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Sad that this could well be that the path to OpenAI and Anthropic profitability of this arms race between defending LLM white hatting a company’s website and th

Sad that this could well be that the path to OpenAI and Anthropic profitability of this arms race between defending LLM white hatting a company’s website and the black hat LLMs attacking it? So the whole thing is forcing the good guys to outspend on tokens to preemptively defend against the risk of the bad guys outspending them on tokens, rather than buying tokens to actually add features to the product etc. So are they creating a market for the solution by helping create the problem? A kind of rent-seeking AI security-industrial complex!!

agileAlligator 8d ago
The only thing AI has changed is that it has dropped both: the cost of attack and the cost of defense. Nothing in the game has materially changed; the game has just sped up.
- wood_spirit 8d ago
  Who gets rent has changed. It puts me in mind of cloudfare et al
  - agileAlligator 8d ago
    Not really. Actually, for the purposes of cybersecurity, local models are far superior. Both offense and defense.
- emzo 8d ago
  The game has increased in scope.
  - agileAlligator 8d ago
    That is the direct effect of reduced cost. Jevon's paradox type effect: cost goes down demand goes up. You can AI-check so many more things that would be very time consuming earlier.
- red-iron-pine 8d ago
  plenty more has changed. for example the barrier to being a skiddie is basically gone, and low-skill would be hackers can hit very hard. to develop a CVE into a KEV in 2017 might take 2-3 months with a skilled team of serious security engineers; now my intern can get into police radios without knowing anything about the underlaying technology, essentially on a whim. any random tier 1 IT drone who can define a VLAN can potentially hit as hard as that team of security engineers now
  - agileAlligator 8d ago
    Yeah that is what I said, cost has gone down.
adventured 8d ago
The path to vast OpenAI profitability is trivial: advertising. Monetizing several hundred million users = $100+ billion ad network. 900 million active weekly users. Silicon Valley can do ad networks extraordinarily easily. Anybody doubting the ability of OpenAI to build an ad network around GPT will likely be embarassed in the near future. The path to substantial profitability for Anthropic is questionable. The Chinese LLMs threaten them by far the most of the three major US LLMs. The money for Anthropic is certainly not in $20-$200 subscriptions. And they don't have anywhere near the consumer potential that GPT does, in terms of unleashing an ad spigot. So how far will the API money scale while being undercut by China. OpenAI has to fight with Google for the ad business, they're specifically building Gemini to focus on consumer + search. Anthropic's business looks cute next to Google's search ad business (which is entirely at risk in this inflection). Meta looks like the biggest potential loser right now, ad dollars will be sucked out of the rotting Facebook network (not Instagram) and redirected to the rapidly expanding, hyper rich context LLM interaction. Advertising on Facebook will feel like running dumb banner ads on Excite in a few years, compared to what GPT will know about its users. People that think Chinese LLMs are a general threat, don't understand consumer destination services, which is what GPT's future is. China currently has nothing to threaten with in that realm. There is half a trillion dollars of advertising up for grabs.
- disgruntledphd2 8d ago
  > Silicon Valley can do ad networks extraordinarily easily. This is just not true, building an effective advertising platform costs significant amounts of money, time and people. Remember that you need to hire a sales force for this, and sales scales linearly rather than sub-linearly like engineering. Additionally, you need to spend a lot of money dealing with fraud, fake and malicious ads. Furthermore, you need to figure out where to put the ads and how to rank them. Finally, advertising is a zero sum game (given that the internet has already killed lots of print & OOH advertising), so the only way to win is to better better/cheaper (preferably both) than Google/Meta/Amazon. Best of luck with that (although to be fair to OpenAI they did hire Fidji who knows a lot of this stuff from her time at Facebook). They don't have a Sheryl Sandberg type figure, and she was also really important in selling FB ads to large advertisers. Just looking at their leadership team I don't see anyone with a background in (successful) ads companies, so I'm pretty sceptical that they can build this out quickly enough to matter.
bigfatkitten 8d ago
Assuming an equal level of impact per token spent, the scales have tipped in favour of the attacker. White hats are constrained by needing to pay for their own tokens, only using (expensive) vendors who meet governance and risk requirements etc. Black hats are free to take over accounts and steal services from wherever they can.
- brookst 8d ago
  For white hats, how has the cost of a thorough security review changed since, say, five years ago?
  - bigfatkitten 8d ago
    The price has gone up if you’re getting AI to do it. In terms of finding low hanging fruit, reasonably good code scanning tools have been around for a while. The thing that’s changed for attackers is speed. The things that got you hacked yesterday are the same things getting you hacked today. Finding and weaponising things like memory corruption bugs required an enormous amount of relatively hard to find skill, and considerable time. An idiot can now throw tokens at the problem and have something they can reliably use within minutes or hours.

agileAlligator 8d ago

The only thing AI has changed is that it has dropped both: the cost of attack and the cost of defense. Nothing in the game has materially changed; the game has just sped up.

wood_spirit 8d ago
Who gets rent has changed. It puts me in mind of cloudfare et al
- agileAlligator 8d ago
  Not really. Actually, for the purposes of cybersecurity, local models are far superior. Both offense and defense.
emzo 8d ago
The game has increased in scope.
- agileAlligator 8d ago
  That is the direct effect of reduced cost. Jevon's paradox type effect: cost goes down demand goes up. You can AI-check so many more things that would be very time consuming earlier.
red-iron-pine 8d ago
plenty more has changed. for example the barrier to being a skiddie is basically gone, and low-skill would be hackers can hit very hard. to develop a CVE into a KEV in 2017 might take 2-3 months with a skilled team of serious security engineers; now my intern can get into police radios without knowing anything about the underlaying technology, essentially on a whim. any random tier 1 IT drone who can define a VLAN can potentially hit as hard as that team of security engineers now
- agileAlligator 8d ago
  Yeah that is what I said, cost has gone down.

adventured 8d ago

The path to vast OpenAI profitability is trivial: advertising. Monetizing several hundred million users = $100+ billion ad network. 900 million active weekly users. Silicon Valley can do ad networks extraordinarily easily. Anybody doubting the ability of OpenAI to build an ad network around GPT will likely be embarassed in the near future. The path to substantial profitability for Anthropic is questionable. The Chinese LLMs threaten them by far the most of the three major US LLMs. The money for Anthropic is certainly not in $20-$200 subscriptions. And they don't have anywhere near the consumer potential that GPT does, in terms of unleashing an ad spigot. So how far will the API money scale while being undercut by China. OpenAI has to fight with Google for the ad business, they're specifically building Gemini to focus on consumer + search. Anthropic's business looks cute next to Google's search ad business (which is entirely at risk in this inflection). Meta looks like the biggest potential loser right now, ad dollars will be sucked out of the rotting Facebook network (not Instagram) and redirected to the rapidly expanding, hyper rich context LLM interaction. Advertising on Facebook will feel like running dumb banner ads on Excite in a few years, compared to what GPT will know about its users. People that think Chinese LLMs are a general threat, don't understand consumer destination services, which is what GPT's future is. China currently has nothing to threaten with in that realm. There is half a trillion dollars of advertising up for grabs.

disgruntledphd2 8d ago
> Silicon Valley can do ad networks extraordinarily easily. This is just not true, building an effective advertising platform costs significant amounts of money, time and people. Remember that you need to hire a sales force for this, and sales scales linearly rather than sub-linearly like engineering. Additionally, you need to spend a lot of money dealing with fraud, fake and malicious ads. Furthermore, you need to figure out where to put the ads and how to rank them. Finally, advertising is a zero sum game (given that the internet has already killed lots of print & OOH advertising), so the only way to win is to better better/cheaper (preferably both) than Google/Meta/Amazon. Best of luck with that (although to be fair to OpenAI they did hire Fidji who knows a lot of this stuff from her time at Facebook). They don't have a Sheryl Sandberg type figure, and she was also really important in selling FB ads to large advertisers. Just looking at their leadership team I don't see anyone with a background in (successful) ads companies, so I'm pretty sceptical that they can build this out quickly enough to matter.

bigfatkitten 8d ago

Assuming an equal level of impact per token spent, the scales have tipped in favour of the attacker. White hats are constrained by needing to pay for their own tokens, only using (expensive) vendors who meet governance and risk requirements etc. Black hats are free to take over accounts and steal services from wherever they can.

brookst 8d ago
For white hats, how has the cost of a thorough security review changed since, say, five years ago?
- bigfatkitten 8d ago
  The price has gone up if you’re getting AI to do it. In terms of finding low hanging fruit, reasonably good code scanning tools have been around for a while. The thing that’s changed for attackers is speed. The things that got you hacked yesterday are the same things getting you hacked today. Finding and weaponising things like memory corruption bugs required an enormous amount of relatively hard to find skill, and considerable time. An idiot can now throw tokens at the problem and have something they can reliably use within minutes or hours.