GamingChairModel

joined 3 years ago
[–] GamingChairModel@lemmy.world 2 points 22 hours ago

What passkeys can't overcome is people dismissing the popups asking if they want to switch to passkeys or create them.

I think it'd actually be pretty easy. Just ask:

Trust this device, with biometrics?

Most people will say yes on their Apple/Samsung/Google devices.

[–] GamingChairModel@lemmy.world 2 points 22 hours ago (1 children)

It's been like 25 years since the security world basically moved on from assuming that users could be trusted to act securely. We gotta design processes and protocols that keep things secure even with people who have bad habits.

I can secure my email, but every email I send or receive touches at least one other mailbox I don't control, of some other user. Same with text messages, social media posts, etc. The digital world we use has a billion overlapping people, some with escalated privileges as employees or admins or mods or whatever. We can't make them perfect, so we should design systems that work well even with imperfect people.

[–] GamingChairModel@lemmy.world 1 points 23 hours ago (3 children)

I think you're mixing up compromise of an account with compromise of the data associated with that account.

If a particular piece of data is accessible to people of a dozen accounts, compromise of any of those accounts potentially compromises the data. That's a legitimate concern for people who want certain data secured, whether other accounts with access are also secure. In some cases, it may be best to have an authentication policy that provides a baseline level of protection even for the most clueless users, rather than a system where you're able to secure your own account.

[–] GamingChairModel@lemmy.world 2 points 23 hours ago (2 children)

They don't need to. It just works to log them in when they're using one of their own trusted devices. Being able to unlock their phone gives them full access to the services (apps, websites) that are authenticated to that device.

TOTP tokens are often distributed as QR codes, where you can store in more than one place, store/copy/transfer in plaintext between people or places. Compromise of that token gives permanent access to all TOTP codes generated.

I'm not a fan of how most TOTP apps and implementations actually work right now.

I have a secure password manager, offline, nowhere shared, even the passwords are encrypted.

How can the service provider tell, though?

The point of passkeys is to create an authentication flow that is easier for users to keep secure. The question, then, becomes whether a service provider should make user authentication decisions based on the worst case scenario, best case scenario, or average case scenario. Passkeys are a reasonable way to make sure almost all of your users have secure login credentials, even if the best of the best users would have just as secure login credentials with traditional passphrases.

Apple mainstreamed tech tribalism

I assure you, from car brands to shoe brands to soda brands, brand tribalism by consumers has always been with us. On the tech side, we saw it with console wars of every generation, PC/accessory brand tribalism, even OS/software tribalism. TVs, radios, portable music players, AV equipment of all types, etc. When cell phones came on the scene, you had significant brand rivalries there, even before smartphones. (You see remnants in this when people get nostalgic about Nokias or Blackberries or Razrs).

[–] GamingChairModel@lemmy.world 53 points 2 days ago (13 children)

plagiarism

outright theft

It frustrates me to see that people are suddenly protective of some kind of intellectual property right of people to control creations after they've been created.

I'm pretty skeptical of AI and have my doubts that it will be a net good, but I'm definitely not gonna suddenly be pro-copyright as part of that fight. Copyright has traditionally been used to entrench corporate interests, and strengthening those protections isn't going to suddenly win a fight against some kind of AI dystopia.

[–] GamingChairModel@lemmy.world 8 points 3 days ago (1 children)

Chip industry, both potato and RAM

[–] GamingChairModel@lemmy.world 12 points 4 days ago

That's basically what AI is best at: incorporating lots and lots of data points (every single pixel on an image, many trillions of pixels on previous images used to train the model) to determine the best answer to a question with clear definitions of what is better or worse on a single-dimensional quality axis that most people would agree on. In this case, whether a de-noised photo looks good and accurately represents the image that could have been captured of the exact same scene using more light or a better sensor or whatever.

It's generative AI where things fall apart. The analogy I always use is that these math techniques are great for inferring what is between pixels in a low res image, but starts going off the rails when it starts guessing what's beyond the edges of the image. These AI algorithms are just math, and math with this many data points needs to start considering the limitations described by chaos theory (in the mathematical sense).

[–] GamingChairModel@lemmy.world 10 points 4 days ago

Once there's a public expectation for profit from the two biggest AI labs

I don't think that it's necessarily the order things will go.

Anthropic and OpenAI have bills to pay, including obligations to pay a ton of money to partners/vendors in the coming years. They need cash to do that. And the cash can come from 3 main places: revenue from customers, loans from lenders (usually in the form of issuing bonds), and issuing new stock/equity to raise funds.

The IPOs are basically their last chance to raise funds by issuing new equity. Even if each of them raise $100 billion, that's probably not enough to hit self sustaining profitability. As lenders start to get more skeptical, in a macroeconomic environment with high interest rates and high energy prices, they start to run into a very real possibility that they hit illiquidity issues, even if their core business model actually works by then (and I don't think it will). There's just not enough runway for them, even in the most optimistic long term projections.

I want a convertible, a laptop that folds all the way back and gives a tablet/stylus interface, but has stiff enough hinges to hold the screen like a laptop at any angle with a keyboard, and that closes and covers the screen like a laptop. They played around with some form factors like that 10 years ago but they never really took off. Plus they tended to be Windows only, with poor Linux support on the hardware.

 

In recent years, I've seen people use projectors at night to protest policies: projecting slogans, images, etc., using a normal projector against the wall of the target of a protest (embassies, government buildings, prisons/detainment facilities, corporate headquarters, etc.).

Here's an example, but I've seen lots of other examples. And even outside of protest, people have been doing ridiculous things with 3D projection, like this guy animating a hotel cuck chair (SFW).

This got me to thinking: if the image recognition of Flock and similar cameras is just an AI image recognition function (using ImageNet or something like that) being run on captured video, what's stopping people from projecting false data onto streets and sidewalks in a way that tricks the Flock camera into recording false people/vehicles in places where there was no person/vehicle? Including fake license plates, etc.?

Seems like an attack vector for some kind of denial of service attack, like putting fake faces and license plates all over.

Is there anyone doing this? Would it be possible, at least at night, for certain camera locations and angles?

 

(Note: McSweeney's is a satirical publication)

 

I've read some of Ed Zitron's long posts on why the AI industry is a bubble that will never be profitable (and will bring down a lot of companies and investors), and one of the recurring themes is that the AI companies are trying to capture growing market share in an industry where their marginal profits are still negative, and that any increase in revenue necessarily increases their costs of providing their services.

But some of the comments in various HackerNews threads are dismissive, saying that each new generation of models makes the cost of inference lower, so that with sufficient customer volume, the companies running the models can make enough profit on inference to make up for the staggering up-front capital expenditures it took to build out the data centers, train their models, etc.

It's all pretty confusing to me. So for those of you who are familiar with the industry, I have several questions:

  1. Is the cost of running any given pretrained model going down, for specific models? Are there hardware and software improvements that make it cheaper to run those models, despite the model itself not changing?
  2. Is the cost of performing a particular task at a particular quality level going down, through releases of newer models of similar performance (i.e., a smaller model of the current generation performing similarly to a bigger model of the previous generation, such that the cost is now cheaper)?
  3. Is the cost of running the largest flagship frontier models going down for any given task? Or does running the cutting edge show-off tasks keep increasing in cost, but where the companies argue that the improvement in performance is worth the cost increase?

I suspect that the reason why the discussion around this is so muddled online is because the answers are different depending on which of the 3 questions is meant by "is running an AI model getting cheaper over time?" And the data isn't easy to synthesize because each model has different token prices and different number of tokens per query.

But I wanted to hear from people who are knowledgeable about these topics.

 

Curious what everyone else is doing with all the files that are generated by photography as a hobby/interest/profession. What's your working setup, how do you share with others, and how are you backing things up?

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