riotnrrd

I just had my hole inspected and all the preparation was with over-the-counter supplies. My prep drink was gatorade with some flavorless powder mixed in. It made no change in the taste or texture of this drink. Having the squirts for a day was no fun, but other than that it was a breeze.

This was done in 2012: https://en.wikipedia.org/wiki/STOCK_Act

It's a tech demo.

When you post on a public forum defending child pornography, it's maybe a good time to take a step back and evaluate your life.

What are saying? Spell it out for us.

We'll worry about that when the Presidency and both houses of Congress are controlled by the Communist Party

If you're not afraid of DIY and it looking (much) uglier than these lamps, you can buy extremely bright "cob lights" and make something yourself: https://meaningness.com/sad-light-lumens

It takes an act of Congress to change the name. Trump just made one of his dictatorial proclamations.

That's a pretty well-solved problem at this point, if you want to do it yourself. You'll want some kind of NeRF tool and a way to calculate the camera poses of the photos you took. COLMAP is the tool most people use for the latter.

I'd recommend trying Instant Neural Graphics Primitives (https://github.com/NVlabs/instant-ngp) from NVIDIA. It's a couple years old, so not state-of-the-art, but it runs on just about anything and is extremely fast.

NVIDIA has been selling automotive-specific silicon for a decade.

We experimented with a rig with more cameras on it (four, in a square) but the baseline of the cameras on the drones we were using could be measured in centimeters, so the vertical stereo pairs didn't provide much better results. Further, more cameras means more power, more weight, and much more expensive on-board processing (which also will require more power).

All cables? Everywhere in the entire country? Accurate to the centimeter level and updated on the hour?

Edit: This was flippant, but the real issues are: any map you get will be incomplete and obsolete almost immediately and cables move and sway in the breeze.

Statistics are not theft. Judges have written over and over again that training a neural network (which is just fitting a high-dimensional function to a dataset) is transformative and therefore fair use. Putting it another way, me summarizing a MLB baseball game by saying the Cubs lost 7-0 does not infringe on MLB's ownership of the copyright of the filmed game.

People claiming that backpropagation "steals" your material don't understand math or copyright.

You can hate generative tools all you want -- opinions are free -- but you're fundamentally wrong about the legality or morality at play.

I used to work in perception for autonomous aerial vehicles and horizontal wires were the hardest common object to avoid. Traditional stereo won't help you localize them -- wires are thin so even mere detection can be hard, and one portion of a wire looks much like another so feature matching fails resulting in bad or no depth estimates -- and LIDAR sacrifices resolution for weight and power consumption (which both have to be optimizied for drones). It's been years since I've worked in this field, and Amazon has many smart people thinking about it but I'm not surprised it's still a difficult problem.

> My naive understanding is that by having skins be worth tangible and significant value; this was the primary motivator for players to purchase keys to unbox cases, which was the dominant direct revenue generator for CS.

Yes. The Valve philosophy on the cosmetics marketplace (we called it "the economy") is that you distribute random rewards to players and they can trade and sell and discover the value of those goods for themselves. Obviously, this was done to make money for Valve but, in theory, it's also good for the players. It allows people who have things they don't want to sell them to people who want them. And all this buying and selling happens between Steam wallets (and there is no off-ramp) so at the end of the day, it's all just profit for Valve.

But above all we wanted people to play CS:GO because it was a fun game. We didn't want to turn it into some kind of grim pachinko parlor, with players grinding out matches just to get random loot box drops. So you have to balance the potentially real dollar random rewards so that they're a fun surprise but not economically attractive enough to become a job.

I used to work at Valve -- on the CS:GO team, no less -- although I left nearly a decade ago. I don't know what prompted this change but I have some suspicions. Even when I was there and the loot box system was new to CS:GO, there were concerns that a lot of trading was happening outside of the marketplace. The trading happened elsewhere because you can't have more than $300 in your Steam wallet (more than this would trigger some banking regulations that Valve wanted to avoid), so anything more valuable than that had to happen on 3rd party sites.

We didn't want this for three reasons: we'd lose out on the marketplace cut (10% of all sales I think?); we didn't want people grinding the game to earn money from rare drops; and finally because 3rd party trading ended up creating a lot of scams and therefore angry players.

At the time, we didn't see any way around it: we couldn't prevent people "gifting" items to each other, and despite omniscience and omnipotence in the game and Marketplace, we weren't confident that we could rejigger the drop rates and rarities to lower the maximum perceived value of the fanciest knife to be under the $300 limit.

I suspect that the CS:GO team finally decided to do something about it and chose this. If the team is anything like I left it, they probably modeled this extensively (we had data on nearly every game ever played in CS:GO and complete Marketplace data), and discussed the change with the TF2 and DOTA teams, who also have to deal with this, and decided that the short-term fury of a small fraction of the playerbase was worth it. I wonder if TF2 and DOTA are having similar problems and, if so, whether this change will be rolled out for those games, too.

I would say the Federal Government is different from a private company.

One of the difficulties -- and one that is currently a big problem in LLM research -- is that comparisons with or evaluations of commercial models are very expensive. I co-wrote a paper recently and we spent more than $10,000 on various SOTA commercial models in order to evaluate our research. We could easily (an cheaply) show that we were much better than open-weight models, but we knew that reviewers would ding us if we didn't compare to "the best."

Even aside from the expense (which penalizes universities and smaller labs), I feel it's a bad idea to require academic research to compare itself to opaque commercial offerings. We have very little detail on what's really happening when OpenAI for example does inference. And their technology stack and model can change at any time, and users won't know unless they carefully re-benchmark ($$$) every time you use the model. I feel that academic journals should discourage comparisons to commercial models, unless we have very precise information about the architecture, engineering stack, and training data they use.

> Specifically, the new paper finds that the mud is between 20,700 and 22,400 years old

If these results are as strong as they claim, this absolutely nukes the Clovis-first hypothesis.

I worked with Nick back in the ILM R&D group. He's an incredibly kind man and one of the best developers I've ever met; truly a genius.

In your rush to condemn it, did you actually read the linked article? Let me quote:

"These tests [...] were “supposedly applicable to both white and black prospective voters who couldn’t prove a certain level of education” (typically up to the fifth grade). Yet they were “in actuality disproportionately administered to black voters.”

Additionally, many of the tests were rigged so that registrars could give potential voters an easy or a difficult version, and could score them differently as well. For example, the Veterans of the Civil Rights Movement describes a test administered in Alabama that is so entirely subjective that it measures the registrar’s shrewdness and cunning more than anything else."

> I've never been involved in films, but from my own experience, the answer is a strong 'yes'

I worked in film visual effects for a decade and the answer is a strong 'no.'

In my case, we were in it for the enjoyment of the work and the craft. We didn't write the scripts, and the quality of the film wasn't our job. We were hired to make the best effects we could and if we delivered quality, we were happy. I'm sure a similar attitude works in other aspects of film (or any large collective enterprise, really).

Data augmentation in CPU-space is often compute-light, but requires rapid access to memory. There are libraries (like NVIDIA's Dali) that can do augmentation on the GPU, but this takes up GPU resources that could be used by training. Having a multi-core CPU with fast caches is a good compromise.

Having worked in film in the US, I developed a deep hatred of film tax breaks because they work. "Work" in the sense that studios will chase them, and they make it harder for companies outside a tax-advantaged location to compete and make money.

The effects of relativity cause that thought experiment to fall apart quickly. I build two clocks, and send one to alpha centauri and back in a spaceship. When the travelling clock gets back to Earth it will be showing a different time (because of time dilation during acceleration). What does "the same clock reading" mean then?

I used to work in film, although not in the accountancy/deal-making aspect. Film tax breaks are direct discounts on money spent. If you make a film in Georgia, for example, you get a transferable tax credit (20-30%) on money spent in the state. It's a short term deal (productions usually only last a few months), and is immediate in effect. There's no "spend a billion of public money and maybe we'll hire some people" shenanigans like the Foxconn plant in Wisconsin.

> i mean does the pay stub simply not reflect all the hours they worked?

That's very common, yes. Bosses simply lie about the hours worked or force employees to work undocumented hours.

> are they talking about overtime?

Overtime is a frequent target of wage theft because it costs the employer more per hour.

> is this for part time work or full time?

Yes for both.

> for full time, it should just be 40 hours, how does the employer not pay out the full 40 hours?

Sure. Who's gonna stop 'em? Wage theft claims are difficult to document, expensive to litigate, and usually the people being robbed are the more powerless workers: young people, recent immigrants who face a language and culture barrier, and people simply ignorant of the their rights under the law.

Similar questions netted me about $7000 from the Google age discrimination class-action lawsuit.

Not really. If you include the costs of marketing and distribution, a film needs to gross about twice its "budget" to break even. Furthermore, this rule of thumb only applies to US gross, where studios get much more of the actual ticket price (75% iirc) than overseas. In some markets, India for example, American studios get about 15% of the actual ticket-price gross.

What brand and model did you buy? I've been looking for something like this for my family.