Phi-2: Microsoft's NewPowerful 2.7B Parameter Language Model
Microsoft has released Phi-2, a compact 2.7 billion parameter language model that achieves state-of-the-art performance on reasoning and language tasks, matching models over 25x its size.
LLM58
Check out the latest posts
Openness in Language Models: Open Source vs Open Weights vs Restricted Weights
As language models hype "openness", this article proposes key criteria to evaluate true transparency balanced with safety.
Tapping into Creativity - The Challenge of Activating Imagination in AI
Creativity - the spark of human imagination - remains AI's final frontier. Unlocking true innovation in machines requires blazing new inroads into uncharted conceptual space.
Statistical or Sentient Part 2- Tokens and Thoughts
What drives the eerily human-like capabilities of large language models like GPT-3? Their artificial "minds" operate on a simple principle - predicting the next most likely token. Understanding these basic mechanics provides the key to unlocking their full potential through prompt engineering.
Measuring How Much Leading AI Chatbots Hallucinate
Vectara recently introduced a unique leaderboard that ranks AI chatbots based on how well they avoid 'hallucinations.' Find out which AI comes out on top and why it matters!
Optimizing Large Language Models to Maximize Performance
Getting the most out of large language models requires the artful application of optimization techniques like prompt engineering, retrieval augmentation, and fine-tuning. This guide explores proven methods for maximizing LLM performance.