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#HBM# is now a defining technology of the #AI# era. But its story began long before the AI boom. One question is worth decoding: Who developed the world’s first HBM? Trace the origins of HBM and its evolution into a critical AI memory technology. #SKhynix# #HBM4E# #AIMemory#
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@SKhynix has released its second-quarter 2026 financial results. The quarter was marked by another record performance, continued progress in HBM4, and expanded long-term customer partnerships. 🔗 #SKhynix# #AIMemory# #HBM# #AIInfrastructure#
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🤝@SKhynix and @NVIDIA are taking their AI memory partnership to the next level. As part of a $500B+ strategic partnership, SK hynix will advance next-generation AI memory, including #HBM#, to meet growing global AI demand. 🔗 #SKhynix# #NVIDIA# #AIMemory#
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everyone else: "grok 4.3 is out!! time to make a new account, rebuild all my context, figure out the new interface 🥲" Anuma users: 👁👄👁 Grok 4.3 is now integrated in #Grok4# #AI# #AIMemory# #PortableMemory# #Anuma#
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. @Kimi_Moonshot K2.6 and @Alibaba_Qwen 3.6 Max are now onboarded on ZetaChain. The model layer is moving fast. The memory layer is just getting started. ZetaChain enables: - Model-agnostic memory - Persistent user context - Private, user-owned data Continuous intelligence starts here. #AI# #AIMemory# #ZetaChain# #Qwen# #Kimi# #DecentralizedAI# #PortableMemory#
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AI is changing what we expect from a data center. ⚡ In AI Infrastructure Insight, @SKhynix explores how compute, memory, storage, networking, and power and cooling must work together to power AI at scale. 🔗 Read more:  #SKhynix# #DataCenter# #AIMemory#
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ChatGPT's memory got a big upgrade in 2026. If you haven't looked at it recently, it's worth understanding what changed. It now runs two systems: Saved Memories that store facts about you, and Chat History that references past conversations. You can edit, delete, and manage what it remembers. It's available on every plan, including Free. We use ChatGPT as one of the models inside Anuma, so we spend a lot of time with it. We wrote a detailed breakdown of how the memory system works, what it stores, the privacy settings worth knowing about, and how it compares to a unified memory approach that works across multiple models. Whether you use ChatGPT on its own or alongside other AI tools, it's helpful to know what's happening with your data. Read: #AImemory# #unifedmemory# #chatgpt# #openai# #anuma#
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AI is still eating the extra wafers. According to Industry sources, DRAM contract prices could rise about 20% quarter on quarter in Q4 2026. NAND could rise about 30%. The seller’s market is intact. This is not a PC or phone refresh cycle. Makers cut capex and wafer starts in 2023-2024. That hole never fully closed. Then AI infrastructure soaked up what was left. NAND demand has shifted fastest. Phones and PCs used to set the mix. Now the pull is AI data centers, enterprise SSDs, and high-capacity QLC. Once large models move from training into inference, KV cache, RAG, and intermediate data all need fast, dense storage. NAND is becoming part of the AI memory stack, not only a consumer leftover. Makers are sending scarce bits to those higher-margin parts first. Weak handset and PC demand therefore hurts less than the old cycle would suggest. New supply is late. Kioxia’s K2, Solidigm’s second Dalian plant, and YMTC additions are coming online. Large greenfield fabs do not add much until after 2028. On DRAM, HBM4, server DDR5, high-capacity RDIMM, SOCAMM, and LPDDR keep taking advanced wafers, which squeezes commodity DRAM. Samsung’s P4 and SK Hynix’s M15X are the nearer expansions, and both lean toward HBM and advanced DRAM. $MU $SKHY Micron’s Idaho fab, SK Hynix Yongin Y1, Micron’s Taiwan Tongluo site, and Nanya’s 5A plant mostly contribute after 2027. Taiwan names in the slipstream are Nanya and Winbond on DRAM and specialty memory, plus Phison, ADATA, Transcend, and Team Group on controllers and modules, via higher prices, denser SKUs, and inventory marks. Price is doing the work because bit growth cannot. That lasts until the 2027-2028 fabs actually ship.
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