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DeepSeek V4 Flash 0731 is now 90% off on Nous Portal for the next 7 days, in partnership with @novita_labs. At this discounted price, it is over 1000x cheaper than Fable 5 on comparable tasks while still beating it on Terminal-Bench 2.1. Try it today at

Some have questioned Elon's choice to invest heavily in Grok Imagine early (eg before coding models) It makes sense if you consider his love for the fundamental freedom of expression Hollywood and the streaming platforms have had a monopoly on production and distribution. They are, in all functional ways, a cultural propaganda engine. Every civilization needs one. But who owns it? Very soon, you will. You could say it was technically inevitable that AI video would get good enough to be enjoyable. But it only *felt* inevitable recently when I saw 1) the Spencer Pratt AI election ads which were actually funny and 2) the Sweet Land music video by @heavypulp which was actually poignant (enough so that I listened/watched 4x) AI images are already really good, but they aren't nearly as powerful. Movies are the most potent cultural propaganda tool of all time, but AI has sucked at them. Not anymore. Grok Imagine + a talented creator is now producing content good enough to enjoy without asterisks. The AI version of the Odyssey, no matter how long and expensive it is to produce, will be 3+ orders of magnitude (1000x) less expensive than Nolan's Which means that nearly everyone will be able to try. And based on this short clip, the output will actually be good. Frankly it doesn't even have to be perfect. As long as it is good, the damage to the existing power structure will be done. A solo creator with a vision will be able to singlehandedly put out work that is *actually enjoyable*, direct to the public, with literally no physical overhead. The cultural landscape will change really quickly. Individual people can express a vision in the most powerful medium yet discovered, unadulterated by tastemasters at the studios. We're at the rubicon, about to cross over. The propaganda engine will become distributed to the people, and the outcomes will be judged purely on resonance. This was Elon's point, in my opinion.

Kriptoda zengin olmak basit - 500 dolar biriktir ve solana al - Hepsi 10 farklı erken memecoin'e yatır - Birinin 1000x yükselmesini bekle - 5 milyon dolardan fazla kârla nakde çevir Bunu okulda öğretmezler

Getting rich in crypto is simple - Save up $500 and buy solana - Put it all into 10 different early memecoins - Wait for one to go up 1000x - Cash out over $5 million profit They don’t teach you this in school

Memory cost and capacity are significant issues for AI accelerators. Unlike game rendering, model inference can have a deterministic memory access pattern. You don’t need “random access memory” at all for model weights, and you could tolerate cold-start latencies in the multiple milliseconds, as long as continuous reads were delivered at the necessary bandwidth. NAND flash is over 100 times cheaper per GB than HBM, so there should be opportunity there, even after giving a flash controller a 1024 bit interface with HBM bandwidth. You could make a specialized pin protocol that just supported pipelined transfer of full 16KB+ pages from the flash to program-managed accelerator scratchpad memory and improve per-pin performance over HBM, but it might be more convenient to make it still look like a true random access memory with very fragile performance characteristics, where anything but sequential reads falls off a 1000x+ performance cliff. That has the advantage of automatically using existing cache hierarchies, and providing a natural path to update the flash memory with new model weights. With the stream-to-scratch interface, code has to be completely rewritten before it works at all, while the ram-emulation interface will start off just extremely slow, and you can incrementally sort out the changes for full performance. There may be cases where there isn’t enough scratchpad SRAM to hold the weights for a layer, which might force you to deploy the old optical drive optimization technique of duplicating data in multiple places on a sequential read to avoid seeking, but there would be capacity to burn. It might be possible to do something like cuda graph capture to record a memory access trace and have everything magically remapped to a linear sequence, but deploying programmer / agent elbow grease to manage transfers and access in a scratch ram ring buffer would be lower risk. A split memory system consisting of some channels of flash and some channels of HBM will probably be suboptimal compared to a uniform memory, but it could be much cheaper, and allow much larger models to be run. I think th case is strong for inference, but you have to stretch more for training. You can still linearize all the weight memory accesses, both reads and writes, but flash memory would quickly wear out from the writes, even if they were all perfectly page aligned. Replacing low-latency HBM with massively parallel cheap(er) DRAM at high latency might still be a worthwhile cost savings.

There are many good X articles lately, some superb, intellectual, and honest. They are 1000x better than opinion columns in newspapers. I noticed my chat group has more X article links than links from MSM. In the era of agentic AI, speed in reacting to truthful information is everything, or gradient descent can quickly go in another direction. A rare sign of enlightenment.

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