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Conversations with the world's best investors, founders & domain experts / hosted by @patrick_oshag / part of @colossusmag

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Matthew forecasts an unprecedented natural gas shortage starting in 2028. He names four winners if he's right: gas producers, midstream, nuclear, and solar. (1) Natural gas producers in the U.S. and Canada should be clear winners, especially those with future inventory of wells to drill without infrastructure constraints. "Expand Energy is probably at the top of that list. They control 70% of remaining core Haynesville wells. The stock has dropped. The assets have not changed. It has some of the highest quality rock in the country." "Choosing the specific companies with real, rather than perceived or merely disclosed, high-return well inventory will matter. Ask to see engineered future wells on a map. Ask for the timelines." He also names $CRK, and $RRC ranks first in Appalachia. "Range has significant room to grow production and materially grow returns to investors." (2) Vital midstream assets should be well-positioned to benefit. "Natural gas infrastructure development has lagged the entire 'powering AI' thesis, the imminent 20 Bcf per day growth in supply, 20 Bcf per day of approved LNG project growth, and more than 5 Bcf per day of natural gas-fueled generation growth. The systems strategically positioned to grow throughput and deliverability will win." He names $KMI, TC Energy ($TRP), and Pembina ($PBA). (3) Large-scale nuclear is the only scalable path to avoiding acute baseload electricity shortages. "There's no bridge fuel other than solar and wind, because currently natural gas is the only flex fuel to get us to when we can bring on nuclear. Large scale nukes are the only solution that makes sense, which points us primarily to the AP1000 Westinghouse units. Westinghouse is deeply undervalued within Cameco today." "SMRs are a band-aid on a bullet wound. A nuclear renaissance is coming." Ha names Cameco ($CCJ) and $BWXT. (4) Solar and batteries are critical to the reliability of the U.S. grid. "Solar assets stand to benefit from a windfall. The marginal plant's fuel price is rising while sun costs the same. Residential solar is really one of the only ways to protect yourself from what you pay for electricity at your house once gas gets really tight. We think residential solar grows exponentially from here, even without tax incentives." "That margin expands. The market has not priced it." He names $XIFR and $CWEN at utility scale and $RUN in residential.

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159,427 просмотров • 2 месяцев назад

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Gavin Baker (Gavin Baker) says the disaggregation of inference can extend GPU useful lives from 3-4 years to 10-15. That may single-handedly save private credit and reduce the financing rates for GPUs, which will drive demand and help finance the build-out. "The disaggregation of prefill and inference is going to be amazing for the useful lives of GPU and may single-handedly save private credit. Private credit is in pain from these SaaS loans. But there's a lot of private credit in GPUs too. They were underwriting that to 3-4. The disaggregation of inference means that these GPUs are going to have 10 or 15-year lives. The AI skeptics are like, "Oh, these companies are all cooking their books. The useful life of a GPU is only a year or two. The useful life of a CPU is only four years because the rapid technological change." No. What rapid technological change has done with the disaggregation of prefill and inference is you can put a Cerebras system or Groq LPUs effectively in front of a Hopper or even an Ampere, use that Hopper and Ampere for prefill, and extend the useful life of that GPU until it melts. This is going to be really good for the whole private credit industry. It's gonna help finance the AI build-out. Because if you can start to finance GPUs at 5% or 6% instead of – I think CoreWeave's lowest financing was low sevens – that actually mathematically changes the cost to finance this build-out."

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211,336 просмотров • 4 месяцев назад

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SpaceX reportedly accounts for ~45% of D1 Capital's venture and private equity book. At a $1.75T IPO valuation, that stake would be worth about $20B. When we spoke with Dan Sundheim in February, here's how he described the investment: "SpaceX was pretty obvious to me that the launch business, at a minimum, was going to be a very good business. What they had achieved, just from an engineering perspective, was insane. If I could buy a company that had achieved the most amazing engineering feat I'd ever seen, at some multiple of revenue with very little cash burn at that point, I didn't know what was going to come, I just knew that the skew was very good. The initial prognosis was just always that they were going to be a low cost provider of launch. Starship is a game changer, which we knew about fairly early on, but didn't know if it would work. And what that means, very simply, is that the cost of launching everything goes down dramatically, 97% or whatever. And the engineering that they've done with the satellites to harness solar power and be able to deliver really high-speed bandwidth has surprised me to the upside. And there's a lot of software that goes into that too, just given these networks of satellites are all communicating. The ramification of that is that the telecom market globally is now the TAM. They've come so far down the cost curve, I think that in a relatively short amount of time they're going to be dramatically cheaper than any other form of delivering broadband."

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140,246 просмотров • 4 месяцев назад

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In 1960, 60% of young Americans one year into their first marriage owned their home. By 2023, that had fallen to 42%. Walter Russell Mead (Walter Russell Mead) has a theory for why homeownership feels out of reach, and how we can fix it: "The single family home in the suburbs replaced the single family farm. Think about not only building the freeways and the highways, but subsidies through the tax code so that municipal bonds are tax-free, which means towns can build the infrastructure that attracts developers and homeowners, who then raise the value of the property, so you can repay the bonds out of the higher property values the infrastructure has created. Tis kind of wealth-creating machine. Right now we seem to be reaching the limits of that wealth-creating machine, because it's just too expensive for the average person to buy a house and land close enough to where you work so the commute isn't killing you. Homeownership is one of the real big problems for why young people are unhappy with the economy. Between remote work and hybrid work and self-driving cars, if you only have to go into work once or twice a week, you can work farther out. If you expand the commuting radius from 40 miles to 75 miles, the amount of land that is developable for housing goes up with the square of the radius. It's geometric. Information technology appropriately deployed can open up for another two generations this wealth-creating machine."

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12,679 просмотров • 16 дней назад

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Gavin's takes on Microsoft, Google, Meta, & Amazon: Microsoft ($MSFT): "I like Satya, I admire him. He's an exceptional CEO, and I give him a lot of credit for the decisions he's made. But he did go from, "We're going to make Google dance," to being the product manager of Copilot in 3 years. The decision Satya is making now, which the market has punished him for, but I think is the right decision — who knows how fast Azure could be growing if they were willing to just sell GPUs to OpenAI. 'We're going to use our compute internally to make our own products better.' One reason Copilot was so bad, or has been so bad, is that there wasn't enough compute available. They're fixing that. He's making good decisions that are risky decisions, to position Microsoft for this world where frontier models are no longer API-accessible. It's a really courageous decision that I give him a lot of credit for. Microsoft probably would be an $800 stock today if they were using their GPUs to serve solely OpenAI and Anthropic's capacity instead of using them for their own products." Google ($GOOG): "Google was incredible last year because they had that TPU advantage, which is now gone. The reason I think they're still in a great position is they have the most compute of everyone. We talked about the value of installed bases being higher as a result of shortages — they have the biggest installed base of compute. Google I/O is this week. If they don't release something that even slightly leapfrogs OpenAI and/or Claude, that's interesting. It's not a disaster for Google, it's just interesting. Between the amount of data they have, the YouTube data, the amount of compute, the search business — Google's never not going to be in a good position. You see that with GCP going crazy." Meta ($META): "You've got to give Zuckerberg immense credit, for what he's done in terms of making Meta an AI-first company internally. He is the only one of those true internet giants to have done that. I give him a lot of credit for paying up when he did for contracts, that talent. And Muse was a really big upside surprise. It was the first model from MSL, and it's not on the Pareto frontier with xAI, Google's one entrant, OpenAI and Claude, but it's pretty close. That was very impressive to me. So Meta is in a better position — still not as strong of an absolute position as Google, but a better position." Amazon ($AMZN): "Amazon is in a really strong position because of Trainium. You're going to see real P&L efficiencies from robotics over the next 18 months in their retail business. I actually think Nova — their internal models are not where Muse is, but they're better than they get credit for. The two companies who are the most deeply engaged with startups are Amazon and Nvidia by a mile. It's going to end up being a pretty big advantage for Nvidia and Amazon — with Google right behind them — to have this engagement that you just don't see from these other hyperscalers."

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52,492 просмотров • 4 месяцев назад

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In 2016, five founders and a deck walked into Benchmark to pitch a hardware company. Eric Vishria didn't want to take the meeting. Benchmark hadn't made a semiconductor investment in ten years, and he remembers thinking, why are we even going to a hardware pitch? This is crazy. The team was excellent and the first slide said GPUs actually suck for deep learning. They just happen to be 100 times better than CPUs. This was pre-transformer. OpenAI was a weird research lab. The TPU hadn't been announced. Nvidia was worth $40 billion, not $4 trillion. The first question in 2016 was whether AI was even a big new workload. There had been many attempts at specialized chips for other things that simply never ended up mattering. Benchmark had conviction that this one would. The second question was whether the workload introduced a new constraint. It did. AI benefited massively from the parallelism of GPUs, but GPUs didn't solve the communication between cores. This was a communication-bound problem, and nothing on the market addressed it. There are only three ways to speed up deep learning in hardware, then and still today. More cores. Faster communication between cores. Memory closer to the compute. Their pitch was to take all three to their logical maximum at once. A single wafer-scale chip with 450,000 cores and 20 gigs of SRAM, so the system never has to leave the chip to reach memory, and every core sits on the same wafer, so communication between them is as fast as physics allows. It was the best you could possibly do. As soon as Eric heard the idea, his reaction was, "of course". Engineers had been attempting a wafer-scale chip for 50 years. Every attempt had failed. Cerebras got a working chip on the first try. Then came the long middle of the story that nobody romanticizes, the years of work required to turn a scientific achievement into a business. "In software, if you have that logical block diagram of why it works and everything else, you're 80% of the way there. And it's a matter of go-to-market execution. In hardware, you're like 2% of the way there." A chip that powerful has to be packaged, heated, cooled, programmed, and sold. In 2019, Eric sat in a board meeting watching the chip melt. The company had raised roughly $500 million by then, and the thought running through his head was "holy shit, we're going to lose all this money." The company kissed death three times. Virtually every respected semiconductor investor passed. People made fun of the early customers. Today Cerebras is worth more than $50 billion. Eric said it years before anyone knew how it would end. Whether Cerebras worked or not, it was an effort worth venture capital. Try to build the thing people have failed at for 50 years, when there's finally a reason it could work. Hardware is hard. This team "just never fucking quit".

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16,120 просмотров • 1 месяц назад