AI

How Transparent Are Foundation Model Developers?

Introducing the Foundation Model Transparency Index

ML/AI Platform Build vs Buy Decision: What Factors to C...

An ML/AI platform provides a coherent collection of tools and frameworks to buil...

Strategies For Effective Prompt Engineering

When I first delved into machine learning, prompt engineering seemed like a nich...

Adversarial Machine Learning: Defense Strategies

The growing prevalence of ML models in business-critical applications results in...

LLM Training: RLHF and Its Alternatives

I frequently reference a process called Reinforcement Learning with Human Feedba...

From Self-Alignment to LongLoRA

Another month, another round of interesting research papers ranging from large l...

LLM Business and Busyness: Recent Company Investments a...

Discussing Recent Company Investments and AI Adoption, New Small Openly Availabl...

AI and Open Source in 2023

The Highs and Lows: A Year in Review

Practical Tips for Finetuning LLMs Using LoRA (Low-Rank...

Things I Learned From Hundreds of Experiments

A Potential Successor to RLHF for Efficient LLM Alignme...

From Vision Transformers to innovative large language model finetuning technique...

Tackling Hallucinations, Boosting Reasoning Abilities, ...

This month, I want to focus on three papers that address three distinct problem ...

Ten Noteworthy AI Research Papers of 2023

This year has felt distinctly different. I've been working in, on, and with mach...

Understanding and Coding Self-Attention, Multi-Head Att...

This article will teach you about self-attention mechanisms used in transformer ...

Model Merging, Mixtures of Experts, and Towards Smaller...

Model Merging, Mixtures of Experts, and Towards Smaller LLMs

Improving LoRA: Implementing Weight-Decomposed Low-Rank...

Low-rank adaptation (LoRA) is a machine learning technique that modifies a pretr...

Tips for LLM Pretraining and Evaluating Reward Models

Discussing AI Research Papers in March 2024

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