3,852 karma · joined January 16, 2017
rugnirtheviking@gmail.com
It also doesn't seem that unlikely. I know a fair few adults who mutter to themselves under their breath while reading, never having managed to kick the habit of reading aloud.
we don't dismiss claims of poorly written code with "but it compiles!"
I've long dreamed of a reprise if I ever get the space and friends again, perhaps with dressing up fancy and/or a really nice champagne for that real diplomacy feel
I do. I used to use haiku for the speed. Now its just as slow as the rest. Speed is my #1 ranking of how good a model is
I ask because I dont know. The devil is in the details with this stuff
For her its rarely the specific tells ("not-x-but-y" etc) but rather its bad metaphors and analogies that get her.
Also "vintage" photography being corrected, where the original is clearly ai generated with unrealistic sharp focus everywhere
that was pretty much what coding bugs were already. Type systems and compilers sorted the other kind already. Unit tests and code review the rest
> Tokens are the new computing paradigm. Everything will be re-made on top of it.
what?
> In 99% of software it does not matter that you could’ve written a faster algorithm
a 0.5 second delay makes a huge difference. So does 0.1. Try setting animation speed to slow on your phone... You'll be tearing your hair out immediately.
you speak as though performance can be sorted out after you have users. Performance is extremely often a huge barrier to getting any in the first place. Jim from hyderabad doesnt care that it works on your iphone 18, hes using your software over a 3g internet connection.
Sure if you specifically prompt agents about such concerns, and specifically tell them that they need to make before and after timing tests, they will do things. Maybe even passable things. But my PM isn't going to do that.
This goes for a bunch of what coding is, professionally. My PM isn't going to ask if the fact the robot chose to use http in their prototype is a problem. They'll just deploy it right to prod.
My PM isn't thinking about if our interface is compliant to all the standards required. They also aren't thinking about scalability.
They aren't thinking about all the platforms we deploy to, and the quirks. They aren't thinking about the cloud costs, or any other costs we might employ. They aren't thinking about if the amount of network traffic their prototype is generating could be a problem for the services it talks to.
and to be fair to my pm, if I asked the LLM for what I wanted to use, it probably would be a niche product, and certainly not incorporate what the sales team needs to sell the latvian government on the next big deal.
You need specialists. "Taste" exists in the domain of technical decisions as well.
Some people think we will escape this with a massive long prompt telling an agent to call a bunch of subagents to think about all of this, and it will be instant and remember it all perfectly. That you can have a "dark factory" software company run entirely by agents (or more specifically, a company run entirely by agents apart from whatever their own job role is because of course they will be necessary unlike all the other people doing presumably very easy jobs I wont check)
Maybe it will, maybe it won't. Such things certainly don't work right now. They just can't contain enough context at once to do this (and much of the context is not digitalised in a high enough quality way i.e. without contradictions and errors). If we have a revolution where we get 100x context window or something we can come back to this conversation
Wonder why that changed? (or if it did?)
what do you think this process is? why don't we just write lists of ideas to each other, in the raw format you presumably started with? is there any value in it?
my opinion is that the process is literally nothing more than thinking deeply about the ideas and trying to phrase them in the clearest possible way such that you lead someone else into understanding them.
LLMs have awful, terrible judgement of what other people know, or are likely to infer from a piece of text.
The games market has a massive oversupply. It's not enough to just "make a game", you have to make a good one. That is to say, better than all the other things your audience could be playing. Cheaping out is literally not an option. You can cheap out in one area to spend more effort in another area, but you can't just say "this is cheaper therefore it will be the default" because the default isn't good enough. Most games fail
it shows that you don't get anything for free. If it was without any cost in other areas to make a human massively more intelligent, it would presumably happen over time via the same processes that led to us.
As it is, the higher (and lower!) ends of the distribution tend to be highly correlated with other issues (mental+physical), and the further you go, the more unfortunate things which make it harder to do stuff in general start to crop up like psychosis, autism, ocd, anxiety, addiction etc
Misinterpreting the results of performance testing it had just run to argue for the exact opposite of what the data it generated showed.
Stating something was current guidance (a quick read shows the document it found was from 2016, it was served the last edit date in it's API call, along with newer documents that contradict it).
Assuming what a Jira ticket said without ever reading it with it's tools and then doubling down on the contents it has assumed.
On learning specifically, it constantly gets grammar in foreign languages wrong it can write fluently when prompted correctly but when asked the sort of wrongheaded questions from flawed premises learners commonly make it is prone to making stuff up. I experienced this yesterday when asking about how danish comparisons work.
Heck i mean see https://alignment.openai.com/misalignment-reports/self-gener...
They are prone to make up restrictions for themselves you never asked for. Ive seen this behavior on occasion also.
You need both. You really need both. A salesman to keep the craftsman from getting too bogged down in details to ever finish, and the craftsman to keep the salesman from ever lowering quality too much that customers start seeing the company as money grubbing misers trying to make a quick buck.
It only works with both. Too much of one and you sink.
This can be seen time and again in successful endeavours. (Apple, Microsoft, Google, star wars, honestly so many movies, moon landings, the list could go on)
The only problem I have at the moment is it's very prone to hallucinations, even now, yes frontier models astra fable with all the bells and whistles. This makes it hard to confidently use while learning because I have to be on the lookout for lies while I'm learning, which is precisely the moment I am least able to distinguish them. So instead theres just a constant low lying dread.
Nonetheless, I am able to get some value out of them. Just not all, everything requires manual effort to duplicate and check which you should probably be doing anyway as part of learning