Dario Amodei (Anthropic CEO of a $965B AI company):
"I don't believe there's a "secret ingredient" to intelligence.
There's one dumb pattern - and it explains everything.
his actual words on stage: "We can't stop a powerful agentic model"
Claude ran 700 experiments in 2 nights - found improvements its creator missed in 20 years - it didn't wait, it didn't plan - it just started
the gap between people who use Claude and people who don't is no longer months. it's years.
He said it. The CEO of one of the most important companies on Earth
the progression he described:
→ before: we thought intelligence was about clever architecture and the right algorithms
→ then: we noticed the improvement curve from scale was too smooth to be an accident
→ now: scale isn't a trick, it's a law - the same kind of law that turned a worm into a human through gradient and a loss function
what it's already changed:
• new abilities (language, code, reasoning) aren't programmed in - they just "emerge" with scale
• predicting exactly when a skill shows up is nearly impossible, but the fact the model gets smarter overall is predictable
• the same laws run into real bottlenecks: data, compute, money - and that's the only thing that could actually stall progress
his point: stop hunting for the magic idea. intelligence isn't a mystery, it's scale applied to the right signal.
and then he gets honest about what scares him: bioweapons risk, cybersecurity, and what happens if all of this goes the wrong way.
Watch this, than read the article below
Andrej Karpathy in 5 min reveal ALL TRUTH about AI: "Neural networks are complicated alien artifacts"
The man who built the foundations of modern AI just admitted we have no idea what we actually created
Evolution ran a multi-agent self-play system for billions of years
5 min. free. professional look from OpenAI co-founder
bookmark & watch
Andrej Karpathy: "the model is one click away - for you and for everyone else"
access was never the wall.
the wall starts the second you open the tab.
most people type a question into a box and call it AI.
the top 1% never «use» the model - they build a system it runs inside.
→ they don't send prompts. they hand it context, rules, memory.
→ they don't live in single chats. they ship processes.
→ they don't chase the smartest model. they out-discipline everyone on the dumb one.
not the smarter one. the one with a process.
9 minutes. the clearest take on what actually separates the people shipping from the people asking ↓
bookmark & watch
Andrej Karpathy: "95% of what AI twitter sells you dies the moment the model updates"
the $20/month subscription was never the unlock. most people never even got past the tab. access was never the gap - same model, same window, one click away for everyone.
copy-pasting prompts all day, arguing with the model in circles, asking it questions like it's google, rewriting the same code 5 times, "the AI just doesn't get it"
here's what nobody wanted to hear: the experts who dismiss LLMs lose to the experts who learn to route around them. it's not about capability. it's about discipline.
what the difference with the top 1%:
→ they configure the tool instead of just opening it
→ they give it context, rules and memory, not one-off prompts
→ they build systems the model runs inside, not single chats
the model isn't the problem. the way you talk to it is. agents fail in ways nobody saw coming in training - you don't fix that by switching models. you fix it by routing around the failure modes.
most people sit next to the tool. almost nobody makes it work for them. one group types questions. the other ships systems.
you're not behind on access. you're behind on leverage
The creator of Claude Code, on stage in front of a room full of devs:
"Prompting is the old way. I just kick off a loop, and Claude does the rest of my job on its own."
24 minutes where Boris shows the stuff people usually hide
One breakdown worth more than a $500 course
Boris Cherny (Claude Code's creator): I deleted my IDE in November and hasn't opened it since. I writes more code than ever.
his actual words on stage:
I don't prompt Claude anymore. I have loops that are running. They're the ones prompting Claude. My job is to write loops.
the progression he described:
→ a year ago: writing code by hand with autocomplete
→ then: running 5-10 Claudes in parallel, prompting each one
→ now: he doesn't prompt at all - he writes the loops that prompt Claude
what it's already done inside Anthropic:
• ~3x more code shipped per engineer (he says that number is already outdated and higher)
• Cowork - a full product - built in ~8 days, 100% with Claude Code
• designers, the finance guy, even the chief of staff now ship code
his advice to founders: give everyone as many tokens as possible, and underfund every project on purpose - 2 engineers + a pile of tokens instead of 4.
the roles are melting into one "builder."
Watch this, than read the article below
Citadel hands out $750k/year to quants who understand why markets are irrational
This single Yale lecture hands you the exact psychology behind every market mistake
Save it & watch it today
30 years of research
→ "ChatGPT is expensive autocomplete."
→ 500B training words
→ a human would need 1,000 years to read it.
→ 1 GPU architecture
→ turned NVIDIA into a $1T company.
And MIT's Westerman explains how SMBs turn all of that into revenue
25-YEAR-OLD BUILT AN AI "SECOND BRAIN" for his YouTube channel
He ported Karpathy's LLM Knowledge Base framework into Obsidian + Claude Code - every chat now writes back into a vault that compounds his context over time
22 min. free. Bookmark & watch
a16z and Bankless are loud about one thing right now: 1 billion AI agents are coming
$2.59T global AI spend in 2026 (Gartner). Meta paying $200M+ per AI hire
OpenAI engineers on $1.5M comp packages
The money is already moving
Bookmark & watch then read the article below
Claude Code's creator Boris Cherny just explained why coding is "solved" - and what's coming next
21-minutes. Free. By Anthropic at Sequoia AI Ascent 2026
i've seen $500 vibe-coding courses that don't say half of what he says in the first 10 minutes
Origin story of Claude Code → his personal workflow → the SaaS apocalypse prediction
Worth more than any $1000 vibe-coding course
works whether you've never opened claude code, or you've been shipping with it for months
Whale bot printed $50k/week using Bayesian Update formula
Start with prior from Markov state history, update on micro-signals in real time → posterior becomes your edge probability
Formula:
P(H|E) = [P(E|H) × P(H)] / P(E)
(H = hypothesis like "BTC up in next 5 min", E = new evidence: order flow spike + vol cluster)
Check him -> https://t.co/vIa3jOEa79
- Target ultra-short BTC/ETH/SOL/XRP Up/Down windows (5–15 min)
- Layer evidence: net buys >2σ, on-chain tx acceleration, cross-asset momentum delta
- Only enter if posterior shifts >10–15% from market price → high-conviction micro-edge
- 92,722 predictions = ~300 trades/day compounding at scale
Small belief updates × 300 trades/day × geometric compounding = $50k/week
@merlin_future just shipped Whale Autotrade
It tracks every profitable whale and detects the entry the moment it executes, mirrors it to your account instantly
44-min Yale lecture on the winner's curse will teach you more than 20 years inside Goldman Sachs or Citadel
It revealed that fading mispriced isn't a "strategy", and edge of a $10B hedge fund books every day
Bookmark, skip one movie today & watch it
Top-1 bank manager ran $2B+ in the 80s and explained the exact edge that traders still use
He wrote 5 books on the mathematics of market timing. Then gave this talk at the MTA Symposium in 2009
Most people still haven't seen it
Bookmark & watch
This trader turned $80 into $2,732 with a single bet on the temperature in Shanghai
$20,969 last month and $42,105 all-time with 1,237 predictions
His model: GFS + ECMWF for weather. Public filings + hiring data for corporate
He pulls 3 independent weather models per city. When they all agree - he enters. When there's any doubt - he waits
The crowd prices Seoul 20°C at 25.9¢. The models already say it's happening. He loads
Market catches up at resolution. +210%
The 2.8¢ entry is the one that breaks your brain. $80 in. $2,732 out
The market gave 97% chance it won't happen. Three weather models said otherwise. He trusted the math
This is the same edge a meteorologist has over a tourist who checks the sky
Except he built a system that does it automatically. Across Seoul, Shanghai, Taipei, Shenzhen
That's not luck. That's reading a forecast 12 hours before the crowd does.
Profile: https://t.co/bh3jRWHYHz
Jim Simons built a $31B fortune using math that most people will never understand
- he was a code-breaker for the NSA before he ever touched a market
20-min and you'll understand why he has been running the most profitable hedge fund on earth since 1988
This is one of the last public talks he ever gave before he died in 2024
The Medallion Fund never had a losing year
Renaissance Technologies made 66% annually for 30 years
Bookmark & watch
Jane Street pays $650,000 a year to quants who trade using neural networks
This 1 hour lecture of a Jane Street talk on real ML infrastructure > 6 months of any course on YouTube
You'll finally see what tier-1 quants actually optimize
Bookmark & watch, no matter what
Ex-meteorologist turned $400 → $143,076 with 1 strategy and quit forecasting weather for betting on it
He bets only on weather. And he reads it better than the crowd
BEST TRADES
$29.88 → $14,602 · Wellington highest temp 16°C · Yes @ 0.1¢
$25.41 → $12,452 · Tokyo highest temp 16°C · Yes @ 0.1¢
$24.88 → $12,398 · Chicago highest temp 54°F · Yes @ 0.1¢
His model: GFS + ECMWF before the market checks the forecast
He enters Yes or No at 98–99¢ when the weather models already know the answer. The market hasn't caught up yet
Same strategy as an insurance company
He sells certainty to the crowd that's unsure. Buys No at 99.1¢. It resolves at 100¢. +0.86%. But at $3,977 position size - that's $33 per trade, risk-free.
High-certainty weather positions: tiny return, zero variance, stacked in size
Profile: https://t.co/9osDnldiRJ