AI summary:

Temu Just Got Destroyed By The US Government - Here’s The Full Story

The video discusses significant changes to US import rules affecting the e-commerce platform Temu, which has benefitted from the de minimis exemption allowing cheap imports. Recent regulatory updates are likely to increase prices on Temu, challenging its business model and impacting its competitive edge against US sellers. The presenter outlines how Temu has dominated the e-commerce space and the potential fallout from the new regulations.

Key Points:

Temu’s Dominance in E-commerce Temu has thrived in the US e-commerce market with significant backing from PDD Holdings, which has invested heavily to acquire market share despite their substantial losses. The platform has utilized low labor costs in China and the de minimis threshold of $800 to avoid tariffs, allowing them to offer lower prices than US competitors.

Impact of New Import Rules Changes to the de minimis rules introduced by the Biden Administration will require that many products previously exempt from tariffs now be subject to duties, undermining Temu’s pricing model. Sellers must also provide additional information, which could deter consumers and complicate shipping.

Increased Scrutiny and Compliance. New regulations mandate that all low-value shipments under the de minimis exemption meet US safety standards, requiring certificates of compliance. This change targets the influx of unsafe products, particularly children’s items, that Temu and similar platforms have been selling.

Sellers’ Discontent There is a growing dissatisfaction among Temu sellers who face pressure to reduce prices and have recently protested against unfair practices, adding strain to Temu’s business model as conditions become untenable for them.

Future Prospects for Temu With the decline of PDD Holdings’ financial stability and the introduction of strict regulatory measures, Temu’s future profitability is uncertain. The platform may struggle to maintain its competitive pricing, while US sellers are likely to benefit from this shift.

what a shining example of unbiased and impartial reporting 🙄

This is one of my favourites 😄

Another occupation ruined by millennials

Caaaaaaaaaat.

Thanks for posting, please ignore the stochastic luddites 🙂

One must imagine Sisyphus strapping

Switchcraft!

Espera, ¿todo es Ohio?

…can’t argue with that

Thanks, that was interesting. I kept thinking that this reads like something out of Quanta Magazine, and then at the end there was an attribution to them :)

To all the reflexive AI-downvoters: This is about an application of machine learning, not an LLM. Don’t behave like an advanced autocomplete; think before you click :P

Thanks for posting, don’t mind the downvotes from the luddites :D

Well, natural language processing is placed in the trough of disillusionment and projected to stay there for years. ChatGPT was released in November 2022…

Arrows

Pointless

Pick one

If you’re logged in to lemmy.world, I think you can click the hamburger menu top right and then “Create community”?

Edit: sorry, just noticed your account is on programming.dev, where there’s no such option? Then I’m afraid I don’t know :/

Edit 2: From the programming.dev sidebar:

Community Creation

Communities in our instance are created from our community request zone. If you have an idea for a community that fits our instance that hasnt been made already feel free to create a post for it there. Communities will be considered for creation if theres enough interest in the idea shown by people upvoting it

Definitely possible, but we’ll have to wait for some sort of replication (or lack of) to see, I guess.

True, but as far as I can tell the AUROC measure they refer to incorporates both.

What they’re saying, as far as I can tell, is that after training the model on 85% of the dataset, the model predicted whether a participant had an ASD diagnosis (as a binary choice) 100% correctly for the remaining 15%. I don’t think this is unheard of, but I’ll agree that a replication would be nice to eliminate systemic errors. If the images from the ASD and TD sets were taken with different cameras, for instance, that could introduce an invisible difference in the datasets that an AI could converge on. I would expect them to control for stuff like that, though.

From TFA:

For ASD screening on the test set of images, the AI could pick out the children with an ASD diagnosis with a mean area under the receiver operating characteristic (AUROC) curve of 1.00. AUROC ranges in value from 0 to 1. A model whose predictions are 100% wrong has an AUROC of 0.0; one whose predictions are 100% correct has an AUROC of 1.0, indicating that the AI’s predictions in the current study were 100% correct. There was no notable decrease in the mean AUROC, even when 95% of the least important areas of the image – those not including the optic disc – were removed.

They at least define how they get the 100% value, but I’m not an AIologist so I can’t tell if it is reasonable.

Column A: yes

Column B: also yes