stri8ed

It's not a conspiracy. There's a finite amount of compute available, and they will sell it to the highest bidder. If another company can produce the same intelligence for cheaper, then they will drive the price down.

Output cost is 3x from Gemini 3 flash.

Given the cost increase associated with this model, and previous model releases, I think the size is trending upwards, not down.

Is it fair to characterize a founder of a failed startup as a con man? I.e. did he make claims that were factually untrue, and intentionally deceived investors?

What is the counterfactual? Without knowing the number of attacks prevented by these tools, we don't know what the baseline would be.

Having adequate law enforcement training and funding, is not mutually exclusive with leveraging technology for more effective enforcement. In fact that's where some of the funding goes. I would be interested in seeing some data reflecting a reduction in crime as a result of increasing the welfare system, as you claim.

https://en.wikipedia.org/wiki/Flock_Safety#Efficacy

Not a chance. Even if American companies did abide by it, there is no reason Chinese companies would. And good luck definitely proving that a model trained on it.

That problem along with its many solutions are surely littered throughout the training data. Not to mention, it would be trivial to overfit on that problem. I don't know why people still reference that.

It's a result of the system prompt, not the base model itself. Arguably, this just demonstrates that the model is very steerable, which is a good thing.

Trained at least in part on Chat-GPT data.

It would happen in China regardless what is done here. Removing billionaires does not fix this. The ship has sailed.

The benchmarks agree as well.

Isn't that how previous models were, before the attention is all you need paper?

Or be in the business of building infrastructure for AI inference.

You can modify this, by setting the GPT4 system prompt, with instructions of your preferred response style.

For programming, GPT4+. I was excited to switch to Claude after hearing all the positive anecdotes. Having tried it, I'm very unimpressed. It spouted complete, confident sounding nonsense, when I prompted it with a bug I was trying to solve. GPT4, did not get it right initially, but it was more suggestive, instead of wrongly declaring the fault, and lead me to the answer after a few more prompts. Will not be renewing my Claude subscription.

It's impossible to prove.

I don't think you can infer someone's age and skin colon from that post.

In humans, a software problem can become a hardware problem, due to plasticity in the hardware. See alcoholism for example.

Do existing LLM's not already train on this data?

In such a scheme, wouldn't synonyms of the same word be no closer to each other, than any other random string?

What is the rate of increase, and how does it compare to CPI inflation?

How does the quantization happen? Are the weights preprocessed before loading the model?

Let's not forget Google maps, which already integrates other ride share platforms.

Very important distinction here, and that is self volition. To be clear I'm not saying it's good or bad. I think it's a genuine question. What if there are simply not enough jobs available at the rates that people want to be paid?

Would there be any demand for those gig works, if it had to pay comparable to full employment? And would that be a good thing?

It's the cost factor. Using AI, it's economically feasible to contact a million people, even if only a fraction bite. Not unlike the current spam calls.

The authors address that by looking at hospitalizations for self harm.

In the article, the author makes a point to include objective metrics like rate of hospitalizations, and the data is quite conclusive in showing an actual increase. So these issues definitely did not exist before, at the same scale.

For the same reason that people oppose monopolies. Unions are effectively a monopoly on the labor market.