Hello Everyone,
During the summer of 2023, I took the liberty of doing a survey of A.I. Newsletters on the web. I paid special attention to Newsletters from platforms such as Substack and beehiiv. Though not exhaustive (and a work in progress), it soon became clear that it was an archives and knowledge base way too deep to introduce to readers in one sitting.
That’s how this occasional Sunday series was born. “Good Reads in AI”
To that end, on some Sundays I will feature some Newsletters from the list in a bit more detail. This is a casual series for easy browsing. It’s supposed to simply ✨ spark your interest, thus exposing you to new thinkers, writers and their work.
Format
Two polls related to A.I.
Three “featured” Newsletters
Their 3 best pieces (preferably posts that are free)
Want to support the channel?
Image source: Pexels.
📖 Good Reads in A.I.
For this series, we will be going in random order through our big list.
1. Ahead of AI
Category: Machine Learning and Generative A.I.
What is it?
Ahead of AI is one of the fastest growing AI Newsletters that is educational.
Sebastian is a machine learning and AI researcher with over a decade of experience in the field. He is very passionate about explaining complex technical concepts and “taking the magic out of AI.”
See his Books
Sebastian in recent months has gone viral on both LinkedIn and Twitter X. Combined in those he’s nearing 300,000 followers.
Educational Newsletters in A.I. have done really well so far in 2023. Sebastian is Lead AI Educator at Lightning AI, where as an author he is excited about making AI & deep learning more accessible and teaching people how to utilize AI & deep learning at scale. In a short time, he’s grown the Newsletter to over 29,000 readers. You can also find him on threads and Notes.
What to read?
Understanding Large Language Models
Finetuning Large Language Models
AI Research Highlights In 3 Sentences Or Less (June-July 2023)
2. Supervised
Category: Long form journalism on Generative A.I.
What is it?
Supervised combines the expertise of a long time investigative journalist with the dawning of open-source Generative A.I. models.
Matt has been reporting on the tech industry for almost a decade, including at publications including Business Insider, The Wall Street Journal, BuzzFeed News, and TechCrunch. Most recently I was Business Insider’s lead reporter on AI and big data, covering companies like Databricks, Snowflake, OpenAI, and others.
In the span of six months, we’ve gone from a cheeky experimental web interface for a highly-sophisticated large language model to one of the single-biggest technological arms races in the industry’s history. ~ Matthew Lynley
What to read?
What Neeva’s quiet exit tells us about the future of AI startups
Databricks and Snowflake’s rivalry in AI enters a new chapter
3. Embeddings
What is it?
Embeddings is an interview series exploring how generative AI is changing the way we create and consume culture. In conversation with AI researchers, media theorists, social scientists, poets, and painters, we’re investigating the long-term impacts of this technology.
The authors are students at Stanford studying Symbolic Systems, with a joint interest in ethical AI and the arts. Their research is supported by Stanford HAI.
What to read?
On the future of cinema, creating with AI, and stories as intellectual DNA
On personalized media, alternative AI writing futures, and reconciling the poetic with the political
On collective creativity & AI, speculative design, and emergent aesthetics
What else? Next.
As a reader you might find something to read in the long list, which I recommend to bookmark. It represents dozens of hours of research in A.I. Newsletters covering a wide variety of related topics, intersections and future insights.
Let me know if you appreciate this series with positive feedback, which does wonders for my mental health. Showcasing the work of others in our discovery of A.I. insights makes for a valuable knowledge base for us all.
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