let's not forget that these major LLMs are all the children of corporate hyper-piracy en masse, none of them are ethical even in origin unless you're talking about the pre-product company charter kind of ethics, like google .
Last I heard, claude was the model powering maven when it bombed that school. Most aren't up-to date on that because anthropic launders their culpability through palanntir. Anthropic is better at optics not ethics.
No matter what you say, you know yourself the truth that the DoW wanted to go over the red lines of anthropic and they said no, while openai said yes. This is as clear as day to everyone and you are just lying yourself to believe something else.
You use the term piracy, which potentially hints at ur biases.
American IP laws aren’t universal, and last I checked neither is it popular in Silicon Valley.
Institutions surrounding dealing with IP Piracy is an American strong arm attempt to own the unownable and to use Russel conjugates to make the flagrant attempt seem just.
Anthropic is _unquestionably_ ahead product wise because of their agentic coding tools, but they are not _years_ ahead. In particular, their advantage is in the harness, which is not hard to replicate!
Lol if CC is the advantage that's the larges indictment of AI coding there is. Don't get me wrong CC gives me good results, but I very much doubt their tooling is great, they just spew tokens at the model and the model is quite good at making sense of it and following through.
I suspect they have better RL setup for coding that makes their models better at coding than GPT/Gemini in practice.
They’re about even in general, but for me OpenAI is slightly or significantly ahead in the areas I care about the most. E.g. claude code is a backend slop cannon if you don’t tell codex/gemini to review the outputs.
Give it a year or two, and apple or any other hardware will have unified memory OR AMD will have a good offering to run all that stuff locally. It won't be as good as Claude, but it'll do for 90% of the things. It will be expensive as first, just like the first mainframes, then give it another 5 years or so, and it'll be affordable.
People that do light office work tend to have light office machines, which are very unlikely to have powerful NPUs or even a lot of RAM. Therefore with this minimal setup is it even feasible to do any sort of LLM based work locally on those machines, or will they all be dumb terminals connecting to hosted LLMs of the big companies?
This is also what I wonder, what practical applications can you actually do locally on something like a minimum spec NPU?
My company is now removing all microsoft products, all of it.
Laptops are moving to OSX.
Office365->Gmail+G-suite.
Zoom->Google meet.
Fortunately we don't use Azure or Github, so that will make the transition easier.
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