🔥 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: 🔗

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.

"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#

📈 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: 🔗

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

"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#

"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#

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

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.