EagnaIonat

7 ms·

91.
by EagnaIonat 4mo ago
Seems like something for people with more money than sense. If you could afford to drop money on this, odds on you can get a weekly maid who will do it for a fraction of the price. Watching the videos, they have the cleanest kids in that ho
92.
by EagnaIonat 4mo ago
You can use something like Grand Perspective app to find whats taking up all the space. But for oddness like you mention, run a disk check to make sure it's ok. Failing that do a NVRAM reset. https://www.macworld.com/ar
93.
by EagnaIonat 4mo ago
> Both machines will be stuck in the 30-50GB model range, That is not true. 3090 is only 24GB. It will absolutely outperform the M5 on models that will fit in that space, but M5 will outperform with larger models as the whole 128GB is GP
94.
by EagnaIonat 4mo ago
With a dedicated GPU, the lag is in transferring data to the GPU. You don't have that lag in ARM. But it really depends on what it is you want to do. An MLX optimised recent model will run fine and at decent speeds. Granite4.1 (a few m
95.
by EagnaIonat 4mo ago
Latest MBP goes up to 128GB of memory.
96.
by EagnaIonat 4mo ago
> MacBooks with their unified memory behave like a slow GPU with enormous amount of video RAM. So you can run large smart models slowly. With the model using MLX the speed increase is night and day. Even non-MLX is good. You also don&#x2
97.
by EagnaIonat 4mo ago
I still have memories of having to install Wordstar 2000 on 5 1/4" floppies. I think it was like 20 discs and painfully slow.
98.
by EagnaIonat 4mo ago
> That’s such a benign vulnerability that it doesn’t even feel like one. You could farm the data to see how the shop is doing.
99.
by EagnaIonat 4mo ago
Well Watson went from a product, to product line branding. Then changed to Watsonx. Doing a search on that there are loads of news articles.
100.
by EagnaIonat 4mo ago
I didn't upvote it.
101.
by EagnaIonat 4mo ago
Why post a link that people have to pay to read? Same article: https://www.businesstimes.com.sg/opinion-features/zombie-uni...
102.
by EagnaIonat 4mo ago
It's been a fact of life for as long as I can remember. If you using the companies resources, they are well within their rights to monitor what you are doing. Just don't use the company stuff and you are fine.
103.
by EagnaIonat 4mo ago
For me the other models are faster and results are good enough.
104.
by EagnaIonat 4mo ago
> thers, like coding or more advanced agentic workflows can demand much more powerful models. You can do coding and agentic fine. For coding I use qwen3.6:35b-mlx and agentic granite4.1:3b works fine. These are the models I use. - granit
105.
by EagnaIonat 4mo ago
Depends what you need the model to do. The recent granite4.1:3b just takes 2GB of memory and is fast. Results are pretty good and support tool calling. Barely a squeak out of the Mac laptop. Even faster with the MLX builds. Then when I need
106.
by EagnaIonat 4mo ago
Not sure if it's someone finding out about compound interest for the first time, or a veiled advert for start-ups.
107.
by EagnaIonat 4mo ago
> This. Here's a quick experiment I did yesterday. It's like running a sports car and then complaining it burns through petrol too fast. The truth is the model while impressive is not needed for much of what people need. Local
108.
by EagnaIonat 5mo ago
The emphasis on the fans kicking off also had a bit of a turn-off.
109.
by EagnaIonat 6mo ago
It's a well known technique. I first heard about it from Barbara Oakley, so there is probably some neuroscience research done about it.
110.
by EagnaIonat 6mo ago
https://github.com/ibm-granite https://huggingface.co/ibm-granite I think if you were genuinely interested, you could have found this yourself.
111.
by EagnaIonat 6mo ago
I'd like to assume you are not trolling and just want everything handed to you. The granite site covers everything you keep asking for. Granite is made using lm-engine and the details are there. Without the weights you are not going to
112.
by EagnaIonat 6mo ago
The training datasets are listed there and are all open source. > the complete recipes to make the models. You mean the weights which most companies don't release. Again you can find from that link.
113.
by EagnaIonat 6mo ago
You could have found in 5 seconds. The weights are also open sourced as well. https://github.com/ibm-granite
114.
by EagnaIonat 6mo ago
Can you clarify what you mean? If you check HF you will see its Apache2 and the datasets were also permissive. It's one of the few models on the market where the creator indemnifies it against copyright claims. https://resea
115.
by EagnaIonat 6mo ago
> specifically ask it to think hard before doing anything that gets close to the production data, etc. Standard rule is you never let your developers at the production instance. So I can't see why an LLM would get a break.
116.
by EagnaIonat 6mo ago
I tested with Gemma4 and it sent it into an endless loop.
117.
by EagnaIonat 6mo ago
Bit of a straw-man there.
118.
by EagnaIonat 6mo ago
It scales fine if done correctly. Even with the weights the extra context allows it to move to the correct space. Much the same as humans there are terms that are meaningless without knowing the context.
119.
by EagnaIonat 6mo ago
https://www.promptingguide.ai/techniques/knowledge
120.
by EagnaIonat 6mo ago
LLMs don't see words. They see tokens, which is why previously they had a hard time counting the r's. You can certainly prove that mathematically, and giving that proof to an LLM it will give you the correct answer. Which is a pro

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