bredren

That may be true, though Anthropic reported 3.4 million exchanges with Moonshot months before Fable.

Why bother creating hundreds of (presumably paid) accounts and the tooling to create and consume the data if not of tangible value to their core mission?

https://www.anthropic.com/news/detecting-and-preventing-dist...

There is also some life stage appropriate utility in its ~disposable entry tier pricing.

For example, having young kids is not a good time to have a nice teak dining room table. (Or new wood floors for that matter) (or really anything nice you don’t want to hide in a locked box or room)

Also, pets, like a cat is wonderful. But without great diligence a more lower mid-tier couch will get clawed up the same as an ikea special. At least it may be more comfortable in the meantime.

I suspect wealth may be having your cake and eating it too—-you have fancy furniture that kids or pets wreck and you file that under dc.

All of it screams for automated materials reprocessing. One can only hope that the collision of robotics and AI will reduce the amount of landfill we create.

He also neglected to mention that Larry Harvey attended up through his death, afaik. Or how deeply affected the city was the year Larry died.

Or that the man design was done for so long by a close collaborator of Larry’s. And that the man base has been frequently spectacular both on fire and not.

The historical perspective and old photos are great but I’m not much for the conclusion. I would be willing to bet the title and byline are editorialized by the publisher.

You can still go out there with not much, be new and participate and just smile at some famous or not person also on their way back from the Portos.

There is a lot of money involved, no doubt and there is a lot of bullshit too, like art cars that do fundraisers and take volunteer contributions only to remain largely private vessels for a particular crew, a few celebs etc.

And there’s a lot to not like about the org or how art grants are handled, it’s a big system it has the exploits and nepotism that might infect anything scaled and offering power.

But if you go and do not look closely and just give in small ways none of that would likely be visible to you.

You could have the time of your life. Or not. Which I think suggests the opportunity for adventure and chaos still remains at that thing in the desert.

Bartering is not a thing at the burn. It intended to be a gift-based event.

Rainbow Gathering is barter-based.

This reminds me a lot of “dreaming” for skill improvements rather than lost tasks and ideas from past sessions.

Presumably their agent was running an anthropic model, or it wouldn’t have been a partner case study.

So, the premise is a bit of a self-own.

That said, the solution may still have merit regardless of the model that sent them looking.

If the distillation "attacks" created useful inputs to open weight models, ai-2027 was directionally correct that the Chinese would find ways to extract IP from western firms. (Scaled account creation and grinding outputs etc is not a dramatic story element as spies, though!)

Whether the distillation has constituted "attacks" or has or will meet the bar of "stealing" IP is not super interesting to me, though.

With multiple 200 a month subs you are getting a multiple of those subsidized tokens. At least if you tabulate at retail api prices.

This rent in the era of expensive hardware thing is not exclusive to inference.

I’ve needed x86 architecture for windows builds recently and have just hemmed and hawed over buying a decent windows 11 box.

I can’t make the math work against Azure instances.

I can spin up a nice one for build deallocate,spin up something cheaper for QA and then turn that off.

I can build all the devops around that, with a number of passes, with a skills based interface so working with the cloud is not too bad.

The only thing that still has me thinking about it is the prospect of price is going up even more, which is acid as far as I know.

And I’m hopefully going to need this x86 stuff enough that I don’t wanna wish I had gotten one for that high prices now.

Also: the enclosure, and the hinges.

That is a big claim. I know some of it is because I have interviewed people who have described ~exploits building LLM redditors.

But >90%? Can you provide something that supports something in this ballpark?

Notably done on Opus 4.8.

Thanks for sharing. I do not keep a neutral tone with the AI.

If things are stressed and I’m up late, the AI gets less leeway. If we happen to be in the performance dip just prior to completion of a new major model, it can get salty.

Some of the time it can be helpful for the prose to shape around how I’m expressing myself. The frontiers are pretty good at it.

That said I’ve also had the latest Sonnet seemingly ~maliciously implement something because my prompting disagreeing with it was a bit callous. (It turned out to have been right also)

I don’t think you can build a good model that is supposed to interact semantically that does not carry some ability to express empathy.

Partly, because we need the model to have humility when it does mess up. So it can express the right amount of concern or remorse when mistakes are made and identified. (For example, reading a secret into context by mistake forcing the roll of a private key)

Design is how it works, which means the way it responds can be as important as what it responds with.

How are you using email despamming?

I am looking to automatically recover mail from junk folder due to bad icloud mail filtering.

It is bizarre. There has been no statement, no mention of even hearing concern about Opus 5.

I presume something is forthcoming, but it may be they don’t want to come empty handed—-5.1 is intended to “fix the glitch.”

> Do I have to read the whole transcript just to understand what's going on?

No but you will want all of the transcripts anyway.

> AI will summarize it for me?

Not exactly. You will have some question later that you would never have entertained during your thousands of conversations about code.

You’ll ask your AI something fairly abstract but it will be deep in the context of some other idea.

And the AI will find among all your conversations those turns that are relevant to solving your problem or explaining why.

I know this is the case because I’ve built this and use it every day.

Here are some examples:

   1. Resume unfinished work → "where did we leave off on that?"
   2. Recover the intent/scope → "what was the actual goal of this whole effort?"
   3. Verify it got done → "did we ever finish that, and which session proves it?"
   4. Recall a fix → "how did we fix this the last time it broke?"

I shared these and more in my post in the August “what are you working on?” thread. [0]

You would be amazed how good the agent can be at assembling queries against a corpus of transcripts and assembling the results.

My product is called Contextify: https://contextify.sh

[0] https://news.ycombinator.com/item?id=49236853

Sometimes it is useful to simply know something was brought up, but then someone had a sneezing fit and everyone lost track of the thread and the important edge case under discussion just fizzled.

A similar thing happens in agentic conversations, where a model may point out something but it is not recognized as important by the operator.

A few directives later and the model is being pushed another direction.

It can be very useful to have perfect recall of moments like these.

Thank you!

Right now Contextify parses the developer surfaces: Claude Code (including the Desktop "Code tab") and Codex.

Claude Cowork and Claude Desktop chat are on my radar. IIUC, they store local, plaintext transcripts, however the schema differs enough from Claude Code that it's a new parser.

I'm not totally clear on how the ChatGPT app will work. I believe it went through some major revisions recently, and it used to encrypt transcripts. I'll look at it more.

Which apps do you and your students use most?

I saw your comment about the AI Authenticity Audit. Focusing on their questioning, curating, editing, and iterating process is exactly the kind of thing Contextify is built to surface. I'm curious what format you had students submit it in?

If their tool were covered, the audit could be as simple as running Contextify and asking: "prepare a report showing the key turning points in pursuit of this insight: [some key passage]."

I've been working on Contextify, which backs up your Claude Code and Codex conversational history and makes your entire history available via a skill or mcp.

Contextify (https://contextify.sh)

It is very flexible, you use it the normal flow of CLI AI conversations:

   1. Resume unfinished work → "where did we leave off on that?"
   2. Recover the intent/scope → "what was the actual goal of this whole effort?"
   3. Verify it got done → "did we ever finish that, and which session proves it?"
   4. Recall a fix → "how did we fix this the last time it broke?"
   5. Reconstruct a decision → "why did we go this way instead of the other one?"
   6. Branch/PR archaeology → "what was this branch even for?"
   7. Recall a plan → "what was the plan we landed on for that?"
   8. Activity over a window → "what did I ship or close in the last few days?"

Just add "use total recall" or invoke the skill directly via /total-recall or $total-recall.

You can self-host your database to keep it local and sync your history across multiple computers. The local server is source available under FSL-1.1-Apache-2.0.

There are macos and linux clients, and I'm pretty close on a windows client. All share a common Swift-based core.

Yes, also reminds me of the lead up to the Tobacco Master Settlement Agreement: https://en.wikipedia.org/wiki/Tobacco_Master_Settlement_Agre...

Possibly content that appears only briefly? I'm not sure otherwise. It seems wasteful.

Even more so has been what appears to be a miss with Opus 5 in Claude Code.

It is a bit of a tagent but still--Theme Park was dope. I was too young to grasp the compete with other businesses (stocks and shares?) level but still had a lot of fun building parks.

Instant nostalgia: https://youtu.be/tQJJ_rhHxIk?si=V8pOVwj3gYkw0xKB&t=188

This seems to be an institutional, massively scaled version of https://github.com/karpathy/autoresearch.

In March Karpathy described this direction:

   The next step for autoresearch is that it has to be asynchronously massively collaborative for agents (think: SETI@home style).

Tweet is protected but in SERP caches: https://x.com/karpathy/status/2030705271627284816

Seems like Karpathy was largely focused on ML / SWE research rather than the other domains this group is after. Still, hard to imagine they were not influenced by autoresearch.

Andrej, if you're around, please share your thoughts on Discovery Loop.

Securing cyberspace matters to everyone. Defending critical infrastructure or design of tactical cyber-offense is reasonably in scope for military work.

However, reducing (or rather limiting the increase of) PII leakage and impact of ransomware activities is much closer to day-to-day mainstreet of most people.

Anyone committed to advancing science should care about this regardless of its potential contributions to defense.

Thank you, for your patience in my reply here it is:

https://banagale.com/cinematic-canvas-ai-film-animation.htm

I provide a "how I got to this" up front, but if you want to jump right to the Apocalypto stuff, use this:

https://banagale.com/cinematic-canvas-ai-film-animation.htm#...

And if you want to play with interactive demos of the two animation sequences (the tuning tooling I described in my OP) you can go directly there:

https://banagale.com/cinematic-canvas-workbench-demos

If anyone wants to collaborate on building out the cinematic-canvas-workbench project please email me.

Please feel free to do so! I have a source available copy of the self-hosted sync server up on github here: https://github.com/PeterPym/contextify-cloud-self-hosted

If you have time to try the product as it stands, I would definitely appreciate your feedback in particular, and would be interested in checking out what you've built so far for yourself.

I will publish the API to the database as well.

Thank you for mentioning it and for putting your suggestion in the language you did.

That page with the time machine may not make it obvious, but the product does have a linux client!

It doesn't have the same app window and summarization of the macos version, but the transcript ingestion engine is efficient and the real value is in leveraging the database it builds using the packaged `/total-recall` or your own use of the api. (which is not yet documented but discoverable)

I am building the windows version now. I have been for the past four days. It uses a shared swift-core with the macOS and Linux versions which has been part of the reason it has taken "so long."

If anyone is on windows (or linux!) and would be willing to try it either of the clients my email is in my profile, I would be grateful.

Also I'm working up a short post with that apocolypto anim now.

I worked with an LLM to build a ~3D animation of the Back to the Future delorean Time Machine as a way to spice up the hero on a docs page.

That took a fair amount of custom tuning and I had to create a tuning view to get some of the behaviors right.

But it was enough fun that I generalized it to take in ~any scene description from a film. It goes out and gets more detailed descriptions and film stills if available but also takes custom stills if you provide them.

My test scene was the Gauntlet scene from Apocalypto. It is low fidelity but does a pretty amazing sequence with somewhat believable physics of the javelins etc.

Here is the docs page with the vertical takeoff / 88 miles an hour time travel: https://contextify.sh/docs

I can share some of the Apocalypto bit if anyone is interested.

I thought this was going to be about AI / agentic development stacks.

Because long running, well tuned pipelines can deliver on some important goals but be broken by the changes from adopting a new model (ahem opus 5) or rot in some key web automation path.

A month ago the highly upvoted blog entry [0] about Rivian’s rejection of CarPlay included this quote from Rivian’s Chief Software Officer, Wassym Bensaid:

   The challenge with screen mirroring solutions is that they take over every single pixel in the car, and that’s not the way we see ourselves interacting with our users.

Yes, it’s clear the companies’ see the way they want to “interact” with their customers is to force whatever content they please.

[0] https://news.ycombinator.com/item?id=48769397