- anthropic IPO repricing

- pareto frontier gap decreasing by the month between open and closed models

- SpaceX disappoinment

- enterprise buyers as main consumers of closed tokens are being displaced by OS competition for pennies

- job loss and entry level hiring collapse

- massive discounts of current data center contract debt

- consumer open weights model efficiency improving constantly

- the Chinese arms race

- a possible rapid downward spiral that may force governments to step in and subsidize

Am I missing anything?

Everybody knew it.

But some investors don't have the patience for these "sure things" to mature into their commercial destiny and others know they can siphon off a killing by taking advantage of them as they speculate.

These bubbles aren't about potential, they're about timing.

And today's AI, for as revolutionary as it may be, is taking just as long to mature as anything in the past.

Most of the top players involved in AI right now are going to be rich. And in 20 years, the world is going to involve a lot of AI in soooo many things. But a lot of shirts are going to be lost below those top players and a lot of companies are going to fold because infrastructure, refinement, and integration take time while the FOMO speculation starts as soon as the big discovery is recognized.

It is their job. You take decisions that are worth billions, you influence people that take decisions that are worth billions, and affect their countries.

They are going to study you for years. Your personality type and that of the people around you. Your weaknesses. Your problems and that of your family.

They will employ the most sweet and the most pleasurable and gorgeous honey that there is in the world to create the perfect Honey trap.

Normal people just can not imagine how sweet, specially when it has been customised around your needs and desires.

It is not just a woman wanting to have sex with you. It will be the woman in your dreams.

I’m still looking for work in the mean time but I’m proud of what I’ve achieved so far.

https://getcrewbird.com/

At my very first job, we had a weekly meeting to assign tickets and estimates.

Our non-technical PM wrote "drag-and-drop" on a whiteboard, and then my name.

"Gavin, how long do you think this will take?"

"All week. At least. Maybe longer?"

PM laughed, then realized I wasn't making a joke.

"What do you mean 'all week'? That's ridiculous, do I need to give this to someone else?"

"Well, you could, but I wouldn't count on you getting it any sooner."

Appalled, he exclaims: "It's just drag-and-drop!"

After 10-15 minutes of a room full of engineers trying to explain the difficulty, he gave up with an unhappy "Fine."

The phrase "it's just drag-and-drop" became an inside joke for the rest of my time there...

So I limit myself to at most 2 or 3 things at once, and if all of those are in long running sessions, well so be it, I know I'll be deep back in it soon.

But it's tempting to start "just one more session", especially something like getting it to better profile and improve performance. That feels super productive, but is often just to stop me feeling "idle".

Nvidia is doing an investigation of Jensen Huang being targeted in an intelligence operation; ie, an investigation of something that happened to him.

The title implies that Jensen Huang is the target of Nvidia's investigation.

Outlook.com and similar are an anathema to email. This is why they tell you not to run a mail server .

On the other hand rejecting domains without dmarc is fine. Just not happy it is silent.

You cannot have semi-unattended agents running on the same workstations that have access to client/trade/prop information and email client, and internet, and internal networks, it's too dangerous--a major leak is just one small mistake or prompt injection away. Banks are not stupid, they are getting it and shutting it down.

Anything above that requires an Enterprise plan, which is billed at API rates.

Gemini is swooping in because they offer flat consistent billing and handle overages through throttling access to higher models. For 90% of the non-engineering org the experience is near enough it makes no difference.

The problem with AI writing is that it makes people believe that writing is just writing and not a tool for thinking very deeply about the topic you are writing about. I am not completely opposed to AI assisted writing, but if I see AI writing, it’s telling me that the author tried to take a shortcut in their own thinking and it’s a good heuristic that the ideas will not be thought through enough to warrant my complete attention.

The GUI is less verbose with the nitty gritty hidden in expandable sections, which makes history easier and cleaner to scroll through, also no scrolling bugs, rich text is easier to read with tables, and images integrated into the chat, resources like browsers in the context of the session. Drag and drop session organization (pins), scheduled tasks, etc.. all that in the side bar.

Usually a TUI would be open in VS Code and scoped to whatever repo I'm working with so 10 projects, 10 VS Code instances open, not super scalable. With the GUI desktop app it's one app, and I can start sessions in an repo and switch between them easily, no need to open VS Code for each. I don't see what could make me want to go back to using a TUI.

Who else is just using the GUI nowadays, or are you still on the TUI, and why, have you tried the GUI interfaces?

That said, a few thoughts:

1. .claude/settings.local.json is meant to stay local. This is not a file you should check into source control. We automatically gitignore it when Claude creates the file, so in this case the files were manually created and checked in (docs: https://code.claude.com/docs/en/settings)

2. Permission rules are old hat. Everyone should be using auto mode instead. It is safer and also does not require manually maintaining finicky allow/deny lists. Auto mode is enabled by default and is included for free in all plans.

3. Regardless of what agent you use, you should have secret scanning enabled. GitHub and other source control hosts offer it. There are many threat models that it protects against and you should absolutely use it if you can. (see https://github.com/security/plans)

RCA developed the first good color TV cameras. They were monsters. Originally, electronic TV (as opposed to mechanical scanning) used Zworykin's iconoscope. This needed huge amounts of light. It didn't have a photo-multiplier stage to boost sensitivity, but it did accumulate charge from light over the whole frame time. There was an alternative approach, Farnsworth's image dissector, which also needed huge amounts of light. It had a photo-multiplier stage but only the light from the dot currently being scanned by the scanning beam mattered.

So RCA threw money at the problem. They developed the image orthicon camera tube. It combined the advantages of both approaches, integration over a full frame and a photo-multiplier stage. It was insanely expensive, costing thousands of dollars in the 1950s. It needed about twenty different voltages and multiple independent power supplies. It worked reasonably well.

Then came color. That took three image orthicons (RGB) inside a box the size of a small refrigerator, along with optics to split the incoming image into three colors. Plus a rack of analog electronics per camera, connected through a large cable. Plus an alignment problem from hell, with a huge number of adjustment knobs.[1]

Scaling worked! From the 1950s to the 1970s, color TV broadcasting was powered by those monsters.

Now, independent of this, other people were working on other approaches. Vidicons, silicon detectors inside camera tubes, and finally fully solid state image sensors. Eventually, in 1983, after thirty years of image orthicon monsters, RCA produced a usable solid state camera. Today, a cell phone camera costs about US$10 in bulk, and it's far better than the monsters.

It took thirty years of low-priority development to get past the giant image orthicon cameras.

Electronic fluorescent lamp ballasts had a different problem. That was a suppressed invention. The magnetic ballast industry was dominated by Magnetek. Someone invented a solid state replacement, which was smaller and cheaper, and licensed their patent to Magnetek for royalties. Magnetek just sat on it, not wanting to gut their core market. The inventor hired Townsend, Townsend and Crew in Palo Alto and sued. (Read this in the law firm's brag book in their office.) Eventually, the inventor got a hundred million or so, solid state ballasts went into production, and Magnetek seems to be gone. (The company called Magnetek today, which makes crane controls, is an offshoot of a Litton unit, and seems to be unrelated.)

There are also parallels from the steam locomotive industry, the Baldwin Locomotive Works being the best known. Baldwin actually built the first Diesel locomotive. They made a few half-hearted tries at Diesels over several decades, then gave up and went back to steam. Baldwin ceased all locomotive production in 1956. The corporation lingered on for a while, not doing much.

[1] https://www.tvcameramuseum.org/rca/tk40a/pix/rcatk40aart.pdf

Producing "trump is …" when a user wants that is one thing. Producing that when the user wants something else could be construed as coming from the software itself, and we all know that people looking for a shitstorm will seize the opportunity.

So probabilistic software like a swipe interpreter will often be written to avoid some guesses, to lessen the chance of a shitstorm. Users who want that output have to use a dependable input method instead of one based on probabilities and guesswork.

IMO this avoidance isn't among the ten worst consequences of shitstorms.

To the shocking number of people here who are justifying this or explaining how it only affect swipe input as if that makes it better: soft coercion is still coercion. If I made a physical keyboard that stops keys from working when you're about to finish typing something I don't want you to type, but you can still circumvent it, I still made a censorship keyboard. It's a sign of the times with how used tech companies are to 'softly' moderating societal trends by unilaterally tweaking the software that everyone uses.

Almost all statements Yann LeCun made back then (LLMs won't be able to do this or that) turned out to be wrong. They were right to fire him.

The transformer based approach is seen as a highway to race down in terms of training and building better models with minimal organizational distractions allowed while every company puts its foot down on this highway. Exploratory research into other AI methods is highly discouraged for now and organizations are encouraging transformer based scale out and iteration as a top priority.

As an example Meta literally fired it's previously head of AI who held views that transformers won't scale. He wanted to veer off the highway and heavily fund exploratory new types of models. They got someone willing to scale the current method out. Essentially the messaging it "Foot down, there's a straight highway ahead don't divert".

I have the view this makes sense too. Current top models are mere (mere in big datacenter terms) trillions of parameters right now. We definitely haven't hit the ceiling and everyone's noticing "Hey this Opus 5.5 with the increased parameters seems much better than the last one". Well that's a trillion parameter model. We'll soon start hitting 10's of trillions and 100's of trillions of parameter models. Unless there's a ceiling which nobody expects they should keep scaling just as they have been. I really do agree that it'd be insane to veer off this highway with exploratory research at this particular point in time. Foot down, get to 10 trillion parameters, see if the scaling holds, if so off to 100 trillion parameters. If the scaling continues to hold we'll be asking the AI to do the exploratory research for us soon enough.

I wouldn't be surprised at all, given that Photos knows the names and faces of all the loved ones in my life. Not just people, in fact, but the "furry friends." And Calendar and Reminders knows where I go. And so forth.

The feature is genuinely useful. Only thing is it should be opt-in and have guarantees about where/how the data is stored, such as encrypted-at-rest. I trust Apple with that more than all other Big Tech combined, but still in a "trust, but verify" way.

I wish the circumstances around abandonware games weren’t so tenuous, there’s so much great stuff out there and reverse engineering with AI unlocks all sorts of cool possibilities. The multiplayer features here have me thinking about other old games that could be brought online and how fun it could be. SimCity 2000 where all the neighboring cities are real and operated by other players…

Electron's value prop has always been about having one team producing one app that is supported on multiple platforms with minimal additional effort.

This article does nothing to address that.

A similar discussion came up recently with Siri Recap[1], where some expressed how useful they thought it was and that, as a party to the conversations it summarizes, there was very little moral or ethical concern. But I have a social concern.

If I'm having a chat with someone, there's a milieu constructed around the fact that not everything will be remembered verbatim. There are all sorts of social and contextual cues that can easily get lost if listening gets replaced by flat relentless transcription.

With Recaps and this social graph (were it to be productized), the informal fluidity in the way we relate to one another starts to go away, and the expectations that follow from that become artificial and burdensome. In the same way that autocorrect has made typos unacceptable, how could you ever be forgiven for forgetting the name of your colleague's new nephew or the Italian village that your neighbor took a spontaneous boat trip to while on vacation last year?

[1]: https://news.ycombinator.com/item?id=49641401

Will we go back to PCs? As in: are we going to get cheap local hackable frontier AIs at some point? I hope so.