Then you do forensic and catch the predator instead of the age verification nonsense

What's your opinion of glm5 if you had a chance to use it

I haven’t yet, though I will be this weekend!

Yeah gemini 3.0 is unusable to me, to an extent all models do things right or wrong, but gemini just refuses to elaborate.

Sometime you can save so much time asking claude codex and glm "hey what you think of this problem" and have a sense wether they would implement it right or not.

Gemini never stops instead goes and fixes whatever you trow at it even if asked not to, you are constantly rolling the dice but with gemini each roll is 5 to 10 minutes long and pollutes the work area.

It's the model I most rarely use even if, having a large google photo tier, I get it for basically free between antigravity, gemini-cli and jules

For all its fault anthropic discovered pretty early with claude 2 that intelligence and benchmark don't matter if the user can't steer the thing.

Too bad will stick with codex as thinker and glm5 as hands, at a fraction of the cost.

Unfair reading bordering with propaganda.

On one hand Boston Dynamics showed similar skill robot well before this demo, only without coreography, which is were most of the wow effect comes from here.

https://m.youtube.com/watch?v=UNorxwlZlFk

Heck check were they were 5 years ago

https://m.youtube.com/watch?v=fn3KWM1kuAw&pp=0gcJCUABo7VqN5t...

Things is american research is financed by outcome potential not for grandstanding, and free standing robot that can only do recorded coreography aren't that useful outside factory floors, and factory floors can use ceiling rails or wheels to better effect.

So yeah video is suler cool, but there isn't much to it beyond that to read in terms of capabilities. You seem just to be projecting what the truth you want to be on top of a funny dance.

China installed 295,000 industrial robots last year, more than the rest of the world combined, and has over 2M deployed total. China makes its own robots (57% indigenous) and its rate of robot deployment continues to grow year to year.

Meanwhile, the US installed 34,200, a decrease on the previous year, and virtually all of those were imported.

https://ifr.org/ifr-press-releases/news/global-robot-demand-...

Do these dance?

And what was the % of industrial capacity non automated over this percentage increase, because of course an industrializing country will have more manual processes to automate.

You asserted that American research is "financed by outcome potential not for grandstanding". But China is not just building dancing robots, they're also installing tons of industrial robots whose sole purpose is making money right now.

What is the automation gap tho

american research is financed by outcome potential not for grandstanding

Ah yes that explains Tesla...

I use small model I like to give them TOC more than lines wonder how it'd stack up with the hashline approach

read_toc tool:

...

  {

    "name": "mcp",

    "qualified_name": "mcp",

    "type": "constant",

    "docstring": null,

    "content_point": "src\\mcps\\code_help\\server.py::17::18::python::mcp",

    "is_nested": false

  },

  {

    "name": "handler",

    "qualified_name": "handler",

    "type": "constant",

    "docstring": null,

    "content_point": "src\\mcps\\code_help\\server.py::18::19::python::handler",

    "is_nested": false

  },

....

update_content tool:

{

  "content": "...",

  "content_point": "src\\mcps\\code_help\\server.py::18::19::python::handler",

  "project_root": ....

}

> This is a critical narrative shift.

also this, having done a number of ai conspiracy for funsies, that's always the mid point

however I don't mind ai slop, if it's creative and well thought out (and editorialized, as this seem to be)

Worse still I created a mcp with refactoring tools and symbol based editing but because it's a) of of distribution for llm b) agent get their own heavy handed system prompts all the goodies get ignored

nice writeup, terrible website garbling the page history

I wonder how it compare with geohashing, I know it is not as efficient in term of partitioning and query end up weird since you need to manage decoding neighbor cells but finding all element of a cell is a "starts with" query which allow to put data effectively on most nosql databases with some sort of text sorting

"finish Claude tokens quota in 3 minutes, largely over delegation and result messages instead of code writing"