Next generation of. The Type 25 HVGP just entered service few months ago. That one is just a two-stage Scud, but the Block 3 or NG or Type 35 or whatever of that could have this tech.
I was skeptical about the article considering Japan's draconian stance regarding copyright. Turns out I was right.
This is an opposition figure advocating for stronger copyright protection. He was clearly trying to make a point by asking what the current laws allows regarding the use of copyrighted materials by AI. The minister simply confirmed that no regulations are currently in place to limit that.
The whole article is a blatant lie. Neither politicians went "all in" advocating the use of copyrighted materials by AI. They just confirmed what the current laws say. The fact that they're even discussing this likely means that there will be even more regulation, not less.
Yeah. Copyright laws in Japan are extremely strict. I would not be surprised at a complete ban on this. This is just a fluff piece like a lot of ads coming in recently.
Japan was behind about developing search engine service. Some people argued that it's due to copyright law (there's no fair use) and it shouldn't be repeated again. So the gov want to encourage AI developing by explicit law.
I thought it would be too ironic for people to misunderstand this based on a machine translated version, so here is a genuine, human translation of the transcript, with boring bits redacted.
Kii: Next question, again regarding generative AI. I would like to ask from the two perspectives of copyright protection and educational use. [...]
First, can we understand that Japanese law permits the use of works for information analysis, both for non-commercial and commercial purposes, and acts other than copying, and using content that was uploaded illegally?
Nagaoka: Use for non-commercial information analysis is permitted under Article 30-4 of the copyright act, provided that the purpose is not the enjoyment of the ideas and emotions expressed in the copyrighted work.
Kii: Minister, I asked about four aspects of use for information analysis: non-commercial use, commercial use, acts other than copying, and illegally uploaded content. Please address the other three.
Nagaoka: Use for commercial purposes is permitted under Article 30-4 of the copyright act, provided that the purpose is not the enjoyment of the ideas and emotions expressed in the copyrighted work, because that Article does not distinguish between information analysis for commercial or non-commercial purposes.
Regarding copying, Article 30-4 of the Copyright Act does not distinguish based on the method of use, so use by means other than copying is permitted provided that the criteria are met.
[...] Regarding content obtained from piracy sites and the like, [...] illegal uploading itself is infringement of copyright, and is subject to a damage claim, petition for injunction, or criminal punishment. However, it is not practically feasible to identify whether any particular work in a large collection obtained from the internet is copyrighted or not, so making this a criterion for information analysis would make it difficult to use information analysis for Big Data.
In addition, as the use of a work for information analysis is not use for the purpose of enjoyment of the ideas or emotions expressed in the work, and even if [it were used in that manner] it would not overlap with the original market for the use of the work, so it is not considered to harm the interests of the copyright holder that are protected by the Copyright Act.
As such, Article 30-4 of the Copyright Act does not have the legality of the work as a criterion.
Kii: Minister, based on your answer, I think the greatest issue is that there is no protection against use that goes against the intentions of the creator or the copyright holder. I believe that new regulations will be necessary to address this point; will you consider such new regulations?
Nagaoka: Article 30-4 of the Copyright Act provides for use that is not for the purpose of enjoying the ideas or emotions expressed in the work, and applies to acts that are considered not to affect the opportunities to collect revenues from the work, and not to harm the interests of the copyright holder protected by the Copyright Act.
That Article also provides that the use is limited to the extent considered necessary, and it does not apply to cases where the interests of the copyright holder are unduly harmed. [...]
Interesting. So, when the "open source" movement was born out of a desire to become business friendly, it did not envision that the approach would eventually come back, 30 years down the road, to nastily bite them. Problem is big corps live long, longer than the average concentration span of a free software shop. And they have plenty of money and corporate hacks to co-opt "open source" and then take over. But hey, "open source".
How many digital nomad influencers vs would-be entrepreneurs who keep wasting time on IT social networks? This ratio alone should make it very clear to you that most of that world is fake and just here to entertain you when you feel alone in front of your machine.
Meta's language models, GH Pilot, real life car auto-pilot. When it fails, it fails big. And the "we were 10+ years early to market" is just a big lie that bought them plenty of VC money. Good for them.
At least partially over. It's one of those things though; when you first see what's possible with neural networks it does get your hopes up. When you later realize the limitations, it's hard to walk back your old claims. Even Elon Musk has to realize that FSD is never going to happen by now. Google with all their learning and training data, still can't correctly find and smudge license plates or faces correctly on Google maps. If that much processing power cannot correctly identify two classes of objects, what chance do these cars have to classify tons more objects + adapt how they steer based on that information in real time?
The internet was a hype cycle, which ended with the dot com bubble burst. But some of the companies that came out of the bubble came out strong. AI has had multiple hype cycles, like every washing machine with "fuzzy logic" in the 90s, they usually end, but they do usually leave us with more than we had. This AI hype cycle is ending now, and we have seen a lot of progress on image detection, video editing, etc. but the highest targets haven't been reached.
It's kind of the explore-exploit dichotomy. You have some new technology (internet), in the first few years you have exploration and all the low hanging fruit are implemented, then everybody just starts iterating on similar ideas, which lead to less and less gain. The Uber/AirBnb/Amazon for X pitches. If you hear those you're in the late phase of the hype cycle. Because Y for X just means it's not a really new idea and plenty of people have thought of those.
Similarly you have some new technology like fuzzy logic, then some people thought of some good applications. But because the hype train was running it was put everywhere where it didn't make sense.
Or deep learning which was the first to have useful image processing. Now most research is tuning some parameters, adding compute, and hoping for better results.
But in the end we'll be left with some technological advances, and maybe in ten or twenty years somebody has a new idea which beats deep learning in learning efficiency.
The Google Maps smudging point is an interesting one and definitely worth considering, but the incentives at play are very different. While I'm sure they want to be seen as making an effort, Google isn't rewarded in any way for achieving high accuracy in their smudging. It just has to be "good enough" to the point that they aren't getting in trouble for deliberately neglecting it. For this reason, I'd imagine the resources they devote to it are quite limited. It's not having billions poured into it like self-driving AI is--while I have no inside knowledge, I'd guess the budget is orders of magnitude less.
> I'd imagine the resources they devote to it are quite limited
That's a problem inherent to AI or neural networks. We cannot spend our way out of these problems; they are underlying to the technology itself. Nobody knows what "doesn't work" when a neural network does something unexpected. AI is not a technology we have invented, it's a technology we've copied from nature. Nobody knows anything about what really goes on, this is why we're not getting anywhere.
Google could spend their entire budget on that smudge-bot, and it still wouldn't get any better using AI; they would have to go back to regular image analysis to make any improvements at this point. Google has trained it to be so good at finding faces; it started smudging faces on billboards/ads/shop-windows, but when these are flagged as errors, then it starts showing regular faces in shop windows un-smudged. The problem is that we have no idea of what's going on, so all we can do is to add new layers to the neural network, or give it more training data, neither of which gives an accurate result typically, making it impossible to use for self driving cars etc.
It is "carbon neutral" because of a bet on the future of trees that will be planted in replacement for the burned ones. The future trees do not exist yet. And with global warming probably won't come soon enough. So that's extremely stupid and criminal to do what they're doing.
https://green-innovation.nedo.go.jp/en/article/liquid-lithiu...
“While these targets have already been achieved at the laboratory level, we are now moving into the phase of mid-scale demonstration,”