This AI newsletter is all you need #27

Author(s): Towards AI Editorial Team

Originally published on Towards AI the World’s Leading AI and Technology News and Media Company. If you are building an AI-related product or service, we invite you to consider becoming an AI sponsor. At Towards AI, we help scale AI and technology startups. Let us help you unleash your technology to the masses.

What happened this week in AI by Louis

We hope you had an amazing Christmas for those of you celebrating it, else, we hope it was a fantastic week full of great challenges and success, just like 2023 will be!

We are excited about many new announcements with Towards AI and the Learn AI Together community, such as podcasts, competitions, more resources to help the Learn AI community, new learning resources and tons of other open-source exciting stuff we are working on for the AI community. We will announce everything in this newsletter and on Discord. Stay tuned!

As you know, this week was the week of the year with all the predictions for 2023 and recaps for 2022, which we share below as some of the coolest along the article by our head of community sharing and explaining his favorite papers of 2022 with dedicated articles for each of them.

We hope you enjoy this last iteration of the year, and the Towards AI team wish you an amazing week and year ahead, which we hope to share with you on Discord.

Talk with you soon!

Louis

Hottest News

1. 2022: A Year Full of Amazing AI papers — A Review 🚀
   Towards AI has compiled an in-depth list of the latest breakthroughs in AI and the key aspects of AI that were highlighted this year. The list includes developments such as ChatGPT, Galactica, DALL-E 2, and Stable Diffusion, and provides a clear video explanation, a link to a more detailed article, and access to the code (if applicable).
2. OpenAI releases Point-E, an AI that generates 3D models
   OpenAI has open-sourced Point-E, a machine learning system that generates a 3D object from a text prompt. Point-E creates point clouds, which are sets of data points that represent a 3D shape. These point clouds can be used to fabricate real-world objects. This is a major breakthrough in the field of AI and is likely to have a significant impact on the industry.
3. A thread on prediction for GPT-4 in 2023
   Open AI’s GPT4 is set to be one of the first big AI things in 2023. In this Twitter thread, @RamaswmySridhar shares his predictions about the future of GPT-4, including the largest model size, pre-trained models, user-facing changes, and more.

Three 5-minute reads/videos to keep you learning

1. How to spot AI-generated text
   The internet is increasingly flooded with text written by AI. This article provides insight into the current tools for detecting it and explores new ways to train the human eye to spot the signs of AI-written sentences.
2. What Building “Copilot for X” Really Takes
   Copilot is the start of many potential models for productionized artificial intelligence. This guide highlights the importance of estimating inference scale, determining real-time infrastructure, optimizing prompts, and integrating model outputs & UX.
3. ChatBot Prompts
   The ChatGPT prompts dataset is a valuable resource that includes prompts for a variety of action strings, such as travel guides and translations. It is a useful tool for those looking to utilize ChatGPT in a production environment.

Enjoy these papers and news summaries? Get a daily recap in your inbox!

The Learn AI Together Community section!

Meme of the week!

Featured Community post from the Discord

roycoding#2504 published a new book, “Zef’s Guide to Deep Learning,” which provides a conceptual overview of ML and DL. In addition to the basics, the book discusses the technical concepts behind Transformers and stable diffusion. Check it out here and support a fellow community member. Drop your questions and feedback in the thread here.

AI poll of the week!

TAI Curated section

Article of the week

10 Essential Skills for AI Leaders by Dr. Mandar Karhade, MD. Ph.D.

As the field of data science and artificial intelligence (AI) continues to grow and evolve, it is important for leaders to consider whether they are equipped to navigate this complex and rapidly-changing landscape effectively. The author provides a few key considerations for determining whether your leadership is fit for data science and AI.

Our must-read articles

Text Recognition With TensorFlow and CTC Network by Rokas Liuberskis

Paper Review: Summarization using Reinforcement Learning From Human Feedback by Building Blocks

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This AI newsletter is all you need #27 was originally published in Towards AI on Medium, where people are continuing the conversation by highlighting and responding to this story.

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