weekend ai reads for 2024-05-03

One day you will reach into that bag and your hand will meet nothing but air and you will be bereft. You will realize the loss of something you did not know you ever had.

In the few weeks that I spent as a virtual-assistant taskmaster, I realized that much of the busywork claimed by the apps is actually quite personal, often rewarding and occasionally transformative.

However, effectively prompting LLMs is both an art and a science—significant performance improvements can be achieved by slightly tweaking our prompting implementation or strategy. In this overview, we will develop a comprehensive understanding of prompt engineering, beginning with basic concepts and going all the way to cutting-edge techniques that have been proposed in recent months.

Without empirical data, it’s difficult to know how effective this type of strategy is in helping viewers grasp and retain educational content. But Kab suggested the main function of his videos is to get people interested in exploring deeper concepts in math, physics, and engineering.

This work identifies 18 foundational challenges in assuring the alignment and safety of large language models (LLMs). These challenges are organized into three different categories: scientific understanding of LLMs, development and deployment methods, and sociotechnical challenges. Based on the identified challenges, we pose 200+, concrete research questions.

Our most striking result is that agent architectures for HumanEval do not outperform our simpler baselines despite costing more. In fact, agents differ drastically in terms of cost: for substantially similar accuracy, the cost can differ by almost two orders of magnitude!

We've analysed 5677 AI Tools and identified their capabilities with OpenAI GPT-4, to bring you a list of 30326 tasks of what AI can do today.

This curated collection is part of a broader research endeavor in which data, sonification and design converge to explore the potential of sound in complementing other modes of representation and broadening the publics of data. With visualization still being one of the prominent forms of data transformation, we believe that sound can both enrich the experience of data and build new publics.