GenAI/AI News Jun 24, 25: Ethan Mollick's Practical AI Tool Advice, Coding Agents Have Crossed A Chasm, and More...
There's no substitute for hands on experience in this new era.
I have had the good fortune in my life to travel extensively. There are some places in the world that pictures can’t capture. The Acropolis and the Taj Mahal were two such places for me. No matter how many pictures, movies, models, etc. you see they just don’t do the location justice. GenAI is like that. No one can understand what these models are like to work with until you use them, think with them, live with them. They are more like a relationship with a pet or a person, than a tool. Today, Ethan Mollick’s guide leads our news and it’s a worthwhile read for anyone finding their way in this new world of conversation with the hive minds!
Good Evening, GAI Insights Community! If you missed us today, watch today's show on YouTube. Join the fun! Watch and comment on our Live feed on Linkedin or YouTube. We post articles for the daily briefing here so you can follow along and comment. Today there were 1 Essential, 2 Important, and 4 Optional articles.
Using AI Right Now: A Quick Guide
Rating: Essential
Rationale: This article by Ethan Mollick offers a concise and actionable overview of current generative AI tools, comparing platforms like ChatGPT, Claude, and Gemini, with practical tips on pricing, deep research, and voice mode usage. Our analysts emphasized its value as a comprehensive refresher for AI leaders, noting it reflects the real-world tools their teams are using and provides essential frameworks for model selection and user guidance.
Coding agents have crossed a chasm
Rating: Important
Rationale: This article discusses a significant advancement in AI-assisted coding, where generative AI agents now handle not just code generation but debugging and iterative refinement. Our analysts highlighted its importance for leaders in software development, likening the tools to capable interns and emphasizing the shift from novelty to practical collaboration in AI-driven software engineering.
Reinforcement Learning Teachers of Test Time Scaling
Rating: Important
Rationale: Sakana’s research introduces a novel approach using reinforcement learning to create teacher models that train other models more effectively. While not yet widely adopted, our analysts recognized its conceptual importance and the potential to transform generative AI training efficiency, calling it a thought-provoking direction worth noting for AI researchers and strategists.
Why CIOs must embrace persona-based AI
Rating: Optional
Rationale: This article promotes the idea that CIOs should tailor AI to user personas to increase adoption and value. Our analysts dismissed it as a buzzword-heavy piece offering little actionable insight, with conclusions that were viewed as obvious and lacking in depth.
Harvey transforms legal work with Claude
Rating: Optional
Rationale: Harvey's integration with Claude to assist legal professionals is presented here more as a marketing update than a substantive case study. Our analysts found the article lacking in technical depth and practical detail, reducing its value to a general audience despite Harvey’s prominence in AI legal tech.
Recalculating the costs and benefits of GenAI
Rating: Optional
Rationale: Although framed as an analytical piece, this article fails to offer new insights or data on the real costs and benefits of generative AI. Our analysts criticized it as vague and lacking content, offering generic advice without meaningful takeaways.
Arc Institute’s first virtual cell model: State
Rating: Optional
Rationale: The Arc Institute’s development of a virtual cell model showcases generative AI applications in biosciences, particularly cellular biology. However, our analysts deemed it highly specialized and not directly relevant to most AI leaders outside of life sciences, thus classifying it as optional.
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Enjoy,
John Sviokla,Paul Baier and our AI Analysts Luda Kopeikina and Adam Rappaport.