I cannot do this by crossing my eyes (focusing on a point between you and the image), I have a hard time getting the cross to stay consistent and it never really "locks in" for me. Instead of crossing my eyes, I unfocus them, effectively look through the image. Once I get the repeating part to overlap cleanly, after a second or two, my pupils adjust their focus and the image fades from blurry to clear in a really satisfying way and kind of "locks in" in a way that takes little to no effort to maintain. With a bit of practice, I can even move my eyes around and look at different parts of the two overlayed images without distrupting the effect at all.
I don't know if it's just my brain working differently or if a there is some confusion in the discussion between crossing your eyes and focusing through an item.
Follow the same steps for callers whose voice you don't recognize, before giving any financial information or reading any codes, call the person back using a verifiable good number.
There was a scam which targeted landlines, where the scammer would call and then keep the line open while you "hung up" (except you didn't) and you dialled the known number of your bank. The scammer simulates a ringing line, and then answers as your bank.
All I’m saying is that if I were a scammer, I wouldn’t bother tricking someone into saying a specific thing. I’d just use gen AI. I’m definitely not arguing against “call the person back using a verifiable good number.” If everyone did that, we’d hear about a lot less fraud.
> The richest man in the world, who just fired 90% of his employees
This isn't true. Best I can guess you are referencing the company formerly-known-as-twitter. The 90% number refers to software engineers, not employees and only applies to one of several companies that Musk runs.
EDIT: in general, my point is that he practically triggered mass layoffs at large companies by being so vocal about doing it at twitter. A ton of investors were celebrating it after and pushing companies to do the same.
>EDIT: in general, my point is that he practically triggered mass layoffs at large companies by being so vocal about doing it at twitter. A ton of investors were celebrating it after and pushing companies to do the same.
His acquisition was in October 2022. Job postings started dropping off in May 2022. It was already leveling off as early as February 2022. You'd have to squint really hard to believe this was caused by musk, or that he played a major factor.
> in general, my point is that he practically triggered mass layoffs at large companies by being so vocal about doing at twitter. A ton of investors were celebrating it after and pushing companies to do the same.
That's an interesting claim, and one I'd be curious to see a more detailed argument for. I'm sure it had an impact, but arguing it had a larger impact than the prevailing market conditions seems hard. The massive overhiring in the year or two before seems like the obvious culprits for the majority of the mass layoffs.
I see a lot of hyperbolic and flat out false things said about Musk. I push back on them because I think that people's habitual innaccuracy when he is involved tends to make the real criticism of him harder.
There are currently two references to “Mangion-ing” OpenAI board members in this thread, several more from Reddit, based on the falsehoods being perpetrated by the author. Is this really someone you want to conspire with? Is calling this out more egregious than the witch hunt being organized here?
"conspire" and "witch hunt", are not terms of productive discourse.
If you are legitimately trying to correct misinformation, your attitude, tone and language are counter productive. You would be much better seved by taking that energy and crafting an actually persuasive argument. You come across as unreasonable and unwilling to listen, not someone with a good grasp of the technical specifics.
I don't have a horse in the race. I'm fairly technical, but I did not find your arguments persuasive. This doesn't mean they are wrong, but it does mean that you didn't do a good job of explaining them.
This story predates that period by well over a decade. Even if the company you worked for isn't one of the ones named towards the end of the article, it is very likely that the company you worked for was in some way connected with people from either or both of Benter's or Woods' operations.
I doubt there is a strong link between the founders of my old employer and Benter or Woods. My old employer did totally different kind of betting. No blackjack or horses.
In general people overestimate how hard it is to make money in gambling. You don't need to be some kind of savant to do it. The people in general are similar to what you would find in your average tech company. Sure there is a founder with a vision and some sort of an insight into making money, but every company has one.
Could you share the name of your former employer, or if you can't, could you share the name of similar employers?
I'm on a bit of a probability (gambling, sports betting, stats, etc) kick these days, and I'd be interested in reading more about people and companies doing this in practice. I'd been imagining there must be organised sports gamblers, but they don't seem to be overly searchable.
I don’t know exactly how these companies make their money and how successful they are, but I at least believe all of them are in the odds computation business. They might be supplying prices to bookmakers instead of betting themselves etc.
Longshot Systems
Football Radar
Gambit Research
SportsRadar
Odds Reactor
Star Lizard
Smartodds
Smarkets
These companies are known more for their HFT trading in financial markets, but I believe they have also expanded into sports betting.
jane street
jump trading
Susquehanna
Also some of the bookmakers such as matchbook have started as betting group and then overtime turned into a bookmaker as that is where the real money is.
Oh wow, it's happening there! I've followed and starred and bookmarked and all that, and will be having a browse around a bit more closely when I get a moment. I think I'm roughly understanding what the group is about. I'll follow up, thanks!
Yeah; I briefly did some consulting work at a sports betting company. They have a database of hundreds of people who are essentially banned because they’re too good at picking winners, and the betting company loses money having them as clients.
Internally they track how much each account wins & loses. If you win too much, the site gives you worse and worse odds until eventually you’re banned entirely. The reverse is also true: if you’re a terrible better, the site gives you better odds hoping to keep you coming back for more.
They have a whole team whose job it is to instantly block smart betters from opening new accounts. Accounts opened in the name of their girlfriends is the classic thing they watch out for.
Some of the smartest gamblers also get hired as quants, and help figure out what the odds should be on the site.
In Europe bookies just get rid of good players, except for the exchanges and Pinnacle. No one serious will gamble with European bookmakers. Though maybe this has changed lately. I have not been following field recently.
In Asia the bookies are a lot more tolerant, especially the larger ones. You really have to hit their pnl hard for you to get cut off.
So the only possible way for him to be disqualified is if he hung around for the rest of the tournament repeating the same thing over and over again? Sounds like newspeak logic.
The people who already know that a "conditional request" means a request with an If-Modified-After header aren't the ones who need to learn this information.
It is fairly well documented that groups of people can show cognitive abilities that exceed that of any individual member. The classic example of this is if you ask a group of people to estimate the number of jellybeans in a jar, you can get a more accurate result than if you test to find the person with the highest accuracy and use their guess.
This isn't to say groups always outperform their members on all tasks, just that it isn't unusual to see a result like that.
Yes, my shortcoming was in understanding the 10 were implied to have their successes merged together by being a panel rather than just the average of a special selection.
Political content of all kinds often gets flagged on HN as lots of people don't like it and flagging is the easiest way to express that disapproval and impact front page placement.
Yes, flagging is a way for some people to express disapproval of what THEY don't like. A major organization makes a big statement about a major conflict. This is of general interest and would normally make front page headlines, even on HN.
I don't know if it's just my brain working differently or if a there is some confusion in the discussion between crossing your eyes and focusing through an item.
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