This New Prompting Technique Makes AI Outputs Actually Usable

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🪐 What’s happening in tech today, December 4, 2024?

The HackerNoon Newsletter brings the HackerNoon homepage straight to your inbox. On this day, The Montreal Canadiens Hockey Team Founded in 1909, Charlemagne Became King of the Franks in 771, George H.W. Bush Deployed Troops to Somalia in 1992, and we present you with these top quality stories. From Justin Suns $6 Million Banana Purchase Pales In Comparison to the $30 Million Trump Investment to Playwright and Chrome Browser Testing in Heroku: A Beginners Guide, let’s dive right in.

Justin Suns $6 Million Banana Purchase Pales In Comparison to the $30 Million Trump Investment

TL;DR Tech billionaire Justin Suns $6M banana purchase and $30M investment in Trump-linked crypto project blend absurdity, pop culture, and blockchain innovation.

By @jabrilgoodner [ 2 Min read ]

Just last week, Justin Sun purchased a banana auctioned off at Sotheby’s for $6 million. The bill was paid in crypto by the tech billionaire, turning heads as the banana itself was destined to rot just a few days after the steep purchase...

This New Prompting Technique Makes AI Outputs Actually Usable

TL;DR Structured meta-prompting is a technique that dynamically generates JSON schemas for solutions before performing tasks.

By @abhic137 [ 15 Min read ]

A persistent challenge with large language models (LLMs) is their tendency to produce output that is unpredictable. Despite carefully crafted prompts, LLMs often deviate from expectations, making their output difficult to reuse or integrate into workflows. Even worse, the results are often not repeatable, complicating downstream processing...

Playwright and Chrome Browser Testing in Heroku: A Beginners Guide

TL;DR This blog will show you how to run automated end-to-end Playwright tests for your React app with Headless Chrome on Heroku.

By @alvinslee [ 12 Min read ]

I’ve always loved watching my unit tests run (and pass). They’re fast, and passing tests gives me the assurance that my individual pieces behave like they’re supposed to. Conversely, I often struggled to prioritize end-to-end tests for the browser because writing and running them was gruelingly slow.

Success!..

Human Preferences Help Scientists Train AI 30x Faster Than Before

TL;DR

By @languagemodels [ 1 Min read ]

A. Appendix

A.1. Full Prompts and A.2 ICPL Details

A. 3 Baseline Details

A.4 Environment Details

A.5 Proxy Human Preference

A.6 Human-in-the-Loop Preference

Authors:

(1) Chao Yu, Tsinghua University;

(2) Hong Lu, Tsinghua University;

(3) Jiaxuan Gao, Tsinghua University;

(4) Qixin Tan, Tsinghua University;..

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