Superalignment Fast Grants
We’re launching $10M in grants to support technical research towards the alignment and safety of superhuman AI systems, including weak-to-strong generalization, interpretability, scalable oversight, and more.
Similar Posts
AI Weekly Issue #492: AI slop : A $725B bet on what no one wanted
ByWeb Dev
Hyperscalers will spend $725 billion on AI infrastructure this year. The users they are spending it on are now actively rejecting the output. Gartner finds 50% of US consumers prefer brands that don’t use generative AI. Wikipedia just banned AI-generated content 44-2. Stack Overflow’s new-question volume has fallen 78% year over year. Google AI Overviews…
Parameter-Efficient Sparsity Crafting (PESC): A Novel AI Approach to Transition Dense Models to Sparse Models Using a Mixture-of-Experts (Moe) Architecture
The emergence of large language models (LLMs) like GPT, Claude, Gemini, LLaMA, Mistral, etc., has greatly accelerated recent advances in natural language processing (NLP). Instruction tweaking is a well-known approach to training LLMs. This method allows LLMs to improve their pre-trained representations to follow human instructions using large-scale, well-formatted instruction data. However, these tasks are…
AI News Weekly – Issue #413: OpenAI reportedly plans to launch an AI agent early next year – Nov 15th 2024
Welcome Interested in sponsorship opportunities? Join the AI conversation and transform your advertising strategy with AI weekly sponsorship aiweekly.co In the News OpenAI reportedly plans to launch an AI agent early next year OpenAI is preparing to release an autonomous AI agent that can control computers and perform tasks independently, code-named “Operator.” theverge.com Sponsor Get…
Researchers from Allen Institute for AI and UNC-Chapel Hill Unveil Surprising Findings – Easy Data Training Outperforms Hard Data in Complex AI Tasks
Language models, designed to understand and generate text, are essential tools in various fields, ranging from simple text generation to complex problem-solving. However, a key challenge lies in training these models to perform well on complex or ‘hard’ data, often characterized by its specialized nature and higher complexity. The accuracy and reliability of a model’s…
This AI Paper from UNC-Chapel Hill Proposes ReGAL: A Gradient-Free Method for Learning a Library of Reusable Functions via Code Refactorization
Optimizing code through abstraction in software development is not just a practice but a necessity. It leads to streamlined processes, where reusable components simplify tasks, increase code readability, and foster reuse. The development of generalizable abstractions, especially in automated program synthesis, stands at the forefront of current research endeavors. Traditionally, Large Language Models (LLMs) have…
Researchers from IST Austria and Neural Magic Unveil RoSA: A New AI Method for Efficient Language Model Fine-Tuning
Developing large language models (LLMs) is a significant advancement in artificial intelligence and machine learning. Due to their vast size and complexity, these models have shown remarkable capabilities in understanding and generating human language. However, their extensive parameter count poses challenges regarding computational and memory resources, especially during the training phase. This has led to…
