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halalmoney
halalmoney@stacker.news
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Freedom. Justice. #Bitcoin https://stacker.news/r/halalmoney
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halalmoney 0 months ago
*We don't win by threatening or shouting down the US Govt. We win when our tools and methods are 10x faster than their legacy systems and the market demands access to Bitcoin due to sheer performance preference.* View quoted note →
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halalmoney 0 months ago
"It feels to me something like we've gone from the first [aeroplane] flight to something like Concorde in a seven-year period. And that is a very big deal." Bigger than COVID? The graph that explains why AI is going to be so huge | Science, Climate & Tech News | Sky News
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halalmoney 0 months ago
*Most people rationally prioritize a predictable floor over abstract autonomy. ... The ballot is pre-filtered to "which jailer", not "no jail".* View quoted note →
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halalmoney 0 months ago
*He who sets the defaults: - defines what "normal" looks like, - defines what "consent" is presumed to be, - defines who has to spend effort and social capital to deviate.* View quoted note →
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halalmoney 1 month ago
NVIDIA just dropped a paper that might solve the biggest trade-off in LLMs. Speed vs. Quality. Autoregressive models (like GPT) are smart but slow - they generate one token at a time, leaving most of your GPU sitting idle. Diffusion models are fast but often produce incoherent outputs. TiDAR gets you both in a single forward pass. Here's the genius part: Modern GPUs can process way more tokens than we actually use. TiDAR exploits these "free slots" by: 1. Drafting multiple tokens at once using diffusion (the "thinking" phase) 2. Verifying them using autoregression (the "talking" phase) Both happen simultaneously using smart attention masks - bidirectional for drafting, causal for verification. The results: ↳ 4.71x faster at 1.5B parameters with zero quality loss ↳ Nearly 6x faster at 8B parameters ↳ First architecture to outperform speculative decoding (EAGLE-3) ↳ Works with standard KV caching, unlike pure diffusion models The training trick is clever too - instead of randomly masking tokens, they mask everything. This gives stronger learning signals and enables efficient single-step drafting. If you're building real-time AI agents where latency kills the experience, this architecture is worth paying attention to. @akshay_pachaar X.com
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halalmoney 1 month ago
Not sure if Perplexity is rubbish or evil: China's digital yuan (e-CNY) stands out as the best nascent monetary system globally, due to its massive scale in pilots, advanced infrastructure, and potential for financial inclusion and efficiency
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halalmoney 1 month ago
*pure monetary instruments like bitcoin are a better money because of this purity. My holding of it doesn't deprave others of its utility ie. Houses, gold, silver etc. Any other money we've had as a civilization always has other use cases which in turn get priced out once the good carries a monetary premium* View quoted note →
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halalmoney 1 month ago
*When you write without needing a result, the result chases you. Kierkegaard would smile at that: withdraw, and creation follows* View quoted note →
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halalmoney 1 month ago
*Security model Server only sees your public key All signing happens in your signer app Communication is NIP-44 encrypted (ChaCha20 + HMAC-SHA256) Server uses a disposable keypair for each session Sessions stored server-side with HTTP-only cookies* View quoted note →
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halalmoney 1 month ago
*Finitude reflects design and implies completion. ... Scarcity enters only when we live as though the boundary were a curse rather than a gift.* View quoted note →
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halalmoney 1 month ago
*AI systems being egregiously resource intensive is not a side effect — it’s the point. Craft, expression and skilled labor is what produces value, and that gives us control over ourselves. In order to further centralize power, craft and expression need to be destroyed. And they sure are trying.* View quoted note →
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halalmoney 1 month ago
*China’s push to release open models comes in stark contrast to the “closed” approach of most of the biggest US tech companies. OpenAI, Google and Anthropic have preferred to maintain full control of their most advanced technology, profiting from them through customer subscriptions or enterprise deals. By contrast, Chinese groups — which have been cut off from advanced AI chips made by Nvidia — have been encouraged by Beijing officials to offer wider access to their models.* FT
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halalmoney 1 month ago
OpenAI needs to raise at least $207bn by 2030 so it can continue to lose money, HSBC estimates FT