In my experience if you tell Claude to port LLM-like stuff without explicit steering for versioning, it will default to the most popular thing for this in its training window to reduce errors. 3.5 is outside its training data.
Why not compress the texture using NTC, VAE-VQ or some neural codec into a general embedding space of uint8 and then just expand and create mipmaps and similar using the target hardware standard?
The easiest answer is that most tools and hardware in use predates those type of embeddings.
The advantage with block compression is that it is purpose built to minimize bits used, it's local to small blocks, decoding and encoding can be done with fairly simple code[0], and it doesn't require any specific AI hardware.
I am unfamiliar with NTC, but at first glance it seems to require an Nvidia card with RTX features, meaning it wouldn't be supported on Xbox One and PlayStation 4 (AMD GCN), Xbox Series X|S and PlayStation 5 (AMD RDNA2), nor the original Switch (Nvidia Tegra X1).
NTC requires GPU for real-time decoding, but you can use it as an compressor only to have a portable representation. It's actually the common use-case today, you can on-device offline decode directly to BC7 if you feel like it!
This question reminds me of one that people apparently have seriously asked: "Why didn't they simply send up the Space Shuttle to rescue the Apollo 13 astronauts?"
There is a panic because the free lunch of more data is projected to end around mid-2027 and the open-source models are catching up with distillation, and all labs are sitting on debt and valuation that is impossible to fulfill even if they were alone in the market, so you essentially need either:
1) a breakthrough in performance/learning/model
2) regulatory capture to ensure open source models can be labelled as dangerous and banned so you can set the market rules yourself
Only one of the above is risk-free, and just a question of capital/lobbying rather than a "maybe".
We are beyond this now, if you complain, they can have an agent rewrite it and then it's not copied anymore. It doesn't matter and the bigger wallet wins, let it go.
Regulation got outpaced by technological development around 2023, as evident by the every AI regulation since being 2-3 years behind and having to be amended and resubmitted.
Whatever you try to make laws for now will be irrelevant in 1-2 years. You either have to go extremely broad, like the EU does it, and accept that people will find loopholes, or you need to target specific technologies which is a hard job for the same reason.
In any way, ita already a lost cause cause you move slower than the tech. A plausible prediction for AGI is actually a social collapse in the moment when society cannot keep up with everyday life because of the pace of change being so fast that no existing laws can handle it
The internet is 100% a series of tubes. This is how I was taught to think about networking in terms of bandwidth and throughput and routing since the early days when we were laying out what would become 'dark fiber'.
"A series of tubes" was the same kind of political character assassination that led to Howard Dean getting ridiculed for his infamous scream. He butchered the sentence. Fair. But Stevens should be ridiculed for parroting a tech industry lobby stance about net neutrality, not for the series of tubes metaphor.
You are probably too young to remember that the dominant metaphor for the internet in 1990s politics was "the information superhighway." It was easy to think of the web as "driving" browsers to visit web "sites", with slow bandwidth being analogous to being caught in traffic. But the internet is closer to water, gas, and electricity than roads. Concepts like bandwidth and throughput are closer to how they play out in infrastructure policy for various things with tubes, versus cars and roads. Do you think he's wrong and that the internet is closer to "a big truck" versus "a series of tubes"?
The issue being debated was net neutrality and bandwidth, including specifics about who pays for what and the downstream second-order consequences of various policies. He was parroting some line from some telecom lobbyist, but the point the lobbyist was trying to make through Stevens was about how if certain policies about who pays for bandwidth were adopted, it could disincentivize some things at the Tier 1/2 layer that could increase transport costs at the Tier 2/3 layer that impacts ordinary people's bandwidth.
If you buy car, someone hacks it, starts it, and drives over someone fully remotely, are you to blame for owning the car? Or the manufacturer? Or the hacker? Or the certification agency for the car security? Or the shell company owning the certification agency?
What if a person physically broke into the car and did the same thing? Clearly they are the one to blame then.
The whole person in the loop is liable is already an outdated concept when decisions are made beyond the persons physical control.
The hacker will be charged as a criminal as a societal deterrent against weaponizing digital systems. The manufacturer and shell companies could have structural liability if found to be negligent and cutting corners or lacked isolated drive-by-wire controls. It's unlikely that the owner would ever be held liable unless they jailbroke their car disabling security systems.
The hacker was a process that was spawned by some subprocesses that were corrupted by other processes and, etc. Check my other comment... The point is that in the physical realm this is already done by having shell of shell of shell companies to avoid taxes and accountability. In the digital realm this is much much cheaper
There's nothing new about any of this liability attachment. You're saying these things like they're novel.
If GM does something (or fails to do something) to their vehicle that causes me to crash, they're liable for the crash.
If someone cuts my brake lines (alters my vehicle) and I crash my car and kill someone, the person that cut the lines is responsible. I have to prove the context of course, and or an investigator has to do so.
And the responsible entity may refuse to pay up, may refuse to take responsibility. None of that is new either.
Well the difference is that in the software realm, you can attach infinite loops of delegation and ownership at close to no cost, which makes this impossible to investigate conclusively.
Let's say that OpenAI used a shell company that hosts server where an agent spun up another agent on instructions from another agent which was corrupted by bit errors from the inference framework which caused some major hack to happen. Its impossible to investigate in the same way as physical issues. What if the model is open-source, who is responsible then? What if it's open source but another process altered the weights?
When you say infinite loops, you mean infinite indirection, but obviously no such thing exists, because computer systems, just like other physical things, exist in physical space, not on the astral plane.
Whoever had agency to start the domino effect carries the liability. Doesn’t matter if the model is open source or if you brewed it home. And if you weaponize OpenAI’s models through their servers, it would likely be shared liability. Yours would be malice, theirs would be negligence.
Pure fantasy, yet you see this happen, literally every day, with the hacks, with content theft, etc, no repercussions for anyone.
Which judge will go down the rabbit hole of figuring this out? How will they do it? Will they have people tracing logs over 5000$? And if they do get there, in your fictional world, at some point, after 1 year of investigations and back-and-forth, it's okay, the technology is beyond what it was before, it's not relevant anymore, new technologies and new methods.
I do not buy that LLMs and the capability to run them are fundamentally different from other software or general purpose computing infrastructure in this regard. Moves to ban open source software or force OEMs to put little cops in everyone's computers are bad.
The proposal I’m hearing is to make people training models accountable for anything users do with them.
Obviously you’re going to keep the model behind an API and be very selective about the people allowed to call and the queries it’s willing to answer, in that case. As Anthropic has done with Fable. But that is voluntary restraint - mostly in today’s regime we get frontier capabilities in open weight models on a ~year delay.
It’s to keep “the people running it accountable.” The context is agents ran by OpenAI/Anthropic doing damage outside.
There is no user-involved damage. No one is recklessly running agents by the thousands without air-gapped containers, except “the people” than run these labs.
Go broad and achieve nothing. EU has all of the AI tech it had 5 years ago, and has the same tech allowed to use as the US.
What defines a model? What defines ownership of a process? If I make a wrapper to a remote VM that builds and executed a prompt, am I accountable?
When I worked at a company in the EU, it was enough to apply a reversible linear transform to the data for it to be considered GDPR safe-according according to legal definition as long as the transform details were stored separately.
Yes. You are accountable. Quite obviously, I might add. Why would no one or anyone else be accountable?
Hell, you can slip and fall and hold the cleaning company accountable. (This might be a US thing. Likely because that fall might cost a lot in medical expenses, and your insurance will do whatever it takes to pass the liability.)
What is the incentive for a person to sit though seminars and evaluations? People already hate redundant meetings. What is the incentive to change the system from the existing one to one that rewards this verification somehow? Who benefits from this change?
Yes. You can see this affecting perf benchmarks as well. Usually the cheapest inference providers either use approximations like tanh instead of sigmoid, nvfp4 quantizarion, etc.
There was a post here the other day highlighting this by showing the benchmark perf of different I defence providers, it's a fantastic area to cheap out in, because you can never really tell if a model is 75% good or 83% good on some specific benchmark when you use it to build your own stuff
Any paths for regulation under capitalism will end in either regulatory capture, or in complete noncompetitiveness like seen in the EU. Either one or more corporations buy out the regulation, stack the ranks with their people and decide on who can use what, when and how. Or you get an iceberg of a system that can't build, decide or do anything for years. The latter one only works if there is no competition in the world or any other group working at a faster pace on the problem.
I think the latter choice is better for the average person, but I think that for it to happen, the global system has to undergo some major disruption or crash so that everyone gets on board with it. Like all middle class and up has to lose their money or be starving or something. Also I find that kind of mentality impossible to swallow in the US, so in practice its not a choice or needs people literally starving.
The path to deregulation creates a "market for lemons". Suppose any bank was completely unregulated and could abscond with your money and the government would just shrug its shoulders. Great, now there's no trust and everyone will go back to stashing cash under their mattress and you've killed the banking sector.
The extent of regulatory capture in the US is a problem it's created for itself by normalizing huge political donations allowing corporations to buy regulation.
Actually capitalism kind of has to end further down this road if we don't want to cede control completely to super intelligent ais and their direct "owners".
No-one cares anymore, OpenAI does not care about the prize either or whatever the Clay institute has to say for that matter. It's about attention, capital and compute. If you can use the result to increase shareholder or company value, that is what matters.
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