Welcome to the winner announcement of the Future of AI Writing Contest by GadflyAI and HackerNoon. This contest is the most successful one-month writing contest so far. We published 125 stories in 1 month, generating 200,000+ reads and 24 days of reading time! We thank the HackerNoon writer community for sharing such diverse, well-researched, and educational stories on the future of AI. It was fun reading all the entries.
The Future of AI Writing Contest: Top 15 Nominations
For selecting the top 15 nominations, we picked all the stories with the future of ai tag on HackerNoon, published in August. Then, we chose the top stories weighing in the following factors:
- Number of hours read
- The number of people reached
- The originality of the content
- Sponsor feedback
Here’s the list of the top 15 stories:
-
How to Make Any LLM More Accurate with Just a Few Lines of Code by @FrederikBussler
-
Decoding the Future: 50 AI Statistics Highlighting Marketing's Transformation In 2023 by @darragh
-
Creating a Domain Expert LLM: A Guide to Fine-Tuning by @shanglun
-
A Beginner's Guide to Using Large Language Models (LLMs) With the PaLM API by @wise4rmgod
-
Critical Thinking to AI: Are you a Friend or Foe? by @meadhbhh
-
It's Not the Machines, Dummy — It's Our Sociopolitical-Economic System by @djcampbell
-
Automating the Automation: Can AI Fully Take Over the Data Scraping Process? by @cerniauskas
-
Could Wall Street’s ‘Roaring 20s’ be Powered by Undervalued Generative AI Stocks? by @dmytro-spilka
-
How LLM Models Secretly Push Political Agendas - Shocking Truth Revealed! by @Manish-sharma
-
How to Prioritize AI Projects Amidst GPU Constraints by @prerakgarg
-
How to Structure Your Machine Learning Team for Success by @cheparukhin
Wow, a solid line-up HackerNooners! You made it difficult for us to choose one winner, but there has to be one.
The winner #future-of-ai story with 4800+ reads and the highest number of votes is:
https://hackernoon.com/how-to-make-any-llm-more-accurate-in-just-a-few-lines-of-code?embedable=true
Context-dependent, ambiguous, and diverse, language data is a wild beast that even the best algorithms struggle to tame. It’s impossible to accurately label all this data, which inevitably means that even state-of-the-art LLMs are trained on tons of incorrectly-labeled data.
Congratulations, @FrederikBussler! You have won $1000. We will contact you to share the next steps to claim your reward.
Shoutout to all the finalists! Visit contests.hackernoon.com to learn more about running and upcoming contests.