scrlk

I think that public/permissionless crypto is going to remain a niche. It's clear that there are too many footguns and failure modes for the average user.

But I think private/permissioned chains will gain some adoption in the background of tradfi, especially for clearing and settlement, collateral management via tokenisation etc. Your bank might eventually use technology developed in crypto, but it'll be called 'distributed ledger technology' or 'tokenisation' rather than crypto because of the negative image.

It's a (weak) bear market capitulation signal - max fear when people think everything is broken.

Their insurance fund (SAFU) is completely wiped out, it's only $1 billion in BTC: https://www.binance.com/en/academy/glossary/secure-asset-fun...

The name of the fund was originally inspired by this meme: https://www.youtube.com/watch?v=DelF6zEHXpE

FWIW, at the end of every crypto bear market, a CEX usually blows up (eg FTX)...

True. But I'm cautiously optimistic based on their track record of not shipping dud MacBooks (on the thermal and battery life front) since the switch to Apple Silicon. The Touch Bar/butterfly keyboard era of MacBooks was a total disaster. The chassis design didn't fit the hot and power hungry 14 nm Intel CPUs + generally poor reliability.

Back to similar weight as the 2016 Touch Bar era MBPs (13" 1.37 kg; 15" 1.83 kg), except way better thermals and battery life.

Nanotexture on non-folding displays is etched glass.

The base iPhone 17 has a 120 Hz display, I suspect they are going to drip feed it through their products as a cheap spec bump (vs adding extra RAM or storage).

You're an order of magnitude off: $1M in 1943 is ~$19.5M today.

https://www.bls.gov/data/inflation_calculator.htm

The Kickflip demo showed it taking off from the ground: https://www.youtube.com/watch?v=r5vsHHPVhJg

If you view LLMs as lossy data compressors, this exactly what you'd expect.

Feb 2000: Record orders for chip gear push SEMI index to four-year high

https://www.eetimes.com/record-orders-for-chip-gear-push-sem...

> Capital equipment suppliers have been increasing their forecasts for revenue growth in 2000 as chip manufacturers begin to add new wafer fabs and backend assembly plants. Last week, for example, Applied Materials Inc.–the world's largest semiconductor equipment supplier–announced it had increased its forecast for industry growth in wafer fab equipment sales to 46% from a projection of 19% at the end of last year (see Feb. 16 story).

> The strong wave of new orders “confirms the strength of the current market cycle,” said Stanley T. Myers, president of SEMI.

This time it's different.

> 2/3 of those are completely cuckoo regarding long term planning

The network operators or the system operator? Hard to do any form of sane long term planning when the regulator changes their mind every 5 years.

I wouldn't trust any of the hardware wallet vendors. Pretty much all of them have had customer data leaks, resulting in wrench attacks.

You're better off just having a dedicated laptop for crypto transactions.

A coffee maker was the subject of the world's first webcam: https://en.wikipedia.org/wiki/Trojan_Room_coffee_pot :^)

Does this imply that it was a one shot prompt with ChatGPT Pro style models (i.e. best-of-N), rather than the agent swarm approach that was used for Navier-Stokes?

After the LK-99 debacle, I'm taking this with a truck load of salt.

The spherical aberration of Hubble's main mirror was caused by a manufacturing defect.

Perkin-Elmer designed a new null corrector to verify that the mirror was made to spec, but the null corrector was incorrectly assembled (one of the lenses was out by a few mm). They also used the previous null corrector to test, which showed that the mirror was incorrectly ground, but decided that the new null corrector's measurements was correct.

> there's a whole family of pool-corruption bugs that have workaround config settings and everything

Back in 2018, a former Oracle developer explained what it was like working on Oracle DB: https://news.ycombinator.com/item?id=18442941

> Here is how the life of an Oracle Database developer is:

> - Start working on a new bug.

> - Spend two weeks trying to understand the 20 different flags that interact in mysterious ways to cause this bag.

> - Add one more flag to handle the new special scenario. Add a few more lines of code that checks this flag and works around the problematic situation and avoids the bug.

> - Submit the changes to a test farm consisting of about 100 to 200 servers that would compile the code, build a new Oracle DB, and run the millions of tests in a distributed fashion.

> - Go home. Come the next day and work on something else. The tests can take 20 hours to 30 hours to complete.

> - Go home. Come the next day and check your farm test results. On a good day, there would be about 100 failing tests. On a bad day, there would be about 1000 failing tests. Pick some of these tests randomly and try to understand what went wrong with your assumptions. Maybe there are some 10 more flags to consider to truly understand the nature of the bug.

> - Add a few more flags in an attempt to fix the issue. Submit the changes again for testing. Wait another 20 to 30 hours.

> - Rinse and repeat for another two weeks until you get the mysterious incantation of the combination of flags right.

Seems like their comment is still valid today.

Artificial Analysis is reporting that 6 Luna scores 2 points lower on their coding index than 5.6 Luna, but is 60% cheaper:

> In the Coding Agent Index, Sol improves but Luna regresses: In OpenAI's Codex harness, GPT-6 Sol (max) scores 57 in the Artificial Analysis Coding Agent Index, up 2 points from GPT-5.6 Sol (max), with gains in Terminal-Bench 4.0 (43% vs 37%) and SWE-Atlas-QnA (58% vs 54%). At $2.99 per task it costs ~50% less than GPT-5.6 Sol (max) and sits on the Pareto frontier of Coding Agent Index vs Cost per Task. GPT-6 Luna (max) scores 41, down 2 points from GPT-5.6 Luna (max), with lower scores in SWE-Atlas-QnA (44% vs 49%) and DeepSWE v1.1 (64% vs 66%), at ~60% lower cost per task.

https://x.com/ArtificialAnlys/status/2102462962758033624

Given that they had to discontinue sales of the 20x Pro plan after the Astra release due to compute constraints, I wonder if 6 Sol & Luna are smaller vs their 5.6 counterparts?

The UK has mini roundabouts, which are just a painted white circle on the road: https://upload.wikimedia.org/wikipedia/commons/b/b0/Mini-rou...

Drivers treat them as a normal roundabout by giving way to traffic on the right.

You can still go to a tailor and commission jackets, trousers and shirts, made with the same quality of fabrics and manufacturing techniques. With shoes, you can still go and buy hand welted shoes.

It all comes at a price but I don't disagree that we have a barbell problem here (ie cheap fast fashion or bespoke, with nothing in the middle).

The share of household spending on clothing has gone from 10%+ to under 5% in Western countries. When you're spending that much, it's not a surprise that clothing was "BIFL" both in quality and upkeep (repair rather than replace).

The overall revealed consumer preference has been "more and cheaper", not "less and higher quality", which still exists as a niche if you are willing to go down the tailoring route, not off the peg.

Might be related to this announcement from Tibo on Sunday:

> We've made some improvements that improve usage on the long tail for power users of Astra when logged in with your ChatGPT account.

> No change in quality and a pure win that on the long tail can result in up to 3-4X less usage being drawn from the subscription.

https://x.com/thsottiaux/status/2096717905614524491 (https://xcancel.com/thsottiaux/status/2096717905614524491)

Is the ARC-AGI-3 score with their custom harness? I'm guessing that is what the footnote is for? (per https://openai.com/index/how-two-settings-tripled-our-arc-ag...)

That's interesting to hear. I should have added that I use Gemini through Google AI Studio as my general chat model, which probably explains our wildly different experiences.