arn3n

For the people in the comments stating that this is just fluff for voters, that may be true. But consider that this memo has another target audience: Investors, Banks, and VCs.

I know that many people in those spaces are investing in AI precisely because they believe that should their AI investments fail, the industry will be bailed out by the federal government. Getting AI to be seen favorably by the administration and putting AI within civic government systems and inside defense contracts is a pretty big push towards that outcome.

It’s actually not more complicated than that: The Commodity Exchanges Act explicitly disallows gaming to be classified as a future or swap. See https://www.cftc.gov/IndustryOversight/ContractsProducts/ind...

The CFTC, since Trump, has become entirely corrupt. Note that the proliferation of sports gambling in prediction markets, which is explicitly illegal, largely exists because the CFTC refuses to enforce their own legal mandate against Kalshi and Polymarket.

It’s actually worse; when states try to shut down sports betting in prediction markets, the CFTC fights on behalf of Kalshi with the reasoning that only the federal government has the mandate to regular futures and prediction markets. And then they refuse to regulate!

The CFTC is supposed to have 5 chairs, with no more than 3 in the same party. The administration has gotten around this rule by simply removing 4 of the commissioners and then refusing to appoint replacements. In effect, the CFTC has only 1 republican chair and no opposite party representation. The level of corruption is staggering.

What kind of TUI library has a private alpha?

It’s actually really easy to make models that can predict “will the market move up or down in the next X microseconds” that score above 50% accuracy. It’s just that there are so many ways to do it that overfitting is practically guaranteed and most models don’t work when actually trading against the market, which reacts to you. Doing those trades well requires more understanding of the underlying mechanisms, not to mention access to data sources that the public simply doesn’t have.

Cool, thanks for the explanation!

The decision to default to the streaming engine is really interesting. My intuition is that this would be slower than other data frame operations that are more parallelizable with batch processing, because streaming engines necessarily process rows sequentially. Is my intuition off/am I overestimating how much auto-parallelization polars does?

I love these kinds of posts. Simple, fast, AI-free, and I learn something new.

I think you’ll also find that the best way to strongly pressure companies to do something is by law. The work that Right to Repair advocates have been doing across the industry is fantastic.

So be it!

Agreed! It’s a good post.

It was (my) main takeaway and I wanted it to be evident in the headline. I didn’t want to bury the lede; I’ll uneditorialize it because it seems it’s causing some fighting in the comments and I don’t really want to instigate anything, more just warn people using the distro. I don’t think it’ll reach the people who need to be warned if it’s not evident that there’s an issue from the start.

This a fascinating security write up. I had no idea the models were this capable for reverse engineering.

I heard CISA is getting defunded. I wonder if it'll become a common assumption for Americans that all their devices are just perpetually compromised.

Usually the ads on hacker news are accompanied by a press release or a technical writeup so that I at least learn something new.

Everyone suggesting that they simply charge users for commits to drive off AI-heavy users forgets that Github is owned by Microsoft, who has a big incentive to keep having developers use AI.

I suspect that Microsoft would even prefer to have Github operate at a loss, if that loss were because all its users were using their models and paying for OpenAI subscriptions to generate the code.

Always a fun time to bring up my favorite writeups in database benchmarking: https://questdb.com/blog/lies-damn-lies-and-database-benchma...

There’s also an excellent paper called “Fair Benchmarking Considered Difficult: Common Pitfalls In Database Performance Testing”.

Benchmarks are genuinely hard. Modern systems and hardware are notoriously complex and have different behaviors across runs and with minor tweaks to performance settings.

There’s definitely strategies here; A lot of the floating point operations use subnormals, and a lot of the worst instructions are slowed down by really, really fucking with MMIO.

I have this stance. It’s, for me, a tail-risk calculation: For a given nuclear power plant to be more environmentally friendly than equivalent coal, you have to price in the probability of a nuclear catastrophe with the fact that such catastrophes create fallout that can outlast human civilization.

I can expect that a well-built nuclear plant might not have a catastrophe in my lifetime. But when the consequences are so long-lasting it seems prudent to avoid them entirely. One misbuilt reactor or one governmental regime that rolls back safety regulations and you end up with irreversible consequences. Given the tendency of corporations to “race to the bottom” and abandon safety, and the general unwillingness of the US Government to give proper attention to potential catastrophes (like climate change), I don’t believe that we as a society can handle the responsibility of nuclear reactors. I wish we could have nuclear safely; I don’t trust us to be safe, so I’d rather we not have nuclear at all.

It’s meant to be both funny AND highly unprofessional; Anubis makes money of licensing a version of the firewall where you can change the image.

It’s a good strategy; personal websites and blogs can display the anime girl without fear, and companies that care about their image end up paying. Win-win.

There’s the DSA. Organized resistance to the cost of living crisis in NYC has been mostly organized through them, to great popularity.

Eliza is one of the only games that I enjoyed so much that I sent fan mail when it came out — it’s nothing that a standard Zachtronics game but it stands alone as an excellent visual novel.

I would be disappointed if someone took the completion of my degree and the ceremony behind it as an opportunity to push their business. There’s enough advertisements on the internet; We don't need ads in our universities, too.

What do we think is more to blame for GitHub's massive decrease in quality? I've heard the following theories:

1. Increasing amount of AI-generated code in their codebase, decreasing the quality of the service.

2. Bought by Microsoft, and their bad engineering culture has spread to GitHub.

Perhaps it's a bit of both.

Your link is broken.

I often see people frame music as mathematical manipulation or try to approach music making from a “first principles” approach, where those principles are mathematics and physics. But watching musicians talk about making music, I seldom see any discussion of the underlying math, and instead see discussions of timbres, instruments, and stylistic/historical influences; musicians who make good music seems to believe “first principles” involves historical knowledge and a well-listened ear, and nothing involving math. My question is: Is thinking about music as applied mathematics a good way to create good music? Or is it just the most easily digestible model of music for the crowd on this site?