floatingtorch's comments

On: The death of partying in the USA

[floatingtorch]

Yes, it’s surprised me how this meme was everywhere in the comments while the data does not support it. I’d bet it’s splashy headlines in news outlets. Important to correct it so that policy is focused on what’s most effective.

[iwontberude → floatingtorch]

Blackrock sounds scary

[BobaFloutist → iwontberude]

People absolutely also conflate it with Blackstone and even Blackwater.

[lesuorac → BobaFloutist]

tbh conflating blackrock and blackstone is pretty fair. Their named similarly because it's the same people with just a slightly different business.

On: TikTok divestment law upheld by federal appeals court

[floatingtorch]

Your analysis is low quality as it focuses too narrowly and ignores the wider geopolitical tensions between the US and China.

See:

- CHIPs act

- Ban of sale of many nvidia GPUs to China

- Ban of export of ASML euv tech

- Huawei ban

- Chinese EV tariffs (ban?)

- whole host of tariffs

- China south sea tensions

- Chinese support of Russia who is a threat to NATO allies (and invaded a sovereign country) - Ban of most US tech companies in China

- Chinas mutual aid treaty with North Korea

On: TikTok divestment law upheld by federal appeals court

[floatingtorch]

You can simply use specific training examples that teach the model what you please. Eg. a set of examples which lead ranking/retreival/filtering models. The models are already online training and weights likely updated every ~1 hour ( or even less).

It’d be easy to go from a set of “moderators” who find examples and use it to query related content and use it as negative training samples. Just a guess.