
slovak
1.9K posts


@OnodaCapital Can you explain math on why cheap? Especially including incremental funding required?
English

@SouthernValue95 @FundamentEdge People who can't prompt/orchestrate blame the AI.
English

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.
English

@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.
English

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…
English

@krishnanrohit @rfleury How do you see it adding the most value ex coding? In a precise, efficient output. Not one that requires human intervention.
English

@KitCarsonNV This was literally my exact investment process in Mediatek last November.
English

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 ?
English

@JakeKAllDay @mcuban So force a potentially incorrect answer, as long as it’s consistent?
English

@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.
English


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.'"
English

@UnHedgedChatter Absolutely no reason at all for them to wish for this (sarcasm)
English

@GuyTalksFinance This looks pretty bush league even compared to trading platforms at Schwab etc
English

Perplexity Computer is basically a Bloomberg Terminal for normal investors.
You can literally have access to the same information that people pay $30,000/year for.
Morgan@morganlinton
Perplexity just announced a partnership with @Plaid to allow people to bring their own investment portfolios into Perplexity Computer. Here’s the one and only @jeffgrimes9 announcing it.
English

@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
English

I blame @benjaminMlavine for getting me out of my 10s futs short last week.
Mfer owes me a beer or 7.
EconstratPB@EconstratPB
10s at 420 😂
English

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
English












