If there’s anyone left on planet Earth who thinks that GenAI/AI is just a fad just think about two things: 1. GenAI/AI is central to the power and military of the world’s super powers, 2. the most powerful and profitable firms in the history of human kind need to win the race. This is why innovation is accelerating and today’s news has an essential read on how the Chinese are doing in a helpful, visual format. Enjoy!

Good Morning, GAI Insights Community!

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Yesterday there were 1 Essential, 2 Important, and 4 Optional articles.

State of AI: China
Rating: Essential
Rationale: This comprehensive visual report provides a strategic overview of China's accelerating progress in generative AI, challenging U.S. dominance and highlighting models approaching parity with OpenAI’s offerings. Our analysts emphasized the geopolitical significance of China's AI infrastructure investment, noting the report's utility for executive briefings and the clear visualization of shifts in global AI power structures.

Holo-1: New family of GUI automation VLMs powering GUI agent Surfer-H
Rating: Important
Rationale: The H Company has open-sourced Holo-1, a browser-based AI agent framework that mimics human interactions with web browsers and graphical user interfaces, aiming to automate complex workflows. While still early, our analysts noted its relevance in the rising wave of web automation agents and its open-source nature allows immediate experimentation, marking it as a notable step in the evolution of AI agents.

Faster, Smarter, Cheaper: AI Is Reinventing Market Research
Rating: Important
Rationale: Andreessen Horowitz showcases how generative AI is reshaping market research by automating time-consuming data collection and analysis tasks, drastically reducing time-to-insight. Our analysts panel highlighted the shift from manual processes to AI-driven content creation in market research as a major operational change, noting the report as a useful benchmark for emerging practices.

How S&P is using deep web scraping, ensemble learning and Snowflake architecture to collect 5X more data on SMEs
Rating: Optional
Rationale: S&P’s data infrastructure initiative combines web scraping and ensemble learning to better assess SME risk, offering a glimpse into large-scale AI data engineering. However, our analysts viewed this as a narrow case study with limited generalizability beyond its industry-specific application.

Selecting a Model Based on Stripe Conversion – A Practical Eval for Startups
Rating: Optional
Rationale: This OpenAI Cookbook example demonstrates how real-world business metrics, like Stripe conversion rates, can guide model selection. While conceptually useful, our analysts noted the approach is only relevant to startups with high traffic volume and was too technical or niche for most AI leaders.

Why I have slightly longer timelines than some of my guests
Rating: Optional
Rationale: Dwarkesh Patel explores the limitations to rapid AGI development, focusing on the need for continual learning in AI models. Our analysts panel acknowledged the intellectual value but considered the topic speculative and less actionable for enterprise AI leaders.

Memory in ChatGPT
Rating: Optional
Rationale: OpenAI's memory feature in ChatGPT enhances persistent user personalization and conversational depth, representing a meaningful UX improvement. However, since the feature has been widely rolled out since April, analysts viewed it as useful but not newsworthy.

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Enjoy! John and thanks to yesterday’s raters: Paul Baier and our AI Analysts, Luda Kopeikina, Amanda Fetch and our Guest Reviewer today, Alden Do Rosario. Thank you for joining, Alden!