pitandhummus

1.7K posts

pitandhummus

pitandhummus

@pitandhummus

an investoooooor; only the paranoid survive; disclaimer: not investment advice, views are my own and just opinions.

Katılım Şubat 2021
3K Takip Edilen383 Takipçiler
pitandhummus retweetledi
Ronit Pereira
Ronit Pereira@Ronitper·
Charlie Munger’s story on Crashing Plane. “A plane was crash landing due to engine failure. The pilot announced - Those who can swim, go to the right wing, there’s an island two miles away.” “Those who can’t swim, go to the left wing…and Thank you for flying Air Italia.”😂
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TechStockFundamentals
TechStockFundamentals@TechFundies·
$MSFT -> Outlook Copilot fumbling the most basic use case for now?
TechStockFundamentals tweet media
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pitandhummus
pitandhummus@pitandhummus·
@viggy_krishnan Pattern: investors litigate a granular debate (A vs B share split, will X disrupt Y, newcomer vs incumbent) but a much larger, simpler force is the actual driver Brainstorming (non-zero sum thinking): Nvidia vs Broadcom/ASICs Hyperscalers vs Labs/Neoclouds Uber vs Waymo/Tesla
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pitandhummus
pitandhummus@pitandhummus·
@citrini i always travel with my wife because one of us can read and the other one can write
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Citrini
Citrini@citrini·
They really weren’t joking about the literacy rate going down
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Pod Risk Manager
Pod Risk Manager@sadandlonely_69·
The two AV stats that jump out at me from this reporting season are 1) $AUR talking about its trucks annualizing to a 225k mile rate. Insane. At 60mph that takes a human 10.3 hours a day 365 days a year, 2) $UBER NYC farebox rising 7.6% in Mar. Accelerating its biggest mkt
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Quantіan
Quantіan@quantian1·
If you donut a handful of companies—SpaceX, OpenAI, Oracle, some shittier supply chain/power/DC buildout names—and steal a couple hundred billion of EBITDA from SaaS companies, though, then the math basically foots and you’re paying around SPX mults without heroic assumptions.
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Quantіan
Quantіan@quantian1·
My napkin math on the "AI bubble" question. Slice the trade up into baskets- labs, hyperscalers, chips, memory, neoclouds, power, whatever. Observe how much each basket valuation has gone up since ChatGPT release, and comp vs. how much out-year EBITDA estimates have gone up.
Citrini@citrini

People keep confusing a bubble with “stocks go up and get overvalued”. A bubble is when when a prevailing trend and a prevailing misconception about that trend interact reflexively, each reinforcing the other until the gap between perception and reality becomes unsustainable. A bubble is not when everyone realizes that right now every iota of AI demand eventually, at some point upstream, must move through memory OEMs. Nor is it when estimates continue rising because things are better than expected. And it’s not just when stocks trade expensive to historical valuations. The reason behind the moves in the AI infrastructure layer so far have been simply that we don’t have enough. They’ve been driven by the fundamental reality more than the perception of the future. It’s why the bulk of the most bullish parts of this cycle have been lumpy and centered around earnings season when companies uniformly come out and confirm there’s still not enough. In the bubble, the reality is driven by the market - not the other way around. Everyone keeps saying “people are gonna freak out if it’s not a bubble!”. I think that’s silly, we have a transformative new technology that needs crazy capital to fuel it coming to fruition, that has and always will result in a bubble as long as we have financial markets. But if you want to call the top in a bubble, you need a much stronger view on what the misconception is and what negative catalyst forces broad perception to align with realizing it than you do on valuation.

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Bread Crumbs Research
Bread Crumbs Research@breadcrumbsre·
A high profile, almost legendary investor sells the biggest software stock 🤔
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pitandhummus
pitandhummus@pitandhummus·
@pmje73 Boeing / Airbus is an interesting case study in this regard. It's likely the lowest returning duopoly.
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Paul Enright
Paul Enright@pmje73·
A few years ago I mentioned on a podcast that “biz quality” is overrated as an analytical tool and industry structure/barriers to enter the industry are more important. A simple case study of the fragmented SW industry vs the oligopoly like semi and components sub sectors shows how these industry structures can just sit there for years waiting for an internal or external catalyst to come along and expose those structural weaknesses or strengths.
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Admiral Waterworld
Admiral Waterworld@WaterworldCapi1·
@P_Remarks They took up cap-x a lot. Wouldn't call it a really good qtr. I am bullishly inclined on $MSFT.
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pitandhummus
pitandhummus@pitandhummus·
@evrgn11112231 Didn't try, in part default and in part apples to apples (I run the "best" model version across all of them). Router makes complete sense for consumer AI use cases.
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pitandhummus
pitandhummus@pitandhummus·
@evrgn11112231 App; Gemini was fast and okay, GPT slow but good, Claude fast and good, Meta slow and decent
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pitandhummus
pitandhummus@pitandhummus·
@evrgn11112231 tried using it during travel, what I would consider a prime consumer use case for Meta AI; my shallow vibes: - too slow; maybe due to "Thinking"? - answers not as good yet imo; maybe search isn't great yet? feels like it should be wicked fast (something google has figured out)
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pitandhummus
pitandhummus@pitandhummus·
@pmje73 So, for example, evaluate this company as an investment using only its filings and transcripts?
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Paul Enright
Paul Enright@pmje73·
I’ll give some examples here to make this less abstract. When I am training analysts I want to constrain their aperture and their inputs, but completely unconstrain (is that a word) their outputs. Others want to do the inverse. I believe that if you develop good habits in a constrained environment your outputs will improve.
Paul Enright@pmje73

If you want to understand how different people make different investment decisions you just need to learn what constraints they place upon themselves or are placed upon them by others.

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Buyback Capital
Buyback Capital@Larryjamieson_·
the thing about buybacks is that if you don't have terminal value problem they can be pretty good if you do have a terminal value problem, they are not very good it's hard for a management team to admit they have a terminal value problem and return cash another way
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Citrini
Citrini@citrini·
@CL207 @zephyr_z9 @jukan05 Teradyne has a sick segment that sells to Amazon for their Vulcan robotic arm. Ouster has solid LiDaR. FANUC probably best platform for robotic arms. As far as humanoid OEMs most are either Chinese or private.
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Citrini
Citrini@citrini·
Google should go all in on robotics imo
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pitandhummus retweetledi
Bill Gurley
Bill Gurley@bgurley·
I find this conversation foreign - along with the argument that we are "data center constrained" or "energy constrained." Historically, in markets - price is the leveler of supply and demand. If you have a constraint, you price higher - you don't have "surplus demand." But in this market, VC$$$ act as subsidies (as they did in consumer internet). Everyone believes if they have high growth they get unlimited VC$$$. The biggest fear becomes losing market share. So "growth at all costs" becomes the game on the field. With that reality, you are always going to have some constraint, because you are "knowingly" choosing pricing that is out of whack with balancing supply/demand. It will continue until the major players feel they are forced to reconcile unit economics and profitability (as eventually happened in ride sharing when Lyft went public). Until then, you by definition have constraints. We can’t disentangle true demand from subsidized demand yet. Some of the incremental demand is being engineered by the excessive VC$$$ forced into the system, and the competitive dynamic between two companies that are losing massive amounts of money. No one can argue they aren't losing tons of money. Amazon and Uber maxed out around $2B a year. These companies could lose $10B on more in 2026.
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