$SLNH the market is obliterating DC companies with multi billion deals with hyperscalers. What did you think it would do to a company without a deal, and about to announce its results of billion shares of potential solution, it’s an easy short, and it’s easy to get shaken out by the price action. but fact, this DC AI spending is not slowing down, and they have the assets coveted by big players. Im betting they get deals for multiple sites. R/S fears are overblown. They have 6 months after NAS letter, plus 6 month extension if needed. The market also has a way of not letting companies fail that have value. Bought more today, will buy lower just as I stated in my previous post. I feel sorry for those that bought the pump, but you never buy pumps in small caps, you wait until they flush out.

following the trail: 1. Darkhorse $DRK adds partners for Data Centre exapnsion in TVA! Sept 23, 2026 2. US dept of energy announces Tennesee Vallaey Authority (TVA) power grid expansion Oct 13, 2026 energy.gov/articles/energy-d… nasdaq.com/press-release/dar…

Now that I have successfully rage baited what feels like every AI bear on X, let's systematically break down the most common counterarguments because they are very off the mark. #1. The AI trade is the same as the dotcom bubble or the 2008 crisis This is the most frequent rebuttal, and it is a lazy comparison. When you look under the hood, the numbers do not support it. Looking at the S&P 500 top 10 at each peak: March 2000: 53.6x trailing earnings, 9.1% net margin October 2007: 16.4x trailing earnings, 13.3% net margin Today: 26.5x trailing, 20.9x forward, 33% net margin Unlike the dotcom bubble, today's leaders have the earnings to support their build out. In the three years before the 2000 peak, the tech leaders' stocks rose 7.4x on 2.1x earnings growth, and the rest of the market was priced even higher: the Nasdaq traded at about 175x earnings. Today's AI leaders rose 2.9x on 3.1x earnings growth, and on average they pay about a fifth of the 2000 price per unit of growth. PEG on trailing three year growth: 2000: 1.6 to 5.7 Now: 0.2 to 1.6 2007 was never a valuation problem. It was a leverage problem, which I cover in #4. Yes, today's concentration at the top of the index is real, and it is higher than in 2000, but this time it is backed by profits. Today the top 10 are 40.6% of the S&P 500's value and 36.1% of its earnings. In March 2000 they were 27% of the value and only about 15% of the earnings. Put today's earnings at 2000's prices and the gap is massive: Nvidia at Cisco's peak multiple (178x) would be about $1,210 a share, a $29T company, 5.7 times today's price. Today's top 10 at the 2000 top 10's 53.6x would be worth $43T even on earnings excluding gains, against $28T today. The S&P 500 at 2000's forward P/E of 25.2x would be about 10,160, against 7,659. (See Chart 1) #2. Nvidia is the next Cisco, or the next Enron. From January 1998 to the March 2000 peak, Cisco's stock rose 7.6x while its trailing earnings rose 1.7x, ending at 178x pro forma earnings. Over the last 26 months, the same length of time, Nvidia's stock rose 1.8x and its trailing earnings 3.3x. It trades at 31x. Enron is an even worse comparison. In 2000 it reported $100.8B of revenue, much of it gross trading volume, and kept $979M of it, a 1% margin, while its stock traded at about 74x earnings. Its profits leaned on mark to market accounting and debt kept off its balance sheet, and it filed for bankruptcy in December 2001, then the largest in US history. Over the last 12 months Nvidia turned $303B of revenue into $193B of net income and $134B of operating cash flow, paid in cash by the largest companies in the world. #3. Today's companies aren't profitable These are some of the most profitable companies in history. Over the last 12 months Nvidia earned $166B excluding investment gains, more than Saudi Aramco's $161B in 2022, the largest annual profit any company had ever reported. Until 2024 only Aramco had earned more than $100B in a year. Nvidia, Apple, Microsoft and Alphabet now each do, even excluding gains. The suppliers are the same. Micron earned $85B at a 64% margin and TSMC $78B at 50%. SK hynix made $85B of operating profit, and Samsung made $80B of operating profit in the third quarter alone, a quarter only Aramco has ever topped. The ten largest tech companies of March 2000 earned $37B combined, at a 15% margin. Cisco kept 17 cents of each revenue dollar and Lucent 9. Nvidia keeps 55 cents and Micron 64. To be fair, memory is cyclical. These are shortage profits, and Micron's previous record year was $14B in fiscal 2018. (See Chart 2) #4. The AI trade is built on debt and is not sustainable The dotcom buildout ran on borrowed money. Debt owed by US telecom carriers rose from $158B in 1996 to $380B in 2000, and the junk rated carriers had negative operating cash flow as a group. The seven pure network builders (Global Crossing, Level 3, Williams, XO, 360networks, McLeodUSA, Winstar) owed $31.8B plus $6.5B of preferred stock, and six of the seven did not cover their interest bill even on their own EBITDA numbers. Telecom made up 55% of US junk bond defaults in 2001, and 23 telecoms went bankrupt by mid 2002. In 2000 WorldCom needed 3.2 years of cash flow to repay its debt, Global Crossing 8, and XO's cash flow was negative. Today Alphabet, Microsoft, Amazon and Meta owe $351B, hold $533B of cash, and could repay it all with about six months of cash flow. In the last year the 10 largest US tech companies generated $1.10T of operating cash flow and had $523B left after $574B of capex. At the 2000 peak, the top 10 tech names had about $34B of free cash flow, $66B in today's dollars, and traded at about 57x cash flow. Today it is 24x. 2008 was leverage inside the financial system. In 2007 financial sector debt was 144% of GDP, broker dealers ran 46x assets to equity, and Citigroup ran 18.6x and Bank of America 11.4x, both top 10 companies at the time. Today financial sector debt is 85% of GDP, broker dealers run 17x, and the S&P 500 top 10 run 1.8x. The debt that does exist sits at the edges, with names like Oracle. The four largest spenders are paying for this out of cash flow. (See Chart 3) #5. Demand is inflated, and they are overbuilding capacity like the dotcom bubble. AI provides no long term value and adoption is overstated. In 2000, WorldCom said internet traffic doubled every 100 days. In reality it doubled about once a year, and US backbone networks ran at about 10 to 15% of capacity. The carriers built for demand that did not exist yet, in the hope that it would show up. Yes, AI spend is larger now, but it sits against $2.3T of signed backlog at AWS, Google Cloud, Microsoft and Oracle. Demand is running ahead of supply: TSMC says demand is still far above its ability to supply, Micron says it has no line of sight to when supply and demand balance, and Nvidia's CFO expects supply to remain a bottleneck at least through fiscal 2028. Rental prices for the H100, a chip that shipped in 2022, are up 17% over the past year after halving from their 2024 peak. Hardware normally gets cheaper as it ages; over the past year we have seen the opposite, because demand is outrunning supply. The suppliers see this demand first. They would be the canary in the coal mine here, and they just reported record quarters: TSMC, ASML and Micron each posted the highest quarterly revenue in their history. TSMC raised its 2026 growth guidance at every update, to about 44%. ASML lifted its 2026 sales guide from €34 to 39B to €44 to 45B, says 2027 is close to fully covered with orders for its standard EUV machines, and has customers asking to order for 2029 and 2030. By press estimates a High NA machine costs about $380M and a standard EUV machine about $180M. Nobody books those years ahead on a whim. Memory makers are seeing the same and are signing take or pay agreements years out. Micron has 26 of them, some running to 2031, covering over 35% of its revenue through 2030, and over 75% of its 2027 output is already committed. Samsung's agreements run at least five years, and SanDisk has $93.9B of minimum contracted revenue. For comparison, in 2000 Lucent had committed $8.1B of financing to its own customers. Now the money runs the other way: Micron holds $12.7B of customer cash deposits, and ASML's long term customer down payments rose from €3.6B to €9.3B last quarter. These commitments are funded by the cash flow of the largest companies in the world. Generative AI reached 55% of US adults aged 18 to 64 within three years of launch. The internet was at 30% at the same point, and the PC at 20%. About 2B people use AI worldwide, 55.9% of US businesses on Ramp pay for AI tools, and Census data shows 23.8% of US businesses used AI in the past two weeks. Consumers spend about $40B a year on it, roughly $20 per user, so monetization has barely started. Physical AI is earlier still. Waymo runs about 500,000 paid rides a week, up from 50,000 in May 2024, and Nvidia's physical AI revenue passed $9B over the last 12 months. Each robot or autonomous vehicle needs far more compute and memory than a phone: Micron says an L4 vehicle typically carries over 200 GB of DRAM, about 24 times a phone, and expects humanoids to need as much. Counterpoint expects humanoid memory demand to grow 20x from 2026 to 2030. Volumes are still small; this layer of demand has barely started. (See Chart 4) #6. Today's tech leaders aren't smart This is the most insane one for me. The idea that random people on X can question the intelligence of the people running these companies is nuts. ASML's EUV machines fire a laser at a drop of molten tin twice, 50,000 times a second, creating a plasma hotter than the surface of the sun to print chips. TSMC is mass producing chips at 2nm. These companies turn science fiction into reality on a regular basis. The leadership is also nothing like 2000. Executives at Enron and WorldCom were convicted of fraud, and Congress passed Sarbanes Oxley in 2002 because of them. Since then every public company CEO and CFO has had to personally certify their company's financial statements. For people to throw stones at the intelligence of these leaders is just loony. In summary, I am very optimistic about the transformative nature of AI for our lives and our economy. So as I originally stated, I will continue to be long my picks and shovels favorites like TSMC, ASML, GEV and others. We are still in the early innings; don't let lazy fear mongering tell you otherwise. I am not saying "it is not the same" out of hope or cope. The math and data support me.

Now stacking sats with double the horsepower.

MORGAN STANLEY: POWER IS THE SCARCEST ASSET FOR AI/HPC EV/Watt range from $0.57 to $6.24 for BTC-to-HPC companies $GLXY leads the pack followed by $HUT, $CUFR, $APLD, & $RIOT

JUST IN: Global index fund giant MSCI approves a new rule that could exclude Strategy $MSTR and Metaplanet $MPJPY from its indexes as non-operating companies. JP Morgan said this index exclusion could trigger outflows of about $2.8 billion from Strategy $MSTR. The new rule's changes take effect on December 1st. 👀

Investing thesis. 1) Chop until midterms. S&P 500 10,000 2027 target. 2) Rates coming down. Yield curve normalizes: Bull steepener. 3) Breadth will expand. Look at S& P 500 equal weight. 4) expect flows into interest rate sensitivity areas. Financials, Housing, Real Estate, Small Caps, Consumer Discretionary. 5) high quality AI names still have room to run. 6) Crypto enters a Supercycle. 7) ignore the noise. Have a great weekend

Russell 2000 Seasonal Weakness Ends Now Down 11% from 8/14 high textbook seasonal weakness. Small caps bottom mid-late Oct, then rally into year-end. R2K perking up today, right on schedule. Don’t fear Octoberphobia. October is the best month to buy small caps. $IWM $RUT jeffhirsch.tumblr.com/post/8…

AI Sector extremely Oversold... $SLNH $MARA $IREN