Sitemap - 2024 - Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots
Structural Advancements Developed for Language Models to Support Application Creation
The Shifting Vocabulary of AI (Updated)
How Did We Go From Large Language Models to Large Behaviour Models?
Safety Challenges For Generative AI Agents In Autonomous Machines
The Evolution of AI Agents & Agentic Systems
Anthropicโs Claude 3.5 Computer Use Framework (AI Agent)
Revolutionising AI Agents With Computer Use Tools
Six Years Of Prompt Engineering
The Focus Is Shifting From AI Agents To AI Agent Tool Use
Four Levels of RAG โ Research from Microsoft
Building Conversational AI Agents By Integrating Reasoning, Speaking & Acting With LLMs
Language Models Emerging Technologies
Anthropic ACI (AI Agent Computer Interface)
Whatโs Your Definition Of An AI Agent?
Make Every Application An AI Agent
Contrasting RPA, Chatbots & AI Agents
AI Agent Computer Interface (ACI)
The Advent Of Open Agentic Frameworks & Agent Computer Interfaces (ACI)
5 Levels Of AI Agents (Updated)
Demystifying Large Language Model Function Calling
LLM Symbolic Reasoning For Visual AI Agents
Chain-Of-Symbol Prompting To Improve Spatial Reasoning
Real-World Agentic Applications
The Role of Small Models in the LLM Era
Small Language Model (SLM) Efficiency, Performance & Potential
AgentLite Is A Lightweight Framework for Building AI Agents
Outline-Driven RAG & Web Research Prototype
The Evolution of Grounding & Planning In AI Agents
An AI Agent Architecture & Framework Is Emerging
Emergence of Large Action Models (LAMs) and Their Impact on AI Agents
Strategic Chain-of-Thought (SCoT)
Small Language Models Supporting Large Language Models
The History & Future of Prompt Engineering
Seeding GPT-4o-mini Using Fine-Tuning
Dialog Flow Generation To Constrain LLM-Based Chatbots
AppAgent v2 With Advanced Agent for Flexible Mobile Interactions
Multi-Modal Agentic Applications
Fine-Tuning OpenAI GPT-4o mini
27 Unique Dev Challenges: A Recent Study Explored the Top Challenges Faced by LLM Developers
AI Agents With Human In The Loop
AI Agent Evaluation Framework From Apple
OpenAI Enhanced Their API With Robust Structured Output Capabilities
LLM-Driven Synthetic Data Generation, Curation & Evaluation
Creating Synthetic Training Data
LangGraph Introduced SubGraphs
AI Agents: Exploring Agentic Applications
LangChain Based Plan & Execute AI Agent With GPT-4o-mini
LangChain Search AI Agent Using GPT-4o-mini
Large Language Model Use & Augmentation
RAG Implementations Fail Due To Insufficient Focus On Question Intent
Agentic AI: Creating An AI Agent Which Can Navigate The Internet
AgentInstruct Uses Agentic Flows To Create Synthetic Training Data
LangSmith, LangGraph Cloud & LangGraph Studio
Speculative RAG By Google Research
Moving From Natural Language Understanding To Mobile UI Understanding
Teaching Small Language Models to Reason
Our Human Creativity Is Becoming More Uniform Due To ChatGPT
Evaluating The Quality Of RAG & Long-Context LLM Output
LLM Disruption in Chatbot Development Frameworks
TinyStories Is A Synthetic DataSet Created With GPT-4 & Used To Train Phi-3
LangGraph Studio From LangChain
LangChain Just Launched LangGraph Cloud
RAG Survey & Available Research
FlowMind Is An Automatic Workflow Generator
Can Conversation Designers Excel As Data Designers?
Phi-3 Is A Small Language Model Which Can Run On Your Phone
LangGraph From LangChain Explained In Simple Terms
DR-RAG: Applying Dynamic Document Relevance To Question-Answering RAG
Creating A Benchmark Taxonomy For Prompt Engineering
Language Agent Tree Search โ LATS
Tree Of Thoughts Prompting (ToT)
Using Fine-Tuning To Imbed Hidden Messages In Language Models
Implementing Chain-of-Thought Principles in Fine-Tuning Data for RAG Systems
Assertions Are Like Guardrails for LLM Apps
DSPy & The Principle Of Assertions
Using DSPy For A RAG Implementation
Controllable Agents For RAG With Human In The Loop Chat
How Would The Architecture For An LLM Agent Platform Look?
HILL: Solving for LLM Hallucination & Slop
Teaching LLMs To Say โI donโt Knowโ
Comparing LLM Agents to Chains: Differences, Advantages & Disadvantages
Can Minor Document Typos Comprehensively Disrupt RAG Retriever & Reader Components?
Enterprise Prompt Engineering Practices
GALE Is A Next-Gen Generative AI Productivity Suite
The Conversational AI Technology Landscape: Version 5.0
A Short History Of LLMs & Conversational UIs
Large Language Model (LLM) Stack โ Version 6
LangChain Chatbot Framework With Retrievers
Building The Most Basic LangChain Chatbot
Data Design For Fine-Tuning LLM Long Context Windows
The Importance Of Granular Data Design For Fine-Tuning
LangChain Structured Output Parser Using OpenAI
Three Considerations For Private Open-Source LLM Instances
Intents Are Not Going AwayโฆRoNID Is A New Intent Discovery Framework
The Large Language Model Landscape โ Version 5
LLMs Excel At In-Context Learning (ICL), But What About Long In-context Learning?
Using LLMs For Autonomous Vehicles
Matching Retrieved Context With Question Context Using LogProbs With OpenAI for RAG
Rapid Development Of Intelligent Generative AI APIs
RAG, Hallucination & Structure: Research By ServiceNow
Data Design For Fine-Tuning To Improve Small Language Model Behaviour
No-Code Deployment & Orchestration Of Open-Sourced Foundation Models
LlamaIndex Agent Step-Wise Execution Framework With Agent Runners & Agent Workers
The Case For An AI Productivity Suite
Step-Wise Controllable Agents From LlamaIndex
Improve Conversational UIs Using Social Intelligence
RAG Implementations Are Becoming More Agent-Like
Agentic Search-Augmented Factuality Evaluator (SAFE) For LLMs
FaaF: Facts As A Function For Evaluating RAG
Disambiguation: Using Dynamic Context In Crafting Effective RAG Question Suggestions
FIT-RAG: Are RAG Architectures Settling On A Standardised Approach?
Challenges In Adopting Retrieval-Augmented Generation Solutions
Retrieval Augmented Fine-Tuning (RAFT)
Complete AI Productivity Suite
DRAGIN: Dynamic RAG Based On Real-Time Information Needs Of LLMs
A New Study Compares RAG & Fine-Tuning For Knowledge Base Use-Cases
Chain-of-Instructions (CoI) Fine-Tuning & Going Beyond Instruction Tuning
Performing Multiple LLM Calls & Voting On The Best Result Are Subject To Scaling Laws
Please Stop Saying Long Context Windows Will Replace RAG
TinyLlama Is An Open-Source Small Language Model
Agentic RAG: Context-Augmented OpenAI Agents
RAT โ Retrieval Augmented Thoughts
Exploring the Purpose, Power & Potential of Small Language Models (SLMs)
Large Impact: The Rise of Small Language Models
Large Language Models Excel At In-Context Learning (ICL)
RAG, Data Privacy, Attack Methods & Safe-Prompts
Self-Reflective Retrieval-Augmented Generation (SELF-RAG)
Time-Aware Adaptive RAG (TA-ARE)
Develop Generative Apps Locally
How To Create A LangChain Application That Runs Locally & Offline
Language Model Quantization Explained
LLM Drift, Prompt Drift & Cascading
Catastrophic Forgetting In LLMs
Leveraging LLM In-Context Learning Abilities
Five Stages Of LLM Implementation [Updated]
Demonstrate, Search, Predict (DSP) for LLMs
T-RAG = RAG + Fine-Tuning + Entity Detection
Run A Small Language Model (SLM) Local & Offline
The Case For Small Language Models
Beyond Chain-of-Thought LLM Reasoning
Comparing Human, LLM & LLM-RAG Responses
Craft Successful Conversational User Interfaces: Align User Intent With Developed Intent
A Benchmark for Verifying Chain-Of-Thought
Seven RAG Engineering Failure Points
OpenAI Agent Query Planning Using LlamaIndex
Adding Noise Improves RAG Performance
UniMS-RAG: Unified Multi-Source RAG for Personalised Dialogue
Chain-of-Symbol Prompting (CoS) For Large Language Models
Prompt-RAG: Vector Embedding Free Retrieval-Augmented Generation
Concise Chain-of-Thought (CCoT) Prompting
Retrieval-Augmented Generation (RAG) vs LLM Fine-Tuning
Understanding LLM User Experience & Expectation
Meta Taxonomy Of Large Language Model Correction & Refinement
Considering Large Language Model Reasoning Step Length
Large Language Model (LLM) SWOT Analysis (Updated)
Chain Of Natural Language Inference (CoNLI)
Validating Low-Confidence LLM Generation
Large Language Model Hallucination Mitigation Techniques
What Is LangChain Expression Language (LCEL)?
Random Chain-Of-Thought For LLMs & Distilling Self-Evaluation Capability
Active Prompting with Chain-of-Thought for Large Language Models
Teaching LLMs To Say, โI donโt knowโ