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  • Writer's pictureGeopolitics.Λsia

Weekly Trend Radar and Special Feature on Frontier AI Knowledge

Updated: Jul 31, 2023

In this week's edition of Weekly Trend Radar, we will be exploring the latest trends in political, economic, sociocultural, technological, legal and environment and legal (PESTLEL). As a special feature, we'll be diving deep into the fascinating world of Frontier AI Knowledge, shedding light on recent advancements, groundbreaking research, and potential applications across various domains.

Part I: Weekly Trend Radar and PESTEL Report

This weekly essay aims to provide concise yet comprehensive insights on the most critical geopolitical priorities based on the metageopolitical framework. The analysis is grouped into PESTLE (Political, Economic, Sociocultural, Technological, Legal, and Environmental) sections to facilitate informed decision-making for C-suite executives.

Please access full weekly trend radar at:


  • Title 42 Bipartisan Bill - The recent push for a bipartisan bill on Title 42 highlights the ongoing political debate on immigration policies in the United States. The hard power dynamics at play involve both domestic political forces and international relations with neighboring countries. State actors and non-state actors alike are motivated to address the humanitarian crisis while balancing national security concerns.


  • West Wing Playbook - The West Wing Playbook provides insights into the Biden administration's economic policy priorities, revealing the interplay between economic power influences and noopolitik elements. State actors are motivated to drive economic growth and address pressing issues like inflation and unemployment, while non-state actors (e.g., businesses and advocacy groups) seek favorable economic conditions for their interests.


  • Mushrooms Vitamin D - The potential health benefits of mushrooms as a source of vitamin D reflect the ongoing trend towards healthier lifestyles and the increasing focus on natural, plant-based solutions. This impacts businesses and organizations in the food and health industries, as they adapt to changing consumer preferences and needs.


  • Mechanical Keyboards Tested - The increasing demand for mechanical keyboards signals a shift in consumer preferences for high-quality, durable products in the technology sector. State and non-state actors must keep pace with these trends to remain competitive and meet consumer expectations.


  • Abortion Rights Groups - The ongoing legal battle over abortion rights in the United States demonstrates the interplay between hard power dynamics, noopolitik elements, and the role of state and non-state actors in shaping the legal landscape. The outcome of this battle has far-reaching implications for women's rights, healthcare access, and societal norms.


  • Canada Wildfires - The increasing frequency and intensity of wildfires in Canada underscore the urgent need for global action on climate change. This environmental crisis affects various industries, including forestry, agriculture, and tourism, and requires coordinated efforts from state and non-state actors to mitigate the impacts and address the root causes.

Conclusion: This week's metageopolitical analysis reveals the complex interplay between hard power dynamics, economic power influences, noopolitik elements, and the roles and motivations of state and non-state actors. By understanding these factors and their implications on global power dynamics, C-suite executives can make informed decisions for their organizations in an increasingly interconnected world.


Part II: Integrated Report on AI Frontier Research Trajectory and Implications

In light of the following recent developments and the potential impact of AI on various aspects of our lives, we have applied our trend radar technique to explore the frontier of AI knowledge. By doing so, we aim to identify emerging trends, breakthroughs, and possible future directions in the field. This will enable us to better understand the implications of AI advancements and to devise strategies that can harness AI's potential effectively and responsibly for the benefit of society.

  1. In a recent interview on 60 Minutes, Sundar Pichai shared three bold opinions about the state of AI research: a) emergence, where AI can reason and generate knowledge that doesn't exist in smaller-scale LLMs, b) hallucination, where AI sometimes produces fictitious results confidently, a phenomenon that researchers are still struggling to address, and c) the black box, as the AI research community debates whether the outputs of LLMs are randomly generated without understanding the meaning behind them or are statistically generated outputs that reflect different forms of reasoning than humans are familiar with.

  2. Lately, there have been three significant events in the AI research field: a) the release of ChatGPT on 30/11/2022, which attracted 1 million users in just 5 days, breaking all previous adoption rate records, b) the release of GPT-4 in March, which further fueled the industry's growth in user acceptance and investment, and c) the leak of Facebook's LLaMa model on 4Chan. Due to the Streisand effect, the model has spread uncontrollably, despite Facebook's efforts to contain it. Consequently, numerous open-source AI research projects have emerged, with some developers creating powerful AI models on budgets as low as $100. This aligns with a leaked Google internal assessment on Discord, which stated that the real competitor to Google is not OpenAI but the open-source community. Google's strategy now focuses on joining and supporting these efforts.

  3. Recent research trends seem to focus on optimizing AI capabilities in terms of quality, performance, throughput, reduced hallucination, increased precision, and unified reasoning with minimal effort and budget. This involves a growing emphasis on prompt engineering. Such developments align with the ongoing study of AI-human interaction and the recent debate between Yann LeCun and Max Tegmark on whether AI could potentially be harmful to humans, prompting calls for a temporary halt in AI research. The research community is striving to decipher the "black box" mechanisms of AI reasoning within neural networks to achieve the aforementioned goals.

Recent trajectory of AI frontier research focuses on several key areas:

a) Understanding and controlling AI-generated outputs: Researchers work on reducing hallucinations, improving precision, and ensuring consistent reasoning in AI outputs like ChatGPT and GPT-4.

b) Prompt engineering and interaction optimization: Developing better prompts, instructions, and interaction techniques that guide AI systems in producing desired results.

c) Demystifying the "black box": Investigating the inner workings of large-scale AI models to uncover the underlying mechanisms behind their reasoning and output generation.

d) Multimodal learning: Creating single embedding spaces across different data modalities, as demonstrated by Meta's IMAGEBIND project, allowing for more effective and integrated AI models. Multimodal AI refers to artificial intelligence systems that are capable of processing and understanding multiple types of data modalities, such as text, images, audio, and video. These systems can analyze and integrate information from various sources, allowing them to make more informed decisions and generate more accurate outputs. Multimodal AI models can be used in a wide range of applications, such as natural language understanding, computer vision, and speech recognition, to create more versatile and comprehensive AI solutions.

e) AI-assisted programming: Advancements in autocoding AI, such as Starcoder system, outperforming GPT-4 in coding tasks and paving the way for self-revising AI.

Assessment of AI research within the next 5 years:

a) Knowledge: AI models will grow in their knowledge capacity, potentially learning from external data sources in real-time.

b) Resources: AI models will become more efficient and cost-effective, enabling greater access and contributions to the field.

c) Community: Increased interdisciplinary collaboration in the AI research community.

d) Constraints: Ongoing discussions about AI safety, transparency, and regulation due to ethical considerations and potential misuse.

e) Integration: Prevalence of multimodal data integration, leading to AI models that can understand and process various types of data simultaneously.

f) Autocoding AI: Increased accessibility and efficiency of AI-assisted programming, potentially improving code quality and productivity.

Implications and applied fields benefiting from AI advancements over the next five years:

a) Mental health and well-being: AI systems providing emotional support, therapy, and coaching, helping individuals better understand and manage their emotions.

b) Education: AI-driven tutoring and educational systems offering personalized learning experiences, adapting to individual students' needs.

c) Creative industries: AI assisting in the generation of unique ideas, stories, and designs, becoming a valuable collaborative partner for writers, artists, and other creatives.

d) Business and finance: AI revolutionizing decision-making processes, providing insights and recommendations based on vast amounts of data, enhancing efficiency across industries.

e) Public policy and governance: AI aiding governments in policy formulation, implementation, and evaluation, ensuring that public decisions are data-driven and well-informed.

f) Healthcare: AI models analyzing and processing clinical trial data and medical reports, potentially assisting medical professionals in diagnosis and treatment planning.

g) Legal domain: Improved understanding of legal texts, leading to AI models that can assist in legal analysis and document processing.

h) Customer support and virtual assistants: Improved conversational AI providing more accurate and efficient customer support and enhancing the capabilities of virtual assistants.

i) Programming and software development: Autocoding AI helping developers write and maintain code more efficiently, reducing the time and effort required for programming tasks.

j) Multimodal analytics: AI models processing and analyzing different types of data simultaneously, providing new insights and applications in fields like computer vision, audio analysis, and natural language understanding.

By focusing on these areas, the AI research community can make significant strides in improving human-AI interactions and harnessing AI's potential for meaningful applications across various domains.


We have successfully deployed our Trend Monitoring Radar (TMR) on the Wednesday section. We deployed a Python script to scan weekly news and asked AI to prioritize and categorize it. Additionally, we instructed AI to generate a weekly summary report based on the scanning data in a reporting style for the executive director of the Geopolitical Analysis department. The report is far from perfect, so please do not share the contents publicly. We will strive to make the entire process 100% automated and find ways to improve relevance, consistency, and accuracy in the future. our TMR is inspired by

Geopolitics.Asia will provide serious policy analysis on Mondays, trend monitoring on weekdays, and cultural and lifestyle issues on weekends. Please note that our weekday situation monitoring will not include a trend radar or scenario analysis for the time being, as we work to fully automate these processes with AI. You can, however, access to our previous experiments on trend radar and scenario planning generated by the AI, 1) Simple scenario planning at Jan 26, 2023, 2) Double iteration scenario planning technique at February 2, 2023, 3) Triple iteration scenario planning techniqueat February 9, 2023, and 4) Hyperdimensional scenario planning technique at February 17, 2023.

Stay tuned for updates on this exciting development!



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