LLM – Winston Wang

Evaluating the Mathematical Reasoning Capabilities of Large Language Models: Limitations and Challenges

Leave a Comment / Paper Skimming / By Winston

LLMs have made remarkable progress in various fields, including natural language processing, question answering, and creative tasks, even demonstrating the ability to solve mathematical problems. Recently, OpenAI’s o1 model, which uses CoT (Chain of Thought), has shown significant reasoning capabilities. However, for a long time, the commonly used GSM8K dataset has had a fixed set of questions

Evaluating the Mathematical Reasoning Capabilities of Large Language Models: Limitations and Challenges Read More »

Paper SkimmingAI, Apple Research, LLM, Math Reasoning, TechNews

How RAG Technology Powers AI-Driven Search Engines: A Deep Dive into Tech Behind Perplexity AI

Leave a Comment / Research Highlights / By Winston

Have you ever wondered how AI tools like ChatGPT, powered by large language models (LLMs), manage to answer nearly any question posed by users, especially in open-domain queries that require extensive knowledge or up-to-date facts? Relying solely on traditional LLMs to generate answers can be incredibly challenging. Here’s why: 1. Knowledge Limitations: LLMs are trained

How RAG Technology Powers AI-Driven Search Engines: A Deep Dive into Tech Behind Perplexity AI Read More »

Research HighlightsAI, Information Retrieval, LLM, Perplexity, RAG

Introducing Graph RAG: A New Approach to Addressing Global Query Challenges in Large Language Models

Leave a Comment / Paper Skimming / By Winston

Traditional Retrieval-Augmented Generation (RAG) systems often struggle when it comes to handling global queries that require summarizing entire datasets. To address this limitation, a team from Microsoft Research and associated departments has developed a novel method called Graph RAG. This approach combines the strengths of graph-based indexing and query-focused summarization to enhance the ability of

Introducing Graph RAG: A New Approach to Addressing Global Query Challenges in Large Language Models Read More »

Paper SkimmingAI, GraphRAG, LLM, Microsoft Research, RAG

Enhancing AI Output: Understanding Prover-Verifier Games

Leave a Comment / Research Highlights / By Winston

As Large Language Models (LLMs) continue to evolve, their increasing complexity has brought a new set of challenges. One significant issue is the generation of outputs that are often vague, ambiguous, or logically inconsistent. These issues make it difficult for users to interpret and trust the AI’s reasoning. In response, OpenAI has introduced a novel

Enhancing AI Output: Understanding Prover-Verifier Games Read More »

Research HighlightsAI, LLM, OpenAI, Reinforcement Learning

Advances in Lightweight LLMs and On-Device AI for Enhanced Privacy

Leave a Comment / Posts, Thoughts and Reflections / By Winston

In the past few weeks, both OpenAI and Google have introduced smaller-scale large-language models. OpenAI’s ChatGPT-4o Mini boasts approximately 8B parameters, while Google’s Gemma 2 2B is even more compact at just 2B parameters—small enough to run on the free tier of T4 GPUs in Google Colab. It’s exciting to see the advancement towards more

Advances in Lightweight LLMs and On-Device AI for Enhanced Privacy Read More »

Posts, Thoughts and ReflectionsApple Intelligence, Gemma, LLM, Privacy

The Llama 3 Herd of Models

A Comprehensive Summary of Extrinsic Hallucinations in LLMs.

Large Enough — Mistral Large 2 released

Leave a Comment / Articles, Posts / By Winston

🔍 Exciting developments in the AI space: Mistral AI has unveiled its latest model, Mistral Large 2, boasting 123 billion parameters and a 128k context window. This model excels in code generation, mathematics, and multilingual support, making it a game-changer for complex business applications. It promises unmatched accuracy and performance through La Plateforme and major

Large Enough — Mistral Large 2 released Read More »

Articles, PostsAI, LLM, Machine Learning, Mistral