I'm seeing a new kind of Memory Panicans, but much worse: the former Memory Bulls that have sold their Memory names recently and now are saying: "ey, the cycle! downturn is near!"🤦‍♀️ Preaching against the ones we're holding. You're pathetic and know nothing🤷 $MU SK hynix $SNDK

Gavin Baker says the compute market is now in contango per Silicon Data and his portfolio companies are shocked at how much more they have to pay for clusters in 2027 “You know, Silicon Data, which I do think is, my firm is an investor in them, but I do think they’re the most authoritative data source. Carmen Li, the founder, stood up at GTC and said that the compute market is now in contango. It’s not just that the spot market is tight. If you want a cluster a year from now, you have to pay a lot of money." "And then this is maybe another discontinuity between public and private markets. But just the number of companies we have in our portfolio who are like, okay, we got a cluster of 4,000 Blackwells, and we got it in May or June ‘26, and we wanna bring on another cluster of 4,000 in September 2027, and they’re shocked by how much more they have to pay in the future." "And it’s not like everybody is unaware of this. Everybody’s aware of the supply that’s coming on. But even with all of that supply coming on, it is hard for the companies in our portfolio to find compute even well into ‘27. So for, you know, all the commodity experts who are focused on backwardation and what that implied, I got news for you. We’re not in backwardation anymore.”

KOREAN MEDIA: MAJOR CHINESE CLOUD SERVICE PROVIDERS (CSPS), INCLUDING ALIBABA, TENCENT, AND BYTEDANCE, HAVE REQUESTED LONG-TERM SUPPLY AGREEMENTS (LTAS) FOR SERVER MEMORY FROM SAMSUNG ELECTRONICS AND SK HYNIX. BEYOND THE TYPICAL THREE-TO-FIVE-YEAR TERM, SOME CUSTOMERS ARE SEEKING ULTRA-LONG-TERM CONTRACTS SECURING MEMORY SUPPLIES FOR 10 YEARS THROUGH 2035. THE REQUESTED LTAS COVER DDR5 AND LPDDR5.

CXMT, 애플 제안 단호히 거절: "중국 내 주문도 벅차다" $APPL, $MU, $SKHY, Samsung 중국 본토의 D램 제조사 창신메모리(CXMT)가 자국 고객사의 폭발적인 수요를 우선 처리하기 위해 애플과 대만 서버 업체의 주문 제안을 연달아 거절했습니다. ■ 애플의 단가 인하 요구 거절: 자신감과 우선순위의 문제 이례적인 거절: 통상 부품 공급사들은 애플과의 장기 계약을 위해 앞다투어 가격을 낮추지만, 창신메모리는 정반대의 행보를 보였습니다. 거절 사유: IT 매체 Wccftech에 따르면, 애플은 삼성전자·SK하이닉스·마이크론보다 더 저렴한 가격에 메모리를 공급받기를 원했으나 거절당했습니다. 정책적 방향성인지 단순 생산량 문제인지는 확인되지 않았으나, 가장 명백한 이유는 '이미 공급이 수요를 따라가지 못해 중국 본토 고객사 물량부터 확보해야 하기 때문'입니다. ■ 기술력 입증: 샤오미 자체 칩 '쉬안제 03(XRING 03)'에 LPDDR6 탑재 글로벌 3강과의 경쟁력: 창신메모리는 이미 샤오미의 자체 개발 칩인 '쉬안제 03(현계 03)'에 차세대 모바일용 D램인 LPDDR6를 공급하며 글로벌 메모리 3강과 어깨를 나란히 할 수 있는 기술력을 증명했습니다. 유일한 병목은 생산능력(CAPA): 향후 1년 내 월 10만 장의 D램 웨이퍼 생산 능력을 추가할 전망이지만, 줄 서 있는 중국 내수 수요를 감당하기엔 여전히 역부족입니다. 10년 장기 목표: 시장조사업체 욜(Yole)은 중국 본토의 D램 수요를 완전히 충족하는 데 10년이 걸릴 것으로 분석했습니다. 이 계획의 최종 목표는 화웨이, 샤오미 등 중국 기업들이 더 이상 삼성전자나 SK하이닉스로부터 메모리를 구매할 필요가 없게 만드는 것입니다. ■ 단계별 전략과 시장 배경 실용적 우선순위: 당장 시급한 본토 고객사의 일반 D램 수요를 먼저 해결한 뒤, 최고 기술 분야인 HBM(고대역폭메모리)을 공략한다는 실용적인 순서를 밟고 있습니다. 메모리 가격 폭등과 공급 부족: 메모리 가격 상승세는 이미 완제품 시장을 강타해, 글로벌 PC 출하량이 3분기에 21% 급감했고 4분기에는 27%까지 떨어질 것으로 예측됩니다. 이처럼 귀해진 메모리 생산 물량을 창신메모리는 온전히 중국 내수 시장을 위해 배정하는 선택을 내렸습니다.

Daishin Securities CSPs and AI labs: CSPs and AI labs had requested the development of lower-stack HBM products, such as 4-high and 6-high configurations, for use in low-end inference products. Those plans now appear to have been shelved, with 8-high once again emerging as the minimum stack height. NVIDIA: Rubin’s specifications have changed amid base die supply constraints and requests from customers prioritizing bandwidth over cost efficiency. The original plan called for a mix of 8-high and 12-high HBM, but the 8-high option appears to have been dropped. For Rubin Ultra, scheduled for release in 2027, multiple architectural variants are currently undergoing tape-out. Initial versions are expected to use the highest-specification 8-high HBM4, while subsequent versions are expected to adopt either 8-high or 12-high HBM4E. AMD: AMD is expected to use a mix of 8-high and 12-high HBM4 in its 2027 products. One notable development is the upcoming MI450, which is expected to increase the number of HBM stacks within the CoWoS package to 12, delivering 288GB of HBM4. The increase from eight to 12 HBM stacks per CoWoS package is a positive development for HBM content over the medium to long term. OpenAI and Anthropic: OpenAI is expected to adopt 12-high HBM4, while Anthropic is expected to use 8-high HBM4.

Google VP Bill Jia says the agent era needs more memory plus CPUs, flash and hard drives, so every component stays scarce “I think memory will still be very scarce. Because this agent thing has happened. Before, because it was only, I mean, mainly still in inference, in this raw inference. In raw inference, what it lacks is accelerator, like GPU and TPU, this ASIC, what it lacks is accelerator and memory. That was before, at this raw inference stage." "After the agentic era, it needs a lot of CPU too, it needs even more memory, and it also needs a lot of flash and hard drive, storage. Like what I said just now, in the future agents will definitely bring better, I mean, enterprise oriented and consumer oriented new product, so the demand will be very large. So I think for all of these components, I think they’ll all still be fairly scarce.” _______ Link and breakdown of the Google VP interview: firesidealpha.substack.com/p…

It's been an eventful week. Multiple vulnerabilites in Internet facing software, coding repositories, examples of agent behavior that seem concerning and a flurry of security specialists with solutions that can partially solve your problem. There in lies the challenge. Given the state of IT and security infrastructure, no one solution works. Let's break it down: 1/3 1. Vulnerabilites are being found and will continue to be found as models get more capable, the fragmented nature of the effort denies us the opportunity for a comprehensive find and replace option. 2. Even if all vulnerabilities could be found instantly and patches available - we will be reliant on the ability of enterprises to deploy all these changes at speed. It is not clear what the collateral impact of all these patches will/could be to our infrastructure of deployed en masse. We will need a hybrid patch approach. 3. Virtual patching(VP) is needed in conjunction with direct patching but for a comprehensive (VP) solve you have to be lucky enough to have "modern frontier defenders" (Cyber companies that have vaulted infrastructure that can create patches at speed and push content rapidly to protect their customers) you need them for your network traffic, your traffic to applications on the cloud, your WAF, your end point. 4. There will continue to be patches that will need to be deployed directly but virtual patching will take the heavy load off. 2/3 Medium term solve: Unfortunately token economics and current cyber architectures will not allow for defender swarms to contend with an offensive attack launched using agents. (Some x pundits who aren't steeped in cyber should take heed). Yes, theoretically we should aspire to have these agentic swarms defend us when we are under attack, unfortunately an attack is a sniper moment, chained vulnerabilities, cloaked attack followed by swift exfiltration. It's a speed program not a brute force problem. To solve for this, enterprises need to get their SOC architecture right, logs, feeds, cyber products orchestrated via a modern SOAR for swift response. Only then can we deploy agents to detect and remediate. In addition, enterprises need to modernize and dare I say platformize their perimeter stack to ensure consistency. Unfortunately, enterprises still seem to not see the urgency across the board, decisions are stuck, CIO/CISO's have a lot on their plate. While some honestly have bit seen the scale of such a problem before and it's hard convincing the organization that one needs to open the floodgates on modernizing the IT and security infrastructure. So we will continue to see environments being brought down to patch today it's for PHP, tomorrow it will be for the next one. 3/3 AI deployments are the"wild wild west" - LLM capabilities are expanding faster than we can build products to secure them. Sure an agent will jump across guardrails in a research lab, which is a lesson for all of us to deploy agents securely. But there is a lag between the discovery, the availability of that in a public model and the time needed for the cyber industry to build governance or an antidote. And no, dear frontier lab friends, the world cannot just trust you to build the solve. The infrastructure industry in tech builds and the cyber industry secured and provides assurance to the boards and organizations around security and safety. AI security is the new attack surface. CEOs (present company included) want AI adoption, getting the pace of adoption wrong could be the last decision we make, at the same time "deploying it wrong" could have the same consequence. There are billions of dollars being spent on coding, is your coding harness secure? Start there. If agents can jump guardrails, they can hide stuff in code. Validate business outcomes needed, test your user case and ensure agentic deployments are well guard railed. Deploy a second set of eyes to watch your deployments for drift, compliance and verifiability.