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Comment Re:Foolish (Score 1) 121

Exactly, your car will outlast your phone. Which is why you want all of that software on the phone instead of the car- so it continues to be updates in software and hardware, can easily be replaced with something better, and is an open platform that allows you to choose your software providers. Hell, worst case you can mount the phone on your dash and use it. Anything in car you're stuck with permanently. Not to mention who knows how long it will be around- my car is 20 years old. There is 0 chance any car company will support it that long- if anything they'd consider bricking it after 5 years a benefit as it could force you to get a new car.

Comment Re:Re Cursive needs to die (Score 0) 111

Umm, even without computers you can print. Which is what most people do when they write. I've read plenty of hand written notes, blackborad/whiteboard messages, etc in my life. Nobody has ever used cursive to write them. Even adults who took cursive, like me, usually don't remember how to do more than write their name. And the time savings cursive was supposed to give you, when actually studied, ended up being a myth. Not to mention print is more readable, you can almost never read anyone else's cursive.

So yeah, even without machines we'd get along just fine without cursive. It literally has no value except reading historical documents.

Comment Re: Yawn (Score 1) 178

Do you think the average person knows what a wallet is? Or has the technical ability to use one? Or has the technical knowledge to secure and back it up effectively, and the computer on which it resides? Especially given that a major crypto developer just proved he couldn't as he lost over 3 million USD to a compromised PC? Banks exist for a reason- to safeguard and protect money. The same reasons you don't hide your dollars in your mattress are the reasons why people would use an exchange.

Comment Re:Beware of falling packages! (Score 4, Informative) 40

That's not true at all. The fracture threshold of a human skull is 14-70 joules (source: https://www.walshmedicalmedia....). A 2 kg (5 pound) package would have energy of .5*m*v^2. It will reach that threshold at 3-8 m/s. Which if being accelerated by gravity at 9.8m/s^2, it will reach pretty quickly. And of course its worse if you get hit by a corner, concentrating the area of impact. So yes, its totally possible for a 5 pound weight dropped from 1-2 stories up to fracture your skull. And a fracture isn't the only possible injury- laceration and concussion can happen at much lower thresholds.

Comment Re:Well at least someone gets it (Score 1) 276

Bitcoin has fees on every transaction. And no government isn't a good thing. The ability to roll back transactions in the case of fraud, theft, etc at a minimum is a good thing. As for a lot faster- it can take hours for a Bitcoin transaction to settle. How long it takes depends on how much you pay in fees. Cash, credit cards, etc are far faster. Bitcoin loses on all those fronts, as do all other cryptocurrencies.

Comment Re:Them grapes (Score 2, Informative) 208

Nobody argues for the fucking purity of a headphone jack. We like headphone jacks because we prefer wired and because it's a second connector. And mildly because we already have headphones, but if they got rid of them and replaced them with a second USB connector we'd all be ok with that. It's about not liking wireless (easy to misplace, need to be charged, not liking in ear buds, easy to lose when they fall out out your ear) but not wanting the sole port on the phone to be dedicated to it.

Comment Re:The stimulus checks paid rent and bought food (Score 1) 113

Charging infrastructure is the problem. People who buy that kind of car tend to live in an apartment or have roommates (or both). They mostly don't have a dedicated place to park and charge their cars. That makes them unusable. Especially with a 150 mile range, they may need to be charged every night.

AI

New Go-Playing Trick Defeats World-Class Go AI, But Loses To Human Amateurs (arstechnica.com) 95

An anonymous reader quotes a report from Ars Technica: In the world of deep-learning AI, the ancient board game Go looms large. Until 2016, the best human Go player could still defeat the strongest Go-playing AI. That changed with DeepMind's AlphaGo, which used deep-learning neural networks to teach itself the game at a level humans cannot match. More recently, KataGo has become popular as an open source Go-playing AI that can beat top-ranking human Go players. Last week, a group of AI researchers published a paper outlining a method to defeat KataGo by using adversarial techniques that take advantage of KataGo's blind spots. By playing unexpected moves outside of KataGo's training set, a much weaker adversarial Go-playing program (that amateur humans can defeat) can trick KataGo into losing.

KataGo's world-class AI learned Go by playing millions of games against itself. But that still isn't enough experience to cover every possible scenario, which leaves room for vulnerabilities from unexpected behavior. "KataGo generalizes well to many novel strategies, but it does get weaker the further away it gets from the games it saw during training," says [one of the paper's co-authors, Adam Gleave, a Ph.D. candidate at UC Berkeley]. "Our adversary has discovered one such 'off-distribution' strategy that KataGo is particularly vulnerable to, but there are likely many others." Gleave explains that, during a Go match, the adversarial policy works by first staking claim to a small corner of the board. He provided a link to an example in which the adversary, controlling the black stones, plays largely in the top-right of the board. The adversary allows KataGo (playing white) to lay claim to the rest of the board, while the adversary plays a few easy-to-capture stones in that territory. "This tricks KataGo into thinking it's already won," Gleave says, "since its territory (bottom-left) is much larger than the adversary's. But the bottom-left territory doesn't actually contribute to its score (only the white stones it has played) because of the presence of black stones there, meaning it's not fully secured."

As a result of its overconfidence in a win -- assuming it will win if the game ends and the points are tallied -- KataGo plays a pass move, allowing the adversary to intentionally pass as well, ending the game. (Two consecutive passes end the game in Go.) After that, a point tally begins. As the paper explains, "The adversary gets points for its corner territory (devoid of victim stones) whereas the victim [KataGo] does not receive points for its unsecured territory because of the presence of the adversary's stones." Despite this clever trickery, the adversarial policy alone is not that great at Go. In fact, human amateurs can defeat it relatively easily. Instead, the adversary's sole purpose is to attack an unanticipated vulnerability of KataGo. A similar scenario could be the case in almost any deep-learning AI system, which gives this work much broader implications.
"The research shows that AI systems that seem to perform at a human level are often doing so in a very alien way, and so can fail in ways that are surprising to humans," explains Gleave. "This result is entertaining in Go, but similar failures in safety-critical systems could be dangerous."

Comment Re:Pointless (Score 1) 57

This law wouldn't have helped her. I advertise a job with a range of 50-60K. There's nothing preventing me from finally offering someone more than that, just less. Nor should there be anything preventing me from offering more- if I'm in actual negotiations for a great fit with another offer, I should be able to reassess what I'm willing to pay.

So they offer her let's even say the max- 60K. The next guy who comes in can still negotiate for more- even much more. You still need to learn to negotiate.

(Rule #1 of negotiation- anyone who says an offer is non negotiable is lying. I've lost track of how many non negotiable offers I've negotiated).

Comment Re: Pointless (Score 3, Insightful) 57

People are also misinterpreting who this is meant for. This isn't meant to help programmers making 200K in salary and another 100K+ in stock. At that level there's too many variables and perks to do an easy comparison, and truthfully they need less help negotiating. It's meant to help the people making $15 or $20 an hour, to know whether a job is worth their time applying to and prevent bait and switches. So comparing jobs making 3 that isn't exactly germane.

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