the contrary, a lower barrier for skill could bring people from other disciplines with excellent taste to make beautiful, even if technical imperfect, pieces of craft.
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