Edit:

I guess in this description dijkstras is more specific, in that dijkstras is the specific instance of A* with a zero heuristic.

But I think what HAL over here was saying is that you can use dijkstras in a superset of scenarios in which you can use (non-trivial) A*, so in that sense dijkstras is more general than A*, so it's not wrong.

For A*, everything depends on the heuristic, as you said. If h(v) = 0, A* is equivalent to Dijkstra's algorithm, so potentially, it can be as general. But the wrong heuristic (inadmissible, inconsistent) will lead to wrong results, and so calling it a "specialized" tool is correct. The heuristic gives you a specialized version of Dijkstra's algorithm which is faster on specific graphs.

> Dinkstras is a-star with a "min weight on shortest path first" heuristic.

I am not quite sure what you mean here. Dijkstra's algorithm is A* with no heuristic. I am not sure how a "shortest path first" heuristic would look like - do you mean that Dijkstra's algorithm chooses the node to expand next based on its shortest-path cost to the target t? Even if you would construct such a heuristic h(v) = c(v, t) by explicitly calculating c(v, t) each time, this is not what Dijkstra does, as it would basically be a perfect heuristic - you would then only visit nodes on the shortest path.

If you meant that Dijkstra's algorithm is A* with a "neighboring node with shortest path from start node first" heuristic, that's also not strictly true, because expanding the nearest node first is already built-in to A*. A* does not chose the next node v with the smallest h(v), but with the smallest g(v) + h(v), where g(v) is the shortest path cost from the source node to v.

So I wonder if there was substantial fine-tuning for chatgpt specifically to reward it to generate poems, in a particular style.

And here, it's "over indexing" on that and still generating poems in that familiar style

We can finally get the eighty hour long book-accurate Lord of the Rings adaptation we deserve.

But seriously, I can't wait to feed a novel into one of these things and get a comic book version in return.

It's already at the point where you start expecting any knowledge worker to be significantly more productive by leveraging these tools.

It's hard to imagine that it will be more than five years before AI tools are available that can handle almost all tasks in these types of jobs.

For example, on my website aidev.codes I just added preliminary knowledgebase support. It can reference the knowledgebase this to write code. I would say that with the code-davinci-002 model at least it seems about at the level of a junior software engineer already since it's pretty effective with close supervision by a senior peogrammer, except for the fact that it cannot interpret visual information.

Knowledgebases/embedding search can also be used right now with these models for answering support questions. The only thing holding it back from very very wide scale adoption is the problem of making up information. There are already solutions in progress for this. It's unlikely that will take more than a few years to roll out and replace the current generation of models. Google and Microsoft will probably roll out their internet-scale chat search interfaces this year even if they can't fully mitigate the hallucination problem immediately.

I would guess more like 2-3 years for many knowledge-based jobs. If you want employment/contracts you will need to be very good at leveraging AI, or people will just use the AIs instead.