confluxi

valorant radent prodigy demon 64 | tenzedzombie studies my vods (ai engineer)

[confluxi @cata_fps]

🤫🤫🤫

[Wise @trikcode]

You basically need to be unemployed to keep up with all this AI stuff.

[GURGAVIN @gurgavin]

BUSINESSES ARE NOW USING PREDICTION MARKETS TO HEDGE PROMOTIONS LOL

A BAR IN NYC HAD A PROMO IF THE KNICKS WIN, THEY COVER EVERYONE’S DRINKS FOR THE NIGHT

THE BAR PLACED A $5K HEDGE ON KALSHI THAT PAYS OUT IF THE KNICKS WIN

THE BAR WINS EITHER WAY

[Mingu @lowgradef]

In fiction evil is often written to have depth and complexity while good is written to be simple and boring. But in real life evil is boring and predictable while good is complex and unique every single time.

[Yuchen Jin @Yuchenj_UW]

$3M Zillow listing in SF:

“Anthropic or OpenAI stock will be considered as payments.”

Forget cash buyers. The final boss of SF real estate is a 28-year-old MTS offering pre-AGI equity.

[confluxi @cata_fps]

crazy how everyone is pumping $OUST when $HSAI is a 3x better company

[confluxi @cata_fps]

@StockcoachPB u got it unc

[Moody @MoodyWriter13]

I cannot recall a time when the stock market was as distorted as it is today. The valuations of many high-quality companies have fallen to bargain levels, while semiconductor and AI Infrastructure stocks are trading at multiples that price in earnings far into the future. Many read these low valuations as a sign of structural weakness. From my perspective, the clearer cause lies elsewhere.
Capital is not unlimited. The enormous sums being invested in AI infrastructure are not available for other investments. By now, even the hyperscalers are investing more than they earn, they are tapping the capital markets. The concentration is not just visible in listed markets; it runs through the entire capital stack. The same pattern shows up in startup funding. venture capital is flowing overwhelmingly into AI, while founders in other sectors, even with strong businesses, struggle to raise at reasonable terms. When I look at the returns that sectors outside the AI universe currently offer, I doubt that the capital flowing into AI is being deployed wisely and will pay off in the end.
What strikes me most is the resulting mispricing on both sides. The market is currently offering, at bargain prices, companies that will most likely still be successful ten years from now, proven business models, durable competitive positions, reliable cash flows. At the same time, it is paying premium prices for companies that might, in ten years, become what the unglamorous names already are today. The asymmetry is striking, and it is rarely been this clear-cut.
Asset classes always compete with each other, and in a rational market, capital flows to wherever investors can achieve higher returns with a better risk-reward profile.
The problem is that right now nobody really knows what the future return on each dollar invested in AI infrastructure will be. As a result, imagination runs free, and meaningful comparisons become impossible.

At this point, I like to turn to the analogy of the market’s eye, in reference to the Eye of Sauron. When the eye is fixed on a single point, and it is fixed more intensely right now than at almost any time before, everything else falls into uncovered shadow. As an investor, you can choose between two paths. You can march, like everyone else, up to the gates of Mordor, into the place the eye is watching, and try your luck there. Or you can take the long way around and walk to Mount Doom unobserved.
We all know which is the smarter choice. And yet, most prefer right now to go where everyone else is, drawn by quick gains and compelling stories.​​​​​​​​​​​​​​​​

You’ll probably ask which sectors I mean. I’ve written about several companies lately already. I don’t own Mercado Libre, but it’s the perfect example. At these prices, it’s a no-brainer over the long term.

[confluxi @cata_fps]

i’m ain’t trusting anyone with a cut like this

[Bankless @Bankless]

LIVE NOW - The $200 Billion Shadow Market Behind Anthropic's Stock | Dio Casares

Anthropic's secondary market is tens of billions of dollars deep, stacked with SPVs on top of SPVs charging 10% fees plus carry, and almost entirely opaque.

@diogenes of @patagon breaks down how it actually works:

- which deals Anthropic blesses and which get cease-and-desists,
- why fake share certificates show up in 10-20% of executed deals,
- what tokenized equities and pre-IPO perps actually represent,
- and the mess of lawsuits and stuck shares coming when Anthropic finally IPOs.

Enjoy.

--------------
TIMESTAMPS

0:00 Intro
0:40 What is Going on in Secondary Markets?
7:03 How Anthropic Secondary Markets Unfold
14:51 Anthropic’s Secondaries Social Elite
19:00 Emerging SPV Structure
21:51 Accidental Frauds?
27:04 After IPO Consequences
35:13 Private Market Lessons
38:21 Patagon Markets
43:54 Tokenized Perps
44:57 Closing Thoughts

[confluxi @cata_fps]

enter composable memory:
vectors for fuzzy recall
trees for docs
tables for governed data
graphs for relationships
state for continuity

[confluxi @cata_fps]

@yacineMTB how much does this cost?

[Isaac @isaacturnersong]

Explain in genius terms. Explain like I already know everything

[confluxi @cata_fps]

@mattpocockuk what’s the main point of reading before writing to the file?

[good @thenarrator]

the next social network is a prediction market where your feed is ranked by accuracy not engagement. the person who is right 80% of the time gets seen while the person who is loud gets buried

[ア @yuruyurau]

a=(x,y,d=mag(k=4*cos(x/21),e=y/8-20))=>circle((q=3*sin(k*2)+.3/k+sin(y/19)*k*(9+2*sin(e*14-d*3+t*2)))+50*cos(c=d-t)+200,q*sin(c)+d*39-475,k*k>15?2:1)
t=0,draw=$=>{t||createCanvas(w=400,w);background(9).noStroke().fill(w,116);for(t+=PI/240,i=1e4;i--;)a(i,i/235)}#つぶやきProcessing

[ani @anirudhbv_ce]

We finally know why LLMs hallucinate. It's not the model. It's the geometry.

@OpenAI text-embedding-3-large: 91/3072 dimensions do real work.

@GeminiApp gemini-embedding-001: 80/3072 dimensions do real work.

~97% of your vector database is mathematically empty. Your RAG system is retrieving from noise.

@ashwingop and I present "The Geometry of Consolidation" - a proof that RAG compression has a hard floor no algorithm can beat, set by a single spectral number your embedding model cannot escape.

Every hallucination your RAG pipeline produces? This is why.

Paper + results: https://t.co/zut8pdoPbH

[Goodfire @GoodfireAI]

Neural networks might speak English, but they think in shapes.

Understanding their rich *neural geometry* is key to understanding how they work – and to debugging and controlling them with precision.

Starting today, we’re releasing a series of posts on this research agenda. 🧵

[Ryan Greenblatt @RyanPGreenblatt]

How well does this work? One quick independent test is to see if it can recover an "internal CoT" in cases where AIs can solve math problems in a single forward pass. TLDR: it doesn't. (TBC, this might require the NLA to see activations at multiple positions/location to work.)

[confluxi @cata_fps]

someone make an ai launch video of this exact style but the speaker gets abruptly shot in the head. guaranteed viral

[Ayman Saleh @sir_aymansaleh]

Excited to annouce the launch of my company Chronicle Labs (YC P26); the staging environment for enterprise AI agents.

Just like trading teams backtest algorithms before deploying capital, companies should be able to backtest agents before deploying them into real workflows.

We turn operational history into replayable sandboxes, so teams can test, debug, and safely ship better agents.

[Don @donatelli2026]

the american mind cannot understand this

[Unity for Games @unitygames]

Unity AI is now in Open Beta 🎉💫

We believe AI has the most impact when it helps creators move faster while staying in control of the creative process.

Use our built-in agent tuned for Unity workflows or connect the AI tools you prefer via AI Gateway and MCP Server.