slovak

1.9K posts

slovak

slovak

@slovak83

Katılım Kasım 2010
1.4K Takip Edilen169 Takipçiler
slovak
slovak@slovak83·
@OnodaCapital Can you explain math on why cheap? Especially including incremental funding required?
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Hiroo Onoda
Hiroo Onoda@OnodaCapital·
King Leopold had ~25% of his longs in crypto miners Eo25 Think the whole space is still cheap but realizing lot of people (mostly LOs) think it’s a sleazy / degen space. Will change when cash flows show up
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Brett Caughran
Brett Caughran@FundamentEdge·
A big pivot from Ken Griffin on AI: “Number one is, in the last few months, there has been a step change in the productivity of the AI toolkit. It is profoundly more powerful than it was just nine months ago. And for us at Citadel, that has allowed us to unleash a much broader array of use cases for AI. And it has been really interesting to watch, to be blunt, work that we would usually do with people with masters and PhDs in finance over the course of weeks or months being done by AI agents over the course of hours or days. These are not these are not mid-tier white collar jobs. These are like extraordinarily high skilled jobs being, I'm going to pick a word, automated by agentic AI. And I gotta tell you, I went home one Friday actually fairly depressed by this because you could just see how this was going to have such a dramatic impact on society. When you witness it in your own four walls, when you see work that used to be man years of work being done in days or weeks, it's like, wow, like that's the first time I've seen real impact in our four walls.” This echoes my own experience with agents and the conversations I am having with students, friends & clients. The toolkit has dramatically transformed and it feels like in finance, for the first time, AI is real.
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Raghu Gullapalli
Raghu Gullapalli@Bios4Action·
@wolfejosh @LTwolfe Hate the branding, lets call it what it is Always-on AI inference. The question I’m asking, “what becomes supply-constrained IF this thesis works?” - ultra-low power compute - battery density - on device memory - sensor fusion chips Unlikely to be all of them.
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Josh Wolfe
Josh Wolfe@wolfejosh·
1/ On Feb 21 I told my boss aka my wife @LTwolfe that I had my third conviction call not yet appreciated + to buy a basket *In 2016 it was NVDA, pitched publicly at Invest For Kids in Chicago (80x+) when Lux portfolio company Zoox was using NVDA chips and I predicted the narrative would change from gaming consoles PS4/Xbox to simulation and AI…
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slovak
slovak@slovak83·
@krishnanrohit @rfleury How do you see it adding the most value ex coding? In a precise, efficient output. Not one that requires human intervention.
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rohit
rohit@krishnanrohit·
@rfleury I don't know, ai is pretty damn useful
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rohit@krishnanrohit·
One bearish sign of all the AI layoffs is that the companies couldn't figure out how to produce even more by keeping the people and adding AI. I'm not entirely sure how to think about this.
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Citrini
Citrini@citrini·
@KitCarsonNV This was literally my exact investment process in Mediatek last November.
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Citrini
Citrini@citrini·
This is going to really upset some people but this is the part of the cycle where you can pretty much do a screen by sector = semiconductor, find the last names that haven’t tripled this cycle yet and still trade at the lower end of historical valuation range and then just buy em
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Jake
Jake@JakeKAllDay·
@slovak83 @mcuban this is why average accuracy + relevancy > determinism. Non-LLM information processing like indexing (or, sparse vectors) + knowledge graphs are the better way to force a given response that is relevant (the temp config is an independent choice).
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Mark Cuban
Mark Cuban@mcuban·
I’m coming to the conclusion that the biggest challenge for Enterprise AI, and AI in general , as of now, is that it’s still impossible to make sure that everyone gets the same answer to the same question, every time. Which is a great response to the doomers. AI doesn’t know the consequences of its output. Judgement and the ability to challenge AI output is becoming increasingly necessary, and valuable. Which makes domain knowledge more valuable by the second. Am I wrong ?
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slovak@slovak83·
@JakeKAllDay @mcuban So force a potentially incorrect answer, as long as it’s consistent?
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Jake
Jake@JakeKAllDay·
@mcuban Hey Mark— this is my day job (Enterprise AI implementation) Yes, you’re wrong. You can force temp to 0, add multiple passes, use knowledge graphs + indexing, and many other tools to force or approximate result determinism. Happy to expand more if there are questions.
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slovak
slovak@slovak83·
@BillAckman Can you tell Bollore to stop destroying UMG value?
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Bill Ackman
Bill Ackman@BillAckman·
I agree
Brett Caughran@FundamentEdge

AI won't kill fundamental investing because more information doesn't kill alpha. We have decades of priors here (Excel, Bloomberg, alt data...all democratized analysis & information gathering, and didn't kill alpha). As measured by factor volatility, stocks are less efficient and more alpha-rich than ever (and empirically, the ability of multi-eight figure market neutral multi-managers to consistently grind out 10-15% returns in an idio-maximized way proves this point...15 years ago a $10bn hedge fund was considered to be impossibly large). Innovations in investment process have shifted alpha pools, for sure, and systematic investors have arbitraged many old, reliable fundamental alpha pools. But as the players at the poker table have shifted, the constraints of those new players have created new alpha pools. Long duration fundamental investing has been gutted, and definitionally competing against a group of non-fundamental (quants, factor/thematic investors, indexers) and duration-constrained (multi's) investors should be a huge competitive advantage, long term (however frustrating in the near term). To wit, a 9-month thesis where I "look through" the next two prints is now considered a long-term thesis. Rigorous investment process serves investment judgment, but the real alpha generation fits a power-law distribution and there is some ineffable "nose for money" that the great investors have, that cannot be trained necessarily. Investing is a very hard game, that cannot be distilled to a reinforcement learning sandbox (by the time it is, the regime will have shifted and new drivers move stocks). AI has no sense of materiality, no true discernment, and the lack of context of N of 1 situations (if you haven't noticed, we are living in an N of 1 world!). There is a irreducible element of humanness that is critical to success in fundamental investing, and that won't change. What does this all mean? In my opinion, there is no better time to be starting a careers as an investor. My first year on the desk, I spent a lot of time doing grunt work: updating Nielsen files, updating models for my PM, creating same store sales master files, building question lists for CEO meetings, etc. This is grunt work. I can automate this all now, and get more quickly to the deep, value added parts of learning the investment process. Will AI drive alpha? This is a debate people are having, which I find sort of silly. When used correctly, by the right investor, of course it will. Ask any great investor if they had another 4 hours of research time per day whether the quality of their research would improve? That's kind of a dumb question...of course it will. Compressing the mechanical part of your job to focus more on the artisanal part of the job is Step 1, and with agentic systems accelerating fast is now in the strike zone of possibility. This is before we start to layer in a broader monitoring net and use cases to go deeper and build more rigor, finding signals in unstructured data that were missed before, as well as turning your investment genius into a co-pilot pattern recognition system. The future is very bright for fundamental investing, in my opinion.

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Felix Rieseberg
Felix Rieseberg@felixrieseberg·
Today, we’re releasing a feature that allows Claude to control your computer: Mouse, keyboard, and screen, giving it the ability to use any app. I believe this is especially useful if used with Dispatch, which allows you to remotely control Claude on your computer while you’re away.
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Ben Kizemchuk
Ben Kizemchuk@BenKizemchuk·
Opex and quarterly collar looking like a short term floor around here in my opinion, just as everyone is finally starting to understand the gravity of what I have been talking about since late Sept.
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stressed assets
stressed assets@stressed_assets·
My biggest contra says we going lower
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slovak
slovak@slovak83·
@levie What if you’re wrong about everything and it’s all bound to produce a bunch of slop and invite a bunch of hackers into your company?
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Aaron Levie
Aaron Levie@levie·
Without getting into the specific numbers, this underlying concept and trend is going to be very real. For any worker who is able to wield AI agents effectively in an organization, their compute budgets are just going to monotonically go up over time. This will of course start in engineering, where we already know developers can run multiple agents in parallel, or have projects going over night. But this eventually hit the rest of knowledge work as well. Lawyers that can create and review more drafts, marketed that can build more campaigns and test more ideals in parallel, sales reps that can reach out to more customers and process more leads. Many of these activities will essentially be token-dependent in how much work a single person can do. These aren’t chatbot workflows answering a simple question, but agents that are running and processing through incredible amounts of data at scale, and generating all new forms of information. Companies will have to figure out how they budget for this, and it likely won’t be an IT budget item over time, but ultimately owned and allocated by the business. Maybe the CFO is ultimately the head of AI :-).
TFTC@TFTC21

Jensen Huang: "If that $500,000 engineer did not consume at least $250,000 worth of tokens, I am going to be deeply alarmed. This is no different than a chip designer who says 'I'm just going to use paper and pencil. I don't think I'm going to need any CAD tools.'"

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slovak@slovak83·
@UnHedgedChatter Absolutely no reason at all for them to wish for this (sarcasm)
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UnHedgedChatter
UnHedgedChatter@UnHedgedChatter·
FT: Wall St underestimates private capital problems, says top credit hedge fund 😬 $BX $APO $KKR $OWL
UnHedgedChatter tweet mediaUnHedgedChatter tweet media
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slovak
slovak@slovak83·
@jakepaul Chase your American Dream from Puerto Rico
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Jake Paul
Jake Paul@jakepaul·
My Interview with President Donald Trump We cover the Iran war, immigration policies, the assassination attempt, life advice, some funny topics, and more.
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slovak
slovak@slovak83·
@GuyTalksFinance This looks pretty bush league even compared to trading platforms at Schwab etc
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beet-o
beet-o@louie_da_perl·
@benjaminMlavine @EconstratPB If you can’t see a credit cycle turn is in motion while the Fed is pinned by oil and lagging employment data then igotnuthin4yaman
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boaz weinstein
boaz weinstein@boazweinstein·
My partner @kieranwgoodwin has been so right about this space for over a year which has really sharpened my vision. Outflows beget outflows. Gating begets outflows. Selling some of the underlying portfolio to meet minimum redemptions creates losses and begets outflows. Four recent fake abs frauds begets outflows. NAV write downs beget outflows. How is this not going to get way worse, when ‘Frankenstein’s Monster’ of 700bn of products that vastly overpromised liquidity to retail, are so out of favor?
Kieran Goodwin@kieranwgoodwin

wsj.com/articles/banki… 1) This article explains some of the risks of shadow banks but misses a huge risk. It fails to mention that all private credit funds use leverage in order to be able to generate net returns of 8-10% to their investors. @boazweinstein

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