Test Information Space

Large Language ModelOperations (LLMOps) Explained

Workshop: Computational Thinking, LLMs and the Future of Education

BASE TTS: Lessons from building a billion-parameter Text-to-Speech model on 100K hours of data

Learning the importance of training data under concept drift

Suppressing Pink Elephants with Direct Principle Feedback

Cohere For AI Launches Aya, an LLM Covering More Than 100 Languages

NVIDIA CEO: Every Country Needs Sovereign AI | NVIDIA Blog

Gemini - Google DeepMind

How to Choose the Right AI Model for Your Enterprise

Escalation Risks from Language Models in Military and Diplomatic Decision-Making

Better Call GPT, Comparing Large Language Models Against Lawyers

SymbolicAI: A framework for logic-based approaches combining generative models and solvers

Building an early warning system for LLM-aided biological threat creation

Shanahan, M. (2022). Talking about large language models.

Large Language Models are Superpositions of All Characters: Attaining Arbitrary Role-play via Self-Alignment

Meta releases ‘Code Llama 70B’, an open-source behemoth to rival private AI development

How enterprises are using open source LLMs: 16 examples

Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding

Health-LLM: Large Language Models for Health Prediction via Wearable Sensor Data

Automated Testing for LLMOps

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Stability AI unveils smaller, more efficient 1.6B language model as part of ongoing innovation

Self-Rewarding Language Models

Is AI the New 'Truth' Detector?

Mission: Impossible Language Models

Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training

Can large language models identify and correct their mistakes?

Who's Harry Potter? Approximate Unlearning in LLMs

Ferret: Refer and Ground Anything Anywhere at Any Granularity

Mamba: Linear-Time Sequence Modeling with Selective State Spaces (Paper Explained)