Public insights
Published EMAlpha articles on the market themes and questions worth following.
The global equity landscape in May 2026 was defined by a stark divergence between the AI-fuelled euphoria in East Asia and the cautious retreat in other emerging hubs. While the AI and semiconductor s
Bloomberg and Reuters this morning both cited South Korean local media coverage as the trigger behind today’s sharp KOSPI sell-off. But EMAlpha’s MacroMonitor AI Agent had been tracking this narrative
Why Translation Is Not Enough for World-Representative AI A Short Note on Multilingual Representation Gaps in AI Training Data It has become almost routine to describe the next generation of AI models
Commodity Resilience in the Shadow of the Iran Conflict: A Local Lens Analysis The Iran-US conflict has once again underscored that in global markets, local sentiment is the ultimate leading indicator
AI Hype Narrative Becomes AI Disruption It has been nearly a year since the last major AI sentiment flip – when DeepSeek emerged and triggered sharp volatility across AI-linked equities. Now, within t
IPO or No-Go? An AI Agent’s Due Diligence AI Agents are gaining momentum, but how do they differ from traditional Chatbots? In this article, we don’t just explain the difference – we build an AI agent
RAG and Roll: Querying Financial Documents How We’re Leveraging RAG to Enable Chatbot Queries for Financial Documents In this blog, you’ll discover how to create your very first RAG (Retrieval-Augment
RAG Document Parsers How Do You Choose A Document Parser For Your RAG Application? Guidelines For Choosing The Right Text Parsing | Skanda Vivek While RAG has become increasingly popular over the last
Training Compound AI Systems RAG has ushered innovative ways to build around LLMs and data. Lets now see how to train Compound AI Systems that harness the power of LLMs across multiple dimensions Enca
DSPy — Does It Live Up To The Hype? The DSPy framework promises to replace manual prompt engineering with a programming framework for auto-tuned prompts. Let’s see whether this lives up to this promis
Safeguarding LLM Conversations Using Llama Guard Llama Guard recently introduced by Meta aims to safeguard Human-AI conversations — let’s see how well it does in practice Guarding LLM Conversations |
Innovations In Retrieval Augmented Generation Retrieval Augmented Generation (RAG) offers a pathway to integrate large language models like ChatGPT/GPT-4 with custom data, but has limitations. Let’s l
Privacy In Large Language Models In our experience, within 5–10 minutes, potential clients mention privacy as a big concern for OpenAI based apps. Is there any hope for privately hosted LLMs? Generati
How Do You Evaluate Large Language Model Apps — When 99% is just not good enough? LLMs are fundamentally changing the way practitioners evaluate performance . Let’s look at the recent progress towards
Amid the extensive discussion within public forums concerning the technical facets of Large Language Models (LLMs), encompassing both their applications and cost implications, a notable absence prevai
The Economics of Large Language Models A deep dive into considerations for using and hosting large language models There have been many new exciting developments in Generative AI over the last couple
Thematic Investing: Catching Themes with AI Due to recent advances in NLP, algorithms are capable of ingesting raw textual data about stocks from various sources, revolutionizing trading. But how do y
AI in Finance: From Moving Averages to Generative AI Finance is all about capturing changes. If you do well, you win, if not — you lose. Learn how AI significantly changes the game Making predictions
