niklassheth

I'm happy to answer any questions :)

And on secondary markets shares are trading for at least twice that...

So many problems with this:

The benchmark is totally useless. It measures single prompts, and only compares output tokens with no regard for accuracy. I could obliterate this benchmark with the prompt "Always answer with one word"

This line: "If a user corrects a factual claim: accept it as ground truth for the entire session. Never re-assert the original claim." You're totally destroying any chance of getting pushback, any mistake you make in the prompt would be catastrophic.

"Never invent file paths, function names, or API signatures." Might as well add "do not hallucinate".

Nice! Your comparison site is probably the best one out there for image models

I put the output from this tool into GPT-5-thinking. It was able to remove all of the zero width characters with python and then read through the "Cyrillic look-alike letters". Nice try!

This is more evidence that Cognition's SWE-1.5 is a GLM-4.6 finetune

It seems like the repo is mostly if not entirely LLM generated; not a great sign.

I know some consumer cards have artificially limited FP64, but the AI focused datacenter cards have physically fewer FP64 units. Recently, the GB300 removed almost all of them, to the point that a GB300 actually has less FP64 TFLOPS than a 9 year old P100. FP32 is the highest precision used during training so it makes sense.

I've found the same, but I also haven't gained much value out of "deep research" products as a whole. When I last tested them with topics I'm familiar with, I found the quality of research to be poor. These tools seem to spend their time searching for as much content as possible, then they dump it all into a report. I get better outcomes by extensively searching for a handful of top quality sources. Most of the time your question (or at least some subquestions) has already been answered by an expert, and you're better off using their work than sloppily recreating it.

The majority of phones in the US are iPhones, especially in big cities where phone theft is most common.

I've also found it to be good at digging deep on things I'm curious about, but don't care enough to spend a lot of time on. As an example, I wanted to know how much sugar by weight is in a coffee syrup so I could make my own dupe. My searches were drowned out by marketing material, but ChatGPT found a datasheet with the info I wanted. I would've eventually found it too, but that's too much effort for an unimportant task.

However, the non-thinking search is total garbage. It searches once, and then gives up or hallucinates if the results don't work out. I asked it the same question, and it says that the information isn't publicly available.