t0md4n

For the target audience, they’d be none the wiser. If you’re even thinking about ram it’s not for you.

Have you tried Hex?

https://github.com/kitlangton/Hex

Faster than handy and uses way less memory.

Pretty cool. I wonder what the reduction looks like in the bigger SOTA models.

The harmful responses remind me of /r/MyBoyfriendIsAI

400mg L-theanine with my coffee/caffeine throughout the day. However, I am trying to cut back to 50mg caffeine 100mg L-theanine.

One of the ways I like to look at it is, humans have the unique ability to look into the past, and into the future. With this ability and the help of language, we are able to replay past experiences (good and bad) and make predictions on the future (plan forward, avoid things that hurt us before etc). This can cause “stress” or “pain” on the brain/person when those thoughts are negative. As things normally do, this “stress” can vary from person to person, depending on their makeup, life experiences, habits etc.

Just not true though is it?

Touch ID had a ton of downsides. It didn’t work with wet or dirty fingers, didn’t work with gloves, if you have clammy hands it would constantly fail. Plus it has a higher false positive rate than Face ID and has less features. Not to mention the speed and UX of Face ID is significantly better for MOST people than Touch ID.

I also meant landscape Face ID recognition, obviously not landscape device orientation.

Face ID is not terrible. Especially on newer phones which support landscape rotation etc. They check to see if you’re looking at the screen and your eyes are open, so they can keep the screen on regardless of the auto lock setting. It’s a smart and useful feature which you can turn off if you don’t like it.

It wouldn’t be instant, next week or even next month. Pre-training doesn’t happen that frequently and varies between each model provider. As for the strawberry test, this is a tokenization issue that is fundamental to LLM’s, however, most models can now solve this type of question using thinking/code/tools to count the letters.

https://imgur.com/a/NqIJEx6

I don’t believe this is true but I’m willing to be proven wrong. I believe people who think this are just used to Claude’s models and therefore understand the capabilities and limitations due to their experience using them.

I'd personally rather use gpt-5. The sub price is cheap and offers more overall value than an Anthropic sub or paying per token. The chatgpt app on iPhone and Mac are native and nicer than Anthropic's and offer more features. Codex is close enough to Claude Code and also now native. For me it's nicer to use the "same" model across each use case like text, images, code etc. this way I better understand the limitations and quirks of the model rather than the constant context switching to different models to get maybe slightly better perf. To each their own though depending on your personal use case.

tinybox?

Not sure how suitable this is for you.

https://tinygrad.org/#tinybox

Can you explain what the invasive back-end magic is?

License to operate? Idk how it works for food service but with the taxi service I think they need permission to operate, not completely sure though.

I would argue that that’s better than having multiple devices from multiple manufactures and multiple software applications from multiple companies.

We used this in one of my classes last year.

Aren't 'new models' always technically just refinements of old models? isn't that the point?

I’ve always wondered if it’s possible to pool together small amounts of resources from users e.g. similar to torrenting with networking, but with compute and use it to host a large model like this one. If the community wants open source to be the way, I believe this would be the only way to get these large models accessible to users while the community stay in semi-control of the platform.

Edit: would also work with training I'm assuming?

Is this written by AI?