Launchyard is hosting a contest with $1000 in payouts for whoever makes the most viral website by April 24.

Instructions: 1. Give Launchyard your prompt, have it build you something (takes five minutes) 2. Market your website on socials (reddit, hackernews, etc) 3. Top 3 websites by visitor count with $600, $300, and $100 respectively!

See the attached link for more detailed rules. We already have some good submissions: 1. https://humanorclanker.launchyard.app (249 visitors) 2. https://replaced.launchyard.app (109 visitors) 3. https://admitit.launchyard.app (22 visitors)

I'm Maxim. Launchyard is a tool that I built that enables you to vibe-code an entire business. Launchyard will create an app, deploy it, purchase a custom domain, SEO monetize, add advertisements + stripe, etc. I moved my online business to launchyard and now get ~200k clicks/mo on Google. No engineering or technical work needed!

It's crazy how quickly you can deploy end to end apps today. With launchyard it takes hours, and the only bottleneck is token inference. Quality is genuinely on par with some of the best landing pages. Try it out and let me know what you think!

Looks like you can now use LLMs to translate all languages, better than Google.

I'm one of the authors on the paper. Actually, sentence-by-sentence translation is important in a machine translation system because in many cases users will only provide single sentences. We also test document-level translation in Section 5, and find large improvements (but it isn't the focus of our paper).

Although, the paper argues that we can create artificial datasets using the LLMs which would improve the special-case translation models without having to pay for the inference and latency time of the large models.

Yes, but the translation model in the “Attention is All You Need” was trained on parallel sentences (input: English sentence, output: French). LLMs such as Claude are not trained on any labeled data. Yet, they still surpass the special-case models.

They surpass because there is faaaaaaar more language data generally than there is data that's paired english-french.