Leopold

[Ronnie Stoeferle @RonStoeferle]

The Maastricht criteria are about as binding these days as New Year's resolutions on January 15th....

Link to the full report: https://t.co/U0jtUR1Ul4

[dharmesh @dharmesh]

Yes, yes, I know it's cliched.

But, I'm only human.

[Radek Sienkiewicz @velvet_shark]

Ole (@itsolelehmann) deleted half his Claude setup last week and every output got BETTER.

You can do the same with Codex.

Run this prompt inside Codex and enjoy a faster and better Codex experience.

---
```
Read my Codex setup before responding. Inspect the relevant AGENTS.md files, ~/.codex/config.toml, repo docs, and any instruction/workflow files you can access.

Audit every rule and instruction. For each one, tell me:

1. Is this already default Codex behavior?
2. Does it conflict with another instruction?
3. Is it duplicated elsewhere?
4. Was it probably added to fix one specific bad output?
5. Is it too vague to be useful?

Then give me:
- rules to cut, with one-line reasons
- conflicts between files
- duplicated rules
- a cleaned-up AGENTS.md proposal
- anything you would keep because it is genuinely specific to my workflow
```

🚨Caution: don’t blindly accept the cleanup. Codex is decent at finding bloat, but it can also remove "local truth" that matters, like repo-specific commands, safety rules, or your preferred workflow.

Best process: trim, run 3 common tasks, then add back only what breaks.

[Leopold @Backyard_vienna]

@velvet_shark @jb510 @steipete @vincent_koc @TEDTalks Can't wait! 🤩

[Jukan @COMPUTEX @jukan05]

https://t.co/dF5Praw6WN

[Ethan Mollick @emollick]

I suspect that popularity of AI is going to start looking like surveys where people trust their own doctors but are distrustful of the medical establishment

People will increasingly like “their AI” but will increasingly be anxious about “AI” as a category. Some odd implications

[Radigan Carter @radigancarter]

https://t.co/Ys7x2TMb2t

[Lemma the Optimist @DoctorLemma]

Sixteen years ago, one man stood alone on a grassy hill at a music festival in Washington State, USA, and started dancing by himself. People glanced over and looked away. Some laughed. His roommate leaned in and warned him people were filming him.

He did not stop.

Then one stranger got up and joined him.
Then another.

Then the hillside tipped. Within minutes, hundreds of people were sprinting from across the field to be part of something that, thirty seconds earlier, had been one man being laughed at in a field.

Someone filming from higher up the hill said quietly: "See what one man can do. One man can change the world."

The clip spread across the internet in 2009. Entrepreneur Derek Sivers played it at a TED conference to explain how movements actually begin. Not with the first person brave enough to start, he argued, but with the first person willing to join them.

Collin Wynter, the man dancing alone, later said he had no idea he had done anything special. He was just tired of watching everyone sit still.

[Andrew Kang @Rewkang]

Researchers trained a humanoid robot to play tennis using only 5 hours of motion capture data

The robot can now sustain multi-shot rallies with human players, hitting balls traveling >15 m/s with a ~90% success rate

AlphaGo for every sport is coming

[Mark Gadala-Maria @markgadala]

This is wild.

143 million people thought they were catching Pokémon. They were actually building one of the largest real-world visual datasets in AI history.

Niantic just disclosed that photos and AR scans collected through Pokémon Go have produced a dataset of over 30 billion real-world images. The company is now using that data to power visual navigation AI for delivery robots.

Players didn't just walk around with their phones. They scanned landmarks, storefronts, parks, and sidewalks from every angle, at every time of day, in lighting and weather conditions that staged photography would never capture. They documented the physical world at a scale no mapping company with a fleet of vehicles could have replicated on the same timeline or budget.

Niantic collected this systematically, data point by data point, across eight years, while users thought the only thing at stake was catching a rare Charizard.

The most valuable AI training datasets in the world aren't being assembled in data centers. They're being built by people who have no idea they're building them.

[CSPAN @cspan]

Yale Budget Lab Exec. Dir. @marthagimbel on the shrinking appeal of U.S. debt: "We are currently the boyfriend at the beginning of the Hallmark movie in the big city, where the girlfriend is still going out with him even though she knows that it's wrong."

[Zephyr @zephyr_z9]

35% of Samsung's NAND & 20% of Hynix NAND capacity is in China
40% of Hynix's DRAM capacity is in China
They are responsible for the bulk of this growth

[Ethan Mollick @emollick]

NotebookLM: Do a deep research report and make a video telling me exactly how to take over Rome if I time travelled to 66 BC with a single backpack.

Actually pretty fun to watch and gets a lot of historical details in as well.

[Aaron Levie @levie]

https://t.co/O7OiUYKjbh

[Andrej Karpathy @karpathy]

💯 "If you build it, they will come." :)
~Every business you go to is still so used to giving you instructions over legacy interfaces. They expect you to navigate to web pages, click buttons, they give out instructions for where to click and what to enter here or there. This suddenly feels rude - why are you telling me what to do? Please give me the thing I can copy paste to my agent.

[Dan Shipper 📧 @danshipper]

we just wrote the ultimate beginner's guide to OpenClaw

almost everyone @every has one now, and they have completely changed the way we work and live. we're using our claws to:
- build product
- answer customer service queries
- book hard-to-get restaurant reservations
- track our reading notes

and much more

this is the guide we wish we'd had at the start:
https://t.co/66n3Wz6MT0

[Demetri Kofinas @kofinas]

Another great take on the current AI debate. If nothing else @Citrini7’s article has made the last few days on this platform more valuable and interesting.

[Carlos Avendaño @Untiroalaire]

superb piece of writing

my only pushback is on Kofinas requiring humans "to extend our time horizon"

imho, individuals and societies are living in an increasingly compressed present, with ever-diminishing bid-ask spreads (△ liquidity ≠ △ productivity)

this compression sharpens collective decision-making via stealthier wisdom-of-the-crowd marketplaces & widespread Bayesian priors (think near-real-time [nRT] updates refining probabilities on everything from markets to social trends, reminiscent of @howardlindzon's "degeneracy economy")

this isn't inherently better or worse; it just is. And AI accelerates it, tilting us toward an Extremistan society where ~95% dance to the ~5%'s tune (the latter, individuals and megacorps alike, surely are extending their time horizons: longevity, intergen wealth, long-term private capital, depressed discount rates, etc)

conversely, the modern Nation State (MNS) keeps raising its "walls of friction" (see @Mark_J_Perry's chart below), dragging us into a Kafkaesque board game with 2 options:

a) play along to stagnate ("they pretend to pay us, and we pretend to work");
b) face progressive disenfranchisement and eventual drop-off (assets > labor, low tax hubs)

surprisingly, reflexive cracks are already showing both in Western democracies (demand-fuelled yin) and single-party autocracies (supply-fuelled yang)

the outcome/timing of this tug-of-war between nRT economic agents and friction-bound MNSs is anyone's guess

circling back to Kofinas's thesis, I'm betting on humanity's cockroach-like resilience even as fat-tail risks escalate (from AI's unchecked/asymmetric diffusion to MNSs' mounting fragility)

these forces may fracture rigid systems, but humans will outlast them, evolving through the chaos

[Chris Kimble @KimbleCharting]

Don't see 28-year breakouts very often!

[Citrini @citrini]

JUNE 2028.

The S&P is down 38% from its highs. Unemployment just printed 10.2%. Private credit is unraveling. Prime mortgages are cracking. AI didn’t disappoint. It exceeded every expectation.

What happened?​​​​​​​​​​​​​​​​

https://t.co/JzzwCrbJgS