nuclearnice1

I’m not personally aware of anyone who uses these reviews at all.

That said I am excited about tiny gains and the idea evoked by the chart.

The chart from bullshit territory is borrowed from the first chapter James Clear’s book Atomic Habits [1, 2]

The chart isn’t supposed to represent actual data from a specific person’s regular review system. Rather the chapter it comes from is trying to frame the importance and long term impact of incremental change from regular routine actions. In contrast to dramatic improvement from a single decisive insight.

That rings true to my experience. If I do something regularly — exercise, study, or cook — I improve.

I’m not sure a weekly review of those habits is needed or useful.

[1] https://jamesclear.com/atomic-habits

[2] https://news.ycombinator.com/item?id=29774859

I suspect it’s gpt-speak.

Here’s a video interview with Nolan from June this year

https://youtu.be/2A__XuCDgss

Brilliant! What’s your tool chain in terms of hardware and libraries and so on look like?

I imagine your skill set is very rare in that community.

This is a nice game. What technology stack did you use to implement?

What a wonderfully informative and educational comment. Thank you.

Would you also be able to shed some light on what a singularity is? It was not intuitive to me that incompressiblity should lead to a singularity.

The article dances around the term:

> At that point, the Euler equations are said to give rise to a “singularity” — or, more dramatically, to “blow up.”

> Once they hit that singularity, the equations will no longer be able to compute the fluid’s flow.

I agree with the sentiment.

From the text I think he draws a distinction between consciously deciding not to do something and missing it entirely.

Level 5 allows consciously dropping — saying “I’m sorry [can’t do it] a lot”

Level 6 - you aren’t seeing everything and they are getting dropped WITHOUT intent. “Just saying “No” to inbound things is not enough.”

As an aside, guidelines violating clickbait number title? “The Seven Levels of Busy”

How did it fall short?

> The paper does not analyze the transactions directly unless I'm missing that piece.

It looks at transactions and attempts to classify coins as scam or not.

It doesn’t make any claims about the volume in scam coins. That’s more a clickbait headline and HN thread thing.

It’s most trying to contribute an algorithm for identifying scam coins.

See the appendix for features from the transactions that they used for their algorithm.

You asked how it was misleading.

I told you.

Sargos explained how it’s misleading.

> “97% of the tokens are scams so Uniswap is unsafe to use"

People are likely to draw the unsafe assumption.

Sargos attempted to clarify that some safety is created with filtering via a trusted list.

Indeed a very complex question to answer. One of the most interesting parts of the paper is the discussion of the various types of scam — simple rug pull, sell rug pull, smart contract trap door of various flavors.

From their paper, I think sympathetic to your POV:

> For example, it is not clear that cryptocurrencies such as Doge or Shiba have any use case or intrinsic value, but they are among the most popular meme-coins. In our framework, we say that a token has no intrinsic value or use case if the developer knows that the trading price with respect to USD will eventually be zero. In other words, a tradable malicious token in Uniswap induces a zero-sum game between the users and the developers, i.e. the incentives for the investors are not aligned with those of the token creators. Therefore, the main difference between malicious and non-malicious tokens is the developer’s intentionality towards the token. One of the main problems of these definitions is that it is unfeasible to distinguish between scam tokens and under-performing or abandoned projects without accurate off-chain data.

Reminds of

https://en.m.wikipedia.org/wiki/Greenspun%27s_tenth_rule

> Any sufficiently complicated C or Fortran program contains an ad hoc, informally-specified, bug-ridden, slow implementation of half of Common Lisp.

Hey! Fair point but don't be snarky.

I like your opening question. A casual way to establish some context and rapport.

I’m not sure this is a competing take vs the article. More like complementary.

The article mainly says “add more details.” Eg. Don’t write “the system is broken” be specific about what’s broken, what you did, and if you need help.

Basically, don’t assume context.

The author takes himself to be some kind of writer, so he said it in too many words.

Haha now at last I love it

Feel free to share the better phrasing!

One difference might be the pedagogical vs the productive perspective.

Perhaps the magic of a full fledged IDE is thought to obscure some of what is essential to the subject.

No.

You’d find more information on the real person.

But the news might be bad.

The article cites

> In a May survey of about 1,200 Americans, 70% of adult Gen Z respondents (ages 18 to 25) and 53% of millennial respondents (up to age 41) said they watch content with text most of the time. That’s compared with slightly more than a third of older respondents, according to the report commissioned by language-teaching app Preply.

Not sure if you want to trust Preply over your clickbait spidey sense. I’ve never heard of them. But FYI.

Another excellent paper on the similarities between all those linear models is “ A Unifying Review of Linear Gaussian Models”

> Factor analysis, principal component analysis, mixtures of gaussian clusters, vector quantization, Kalman filter models, and hidden Markov models can all be unified as variations of unsupervised learning under a single basic generative model.

https://authors.library.caltech.edu/13697/1/ROWnc99.pdf

First sentence: don’t guess people’s motivations

Second sentence: explain people’s motivations

What’s second and third?

Are stablecoins “widely accepted as a medium of exchange?”

I know some places accept Bitcoin. Tesla accepts Dogecoin for some products.

What can you buy with stablecoins?

You’re quite passionate about it.

Could you explain some of your reasons?

That number might be low enough that there is no need to emphasize the probation period to candidates.

If 20% of candidates are getting cut after the probation, I’m very hesitant.

Losing 5% quickly is only slightly above normal and may, in fact, be a positive sign of quality control.

I agree with the other poster. The possibility of ending up unemployed is a bit stressful here.

What percentage of people get let go within 90 days?

In my experience, it’s impossible to assemble a group of 1000 programmers who are consistently able to read a license and reason correctly about whether the firm can follow it.

The validators have staked 32 ETH to the network. If they stay up, they get rewards. If they go down, they get hit with penalties. This incentivizes building a reliable system.

Is it sufficient? I’m not sure.

> The "6 or so" breakthroughs sounds about right to me.

What’s your logic? Or his if you know it?