stri8ted

Exactly. As far as I'm concerned, the benchmark is useless. It's way too easy and rewarding to train on it.

That is where the money is.

What languages does it support? I can't find this info anywhere on the page.

For video use cases, which will become increasingly popular, we are a long ways away.

Exactly. Or use the interpretability work to disable the distress neuron.

The same is true for Google.

It seems a strong base model is what enabled this. The models needs to be smart enough to get it right at least some times.

Not for coding, it seems. https://aider.chat/docs/leaderboards/

Given Israel's successful precision targeting of various senior Hezb members in recent months, I wonder if the pagers were initially used as such, but as suspicion mounted, and chances of an overhaul increased, they decided to hit the kill switch while they still could.

Although as as per an WSJ article: "The affected pagers were from a new shipment that the group received in recent days"

This is not the case. From Palmer's Twitter:

"Pulsar is one of several Anduril products that has been undercover for years. It has already been deployed to multiple AORs across continents at fixed sites, on ground vehicles, and in aircraft.

RFML (Radio Frequency Machine Learning) is a game-changer for electronic warfare."

What is the pricing? Also, why the strange "neuron" pricing for CF models?

> did you know the nordic countries are among the happiest and have some of the strongest social benefits in the world while still being wealthy?

I do wonder how much of this is due to cultural homogeneity and the benefits that follow. Will this remain the case in the presence of a larger proportion of immigrants? I don't think its a fair comparison, when people contrast Nordic countries with the US.

Many studies have found that social trust is higher and easier to maintain in homogeneous societies.

As far as I understand, these multi-modal models work by embedding the text/image in a shared representation space. To perform OCR on such an embedding, it would require extracting every letter, in the correct order, from the embedding. But given the embedding is a fixed size, and therefor necessarily compressed, I would expect it to loose the exactness of the underlying input, especially with images containing a lot of text. So assuming GPT-V can effectively perform OCR, how is this being done given the constraints?

Or is my understanding completely off? Perhaps it's "Translating" the image to text, by outputting a sequence of text tokens as it scans the image regions, and then the text queries (e.g. "whats funny about this") uses this translation as the context? Presumably, this is how the model handles audio input.

It's not about the events significance. It's about the complete censoring of all information related to it.

You can't prevent it. The best you can do, is prove an account belongs to a human, and that the human only has a single account, via cryptographic ZK proofs + Government issued keys or some other proof of personhood scheme. Assuming this is enforced, it would limit most abuse, and the AI would essentially be acting as an agent on behalf of the user.

Can somebody explain how this works, specifically for OCR? I understand images can be embedded into the same high dimensional space as text, but wouldn't this embedding fail to retain the exact words and sequence, since it is effectively compressed?

The CloudFlare worker is just being used to make a POST request to MailChannels. How is this a CloudFlare problem?

This argument holds less weight, when you consider things like iMessages, where there are network effects and no cross-platform support. Also, there are a number of apps that are only available on IOS, due to its higher market share and greater user spend. So there is a high switching cost, which is a direct function of Apple's dominant market position.

Same experience. Its half baked, and you don't know which half, until you try and implement it. I have a lot more appreciation for Android documentation, after seeing what IOS has to offer.

Agreed re fitness tracking. I have been thinking about that.

I think its more about a mismatch between our evolutionary past, and the modern environment. No different from junk food. Stimuli that would be adaptive in our prehistoric environment, is no longer so, but still triggers the same reward mechanisms. e.g. Seeing pictures of people on a social media app.

I do hear that. But it seems to me, having the company take the deposit creates perverse incentives, e.g. the company is basically betting on the user breaking their commitment.

A key difference also is, by requiring the deposit before resolving the commitment, it removes the escape hatch of just canceling your credit-card. It also generalizes to any app on the platform.

I was considering supporting anti-charities (e.g. NRA, DNC etc..), but I thought that was unnecessarily distracting.

I was initially thinking about doing it crypto-based, but that makes onboarding and the UX more challenging. A fee-less solution like LN could make sense.

Yep. The key difference is, the deposit here is taken before the commitment is resolved. And there is no self-reporting needed. So its 100% fire and forget.

Its not a fool proof solution, but the hope is, it should significantly reduce the likelihood of breaking your commitments.

I was considering supporting anti-charities (e.g. NRA, DNC etc..), but I thought that was unnecessarily distracting.

I don't disagree. My point is more broadly about the ills of social media, and how it's often framed as a Facebook problem.

Assume Facebook no longer exists tomorrow. The same incentives that drive Facebook's behavior, i.e. human consumption patterns, will still exist. And will be exploited by another company. Facebook is merely one instance of a problem deeply rooted in humans.

Sure, there is the anti-competitive aspect to it. But wrt to the divisiveness and polarization, the exploitation by political actors, it would not make a difference. Something else would just rise up to fill that void. It's the digital equivalent of junk food. Banning Coke, would do nothing to solve obesity.

Would need to see this compared to cardiac events in unvaxed group, given Covid seems to cause many of those same symptoms. Comparing it to baseline levels from pre-covid, would be disingenuous.

What about laziness as a motive? E.g. instead of spending time collecting data, just generate it.

You lost me at "experts". Blatant appeal to authority. The story should be able to stand on its own.