

If only there were more support for reticulum.


If only there were more support for reticulum.


You’re giving them too much trust. The only way to be sure that Microsoft isn’t embedding malware into your systems is to not use their software.


It’s hardly their fault for thinking it was related to the AI LLM or multimodal models when in all actuality the article states that these “large physics models” may be any sort of configuration, including LLM transformers:
the models may use the transformer architecture that underlies LLMs, a generalized version of convolutional neural networks known as geometric deep learning, or an architecture that can solve partial differential equations called neural operators.
It seemed you really needed to take your frustrations out on someone else’s comment.


It said a preview was available for thousands of dollars but the full database is selling for hundreds of thousands. That seems more realistic for risk & storage/hosting costs.


They could be. Transitioning doesnt stop them from choosing to identify with a non-binary gender.
Are you thinking of intersex? Even in that scenario, I don’t believe that statement applies.


I would love to see the exploit. There are vulnerabilities discovered everyday that amount to very little in terms of use in real world implementations.


New technology is released into medical field and executive board thinks “how can we harm people with this?”
I understand why you might think that’s best as a cultural more but I ultimately disagree with that stance since it is likely to lead to alienation and less understanding as a whole. Being open to outside perspectives and even constructive criticism from both parties is the best way finding mutual understanding.


This is actually supported by GrapheneOS currently, if you need that extra push. 😉


Not to mention that the flames while combusing are invisible by sight. It’s also really difficult to keep contained and if it leaks it has ~11x the impact of CO2 per this article.
I used to like the idea of hydrogen as an energy medium but all of its attributes combined just make it really infeasible to use except for immediate applications.
The types of AI you mention at the start of your comment has been around for years and isn’t exactly the problem we’re facing as far as I have researched. The AI bubble is a result of the hype around transformer-based generative AI and not so much about AI itself. Neither datacenters nor AI are a new thing and up until 2020 they weren’t as much as a problem as they are today due to the hype and increasing demands by these large models.
The problem is literally a scaling issue for generative AI and those that decide to build new datacenters just for this usage are ignorant to the environmental and socioeconomic issues as being the limiters that they should be.