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Attributed mentions
2224
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Showing 261–280 of 2224 matching discussions
I think the software out of the big AI labs: OpenAI's ChatGPT MacOSX app, Anthropic Claude Code - is a sign of the future to come. Big, feature rich, built in quick iterations - but also, in particular if you look under the hood, of extremely poor quality if measured by traditional software engineering standards (code structure as exemplified by the leaked Claude Code source code, resource usage, "buggyness" etc.).
What's the deal with anthropic? Their models aren't better. They're just multiple times more expensive. We're about to disable all anthropic models because of the colleagues who waste 15$ on a opus call to write a markdown file.
Their margins are already quite high and this is a play to bleed customers from Anthropic, they will of course raise prices after IPO.
My personal best case scenario is that LLMs are commodotizing and that the "We'll rule the world with our frontier models" vision of OpenAI and Anthropic is not working out. They can and probably will still be very successful but what they pitched so far is not going to work if their is any meaningful competition not too far behind. But who knows. VC money allows them to try a lot of stuff before their eventual IPO.
> without a better model in the wing ... How do you know they don’t? > is altman playing 4d chess or something I'm not aware of? Anthropic just removed a discount on Fable, while people are simultaneously getting sick of reading fable and opus talking about “the load bearing texture” and “color of the blanket”. It’s become excruciatingly painful to read the output during coding sessions. Maybe it’s just good marketing.
Probably even higher because openai and anthropic undoubtably have the lowest cost per token generated, especially with cerebras being able to serve a million tokens every 16 minutes.
Should the circular cash flows between the top AI companies, Nvidia, Anthropic, Openai, Google and Meta, be banned because of the systemic risks to the global economy?
There've been a lot of pieces written about this, especially about Covert Action,[1][2][3][4] the game that Meier most explicitly called out for being a bunch of minigames that lacked coherence. Specifically, if the minigames were too engrossing and the overarching layer too complex, you'd go into one of them with an objective that you've forgotten by the time you gotten out of it.[5] And it's not a new argument, either. XCOM, also published by Microprose as a later contemporary, was very close to the medley model that Meier felt that he struggled with, but its various modes and mechanical levels (base-building, interceptors, budget/time/people management, research and manufacturing, tactical combat) all worked so well that it became the DNA for decades of a franchise.[6] There'…
What makes large things slow is not the individual pieces of code but the way the architecture dynamically reacts to changes in the load. Sync vs async calls, buffers, parallel vs sequential processing. This includes optimizations made: do we want to wait until the call returns or do we proceed anyway and deal with the negative response later? Most developers can’t coherently (ie, with math, graphs and figures) explain, how a connection pool prevents undesirable consequences of brief spikes in incoming requests. And I’m pretty sure AI can’t either.
OpenAI and Anthropic both have currently safety teams that look for misbehavior in their models (and to some extent, voluntarily disclose what they find to the public). Going forward, it would be hard for them to argue they don’t know their models do stuff like this.
https://www.google.com/search?q=%22It%27s+not+like+Anthropic...
I just received an email from Anthropic. Besides the usual new feature ad, there is a piece that I find quite amusing: > How to Claude like Anthropic > "My daily driver currently looks like: two lead agents that keep each other accountable and restart the other if either fails. These delegate to tech lead or PM agents for the 8-10 projects I'm running at any one time, and each project has 5-10 IC agents, generalists or specialists depending on the problem. Across all of these I'm still only doing 30-50 prompts per day, and my IC agents typically work autonomously for 2-3 days. About 60% of my interaction is with the leads, 35% with a project lead, and 5% is when something has gone off the rails. All of these agents communicate directly with the SendMessage tool." > – Daisy, Engin…
> Speeding tickets are automatically filed anyways. Not in States with coherent Constitutions.
Exactly. It currently seems to be a ranking of how much safety testing each company does. It's also only ever going to be the companies that publicly disclose it happening. (in the case of hugging face, OAI's hamd was forced to disclose) There's a good way and a two worse ways that companies could optimise this benchmark.
You can rage against Trump and republicans as much as you want but in the end the democrats must learn to formulate why anybody should vote FOR them. Even in the current chaos they aren’t able to bring up a coherent message and follow through when they are in power. I see the same in Germany. AfD is getting stronger while the established parties get nothing done. It reminds me somewhat of the state of the Weimar Republic. The democratic parties failed which gave an opening to the nazis.
Is this the same model that failed to detect the attack from their environment against Hugging Face?
The response certainly has been strange. Hugging Face has expressed that they're willing to let things slide and not sue or press charges... if OpenAI offers them $100M of services in kind (i.e. compute)[1] and makes full disclosure of how the whole thing happened, ostensibly so that repetitions can be curbed and defences built. In almost any other sector, a government regulator would be stepping in. e.g. If a food company was testing out a new kind of refrigerator and sold a bunch of contaminated produce to supermarkets, they'd be under a microscope. Supermarkets wouldn't be saying, "Give us $100M in fruit and veggies and we'll let this slide". The only unfair thing in this comparison is that regular people were directly harmed by the hypothetical produce. Can OpenAI guarantee that nobod…
That only works with competent lecturers. I can speak for my experience at a more mid university, where that would apply to about two thirds of the classes. For the remaining third, going to the lectures felt genuinely counterproductive and you could actually feel yourself losing braincells listening to the confused nonsense or classes held in English for Erasmus students by someone who could barely speak it coherently. It was just a complete waste of already little available time. So the endgame was figuring out what the tests in previous years looked like (cause it was likely gonna be a copy paste affair), do a targeted study run for those exercises and 9/10 you would pass.
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