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anon
RT @james_riney: It was great catching up with Totoki-san (CEO of Sony) today.
What struck me wasn’t any single initiative, but the tone.
Japan’s largest companies are thinking in decades again. More optimism. More ambition.
The lost decades are over. It's time to build. JAPAN IS BACK. https://t.co/6FV3VrJ3nZ
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RT @james_riney: It was great catching up with Totoki-san (CEO of Sony) today.
What struck me wasn’t any single initiative, but the tone.
Japan’s largest companies are thinking in decades again. More optimism. More ambition.
The lost decades are over. It's time to build. JAPAN IS BACK. https://t.co/6FV3VrJ3nZ
tweet
Offshore
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Dimitry Nakhla | Babylon Capital®
Two notable insider buys over the past two weeks:
1. $TDG President & CEO purchasing ~$1.22M worth of stock (02/06/2026) 🛩️
1. $SPGI Director purchasing ~$1M worth of stock (02/11/2026) 📊 https://t.co/rmYx0GeaWi
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Two notable insider buys over the past two weeks:
1. $TDG President & CEO purchasing ~$1.22M worth of stock (02/06/2026) 🛩️
1. $SPGI Director purchasing ~$1M worth of stock (02/11/2026) 📊 https://t.co/rmYx0GeaWi
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Offshore
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The Transcript
Big tech execs commenting on Capex in the latest earnings calls:
$META CFO: "We anticipate 2026 capital expenditures...to be in the range of $115-135B, with year-over-year growth driven by increased investment to support our Meta Superintelligence Labs efforts and core business"
$MSFT CFO: " Capital expenditures were $37.5B, and this quarter, roughly 2/3 of our CapEx was on short-lived assets, primarily GPUs and CPUs. Our customer demand continues to exceed our supply.
$AMZN CEO: "..we expect to invest about $200B in capital expenditures across Amazon in 2026...but predominantly in AWS because we have very high demand."
$GOOGL CFO: "To meet customer demand & capitalize on the growing opportunities ahead of us, our 2026 CapEx investments are anticipated to be in the range of $175B to $185B"
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Big tech execs commenting on Capex in the latest earnings calls:
$META CFO: "We anticipate 2026 capital expenditures...to be in the range of $115-135B, with year-over-year growth driven by increased investment to support our Meta Superintelligence Labs efforts and core business"
$MSFT CFO: " Capital expenditures were $37.5B, and this quarter, roughly 2/3 of our CapEx was on short-lived assets, primarily GPUs and CPUs. Our customer demand continues to exceed our supply.
$AMZN CEO: "..we expect to invest about $200B in capital expenditures across Amazon in 2026...but predominantly in AWS because we have very high demand."
$GOOGL CFO: "To meet customer demand & capitalize on the growing opportunities ahead of us, our 2026 CapEx investments are anticipated to be in the range of $175B to $185B"
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anon
RT @Yuchenj_UW: Taste has always been a core skill. https://t.co/Zm105MZu74
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RT @Yuchenj_UW: Taste has always been a core skill. https://t.co/Zm105MZu74
taste is a new core skill tweet
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God of Prompt
RT @godofprompt: I've written 500 articles, 23 whitepapers, and 3 ebooks using Claude over 2 years, and these 10 prompts are the ONLY ones I actually use anymore because they handle 90% of professional writing better than any human editor I've worked with and cost me $0.02 per 1000 words: 👇 https://t.co/Yx6MCNdLbr
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RT @godofprompt: I've written 500 articles, 23 whitepapers, and 3 ebooks using Claude over 2 years, and these 10 prompts are the ONLY ones I actually use anymore because they handle 90% of professional writing better than any human editor I've worked with and cost me $0.02 per 1000 words: 👇 https://t.co/Yx6MCNdLbr
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Clark Square Capital
RT @ClarkSquareCap: Here is this week's special situations digest.
281 situations in activist campaigns, M&A/divestments, management changes, and other corporate events.
Make sure to check it out https://t.co/NZBTGqVC6P
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RT @ClarkSquareCap: Here is this week's special situations digest.
281 situations in activist campaigns, M&A/divestments, management changes, and other corporate events.
Make sure to check it out https://t.co/NZBTGqVC6P
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Jukan
Why the Memory Big 3 Cannot Exercise Implicit Supply Discipline Like HDD Players
Someone raised an excellent question: "There are only three DRAM suppliers—why can't they implicitly coordinate supply, like HDD makers do, to avoid over-investment?"
Intuitively, it makes sense. In an oligopoly, players should be able to read each other's signals and moderate accordingly. And indeed, after the HDD market consolidated into a three-player structure—Seagate, WD, and Toshiba—the industry maintained relatively stable supply discipline for a considerable period. So why doesn't this work in memory?
The core issue is that memory is an industry where those who wait are punished.
HDD is a mature industry. The pace of generational technology transitions is slow, and being late to adopt a new generation doesn't get you expelled from the market. This creates room for a tacit agreement along the lines of "let's all take it slow together."
Memory is the exact opposite. From DDR4 to DDR5, HBM2e to HBM3, 1-alpha to 1-beta—technology node transitions happen relentlessly, and the first mover to reach a new node captures a 6–12 month premium pricing window. "Exercising discipline" effectively means "falling behind," and falling behind in this industry is fatal.
Consider a concrete example. Suppose Samsung decides to conserve CAPEX and delays its transition to the next-generation DRAM specification. But SK Hynix proceeds on schedule. What happens? Samsung gets shut out of socket qualifications on new Intel and AMD server platforms. Socket qualification, once lost, takes months to quarters to reclaim. In other words, the cost savings on CAPEX translate into months of forfeited revenue opportunities.
This is the textbook prisoner's dilemma. If all three players collectively restrain capacity additions, everyone benefits. But if even one defects, the other two suffer massive losses. So inevitably, every player arrives at the same conclusion: "I have to move first."
On top of this, the cost structure of fabs pours fuel on the fire.
A state-of-the-art memory fab generates billions of dollars in annual fixed depreciation. Once a fab is built, it must be run. The marginal cost of producing one additional wafer is extremely low, which means that running at 100% utilization is the only way to minimize average cost per bit—regardless of whether the market is oversupplied or not.
HDD factories have relatively modest capital investment requirements and offer flexible production scalability. When orders decline, you simply scale back the line. Semiconductor fabs are a different beast entirely. Shutting one down and restarting it involves enormous costs and lead times, and depreciation charges keep accumulating whether the fab is running or not. While the strategy of "cut production to defend pricing" can work, it comes at the cost of enormous losses.
To summarize: the HDD industry features slow technology transitions, high manufacturing flexibility, and a forgiving environment where waiting carries little penalty. The memory industry features rapid technology transitions, enormous fixed-cost burdens, and an unforgiving environment where waiting is existential. Even under the same oligopolistic structure, the fundamental competitive dynamics of each industry are so different that the implicit supply discipline that worked in HDD is structurally impossible in memory.
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Why the Memory Big 3 Cannot Exercise Implicit Supply Discipline Like HDD Players
Someone raised an excellent question: "There are only three DRAM suppliers—why can't they implicitly coordinate supply, like HDD makers do, to avoid over-investment?"
Intuitively, it makes sense. In an oligopoly, players should be able to read each other's signals and moderate accordingly. And indeed, after the HDD market consolidated into a three-player structure—Seagate, WD, and Toshiba—the industry maintained relatively stable supply discipline for a considerable period. So why doesn't this work in memory?
The core issue is that memory is an industry where those who wait are punished.
HDD is a mature industry. The pace of generational technology transitions is slow, and being late to adopt a new generation doesn't get you expelled from the market. This creates room for a tacit agreement along the lines of "let's all take it slow together."
Memory is the exact opposite. From DDR4 to DDR5, HBM2e to HBM3, 1-alpha to 1-beta—technology node transitions happen relentlessly, and the first mover to reach a new node captures a 6–12 month premium pricing window. "Exercising discipline" effectively means "falling behind," and falling behind in this industry is fatal.
Consider a concrete example. Suppose Samsung decides to conserve CAPEX and delays its transition to the next-generation DRAM specification. But SK Hynix proceeds on schedule. What happens? Samsung gets shut out of socket qualifications on new Intel and AMD server platforms. Socket qualification, once lost, takes months to quarters to reclaim. In other words, the cost savings on CAPEX translate into months of forfeited revenue opportunities.
This is the textbook prisoner's dilemma. If all three players collectively restrain capacity additions, everyone benefits. But if even one defects, the other two suffer massive losses. So inevitably, every player arrives at the same conclusion: "I have to move first."
On top of this, the cost structure of fabs pours fuel on the fire.
A state-of-the-art memory fab generates billions of dollars in annual fixed depreciation. Once a fab is built, it must be run. The marginal cost of producing one additional wafer is extremely low, which means that running at 100% utilization is the only way to minimize average cost per bit—regardless of whether the market is oversupplied or not.
HDD factories have relatively modest capital investment requirements and offer flexible production scalability. When orders decline, you simply scale back the line. Semiconductor fabs are a different beast entirely. Shutting one down and restarting it involves enormous costs and lead times, and depreciation charges keep accumulating whether the fab is running or not. While the strategy of "cut production to defend pricing" can work, it comes at the cost of enormous losses.
To summarize: the HDD industry features slow technology transitions, high manufacturing flexibility, and a forgiving environment where waiting carries little penalty. The memory industry features rapid technology transitions, enormous fixed-cost burdens, and an unforgiving environment where waiting is existential. Even under the same oligopolistic structure, the fundamental competitive dynamics of each industry are so different that the implicit supply discipline that worked in HDD is structurally impossible in memory.
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DAIR.AI
// Efficient Evolution of Web Agents //
Web agents waste a lot of compute on cyclic reasoning loops and unproductive exploration.
This new research introduces WebClipper, a framework that models web agent search processes as state graphs and prunes them into minimal directed acyclic graphs (DAGs).
The result: ~20% reduction in tool-call rounds while maintaining or improving accuracy.
They also introduce F-AE Score, a metric that evaluates the balance between accuracy and efficiency in agent trajectories.
Training agents on refined, pruned trajectories helps them develop more streamlined reasoning patterns from the start. Efficiency in agentic systems isn't just about faster models; it's really about eliminating wasted steps. This could significantly reduce costs as well.
Paper: https://t.co/GnvRt0VDq1
Learn to build effective AI agents in our academy: https://t.co/LRnpZN7L4c
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// Efficient Evolution of Web Agents //
Web agents waste a lot of compute on cyclic reasoning loops and unproductive exploration.
This new research introduces WebClipper, a framework that models web agent search processes as state graphs and prunes them into minimal directed acyclic graphs (DAGs).
The result: ~20% reduction in tool-call rounds while maintaining or improving accuracy.
They also introduce F-AE Score, a metric that evaluates the balance between accuracy and efficiency in agent trajectories.
Training agents on refined, pruned trajectories helps them develop more streamlined reasoning patterns from the start. Efficiency in agentic systems isn't just about faster models; it's really about eliminating wasted steps. This could significantly reduce costs as well.
Paper: https://t.co/GnvRt0VDq1
Learn to build effective AI agents in our academy: https://t.co/LRnpZN7L4c
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