Normal users don't profit from anything you listed. They do have to buy a notebook with all components, and thus currently have to pay more for linux/windows hardware compared to Apple.

Also, RAM isn't backwards compatiple. Literally had this problem with my old ddr4 not fitting in the newer ddr5 slots when my ddr5 acted up.

It might still be worth it for those who hugely value open source and repairability but as for value I think its save to say that Apple is currently in a league of their own. Even if the altest os update is a flop.

Also, the Macbook has improved repairability. While its still not great its better than a few years ago.

A skill can also act as an abstraction layer over many tools (implemented as an mcp server) to save context tokens.

Skills offer a short description of their use and thus occupy only a few hundled tokens in the context compared to thousends of tokens if all tools would be in the context.

When the LLM decides that the skill is usefull we can dynamically load the skills tools into the context (using a `load_skill` meta-tool).

1. unreliable in GH copilot. Lots of 500 and 4XX errors. Unusable in the first 2 months

2. not available in vertex ai (europe). We have requirements regarding data residency. Funny enough anthropic is on point with releasing their models to vertex ai. We already use opus and sonnet 4.6.

I hope google gets their stuff together and understands that not everyone wants/can use their global endpoint. We'd like to try their models.

A 10$ GitHub Copilot or 20$ ChatGPT/Claude subscription get you a long way.

And if the employer isn't willing to spend this little money to improve their workers productivity they're pretty dumb.

There are valid concerns like privacy and oss licences. But lack of value or gain in productivity isn't one of them.

Doesn't matter anyways wether their customers are people who search for shortcuts or people who search for "the best designs".

Their problem was and is that tailwind is used by many of the most profitable companies in the world for free.

Thats so unbelievable stupid. You have corporations paying millions for MS 365 subscriptions, confluence, and other software and basically nothing for a totally optional ui library. If the use of tailwind saves 10 engineering hours per month then it's worth it to pay a few hundred $ for a licence.

Given that their team isn't big they don't even need that many customers. Add a bit consulting for a decent hourly rate and they should be golden.

The more I think about it the more I blame the CEO for poor decisions.

There needs to be a greater distinction between models used for human chat, programming agents, and software-integration - where at least we benefitted from gemini flash models.

They, and other companies, should rather depend on corporate users. Don't let multi-billion revenue companies use your tech for free.

Seems like many companies leaned it a bit late, we always have the same news every fewe years (docker, mongodb, terraform, elastic).

What actually makes it an AI platform? Some tight integration of an intel ARC GPU, similar to the Apple M series processors?

They claim 2-5x performance for soem AI workloads. But aren't they still limited by memory? The same limitation as always in consumer hardware?

I don't think it matters much if you're limited by a nvidia gpu with ~max 16gb or some new intel processor with similar memory.

Nice to have more options though. Kinda wish the intel arc gpu would be developed into an alternative for self hosted LLMs. 70b models can be quite good but still difficult / slow to use self-hosted.

That's not even limited to linux or gaming. A few weeks ago i tried to apply the latest Windows update to my 2018 lenovo thinkpad. It complained about insufficient space (had 20GB free). I then used a usb as swap (required by windows) and tried to install the update. Gave up after 1 hour without progress...

Hardware+OS really seems unfixable in some cases. I'm 100% getting a macbook next time. At least with Apple I can schedule a support appointment.

It's just an anti-competitive move that could be very bad for the consumer as it makes the inference market less competitive.

The few people I know back then used keras instead. I switched to PyTorch for my next project which was more "batteries included".

Cheap labor. It doesn't take that much to train someone to be somewhat useful, in mmany cases. The main educators are universities and trade schools. Not companies.

And if they want more loyalty the can always provide more incentives for juniors to stay longer.

At least in my bubble it's astonishing how it's almost never worth it to stay at a company. You'd likely get overlooked for promotions and salary rises are almost insultingly low.

Had to spend quite a long time to figure out a dependency error...

Does the Zig Foundation have a policy against corporate sponsors?

Otherwise the lack of sponsoring from the "big players" seems rather shocking. You'd think that zig has a decent chance in helping MS/Meta/Google/etc. somewhere along the way.

Facebook, Youtube and others put in effort to take down illegal content.

4chan only does the bare minimum such that they don't gain too much relevancy in the public eye.

UK or other countries may decide that 4chan doesn't to enough and ban it because of the help of 4chan in faciliating the spreading of illegal content.

So again, where is the difference between 4chan which hosts/spread illegal content and other sites where we're fine with banning them?

If you wouldn't allow child porn (which 4chan deletes/doesn't allow), where exactly do you draw the line between blocking sites with cp, and allowing sites like 4chan which host porn without consent (voyeur/spy/revenge)?

The API constantly gives you quota errors when you reach about 150 requests/min eventhough the quota should allow about 50_000 requests/min.

We’d like to use the Batch API, but the model isn’t available yet.

Quite a nice model though. Being able to get embeddings for a specific task type [1] is very interesting. We used classification specific embeddings and noticed a meaningful improvment when we used the embeddings as input for a classifier.

1: https://ai.google.dev/gemini-api/docs/embeddings#supported-t...

Was the Java Service in Spring (boot)?

What other technologies were considerd?

I'd assume Go was among them. Was it just the fact that Go's type system is to simplistic or what were the other factors?

I'd like to think that if things went just a little bit better it would have beed the ideal programming language for anything cloud / backend related.