OAI will probably release the Astra model this week and will likely pump the sentiment around AI for science. The recent ERs also showed exciting results of AI accelerating drug discovery etc. ChatGPT helped me build a watchlist in the weekend My favorites are $TWST, $TEM, $GH.

I think today and tomorrow would be great opportunities to observe which software names are just the short covering of hw/sw pair trade vs real buyer showing up. ✅ $SNOW $DDOG $MDB $CRWD $PANW $INOD ❌ $NOW $WDAY $ADBE $INTU $CRM $TEAM

As I expected, Trump taco during the weekend as US10y is at max pain. NQ bounced 500 points since then. Sold all $SOXL at $148, which was bought at $137 in Friday post-market. Still can’t rule out the path of a fake breakdown of 28200 (like 27500) with a quick reversal this week(Wyckoff accumulation). Will patiently wait after Wednesday to decide long or short.

NQ is at key level 28200, AAII analysis is super bearish, NAAIM exposure retraced a lot, market breadth is good, US10Y is at 52 week high and Trump’s max pain point, market priced in July FOMC 25bps hike at 40% chance, the rest of mags already got punished just in case they gave a similar negative FCF as GOOG. HF net leverage at 78%. Seems like all negative catalysts are priced in already and I think the setup supports a short term bounce at least, similar to days after 11/20 last year, but it’s hard to imagine how the path looks like. My favorite setup is a fake breakdown 28200 then a quick recovery.

NQ is at key level 28200, AAII analysis is super bearish, NAAIM exposure retraced a lot, market breadth is good, US10Y is at 52 week high and Trump’s max pain point, market priced in July FOMC 25bps hike at 40% chance, the rest of mags already got punished just in case they gave a similar negative FCF as GOOG. HF net leverage at 78%. Seems like all negative catalysts are priced in already and I think the setup supports a short term bounce at least, similar to days after 11/20 last year, but it’s hard to imagine how the path looks like. My favorite setup is a fake breakdown 28200 then a quick recovery.

Good expert call on Bloom Energy $BE with a former VP at Plug Power - pretty bullish Hyperscalers did not evaluate Bloom against gas turbines and select Bloom. They selected turbines, discovered they could not get them, and Bloom was the alternative that checked enough boxes. Gas turbines from Mitsubishi, GE Vernova, Siemens and Hitachi remain the incumbent workhorse, but his read is that if the order is not already placed, you are not energizing before 2030. Reciprocating engines sit in the same position: Caterpillar, Jenbacher, Generac, Wärtsilä, all effectively sold out. Transformers, switchgear and substation equipment carry 60 month lead times. What Bloom offered was availability plus modularity. A claimed 90 day time to power on smaller blocks, which he believes is credible at modest scale and unlikely at large scale, plus a build-as-you-go capital profile. Turbines want a single large plant. Behind-the-meter deployment wants building blocks you can add to as long as you have secured the land and the gas tap. > Why the Turbine OEMs Will Not Simply Close the Window Turbine and engine OEMs are deliberately not expanding capacity. They suspect the order book is double and triple booked, and they fear being left with stranded factory capacity when projects fail to reach FID. His analogy is the semiconductor capacity cycle, where consecutive quarters of poor absorption caused structural damage. Their posture, as he characterizes the consensus from trade shows and industry conversation: you cannot buy it from me, you cannot buy it from my competitor, you will wait. If that discipline holds, Bloom's window is measured in years rather than quarters, which is materially longer than the market appears to assume. Bloom's product is closer to a solid state electrochemical device than a precision machined turbine, drawing on an entirely separate supply chain that can be ramped faster. > Levelized Cost: A Premium, But Not a Prohibitive One He built his own LCOE model rather than relying on published work, which he found rested on unexamined assumptions. His output: Gas turbine: roughly 4.5 to 7 cents per kWh Bloom: just over 7 cents unsubsidized, below that with federal incentives Reciprocating gas engine: roughly 8 to 10 cents Diesel: high teens to mid 20s The critical observation is that this is not a 3x premium for speed. That pattern collapses the moment supply normalizes, because buyers drop the expensive option as soon as the cheap one is obtainable. A single digit cent premium does not collapse, because the hyperscaler business case still clears at that price. The offset to Bloom's higher capital cost is efficiency: 60 to 65 percent, against roughly 55 percent for a gas turbine and roughly 45 percent for a reciprocating engine. Bring capex down and the LCOE gap narrows or inverts. > Where Bloom Ranks Today Asked to stack rank for a hyperscaler buyer, he puts Bloom third, behind turbines and engines, purely on track record rather than physics. His analogy: you know exactly what you get from a Caterpillar engine or a GE Vernova turbine the way a Toyota buyer knows what he is getting. No buyer has that reflex for a Bloom box yet. The open questions the buying community has not resolved: real world availability, whether maintenance cadence matches or beats turbine schedules, and the roughly 10 year stack replacement cycle. On that last point he offers a mild positive read-across, noting that in the PEM industry stack rebuild intervals came in longer than originally modeled. The path to second or first place requires two things running together: two to four years of collective industry uptime data, and capex reduction. Oracle, Nebius, Brookfield and AEP are the proof points that will settle it. On whether they will work, he says "the jury is still out," while noting early evidence reads favorably. > Non-Combustion as an Unpriced Permitting Asset The Bloom box does not combust natural gas. It runs an electrochemical reaction. The consequences stack up in a specific and useful way: NOx, SOx and particulate emissions at or very near zero, leaving local air quality unaffected Roughly 65 dBA at three feet, which he compares to a lawnmower at fifty feet, meaning nearby highway noise dominates Zero net water consumption, with startup water recycled as steam Materially easier local permitting Each of those neutralizes a specific community objection, and the pushback is accelerating. New York State's one year moratorium is the marker he points to, alongside complaints in other jurisdictions about power draw, water use and air quality. His honest caveat: to date these attributes have played essentially zero role in purchase decisions. Availability and cost drove everything, and he assumes very little of Bloom's performance so far reflects environmental considerations. If pushback becomes electoral, and he says he is watching whether candidates start running on it, then zero emission on-site generation stops being a nice-to-have and becomes the only permittable option across large parts of the country. He expects this to bite first at the 20, 50 and 100 MW sites going into actual neighborhoods rather than at the West Texas mega-campuses. > Market Share Trajectory Data center demand forecasts he is working from run 40 to 60 GW per year. Bloom's share today sits in single digits. His trajectory: Five years: 15 to 18 percent Ten years: 25 to 28 percent Upside case, if emissions constraints become binding in enough jurisdictions: 40 to 50 percent The constraint that drives the upside case is geographic. Not everyone can replicate what Microsoft and Chevron are doing on the West Texas gas fields. Once data centers have to disperse into places that care about permitting, the zero emissions conversation becomes unavoidable. > The Bear Case He Actually Respects Execution, not demand. He flags this above everything else. Bloom has roughly 1.5 GW deployed against a backlog he characterizes as roughly 20 GW. On Sridhar's own description of the factories, that a visitor will see build activity and factory expansion activity running simultaneously, the expert's reaction is blunt. To an industrial engineer, expanding while still trying to build is a very risky proposition. Doable, but it is the precise point at which fast-scaling companies break, and he notes this is the classic failure mode for startups that find themselves in this position. Q1 was clean. The Q2 print, due around the 28th, is the next checkpoint on whether execution is holding. The secondary risks are demand-side and none of Bloom's own making: hyperscale capex circularity, bubble risk, and whether community pushback genuinely slows the build or simply reroutes it to Texas. > Scandium: Directionally Fair, Materially Overblown On the short thesis that Bloom cannot secure enough scandium, he says the report has some points but overstates them. His rebuttal runs on three tracks. Cost sensitivity. Scandium is a dopant in the zirconium ceramic electrolyte, used at very low concentration, valued because it tolerates the 800 to 900 degree operating temperature. Even if it were 2 percent of materials cost, which he considers extraordinarily high for a dopant, a doubling in price takes it to 4 percent. Bloom likely has the pricing power to pass that through, and a half point efficiency gain would offset it in LCOE terms. His conclusion: more price risk than supply risk over the next couple of years. Supply structure. Scandium is almost never mined primarily. It sits in the tailings of titanium, cobalt, aluminum, iron and lithium operations and is generally left behind. The binding constraint is processing capability, not geological availability, and that processing capacity is being built with national security tailwinds behind it. Scandium-aluminum alloys matter for 3D printing, fighter aircraft skins and missiles, which places it squarely in the critical minerals policy agenda. Company mitigations. Bloom has spent 20 years reducing scandium loading per gigawatt. He located a patent application substituting cerium and yttrium, both more available, and Bloom holds IP on recovering scandium from mine tailings. He reads Bloom's willingness to address the topic directly, rather than deflect, as evidence they take it seriously rather than evidence of vulnerability. Non-Chinese supply exists: he points to Sumitomo's Philippines cobalt operation, which publicly identifies Bloom as a customer. Bloom does not disclose suppliers, and the short report's supply map traces its merchants back toward China. > The Competitive Set FuelCell Energy. Molten carbonate rather than solid oxide, but functionally similar: high temperature, slow start, direct natural gas, suited to stationary baseload. Why they never scaled into this comes down to inertia and strategic drift. Their historical focus was a trigeneration box producing hydrogen, power and heat, deployed for applications like Toyota Mirai fueling at the Port of LA. When hyperscale demand arrived they had nothing to show. His read on the pivot: they saw the multiple Bloom trades at and asked why not us. Ceres Power. UK based, probably second globally in solid oxide IP. Pure licensing model, which means most licensees stay invisible. The disclosed one is Weichai, moving from small C&I units up to hyperscale scale. He doubts Weichai exports into the US successfully but expects success in China. Microturbines and aeroderivatives. TurboCell in the BorgWarner orbit, plus aero engine derivatives repurposed as stationary generators. Everything gets a look right now because buyers are desperate for speed to power. Stealth entrants. He assumes several exist that have not been announced, precisely because Ceres-style licensing deals do not get publicized. Asked whether Bloom owns the US market today, his answer: "Pretty much now they do." > Why Hydrogen Never Worked, and the Read-Through to Plug Useful because he lived it from the inside. Delivered liquid hydrogen bottoms out near $8 per kilogram. Run that through the efficiency stack and fuel cost alone lands around 54 cents per kWh, before equipment, labor, warranty or service. He stopped modeling at that point. Even at a hypothetical $4 per kilogram you land near 25 cents, still a non-starter against a 7 cent Bloom box. Plug built a 3 MW unit at its Latham campus that passed Microsoft's full backup generator protocol, the first non-diesel, non-gas system ever to do so. Microsoft publicized it as a breakthrough and then walked away inside six months once the cost picture clarified. Plug's INVISTA facility was outfitted to build stationary modules for the data center market and effectively none of it shipped. Three sites total, including Calistoga in PG&E territory for public safety shutoff backup, and an EV charging site that existed only because a grid connection was unavailable. Both are showpieces that draw tours. Neither is repeatable. source: Tegus

1. Ads spending growth is proportional to the GDP growth, as long as the economy is growing ads spending will go up 2. Ads is not a zero-sum game, as long as the ROI can be justified, it’s a win win game for both advertisers and the platform. 3. Small business has high barriers of leveraging ads to acquire customers, AI can lower that barrier significantly , no matter it’s creating ads, user targeting, campaign management, optimization with A/B test, this is a big market needs to be served.

1. Ads spending growth is proportional to the GDP growth, as long as the economy is growing ads spending will go up 2. Ads is not a zero-sum game, as long as the ROI can be justified, it’s a win win game for both advertisers and the platform. 3. Small business has high barriers of leveraging ads to acquire customers, AI can lower that barrier significantly , no matter it’s creating ads, user targeting, campaign management, optimization with A/B test, this is a big market needs to be served.

Actually, Google is turning non-monetizable queries into monetizable ones by leveraging AI search. In the past, there were many search queries where Google couldn’t place ads; now they can. That’s why advertisers feel more queries are matching. However, I think this is the right direction for Google to gain more revenue and for advertisers to get better ROI, though it will take time for Google to iterate and boost the CTR/CVR of these AI search ads to catch up with the traditional search ads.

slow down my ass 😂 The street underestimated the determination of CSPs fighting the AI race, as I mentioned before: “Aggressive capex only means pressure on the stock price in the short/mid term. But losing the AI race could mean losing the business forever.” $GOOG

Will be back to the US next week. Talked to a few PMs during my trip in the last two weeks. I’d like to share some interesting findings: Sentiment: Overall very panicked and confused. Positioning: 1. Shanghai HFs are extremely long on memory names, partly due to the TRS restriction I mentioned a few weeks ago. They are quickly selling CN semis across the board and buying DRAM ETFs to lower margin pressure. 2. HK HFs are mixed and divided; bulls and bears are balanced. 3. US LOs are waiting—not about stock prices but still don’t believe LTAs can turn memory names from cyclical to growth valuations. 4. Macro HFs sold all of their memory/semi positions. Interesting points from both sides: Bulls: 1. Supply chain checks suggest prices and margins will remain higher for longer. 2. AI capex in 27/28 will grow much higher than most expected. 3. OAI/ATH’s ARR shows no signs of plateauing. Codex’s WAU is growing crazily right now. 4. Kimi K3’s tech report literally suggests every semi component is a bottleneck 😂 5. No macro risks; CPI/PPI much cooler. 6. Even if memory spot prices can’t go higher, these memory companies can do large buybacks or dividends to support the stock price. 7. OAI/ATH is hiring a large team of solution engineers to quickly build vertical solutions (finance/healthcare/legal) to find the next S-curve beyond coding. 8. Even if memory names fade, the entire semi sector will remain intact. Bears: 1. Higher memory prices are not sustainable and will be demand destructive. Clients will push back on further price hikes, and even the government may step in to force massive production expansion. 2. Memory prices will peak in Q4. 3. No doubt on 27 capex, but 28 capex budgets are clouded. 4. Even if fundamentals are solid, the position is extremely crowded and Korean retailers’ leverage is a huge concern. 5. Even though CSPs’ capex planning is aggressive for 27, a large portion of deliveries will be delayed due to power supply constraints. 6. No intermediate story of fast AI application adoption like AI coding. 7. Higher prices and more LTAs during the upcycle can’t prove memory names aren’t cyclical anymore. We need to see resilience during the downcycle to prove that, like memory names keeping the lower bound of margins in a downturn. 8. Memory is the core of AI: if traded memory dies, then everything dies. 9. Memory has no difference vs. other commodities such as silver, oil, or lithium carbonate. When they peak, their narrative and fundamentals all look fucking good 😄

as planned, since SOX didn’t reclaim the 50d EMA today, I sold most of the semi position I recently bought with small profits. For MAG7, I’m holding common share and leap calls. Sold 2x ETF, short term calls and half of my AAPL leap calls(+165%) to lower the risk before the ERs.

SOX dipped to 11867 today, which is a critical low from 06/09 and 07/07. I will give it 1-2 days to reclaim the 50d EMA. Otherwise, I have to stop out any non-Mag7 positions. My thoughts are that semis should remain in a consolidation range instead of any directional breakout before the Mag7 ER, as bulls and bears are debating AI capex and ROI heavily with some balance. Any breakout of the range before the Mag7 ER means the market has reached some weird consensus for reasons we don’t know, and we should be very cautious.

roughly -30% from ATH because of overtrading with over sized position. My LEAP calls account is down only 10% from ATH, with +150% YTD gains still. The difference is much lower trading frequency(patience) + proper position sizing(risk management). It’s not about leverage.

$TSM’s earnings look great but GM is lower than buy-side expectations. But like I said in the interview with 168X, I have great respect for this company as they care about the ecosystem. If they want, they can raise the prices easily to get a higher margin, but they chose not to. Compared to the greedy Samsung, who is always targeting 99.99% GM 😂. I don’t think this is sustainable.

KOSPI is down 7%. The Bank of Korea just hiked 25bps to 2.75%, its first rate hike since January 2023 June inflation ran 3.2%, the fastest in over two years, with the BOK pointing to the chip boom fueling sticky prices and growth strong enough to handle higher rates Institutions and foreigners have absorbed 7.3 trillion won of stock in the last two sessions while retail capitulated with the fifth largest net sell on record The BOK itself says this cycle is different, structural AI demand and HBM supply constraints, not a normal chip upcycle $EWY $SKHY