The sea state in the Taiwan Strait is often pretty rough. If WIG vehicles have any military value it's likely to be on inland waters where weather conditions are typically more benign.
The hisutton.com website is full of the recent Chinese naval developments, including huge floating landing piers and various novel submarines and ships. The pace and scale of investment is such that it seems they are building the capacity to genuinely do an opposed invasion
Even if somehow you had the super hero ability to create this silicon out of thin air and even double it, I'd argue that it wouldn't drive down prices.
Simply because both the AI datacenter's need and their ability to pay is bigger then the consumer market. So far it seems that the more silicon you throw at AI, then the better your reasoning output. So the cheaper the chips, the more these datacenters will buy. Arguably they would buy even more because then you can tell investors that you have more powerful models (due to more compute) and your price per output is cheaper (because average hardware is cheaper).
1. That a new player would offer enterprise level product, instead of consumer grade. IMO it's very likely that if such a scenario unfolded, the market would be segmented into enterprise/consumer not only at the product level, but at the supplier level too. At least initially.
2. That AI compute demand is essentially unlimited AND silicon production capacity is and will remain bottleneck in datacenter buildouts. IMO we are much closer to the point where physical infrastructure becomes the apparent bottleneck than it would seem, IF political climate allows. Datacenter buildout is THE talking point in Ohio elections and if the dems win, datacenters will become THE talking point in the whole USofA. In just a couple of months the landscape they are operating in could become very different.
Isn't too early to see if the Gigadatacenters will really pay off? I'm not trying to be an AI doomer here, but I thought the new really large DCs are just not yet online.
Does it matter how it was created? Whether you had a subordinate create it, or an employee, or a contractor, googled it, cited a study, or some other method. You as the expert look at the conclusion and either agree with it or disagree.
I think if people looked at LLM as just tools or interns, which you should always check or question their conclusions, then they'd 1) not believe everything LLMs tell you and 2) they would get better responses after critiquing the LLM response.
Because it is not about the EU. Google has implemented watermarking for a long time. And soon we will see that all AI providers will do it, because it allows them to filter out AI generated data from their training sets.
This. I also think there'll be more local AI models to fill gaps and people see how we've become needlessly dependent and we start using AI responsibly.
The article says congress should pass a privacy bill to protect kids.
But it's never about the kids. It's always about surviellance and tracking people. For corporations it allows better monetization while for the government it allows better control.
>The article says congress should pass a privacy bill to protect kids.
No. The article says:
Protect Privacy For *Everyone*
There is a better way to protect young people online.
Instead of encouraging a complicated system of age
checks, more monitoring, and more restrictions on access
to information, Congress could finally pass a strong,
comprehensive privacy law[0] that benefits all users. A
great place to start would be to ban behavioral
advertising that tracks us across the web—again, for
users of all ages.
I'm trying to read your comment in the most charitable way, but it doesn't reflect the article's verbiage or the EFF's position. The best I can come up with is that you badly misunderstood the article and/or the proposed privacy legislation for everyone linked in said article.
Or am I missing something? Do tell.
[0] They even helpfully link to the privacy law they advocate here[1].
In practice I agree with the author but I think the issue isn't AI or AI slop as much as people's judgement.
He himself says that some AI assisted projects are actually good while other's aren't so. Devil's advocate can say that it's a matter of quality and also a matter of interest. And quality in some manner is a matter of taste - for example there is a market for regular fast food and organic or more high quality fast food, while others never take part.
He says that "Does your offering contribute anything to the community?" is the bar that should be met in regards whether something made with AI should be shared or published. But let's me honest, a good number of things people made or commented or did even before LLMs didn't meet that bar, and second is that most people think their pet project or pet whatever they made or created does contribute to the community. I have a senior security leader in my organization that thinks his Claude Code security scanner he made is amazing while I think it's a piece of garbage.
I think what you'll find is that most aren't happy with the current copyright law anyway (I include myself in that group) or don't understand it or don't agree with it, and thus will just shrug.
For example, copyright duration is far longer than most people think (life of author plus seventy (or plus ninety-five years if corporation). Corporations treat copyright as a way to create moats for themselves and freeze competitors than as a creative endeavor. Most creative works earn little to nothing anyway, while a tiny minority generate the most revenue. And it's not easy to get a copyright or atleast percieved to be easy, so again it incentivises those that can afford lawyers to navigate the legal environment. Also, enforcement of copyright law requires surviellance and censorship.
Truthfully I think there will be a time when people will look at current copyright law the same way we now look at guilds in the middleages.
It's incoherent to be anti-copyright because it's used to freeze out competition by corporations and be pro-AI (which is exactly that, at vastly greater scale).
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