Yeah, the longevity for tape backups feels entirely theoretical when the tape drives themselves are out of production, so you could end up with a perfect tape, and nothing can read it…

Yeah, same, but every time I look at second hand stuff its crazy expensive, or completely obsolete.

True in general, but I am not convinced its true for OpenAI or anthropic.

Their training data is probably already replicated across multiple datacenters, so tape archiving is less critical. And if tape archiving is critical, then surely they already have sufficient backups already right? And its not like the organic content of the internet is growing anymore, so there isn’t going to be an explosion of new organic data they need to store.

So I don’t buy that they need this. I think this is fujifilm trying to get in on the bubble, and nothing more.

I buy the follow on effects rational, but I’m not convinced that tapes are a suitable alternative to HDDs. The random IO basically doesnt exist. But I guess if there are companies using HDDs for “cold” storage then using tape makes some sense for them.

My personal theory for this announcement is that its pure stock price manipulation. AI investing is full on fomo driven, so announce that your company is investing in X that will help AI, and watch the chuds hit buy in robinhood.

Okay, no need to name call. Tapes are for long term archiving. The access speed is minutes to hours, so these are definitely not for caching.

Thats exactly my point, why bother archiving when you need it accessible for training? Surely they would be putting the training data on a faster medium.

The ship has sailed on the front. But even if its for the corpus of training data, surely that can’t be stored on tape, the access time would be way too slow.

But thats pointless archiving it on tape, the access time is going to handicap the training speed.

I don’t get it, why bother archiving anything AI produces? You can just ask the next AI to reproduce it.

executives practice breathwork and put aside their electronic devices

Headspace for workers, retreats for executives. HR bullshit.

They bought an implementation of RCS, the standard is still open. They even sell there implementation to a few telcos.

You cant self host it because you need to be a telco, it has telco specific protocols. Also, this is one of the things that probably should be gatekept to telcos, if everyone were able to spin up their own instance, the spam problem would be unmanageable.

Your looking for a conspiracy/monopoly that for once, doesnt exist due to Google being malicious. It exists because telcos are shit.

Google didn’t develop RCS, GSMA did. All google did was purchase the startup that actually developed a good implementation of it.

This isnt some gatekeeping exercise from google, they had nothing to do with RCS’s initial design and release. The carriers are entirely to blame for dragging their feet, although some are finally implementing their own servers (China is entirely RCS without google).

As for “federate it, decentralise it”, thats how it already is. Its called “hubbing”, but its basically federation. The networks run their server, and the federate messages between them. It isn’t centralised at all.

Was it kidnapped? Or did the carriers basically dump it on the fire stations doorstep? Not really googles fault if every carrier was too lazy to run their own RCS servers…

I’m aware, and I wish people were more clear about the difference, but its LLMs that are driving these insane buildouts, not the other disciplines. This article is clearly talking about the LLM “AI”, not bioinformatics or anything that may actually be fruitful.

The LLM companies like to claim they’ll solve cancer, but its all snake oil hedged on a mythical AGI popping up and fixing everything.

Medical imaging and medication development would be bespoke models no? Not standard LLMs?

LLMs aren’t gonna give us any of those things. Thats just snake oil.

I get that analogy. However, I would heirarchaically place the agents as subordinates to the developer, which is why I would expect each developer to institute their own customised agents.md file, rather than it being dictated from the repo, which is a level removed.

but agents do

Depends on the model, Gemma 4 is extremely lazy in my experience, half the time it won’t finish the task properly anyway. Deepseek (not sure of the version) was crazily overactive. I personally prefer Gemma’s laziness, because it avoid making the chaotic changes that need to be rolled back, but thats a personal preference.

And thats kinda why I don’t like it being committed. If the entire team is using one model, then sure, commit the agents.md, and everyone gets a sane default, but given this is a multi-developer project with likely many different agents and models in use, it makes more sense to me that each developer manages the agents.md themselves and optimises it for their own model/workflow.

At least for the specific example given, I want developers to do the commit part themselves, so if their LLM is doing any part of that, its already a mistake IMO.

I had a very quick look at the AI agent guidelines, and nothing about them strikes me as overly burdensome for a human to fix up. So I’d rather just do that myself (if I were a kernel dev).

My main objection is forcing it on developers, it should be up to each dev to configure and manage their own agent. Making it a suggestion is fine, just don’t commit it. Also, if developers are using local hosted models, then context may be quite limited, so wasting it on an Agents.MD maybe be unideal.

I’m on board with committing formatter config, because thats deterministic and really should be shared amongst a team.

I don’t get why the agent needs to have the contrib guidelines, it should be a human doing the actual contrib part, so its just a waste of tokens for the LLM to read it?