A large portion of the ML community (rightly) discredits Google papers because:

- they rarely provide the data or code used so it's basically "i swear it works bro" research

- what they achieve is usually through having the most pristine dataset on the planet and is often unusable by other researchers

- other times they publish papers that are basically "we slightly modified this excellent open source paper, slapped an internal name on it and trained it on our proprietary dataset"

- sometimes they achieve remarkably little but their papers still get a shiny spot because they're a big name and sponsor all the conferences

- they've also been caught trying to patent/copyright ML techniques; disregarding that this is the same as privatizing math, these are often techniques they plainly didn't come up with

Also ever since OpenAI did their "we have to go closed-source for-profit to save humanity" PR campaign, every company that releases models that can achieve a large amount in NLP/CV gets dragged by the media and equated to Skynet.

A ton of big advances in AI that community has benefitted from have been from published google research

Notably, the transformer architecture, the basis of the last few years of ML breakthroughs, came out of Google.

IMO the biggest algorithmic advances made by Google such as the transformer have greatly pushed the field forward. The giant model's that will have similar variations released in the next 3 months actually aren't that important on a conceptual level except as a PoC.

While the transformer model is important that was 1 paper in an ocean they put out every year.

Also it’s one of the only papers they put out that falls completely outside what I put above. They released everything about it including the model code, pretrained weights, the techniques; and it took quite a while for the model to “catch on” while it was peer reviewed and reproduced by others.

Something something broken clock

The full author list is on the updated link at: https://dreamfusion3d.github.io/

This is par for the course - there have been other instances where an 'anonymous' paper mentioned training on a cluster of TPUs that weren't publicly available yet - dead giveaway it was Google.

Dead giveaway... Dead giveaway...

> Paper under double-blind review

Once the paper is accepted (or rejected) the names may be revealed.

Though, in reality, the reviewers can often easily tell who wrote the paper.

Lots of reasons to stay anonymous besides for hiding what org is behind the paper. Maybe they don't want to be kidnapped by the North Koreans and forced to produce new paens with "lost footage" to Kim Il-Sung.