211–220 of 261 posts
We need to fight model providers trying to own memory, workflows and tooling. Don't give them an inch more of your software than needed even if there is a slight inconvenience setting up.
Earlier quoted context omitted.
To use an example in the article, what does > Analyzing CI failures overnight and surfacing summaries Look like on ec2 with python? Because with Claude, it’s that prompt, and with your solution it’s infra + security groups + multiple APIs + whatever code you actually write
I would suggest the prompt is an example of garbage in that's going to produce garbage out. Sitting down to confront the problem you're solving will show this, while Claude is going to happily spit out what looks like a plausibly functional system. So for example the only "analysis" of CI failures are which systems failed and who/what committed the changes to those things. The only way AI would help me here is if the…
I think this shows the value.
> Which granted is probably real for a lot of software firms
Here's the rub though; for many many people it's a huge improvement over what they have right now.
Earlier quoted context omitted.
> It quite literally doesn't. Awesome you've backed this up with real literature. Let's just include this for now to easily refute your argument which I don't know where it comes from: https://transformer-circuits.pub/2022/in-context-learning-an... > It also doesn't help that every new context is a new dawn with no knowledge if things past. Absolutely true that it doesn't help but: agents like Claude have access to o…
> Let's just include this for now to easily refute your argument which I don't know where it comes from: https://transformer-circuits.pub/2022/in-context-learning-an ... I love it when people include links to papers that refute their words. So, Antropic (which is heavily reliant on hype and making models appear more than they are) authors a paper which clearly states: "tokens later in context are easier to predict an…
having to answer for opinions with no basis in the literature is I'm sure very tiring for you. Your aggression being met is I'm sure uncomfortable.
> I love it when people include links to papers that refute their words. > So, Antropic (which is heavily reliant on hype and making models appear more than they are) authors a paper which clearly states: "tokens later in context are easier to predict and there's less loss of tokens. For no reason at all we decided to give this a new name, in-context learning".
well I don't really love it when people just totally misread a paper because they have an agenda to push and can't seem to accept that their opinions are contradicted by real evidence.
in-context learning is not "later tokens easier" it’s task adaptation from examples in the prompt. I'm sure you realize this. Models can learn a mapping (e.g. word --> translation) from a few examples in the prompt, apply inputs within the same forward pass. That is function learning at inference time, not just "predicting later tokens better"
I'm sure also you're happy to chalk up any contradicting evidence to a grand conspiracy of all AI companies just gaming benchmarks and that this gaming somehow completely explains progress.
> That is they rebuild the world from scratch for every new session, and can't build on what was learned or built in the last one.
That they rebuild the world from scratch (wrong, they have priors from pretraining, but I accept your point here) does not mean they can't build on what was learned or built in the last one. They have access to the full transcript, and they have access to the full codebase, the diff history, whatever knowledge base is available. It's just disingenuous to say this, and then it also assumes (1) there is no mitigation for this, which I have presented twice before and you don't seem to understand it, (2) this is a temporary limitation, continual learning is one of the most important and well funded problems right now.
> 10 years ago I worked in a team implementing royalties for a streaming service. I can still give you a bunch of details, including references to multiple national laws, about that. Agents would exhaust their context window just re-"learning" it from scratch, every time. And they would miss a huge amount of important context and business implications.
also not an accurate understanding of how agents and their context work; you can use multiple session to digest and distill information useful in other sessions and in fact Claude does this automatically with subagents. It's a problem we have _already sort of solved today_ and that will continue to improve.
> You keep referencing this literature as it was Holy Bible. Meanwhile the one you keep referring to, Chinchilla, clearly shows the very hard limits of those laws.
You keep dismissing this literature as if you have understood it and that your opinion somehow holds more weight...Can you elaborate on why you think Chinchilla shows the hard limits of the scaling laws? Perhaps you're referring to the term capturing the irreducible loss? Is that what you're saying?
> Do you argue things have not improved in the last year with reasoning systems? I don't
Then are you arguing this progress will stop? I'm just not sure I understand, you seem to contradict yourself
We need to fight model providers trying to own memory, workflows and tooling. Don't give them an inch more of your software than needed even if there is a slight inconvenience setting up.
Why? As a user of these tools, I love the convenience factor of having one tool rather than wrangling dozens. It's why in the past I've used an IDE (JetBrains), a language created by the provider of the IDE (Kotlin), web framework created by the same people (ktor), etc.
Earlier quoted context omitted.
Art is and has always been about the creator.
Take a walk in any museum, I'm pretty sure you'll react to some of the art displayed there and find it cool before you read the name of the artist.
We need to fight model providers trying to own memory, workflows and tooling. Don't give them an inch more of your software than needed even if there is a slight inconvenience setting up.
I wish there was a company that was easy to use but wouldn't sell out in this arena.
We need to fight model providers trying to own memory, workflows and tooling. Don't give them an inch more of your software than needed even if there is a slight inconvenience setting up.
You misspelt ">95% discount relative to API pricing" ;)
We need to fight model providers trying to own memory, workflows and tooling. Don't give them an inch more of your software than needed even if there is a slight inconvenience setting up.
Why? As a user of these tools, I love the convenience factor of having one tool rather than wrangling dozens. It's why in the past I've used an IDE (JetBrains), a language created by the provider of the IDE (Kotlin), web framework created by the same people (ktor), etc.
Anthropic wants a world where they own your agent where it can't exist outside of the Claude desktop app or Claude Code.
There could exist a world where your agent isn't confined by the whims of a corporation.