AI prose is distinguishable by word and punctuation choice as well as sentence and paragraph structure. But its hallmarks are not what you might expect. Read our full investigation

AI is getting very good at writing code. But writing code was never the whole job. Architecture. Security. Observability. Testing. Cost. Operations. Incident response. The better AI gets at coding, the more obvious the rest of software engineering becomes.

AI coding agents might create an unexpected problem: More code. Less shared knowledge. If an engineer solves a problem through an AI agent, a lot of the reasoning can stay inside a private human-agent loop. No Stack Overflow answer. No GitHub discussion. No detailed issue thread. Sometimes not even a meaningful commit message. We may become dramatically better at producing software while becoming worse at producing the public knowledge that future engineers learn from. That tradeoff deserves much more attention.

AI JUST LEARNED TO WRITE LIFE Scientists used AI to create genetic code that never existed before. The same technology that writes code and creates images is now learning the language of life. - Evo 2 was trained on the genomes of millions of living organisms - AI can generate new DNA sequences that never existed in nature - Researchers created AI-designed viruses that successfully attacked bacteria - The breakthrough could help discover new medicines faster AI is no longer just predicting the future. It is starting to build it.

AI is transforming productivity—but productivity is only part of the equation. Speaking at AI4 2026, @drfeifei highlighted a critical distinction: while AI tools can make people and businesses more productive, those gains do not automatically translate into shared prosperity. As AI continues to reshape jobs—creating new opportunities while changing or disrupting others—she argued that the conversation needs to go beyond how much more we can produce. It also needs to consider how the economic benefits of AI can be shared more broadly. Productivity ≠ Shared Prosperity. #ChinaAMC# #CNQQ# #AI4# #AI# #ArtificialIntelligence# #FeiFeiLi# #FutureOfAI# #FutureOfWork# #AIProductivity# Risk Disclaimer: Investment involves risk, including possible loss of principal. Any forecasts, projections, or opinions contained herein are for reference only and are not guaranteed to occur. The information in this material reflects prevailing market conditions and our judgment as of the release date, which are subject to change without further notice.

AI is powerful—but access to AI alone won't eliminate the skills gap. At AI4 2026, @AndrewYNg Ng argued that even as AI capabilities advance, there will continue to be meaningful differences between people who know how to use these tools effectively and those who don't. Rather than framing AI primarily as a threat, he offered a more optimistic message—especially for young people: learn the tools, build the skills, and use AI to expand what you can accomplish. The opportunity isn't simply AI replacing human capability. It's what people can achieve when they learn to work with AI. AI Won't Eliminate the Skills Gap. #ChinaAMC# #CNQQ# #AI4# #AI# #ArtificialIntelligence# #AndrewNg# #AISkills# #FutureOfWork# #FutureOfAI# Risk Disclaimer: Investment involves risk, including possible loss of principal. Any forecasts, projections, or opinions contained herein are for reference only and are not guaranteed to occur. The information in this material reflects prevailing market conditions and our judgment as of the release date, which are subject to change without further notice.