LLMs will use your website anyway. You're just choosing whether to pay the cost in structured endpoints upfront or hand that cost to browser emulation and lose control of how you're represented.

Allowing information asymmetry, like insider trading, undermines the regulatory argument that keeps these markets legal.

OpenClaw showed what an "AI Personal Assistant" should be capable of. Now it's time to get it in a form-factor businesses can safely use.

Innovation happens under competitive pressure. The US just created a domestic vacuum.

I wouldn't read too much into the national security justification. It's a political argument to an economic policy.

Anyway, one small nitpick on the website: When on German language the word "FUNKTIONSHIGHLIGHTS" overflows on mobile. I would replace it with "WICHTIGSTE FUNKTIONEN" as that is two words.

Good luck, the website and App look nice!

The way that payments work through SEPA is that the merchant pulls the money from your account. Legally they require a "mandate" - this can be as little as a handwritten signature on a document.

Security is essentially provided by easy reversal and strong penalties for abuse.

The problem is vibe coding AND negligence. Good software practices like testing, code review, documentation are bound to catch the LLM-isms.

No offense on the author, the project specifically calls out that it's a "young" project in the footer, so I personally wouldn't expect it to be quite up to spec yet.

However, active investors have higher trading fees/management costs, so they are bound to perform at least slightly worse on average. It's just mathematics.

For anyone interested, I can recommend the book "Systematic Trading" by Robert Carver. You don't have to be into algorithmic trading, the sections on risk management and positive vs negative skews are already worth the read.

Exports are more "expensive" for countries with reserve currency status. This is a problem for countries that export many primary and "low-tech" secondary sector products. Countries that export many "high-tech" secondary sector products can usually still thrive.

This leaves us with the usual suspects: US, China, Germany (-> EU) and Japan.

People don't read websites linearly, in the best case they skim read all the buttons and links. I personally would include the verb as it gives important context and is a clearer CTA for the "skimmers".

Amaya is W3C's... "Download Amaya"!

It was probably around 7 years ago when I first got interested in machine learning. Back then I followed a crude YouTube tutorial which consisted of downloading a Reddit comment dump and training an ML model on it to predict the next character for a given input. It was magical.

I always see LLMs as an evolution of that. Instead of the next character, it's now the next token. Instead of GBs of Reddit comments, it's now TBs of "everything". Instead of millions of parameters, it's now billions of parameters.

Over the years, the magic was never lost on me. However, I can never see LLMs as more than a "token prediction machine". Maybe throwing more compute and data at it will at some point make it so great that it's worthy to be called "AGI" anyway? I don't know.

Well anyway, thanks for the nostalgia trip on my birthday! I don't entirely share the same optimism - but I guess optimism is a necessary trait for a CEO, isn't it?

After a couple hours of coding something felt "weird" - turns out I forgot to login to GitHub Copilot and I was working without it the entire time. I felt a lot more proactive and confident as I wasn't waiting on the autocomplete.

Also, Cursor was exceptional at interrupting any kind of "flow" - who even wants their next cursor position predicted?

I'll probably keep Copilot disabled for now and stick to the agent-style tools like aider for boilerplate or redundant tasks.

(a-c) LLMs are especially difficult to use due to their knowledge cutoffs and "unpredictability". A self-trained "old-school" machine learning model can go a long way though.

(d) With Crypto the volatility is great for trading, but liquidity can quickly become a problem (even at $1000 non-leveraged positions). For me, the ultimate goal is to find a strategy that is profitable in all market conditions. I personally value consistency and reliability more than absolute profit.

(e) There's some chatting about risk management, but absolutely no discussion on profitable strategies. Resources are incredibly scarce - Systematic Trading by Robert Caver is the only book that was actually useful.

However, over reliance on it - like with all technologies - doesn't end well.

The problem that org-mode and Markdown face is that they are fairly minimal. It's common to use plugins, that aren't supported everywhere. This kills portability, which is a core "selling point".

I have seen it happen it Obsidian and Logseq - but even GitHub has a slightly altered Markdown spec.

[1] https://www.beorgapp.com

LLMs are a drop on a hot stone compared to countless other factors why the world already is routing around the US - but I don't want to get political or economical.