creativeSlumber

> Anthropic is in a business that didn't exist 3 years ago.

but it's already commoditized.

What is your setup like? How much VRAM do you have? I'm curious about what is the minimum configuration that you would need to run this locally.

Can the same mechanism be used to make sure it outputs syntactically correct code?

> All of those things have been demoed, but didn't go to production.

There's probably a good reason for this. Demos usually just show the happy case, whereas in practice you have to deal with all the nasty edge cases of reality.

Could the reason be as simple as saying that every AI model has been trained on basically the same input data sets?

> This happens a lot because at the individual level, it’s sort of in everyone’s best interest to take the deal. The prosecutor wants $2,000 and 0 jail time and it all goes away. If you don’t take the deal, even assuming you win in the end, it will probably cost you way more than $2,000 and however long the probation check ins take. You will recover neither your time, nor the money you spent on lawyers/transportation/days off/etc.

Are there absolutely no provisions for an innocent person to claim all the expenses they had to incur ?

That is a different problem. In this case it should be clear that the prosecutors have messed up and won't admit it, maybe to save their carriers. They are going after someone innocent because it is the easy target while the real criminal is at large.

Isn't it Cashapp that allowed a criminal to open an account with someone else's social security number? Does she have a case against Cashapp?

> Engage in sustained and needless abusive or cruel behavior toward our models.

I'm curious what the reason for including this, because at the end of the day its a string of text (tokens) going into a function and it spitting out another string of text.

Maybe they are using the prompts and responses for training doesn't want these to influence future model behavior?

even if it's for her team, should have been a recruiters job.

Your browser cache is a cache. You don't care if it goes away. On the other hand, your pictures you do care. That's the only copy.

There were plenty of internet connected phones before the iphone. Nokia, Samsung all had phones with full internet access and browsers and other apps. I think there was even a Java mobile app standard called J2ME.

> Earlier this year, we launched Artifacts, a versioned filesystem that speaks Git and can scale to millions of repositories.

> We want you to build your vision for the Git platform of the agentic era using Cloudflare Workers and Artifacts.

> A link to the source code, which must be provided under a permissive open source license (MIT, Apache, BSD)

> We’ll select the top three projects and fly up to two members from each team to San Francisco to attend Cloudflare Connect and show what they built. The first-place team will also receive $25,000 in Cloudflare credits, along with invitations to the VIP speaker dinner on Monday night at Connect.

LOL. So basically they built some new product and it's not getting enough adoption. And they're looking to get (*almost) free labor to do the work for them.

Why would they? You are a paying customer for both accounts.

> then there are 10^100 possible paths through that session.

Is this correct? in practice you would only be deciding what the next turn is going to be. Because the turn after the next turn is determined by the outcome of the next turn. So shouldn't this number be 10 * 100?

What's different this time is that LLMs require orders of magnitude more memory than we could have ever used before. And I think it's getting obvious by now that inference will move to local compute, So everyone's laptops and phones would need a lot of memory.

is this just a fancy way of saying that sometimes humans makes quick heuristic based decisions, and sometimes they think through things thoroughly?

I don't think there's any problem category that is strictly a quick heuristic decision or something that you will think through thoroughly always. I think it's more about how much time you have. If you don't have time you'll make a quick heuristic based decision. If you have more time you will think through it more. Imagine you're driving and suddenly like a branch falls on the road right in front of you. And you need to avoid it. Your brain will quickly use a heuristic based approach to avoid the branch. But on the other hand, if this branch was already there on the road and you saw it from far away, you will probably take a lot more time to think through and figure out which path you need to take.

Wouldn't you need a classifier to even decide if it is system 1 or 2? How capable does this classier need to be?

How relevant is this fast/slow thinking thing with regards to current frontier models?

I know a large organization who's built their AI framework completely around this concept, and I feel that it's not really meaningful concept with the capabilities of current models.

I was wondering about this one too.To make things worse I also use speech to text and that introduces its own inaccurate transcriptions and typos. Are there any reliable research around this ?

> and I am using DeepSeek directly via the API.

Do you know if they retain your prompts or use it for training?

> And the water used must be recycled and self sustaining. If you need a million gallons fine but that’s all we can’t have data centers sucking up all the water.

They can have a closed loop cooling system, but it costs more energy to run and would eat into their profits. so they use evaporative cooling, cheaper, but consumes entire towns worth of water. If this is pumped from the ground, round water levels dry up in all around and peoples wells dry up.

its an ai written article it seems. probably written for engagement bait.

If the debt cancels out doesn't this mean that there was no debt ?

> 6. 200 OK, no answer Reasoning models sometimes put everything in the reasoning field and hand back content: null, finish_reason: "stop". 345 completion tokens, HTTP 200, nothing to show the user. A 200 tells you the request was served, not that there's an answer in it. No content and no tool call is a failure, throw and retry.

I ran into this so much I had to modify my harness to handle this.

do they lend money to their customers to buy their own chips?

> Do we use user feedback and de-identified data to improve ChatGPT and Codex in a holistic way? Yes.

This says that they trained on user sessions. The de-identification here I believe refers to removing PII, which doesn't matter here because the issue at hand is the content of the researcher's session where they likely discussed their approach tackling the Navier Stokes problem.

> Did any human or agent look at user data as part of the Navier Stokes effort? No.

If they trained the model on Lavent's chat sessions (PII removed or not), then this statement is meaningless as the model weights already contain that information.Given it's a new yet unreleased internal model, it is likely a 10+ trillion parameters (Astra is rumored to be 10 trillion), so the model can retain a lot more detail/info from training data.

Why is he leading the with the irrelevant part first ?

> And so does every LLM company.

Nope, not for enterprise users.No enterprise customers would use it if all of their internal business plans / trade secrets would end up in the model weights of the next OpenAI model. Imagine your competitor asking chatGPT a question and the model spitting out your business plan. These models can retain very specific fine grained data. I remember there were examples of them reproducing sections of their training data verbatim.

> Researchers had found signs of CKDu outside Central America, including in Sri Lanka, India, and Nepal. But it had never been documented in the United States.

I searched a bit more and found this interesting bit from an article talking about a similar epidemic in Sri Lanka.

> An analysis showed that trace metal ions such as calcium and magnesium that naturally occur in the hard water reacted with glyphosate. This meant that, instead of breaking down rapidly, glyphosate was able to persist in the environment for up to seven years in water and twenty-two years in soil.

https://www.thinkglobalhealth.org/article/mysterious-kidney-...

> Vibe: users are not opted out by default

> Vibe (Enterprise): customers are opted out of training by default

So they made it opt in for enterprise (how it should be), but intentionally made opt out for regular user.Basically saying "screw you: to regular users.

Any self respecting user should stop using them.

Agree, that it is an ad. Also, unless the full session (in a resume-able format, along all session artifact such as intermediate research/docs used to produce the final output) is also included in the commit, the session id is useless.

I presume this is Anthropic trying to their "usage" stats before their IPO.