Saturday's digest #16

5 Weekly Curated Articles For The Busy AI & Data Professional

Jeremy Lezac
August 17, 2024

#1 - Peter Baumann from Peter’s Substack- What Movies Can Tell Us About AI Visions

What Movies Can Tell Us About AI Visions

Or how my childhood shaped my image of AI today

peterbaumann.substack.com/p/what-movies-can-tell-us-about-ai

Despite the AI hype, this article explores how past sci-fi visions of AI, like in "2001: A Space Odyssey" and "Knight Rider," compare to today's realities. It highlights the need for AI professionals to learn from history and manage expectations responsibly. Essential reading for understanding the evolution and future of AI.

#2 - Vin Vashishta from High ROI Data Science - The Royal Dilemma: How To Use Data & Models To Advise C-Level Leaders & Design GenAI Products

The Royal Dilemma: How To Use Data & Models To Advise C-Level Leaders & Design GenAI Products

Most questions data scientists, analysts, strategists, and product managers are asked don’t capture the full complexity of the challenges behind them.

vinvashishta.substack.com/p/the-royal-dilemma-how-to-use-data

This article go deep into the art of answering questions and designing AI products that genuinely meet user needs. Challenging AI and data professionals to move beyond surface-level responses and to consider the deeper context, much like a strategic advisor. If you want to improve your AI products and decision-making, this read offers insights into avoiding common traps and understanding the nuanced thinking behind effective AI design.

#3 - Beny Benford from Datent - The Intrapreneur’s Challenge: Change Is Too Slow

The Intrapreneur's Challenge: Change Is Too Slow

Datent's first year - learnings and our evolving direction

datent.substack.com/p/the-intrapreneurs-challenge-change

As technology and AI rapidly evolve, the real challenge lies in the slow pace of organizational change. For AI and data professionals, the ability to adapt and drive transformation within organizations is critical. This article emphasizes the need to rethink how we approach change, particularly in leveraging data and AI to make a meaningful impact. Understanding and solving the complexities of organizational change are essential for AI-driven innovation to succeed in today's dynamic environment.

#4 - Ben Dickson from TechTalks - “Planning like a graph” improves LLM performance in asynchronous tasks

"Planning like a graph" improves LLM performance in asynchronous tasks

LLMs perform very poorly at planning asynchronous task. But formulating the task as a graph can help improve their performance.

bdtechtalks.substack.com/p/planning-like-a-graph-improves-llm

A key challenge for LLMs is managing tasks with both parallel and sequential steps. New research suggests that techniques like Plan Like a Graph (PLaG) can enhance their performance, though challenges remain.

#5 - Benn Stancil from benn.substack - A very particular set of skills

A very particular set of skills

If you're really good at something, do that thing?

benn.substack.com/p/a-very-particular-set-of-skills

This article offers a compelling argument on rethinking how to leverage AI. Instead of forcing AI into existing frameworks where it may underperform, the focus should be on identifying or creating new problems that AI is uniquely suited to solve. This shift in approach can unlock greater value and lead to innovative breakthroughs, rather than just incremental improvements.

See you next week!

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