By the 6th generation, your genetic contribution to a descendant is 1.56%. By the 10th, it's below 0.1%. By the 20th, it is dissolved into the collective pool. The obsession with individual lineage is meaningless at civilizational timescales.
There’s a softness that only appears when nothing is forced.
Seedform,
Lindsay Kokoska, 2026
I kept thinking about how life begins quietly, before it has language or shape.
This piece feels like that early moment.
A small beginning, held in stillness, already carrying what it will become.
#artㅤㅤㅤㅤ
This is a fascinating result because it shifts the role of the hippocampus from passive memory storage to active field preparation.
The deeper implication isn't simply that memories influence perception. It's that the brain prepares a coherent dynamical state before sensory information arrives. Hippocampal ripples appear to tune cortical gamma activity according to expected uncertainty, so what we experience depends as much on the prepared state as on the incoming stimulus itself.
Viewed through a field perspective, cognition becomes:
Memory → Coherence → Resonant Preparation → Perturbation → Closure
Information isn't just transmittet, it is received by a system whose resonant geometry has already been configured by context and experience.
This doesn't prove a field-based model of cognition, but it is another piece of evidence that the brain operates as a hierarchy of interacting oscillatory fields rather than a passive symbol processor. The computation is increasingly looking like the evolution of a dynamic field toward coherence.
@bryan_johnson bruh he lived till 99 years old being born in 1924 dying in 2023 I’m not sure even your guaranteed to live that long with only the technology we have now. if you were born the same time you would’ve died just the same. death is inevitable.
Kian Katanforoosh, Stanford AI lecturer (Forbes 30 Under 30):
"Wall Street will pay you $500K a year to build these models. I'd rather teach them to you for free."
this free stanford lecture holds the entire "AI predicts the market, 80% win rate" pitch the 2026 quant threads are selling you. and the man teaching it didn't take the fund money either, he co-built stanford's deep learning class, gave it to millions online for free, and started an AI company instead of a hedge fund.
at the board he builds it from scratch: a neural net doesn't predict the future, it learns the expected outcome across thousands of inputs at once, patterns no single indicator could hold. stack enough weak guessers, let them vote, the noise cancels and the signal survives. that's the whole "100 AI agents auditing the market" idea, minus the marketing.
backpropagation has been public since 1986. hinton won a nobel for it in 2024. random forests came out of leo breiman's free 2001 paper. none of it is secret. it's the same stack i mapped in the article above, old and free and sitting in a textbook the whole time.
and here's the honest part the win rate hides. a model that scored 80% on past data is describing the past, not promising the future. ensembles cut variance, they don't turn a weak edge into a real one, and the market shifts under the model in ways the training set never saw. the lecture is free. knowing whether your 80% survives on live capital is exactly the part the course skips.
The Branch-Point Loom
Some equations do not draw curves but instead draw weave sheets.
This scene comes from the algebraic curve
y² = Δ(z,t),
where
Δ(z,t) = Πⱼ(z - βⱼ(t)).
The moving points βⱼ are branch points. These are special places where two sheets of the curve touch and swap identities. In the animation, those branch points appear as glowing mineral spindles moving across a dark surface.
The landscape is shaped by -log|Δ(z,t)|. Therefore, the branch points rise into sharp seams while the surrounding surface folds around them. The bright threads follow the horizontal trajectories of the quadratic differential Δ(z,t)dz².
#Mathematics #ComplexAnalysis #AlgebraicGeometry #MathArt #MathematicalArt #Geometry #PhysicsVisualization #STEM #Art
THE MOMENT YOUR SECOND BRAIN CLICKS INTO PLACE LOOKS EXACTLY LIKE THIS
scattered dots that mean nothing on their own and then the connections turn on and suddenly there’s a structure that wasn’t there before
this is what karpathy was describing, knowledge isn’t in the notes themselves, it’s in what forms between them when someone finally draws the lines
the LLM wiki does this automatically every time you add a source and your vault has never done this once
bookmark & like this so you remember to actually set it up
The kids will be scary indeed. Imagine +4SD high schoolers who grew up watching DeepSeek/Moonshot/Unitree ascendance and their age peers becoming legends, using frontier models, who learned "wait I'm actually able to build Big Things already"
THIS IS WHAT 3 YEARS OF OBSIDIAN NOTES SHOULD LOOK LIKE BY NOW
what you see here is thousands of connections forming a structure that didn’t exist before
this is exactly what karpathy built with the llm wiki pattern, every source rewires the whole thing and new structure emerges automatically instead of you manually linking notes for years
knowledge that connects itself looks nothing like a productivity system
bookmark this and send it to whoever still thinks obsidian is just for taking notes
This guy owns a roofing company and walked away from an $8,000 job over a $200 difference. He said there were already some early red flags with the customer, and once the guy started haggling over $200 on a project that size, he realized the job probably wasn’t worth the headache.
NVIDIA just open-sourced a model that takes broken, blurry 3D scans and rebuilds them clean from any angle..
It's called ArtiFixer. It uses video diffusion to generate the camera angles you never captured, then reconstructs the scene from the generated frames.
→ 70x faster than anything
→ Finishes in 1 to 4 steps
→ Beats SOTA by 3dB
→ Works from just text prompts
100% Open Source.
Decades ago, Hungarian mathematician Paul Erdős used randomness to illuminate the vast and weird world of networks. Today, mathematicians are making his technique even more powerful.
https://t.co/sccNL8nG1l
GOOGLE HA LIBERADO EN SILENCIO UNA IA QUE PREDICE PATRONES
Ventas. Precios de mercado. Tráfico web.
Demanda energética. Volatilidad cripto.
Se llama TimesFM:
→ Entrenada con 100B de datos reales
→ Forecasting zero-shot, sin fine-tuning
→ Corre en local.
Probablemente el lanzamiento más loco que ha hecho Google en los últimos años, y nadie está hablando de ello.
100% Gratis y Open Source.
Enlace abajo👇
Haven't seen any demos of using vibe coding to prototype gadgets like this
So I made one. Everything here is generated with code
Parts of the code and logic can even be reused on a Raspberry Pi to build the real thing
Some tips ↓
Did some experiments with local models
In this example, all requests are handled by Gemma 4. It generates a new circuit as JSON based on the prompt
Edited out the waiting times from the clip. It usually takes around 5 - 10s
More details ↓