>If Rivian’s native UI is so great, then their customers… won’t use CarPlay. It’s that simple.
I kind of disagree with this. Airpods are purely additive, customers can just choose to use different headphones with their iPhone if they want. But they don't want, because Apple lets Airpods interact with the iPhone in a way that other manufacturers can't.
So no, carplay wouldn't be mandatory but it's likely that Apple's leverage will kill their in house offering.
To be honest I don't think what the models themselves say in relation to these specific questions matter. Because I don't think it reflects are durable underlying worldview. I suspect that the way you frame things is going to influence them so muc that it's irrelevant what they would say when put in a petri dish.
What is a lot more important is how they're develop. To take the two sides of the spectrum - they say has a slightly expansive attitude towards civil liberties, but if you try to use it's tool it will phone it's owners and ask permission for you to use it. Or you can pick up Grok one day and find out that Elon Musk had a bad weekend and Grok is back to being mecha hitler.
Google acquired his company in 2024 for $2.7Bn with him taking about 40% of that. I'm quite sure that no matter where he went, any lab or his own start up, he would be fine financially.
I totally understand the concern that forcing a digital proof of age turns into you having to go to some 3rd party who won't actually just provide a "Yes, this person is 18" style verification but instead will turn into user tracking and ad networking etc. But is that actually required by the bill?
Because what I'm getting at is Apple is already privacy focused. It would be entirely plausible to me that we end up in a situation where Apple's implementation of this is absolutely just "Yup, here's the token that proves I know this is an adult" and if doing that screws Meta's plans for advert-nirvana, I would expect them to take that route.
With the porn ban in the UK we have this worst of both worlds at the moment. We have forced ID verification by these creepy third parties, but it's so fragmented and localized that no big player like Apple is stepping in to provide anything more consumer friendly.
I feel like a lot of this advice is kind of dangerous. How do I draft a tight investor memo? I'll ask the slop machine!
It's kind of analogous to how I'm writing code right now. For simple stuff or low priority stuff I'll fire claude at it and won't look at the code if it works. But for the important stuff I'm very carefully integrated into the cycle making sure what's coming out at the end is just right. I'm carefully constructing prompt loops and validation cycles to make sure what comes out looks like what I want - because I have the knowledge and experience of what works for my specific use case. Drafting an investor memo seems like the second category of thing, you need it to be right. I don't think claude offers much of value there. What's more - if you start slopping your investors, you are going to piss them off. Unless Claude is going to say it has some special data source it's used to train on so it knows good from bad, I think this is a bad idea.
This article also kind of fits in the category of "Here's how to use AI for EVERYTHING!" and actually it would be far more valuable to say "This is the bits that AI is good at, and here's where you need to do it yourself" - which is obviously a position that Anthropic can't hold.
Just to be clear, this is the same reason that social media companies don't tell you about how they detect spam and they create shadow bans and things like this so that people don't know they've been detected and figure out the mechanims.
And it doesn't work. Even a bit. It's a constant constant cat and mouse game. Maybe they can slow people down slightly, but they won't be able to stop them, and good luck protecting yourself from Elon Musk snooping your stuff in his data centre.
What are you even classifying as accurate or correct? Do you take every 51% prediction from FiveThirtyEight and if the result is a win you consider that forecast accurate? And every 49% prediction must result in a loss? This just not how statistical forecasts work.
>What it would be reasonable to say is if his model had correctly predicted the outcome of a significant sample of elections, then you could say his model has some accuracy or predictive power.
I don't know why you're couching that in a hypothetical, FiveThirtyEight has repeatedly done that exercise.
>But it still would never have been accurate or right in the specific instances it got wrong
It is core to the concept of a probability that the result is going to go the opposite way from the prediction sometimes! It's meaningless to call it "wrong".
To give you a trivial example: The simplest way I can put this is that turn out varies based on the weather[1], and turn out is skewed by party. So if it rains on election day you are going to get a different result, and that result can flip the outcome of the election if the election is close. So it’s kind of a nonsense to say. “Trump would have won 100 times out of 100”. Are you saying Nate Silvers model should have had a perfect meteorological model to predict the weather? Or are you saying the election wasn’t close? In which case you’re just wrong on the facts.
The 70% figure is saying “we know most of the information needed to determine what the outcome of the election will be but we don’t know everything so can’t be certain”. There is no process where you can know every factor that determines the result in advance with absolutely accuracy and I don’t know why people expect there would be.
I think it's unquestionably right that these companies can't all win, and those that don't win are going to burn a lot of money for nothing. However there's kind of two directions this can go: Compute gets cheaper, in which case there's no monopoly it'll be easy for many companies to make good models and there won't be pricing power on serving a good model. The other case is compute gets cheaper but we keep using more and more of it, so it does likely become winner take all. The first scenario is good for the economy but likely bad for the returns on these AI stocks. The second is maybe bad for the economy and maybe not even good for the winner.
Take Google or Meta: Today Google makes a shit-tonne of money and to make that money they need to run some servers. The servers are extremely cheap relatively to the revenue they make running the business. This makes them a very attractive stock - the core of why SAAS looks great. Now let's assume the monopoly path. Google can win. I think they likely will win. But now they're going to spending... how many hundreds of billions constantly training new models? The cost of providing the service suddenly isn't small relative revenue they're getting. So even for them it looks awful for their valuation.
One aspect of my job is that I have a lot of autonomy and the work I do is such that I could push something out to the production environment and cause massive problems. We have processes in place to make sure that doesn't happen, but they're not robust processes, if you really wanted to you could get something out there that is harmful to the company. Now, there are two ways of looking at that - one is that it's really important to have robust processes to make sure that doesn't happen. But the other is you need people who understand that responsibility and take it seriously and whose personal values are such that they aren't just going to carelessly do stuff. At the end of the day the processes are only good if they're followed.
So one of the things I strongly look for when hiring is for people who have a high sense of personal responsibility. They're not going to just throw shit out there because it's easy or quick. They know they are responsible for what goes out and they really are going to own that responsbility.
In the same way, take a look at anything senior management says about their ICE or military contracts. It's not that I think they're doing something bad or that the military shouldn't have access to good technology. It's that at best they seem entirely disinterested in that what they're doing could be harmful or that they have any responsibility if it is.
It's not that I think Palantir is helping the US government bomb Iranian school chilren. It's that I don't think it would bother them if they were.
You're forgetting that xAI and X.com have both already been folded into SpaceX (First xAI acquired X.com, then xAI got acquired by SpaceX, both mergers were all-stock acquisitions so they were done with funny money). So when people say "SpaceX" now that does encompass both xAI and X.com as well. The reason Tesla wouldn't do this is because Tesla is a public company so it's more difficult for them to do insane shit without being sued.
Frankly I think it’s kind of childish to just put up a massive Uk wide block on your website. “Call your representatives”, ok dude, can I give you a list of things I want to change about your country’s policies?
Needs a [2010] tag. In almost all modern hardware development you'll have coding guidelines along the lines of "Always use blocking assignments for comb logic, always use non-blocking for sequential logic". You end up back at the same place as VHDL, by nature SystemVerilog is much weaker typed than VHDL. So you have to just have conventions in order to regain some level of safety.
What do you mean by simulate? Do you want the language to be aware of the temperature of the silicon? Because I can build you circuits whose behaviour changes due to variation in the temperature of the silicon. Essentially all these languages are not timing aware. So you design your circuit with combinatorial logic and a clock, and then hope (pray) that your compiler makes it meet timing.
The fundamental problem is that we're trying to create a simulation model of real hardware that is (a) realistic enough to tell us something reasonable about how to expect the hardware to behave and (b) computationally efficient enough to tell us about a in a reasonable period of time.
I guess this really depends on your view of the world. Was Marc Andreessen some visionary without whom no one would've ever figured out images could appear on websites. Some kind of Albert Einstein of cat gifs. Or was the img tag an inevitability once the web had enough bandwidth to transfer images.
There are obviously tonnes of accurate stereotypes in the TV show Silicon Valley, but one of the ones I think about often is when Richard calculates how much money Russ Hanneman has made investing his billions... and it works out to less than sticking it in the bank.
You've got all these silicon valley guys running around "venture investing", the truth is it's more of a life style than a money making exercise. They made their money decades ago, and now they're just sort of hanging around desperately trying to tell everyone how clever they are.
I'm always a little surprised at how these Tech CEOs are willing to go on TV and just spout nonsense. Firstly, 40% of college educated white women voted for Trump at the last election. Secondly, isn't the entire theory of Trump's support amongst working class voters an appeal to economic populism due to an erosion of their economic position? Aren't you literally describing a process that last time lead to a massive political shift in favour of those who were negatively economically impacted? Oh and you think all the white collar workers are going to lose their jobs, but you don't think that's just directly going to cause a recession that wipes out blue collar republican jobs?
It's difficult to (a) see how he can say this having given any real thought at all and (b) understand why he's going to on news interviews and winging it.
Whilst this is interesting I find the topic bought up on odd lots is more interesting. The idea was this: Once you've built a model, if you can sell tokens for a profit, this is a great business - just sell more tokens. But you can't just build a model and sell tokens. You need to build the best model to sell new tokens. So the question is much more "How much does it cost you to build a new SotA model" and then "How effectively can you monetize it". And since you need a SotA model, your only option if you have a bad model that isn't selling is to invest billions more into building a better model whose tokens you can sell.
So this turns into a death march.
If you are behind, the only thing you can do is make massive capital investments to catch up. Once you're ahead you can sell tokens until someone else catches up. And, breaking the model of normal of places like chip fabrication, your billions of investment may only keep you ahead for 2 months. So you have a tiny window to sell those tokens.