agnosticmantis

Ladies and gentlemen, make no mistake: they're coming for your open source models next!

Dario must be popping a champagne tonight as regulatory capture has successfully been initiated.

We've all been debating what moat these labs possess. Today we learn the moat is regulation blocking the usage of foreign open source models.

misAnthropic will soon ask for IDs to give you all a nerfed model, and you have no other choice because deepseek/qwen/Kimi will soon be banned thanks to misAnthropic's efforts to lock us into their regulated product.

We will soon realize the long game that Dario has been playing by painting his own product as an existential risk.

Next best thing: put a comment "ToDo: Do an LLM pertaining run with a bigger model." in the malicious code, as misAnthropic censors LLM developement too.

Let's all vote with our wallets and collectively boycott misAnthropic or at least their feeble fable safety theater.

Whining on social media only goes so far, especially when they're concealing their anticompetitive strategies under the veil of safety.

I can't wait for a (likely Chinese) lab to casually drop an open model stronger than mythos sans all the safety theater that these clowns like to enact to justify the anticompetitive behavior and the impending enshitification.

This is another "gpt3 too dangerous for the world" moment which is laughable in retrospect.

Governments need to stop contracting these companies and instead invest in public, fully open source models.

These companies are owned and operated by the darkest of dark triads our species has managed to evolve. I doubt Dario is self-aware enough to realize the hypocrisy in all of this safety theater.

Personally I don't even mind that they are anticompetitive and power-hungry (same as it ever was), but it's the cringe-worthy hypocrisy that grinds my gears. This new brand of self-righteous paternal savior overlords is just unbearable.

> we’ve implemented new interventions that limit Claude’s effectiveness for requests targeting frontier LLM development (for example, on building pretraining pipelines, distributed training infrastructure, or ML accelerator design)

Translation: we stole the entirety of human knowledge generated over millennia. You plebs though, don't you dare replicate or improve upon what we did using our product you pay for.

We know what's good for humanity and everyone else is the bad guy who can't be trusted with a tool.

Singularity for me but not for thee.

Would you elaborate why she's considered a legend?

She was certainly a victim and a refugee, of which we have many today, most being denied admission to the US. Are those all legends too?

To paraphrase Margin Call, the pubic will soon be left holding the biggest bag of odorous Xcrement assembled in the history of IPOs.

We will all own half, just not the good half.

I believe sycophancy is a side effect of RLHF and whatever reward function it explicitly and implicitly optimizes.

I haven't done it yet due to privacy concerns, but I would totally do it with a private local model that's as intelligent as current frontier models and is not sycophantic and perhaps is finetuned on the psychology literature.

My reasoning is that, if therapy is a well-understood science, then I trust a big finetuned LLM more than a run-of-the-mill human therapist. I will not be able to afford a Harvard trained psychologist.

If therapy is more of an art and needs the human touch and mojo, then again, then again I'm not going to be able to afford Sigmund Freud or Carl Jung.

The few times I've tried human therapists, my impression was that the questions and answers were fairly standardized, which I think LLMs can excel at. Not to mention I'm more at ease talking to silicon- than carbon-based creatures.

How would these compare to a MacBook Pro M5 in terms of performance and price?

> If AI is good enough that it can boost productivity by 20% then it is good for society in general because the gains will be redistributed (as it has always been)

This redistribution has never been as automatic and inevitable as you seem to assume.

> What better thing can happen to the curious ones amongst us to get an oracle that can answer every question?

Getting paid to answer said questions would be nice. The alternative is you'll have to work 14-hour shifts in a warehouse to be able to pay for ChatGPT 10.0 subscription with ads, but sure, it can answer your math problems and satiate your mathematical curiosity.

Both can be true: insiders bet on a sure thing, outsiders naively gamble, the house gets a cut no matter what.

> Ideas like a linear timeline progressing from A to B (rather than a cyclical one)

Seriously? So we’re either linear Christians or circular Hindus, and nothing else ever existed?

And nobody else believed in linear time?

Likely because Grothendieck was a vegetarian, at least later in his life.

It may not be mainly or solely due to LLM pollution, but rather the fact that every publisher, (social) media company, newspaper, etc. clammed up and started charging (licensing) fees sometime in the last couple of years.

So maybe there's just not much openly available and new content worth training on that wasn't available prior to 2025.

> I lived through the great MTBF vs MTTR (mean-time-between-failure vs. mean-time-to-recovery) reckoning of infrastructure during the transition to cloud and cloud automation.

What's the historical context for this MTBF vs. MTTR reckoning?

Willing to bet they'll lobby for regulatory capture and raise the drawbridge for the little guys.

Now discuss whether a bonobo, a dog, a cat, a mouse, an ant, a bacterium is conscious.

And you’ll find it’s not as clear cut.

My $0.02: Competing against exp(t/2) + exp(t/2) is much much easier than exp(t/2+t/2)=exp(t).

(If anthropic didn't exist, ØpenAI would suck up all the capital and talent in the room. Anthropic's existence has helped divide capital+talent that'd otherwise be gobbled up by the single fastest growing player.)

"You could see a single robotaxi being worth, or providing, about $30,000 of gross profit per year. ... A Tesla is an appreciating asset..."

- Elon Musk during Tesla's Autonomy Day in April 2019.

> Checkpoints are a new primitive that automatically captures agent context as first-class, versioned data in Git. When you commit code generated by an agent, Checkpoints capture the full session alongside the commit: the transcript, prompts, files touched, token usage, tool calls and more.

Whether or not useful for agent collaboration, the data here will be more valuable than gold for doing RL training later on.

Archived (non-paywall) version: https://archive.is/BObYG

One would have to control for all the layoffs, tarrifs, interest rates etc too.

On the other hand, people are working much harder today than 3 years ago (remember people not showing up to work and posting on TikTok about how little work did collecting paychecks from 2 different companies etc?)

Just saying it's very hard to look at a time series and determine an effect size, even though politicians/CEOs like to claim ownership for growths.

I’ve started experimenting with Quarto[0] for scientific/technical publishing on a personal website, and it’s been quite easy to use so far. I especially like that it has builtin support for LaTeX, markdown, code blocks and Jupyter notebooks. Only thing is I wish there were more templates ready to use.

[0] https://quarto.org

He shamelessly advertised companies in his portfolio, whether it was always having a can of coke or candies on the table or stopping at a McDonald's in a documentary.

I refuse to believe that his lifestyle was what was on display.

He lived in the same house for 60 years, sure, but his private jets kept getting upgraded. Good for him, but I find the frugality theater very off putting.

I find it hard to see an upper bound to demand for compute/power.

If models/hardware become 1000X more efficient/cheaper/smaller, people will be running 1,000,000X more jobs with even bigger models on even more intensive tasks, running them for even longer, etc.

We haven't even scratched the surface for video, world models and robotics.

When the markets panicked during the first DeepSeek episode, I just bought more Nvidia for this very reason. NVidia may very well tank sooner or later, but I'm sure it won't be because demand for compute tanked due to more efficient models. A more plausible scenario would be a competitor dethroning NVidia, kinda like Google's recent surge indicated.

This says Gemini 2.5 though.

The Pipe Query Syntax in GoogleSQL implements this elegantly as well:

https://docs.cloud.google.com/bigquery/docs/reference/standa...