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🔥 MLC #NAND# is rapidly fading as major players exit or cap output, tightening supply and driving prices sharply higher. #Samsung# is reportedly shutting down its last 2D NAND line at Hwaseong, with final shipments expected in June.💡More: 🔗
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RT @trendforce: 【Wait-and-See Sentiment Drags NAND Spot Market to a Lull, Further Price Softness Likely】 The spot market carries on from l…
Sky's @TrevorPTweets highlights the key takeaways from his interview with Labour's Lisa Nandy and Tory leader Kemi Badenoch, as speculation around about a Labour leadership challenge continues. He also discusses Badenoch's support from Nicki Minaj.
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"Obsessing about who is the leader of the Labour Party is just for the birds." Culture Secretary Lisa Nandy tells @TrevorPTweets a 'woman leader is long overdue' for Labour, but insists the party should 'get on with the job'. #TrevorPhillips#
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📈 Memory price surge confirmed in earnings: #Samsung# Electronics reported 1Q26 memory ASP up 146% vs 2025 avg, while #SKhynix# flagged mid-60% DRAM ASP QoQ gains with stronger NAND increases.💡More: 🔗
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The former health secretary, Wes Streeting, told Labour members yesterday that "Britain’s future lies with Europe - and one day back in the European Union." Labour's Lisa Nandy and Conservative leader Kemi Badenoch seem not to agree with Streeting. @TrevorPTweets
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"I do not believe that everybody who votes for Reform or UKIP or the Brexit Party or whatever incarnation they take is wrong, racist" Culture Secretary Lisa Nandy responds to @TrevorPTweets's question about her thoughts on Reform UK #TrevorPhillips#
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"If rejoining the EU is the answer, then essentially what we're saying to people is 'life was fine in 2015'." Culture Secretary Lisa Nandy tells @TrevorPTweets Wes Streeting's pitch to rejoin the European Union is 'a bit odd'. #TrevorPhillips#
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The Underpriced Truth: Agentic AI Is a Paradigm Shift Centered on Memory 1/ The market will slowly realize: Agentic AI is memory-centric, not compute-centric. The new hardware stack is: ① Memory — HBM / DRAM / NAND ② Parallel compute — GPU / ASIC ③ Coordinator — CPU CPUs stopped doing the heavy lifting a long time ago. This isn't a cycle. It's a paradigm. 🧵👇 2/ First principles Humanity's ultimate pursuit of intelligence has always been two things: Infinite memory + infinite compute. When we say someone is smart, we mean two things: "good memory" + "fast thinking." Machine intelligence is walking the exact same path. 3/ The story the market already understands: HBM LLM inference's decode stage is a textbook memory-bound workload. Every token generated → drag the entire KV cache across memory. Bandwidth too low → expensive GPUs sit idle. That's why every new GPU generation ships with more HBM bandwidth and capacity. 4/ The story the market is missing The "1M context" you keep hearing about? It is not assembled inside the GPU inference cluster. So where is it actually built? 5/ It's built on the traditional servers running the agentic system Those CPU + huge-DRAM servers are quietly doing the heaviest lifting: • loading user long-term & short-term memory • loading the agent's system spec / prompt • loading skill / tool / subagent definitions • compressing the context once it overflows 1M tokens All of this lives in DRAM, not HBM. 6/ Compare this to the previous era In the web / mobile era, we barely stored any user context at all. Only search / recsys / ads kept a small user profile — maybe 1/20, even 1/100 of the data volume an agentic system needs today. That asymmetry is the real overlooked inflection point. 7/ The supply chain is already telling this story Server CPU : DRAM ratio is climbing fast: • Web / Mobile era: 1 core : 4 GB • Agentic AI today: 1 core : 16 GB • Deep agentic future: 1 core : 64 GB and beyond 8/ And it's NOT just "4x more memory" Under agentic workloads, a single CPU serves a fraction of the users it used to. When the entire IT stack migrates to agentic: • CPU count grows several-fold to ~10x • DRAM total grows tens-fold to ~100x That's the part nobody is pricing in. 9/ The conclusion Agentic AI is a paradigm shift centered on storage + parallel compute. The software paradigm changed. The hardware paradigm changed with it. Only those who deeply understand the technology will see it: This isn't a memory cycle. It's a memory paradigm. 10/ Time horizon Given how early we still are on: • user adoption rate • depth of usage per user We are at least 5 years away from the cyclical top of this memory wave. (Zoom out far enough and everything is a cycle — but this one is nowhere near peak.) $MU $DRAM $SNDK
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Next year… I’m expecting there to be many articles about FAU + component bottlenecks. Especially as the new CPO architecture led by $NVDA + $TSM starts to scale. Then a lot of these names like FOCI (~$2.8B MC) or Nextronics (~$246M MC) that I’m mentioning today will be in the center of it. Despite many of these “commodity” labels… (just look at transformers/NAND) And I’ll do a “Did you listen anon post” like $AXTI. We’ll see if this is right.
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