✷ The archive · 11 labs · 3,432 dispatches
The labs
No more opening a dozen official blogs every morning. First-hand releases from OpenAI, Anthropic, DeepMind and the rest, each with its substance pulled out.
Databricks and Hugging Face Integrate Apache Spark for Faster LLM Training
Databricks has introduced first-class Apache Spark support in Hugging Face Datasets via the Dataset.from_spark() function, reducing data loading times by up to 40% for large-scale model training and tuning.
Running DeepFloyd IF on Free‑Tier Google Colab with Diffusers
Hugging Face shows how to run the open‑source DeepFloyd IF text‑to‑image model on a free Google Colab notebook by using 8‑bit quantization, modular pipeline loading, and Diffusers‑integrated optimizations.
Anthropic and Scale Partnership for Enterprise Generative AI
Anthropic has partnered with Scale to integrate the Claude AI assistant into Scale's platform, providing enterprises with deployment tools, prompt engineering, and secure data integration.
OpenAI Introduces New Data Management Controls for ChatGPT
OpenAI has introduced a new setting to disable chat history to prevent model training on user conversations, alongside plans for a ChatGPT Business subscription and a new data export tool.
Hugging Face Launches Chinese Language Blog to Support Global AI Community
Hugging Face has launched a dedicated Chinese language blog (hf.co/blog/zh) to provide translated technical resources and foster deeper collaboration with the Chinese AI community.
Hosting Unity Games on Hugging Face Spaces
Hugging Face Spaces can host playable Unity games by utilizing the Static HTML template and WebGL build targets.
Anthropic Proposal for Increased NIST Funding for AI Measurement
Anthropic proposes ambitiously funding the National Institute of Standards and Technology (NIST) to develop standardized AI measurement tools and safety thresholds, which they argue is a prerequisite for effective AI regulation.
Accelerating Hugging Face Transformers with AWS Inferentia2
Hugging Face and AWS have optimized Transformers for AWS Inferentia2, a purpose-built inference accelerator that significantly reduces latency and increases throughput for large-scale models.
Graph Classification with Transformers
Hugging Face demonstrates how to perform graph classification using the Graphormer model within the Transformers library, covering data formatting, preprocessing, and fine-tuning.
Creating Privacy Preserving AI with Substra
Hugging Face and Substra highlight how federated learning enables the training of AI models across decentralized data sources to maintain privacy and security, particularly in sensitive domains like healthcare.
OpenAI Bug Bounty Program Announcement
OpenAI has launched a Bug Bounty Program in partnership with Bugcrowd to reward security researchers for identifying and addressing vulnerabilities in its systems.
Snorkel AI and Hugging Face Integration for Enterprise Foundation Models
Snorkel AI has partnered with Hugging Face to integrate Hugging Face Inference Endpoints into Snorkel Flow, allowing enterprises to easily access and adapt over 150,000 open-source foundation models.
OpenAI Approach to AI Safety
OpenAI employs a multi-layered safety strategy combining rigorous pre-deployment testing, iterative real-world deployment, and continuous alignment research to mitigate risks associated with powerful AI systems.
StackLLaMA: Training LLaMA with RLHF for Stack Exchange
Hugging Face introduces StackLLaMA, a model trained using Supervised Fine-tuning, Reward Modeling, and Reinforcement Learning from Human Feedback (RLHF) to answer Stack Exchange questions.
Hugging Face Ethics and Society Newsletter #3: Ethical Openness Initiative
Hugging Face announced new ethical openness measures—including six ethics tags, a flagging system, and audience‑guiding metadata—to make open‑source ML safer and more inclusive.
Accelerating Stable Diffusion Inference on Intel Sapphire Rapids CPUs
Hugging Face shows how to cut Stable Diffusion image generation from 32 seconds to about 5 seconds on Intel Sapphire Rapids CPUs using Optimum Intel, OpenVINO, system‑level tweaks, IPEX BF16, and a faster scheduler.
BLOOMZ Inference on Habana Gaudi2 Accelerator
Hugging Face demonstrates that the Habana Gaudi2 accelerator achieves faster inference for the BLOOMZ 176B model than the Nvidia A100 80GB, leveraging the Optimum Habana library and DeepSpeed-inference.
Federated Learning with Hugging Face and Flower
Hugging Face demonstrates how to use the Flower framework to perform federated learning on a pre-trained distilBERT model for sentiment analysis on the IMDB dataset.
OpenAI March 20 ChatGPT Outage and Data Exposure Analysis
OpenAI took ChatGPT offline on March 20, 2023, due to a bug in an open-source library that exposed chat titles and payment information for a small subset of active ChatGPT Plus subscribers.
Training ControlNet with Hugging Face Diffusers
Hugging Face provides a comprehensive guide and training script via the diffusers library to enable users to train custom ControlNet models for Stable Diffusion, demonstrated through the creation of an 'Uncanny Faces' pose model.
ChatGPT Plugins Release
OpenAI has introduced plugins for ChatGPT, allowing the model to access real-time information, perform computations, and integrate with third-party services to expand its utility and reduce hallucinations.
Hugging Face Hub Improved Jupyter Notebook Support
Hugging Face has introduced human-readable rendering for Jupyter notebooks hosted on the Hub, improving reproducibility and accessibility for machine learning practitioners.
GPTs are GPTs: Labor Market Impact of Large Language Models
OpenAI research indicates that approximately 80% of the U.S. workforce could have at least 10% of their work tasks affected by Large Language Models, positioning them as general-purpose technologies.
Anthropic Reveals Privileged Bases in Transformer Residual Streams
Anthropic discovered that transformer residual stream dimensions are not arbitrary but align with privileged bases, likely due to Adam's per-dimension normalizers, challenging prior theoretical assumptions.
OpenAI GPT-4 announcement and capabilities overview
OpenAI announced GPT-4, a large multimodal model that achieves human‑level performance on many professional benchmarks and is now available via ChatGPT, API waitlist, and open‑source evaluation tools.
OpenAI announces GPT‑4 powered Virtual Volunteer for Be My Eyes
OpenAI integrated GPT‑4’s visual input into the Be My Eyes app, creating a Virtual Volunteer that can describe, analyze, and converse about images, dramatically expanding visual accessibility for blind and low‑vision users.
Stripe GPT-4 Integration Case Study
Stripe integrated GPT-4 across its platform to automate business summaries, enhance developer support via documentation analysis, and improve fraud detection on community forums.
Duolingo Integrates GPT-4 for Advanced Language Learning
Duolingo has launched Duolingo Max, a new subscription tier featuring GPT-4 powered Role Play and Explain my Answer to provide immersive conversation practice and contextual grammar feedback.
Khan Academy Integrates GPT-4 to Power Khanmigo AI Assistant
Khan Academy is piloting Khanmigo, an AI-powered tutor and teacher assistant powered by GPT-4, to provide individualized learning and instructional support.
OpenAI and Government of Iceland Partnership for Icelandic Language Preservation
OpenAI has partnered with the Government of Iceland and private industry to use GPT-4 and Reinforcement Learning from Human Feedback (RLHF) to preserve the Icelandic language in the digital age.
Introducing Claude
Anthropic has released Claude, a next-generation AI assistant designed to be helpful, honest, and harmless, available in high-performance and fast, lightweight versions.
OpenAI GPT-4 Release
OpenAI has released GPT-4, a large language model that demonstrates advanced reasoning, higher accuracy in problem solving, and improved safety and factual reliability compared to GPT-3.5.
Multivariate Probabilistic Time Series Forecasting with Informer
Hugging Face has integrated the Informer model into the Transformers library to enable efficient multivariate probabilistic time series forecasting with reduced computational and memory complexity.
Fine-tuning 20B LLMs with RLHF on a 24GB Consumer GPU
Hugging Face released an integration of TRL and PEFT that enables reinforcement learning fine‑tuning of 20‑billion‑parameter language models on a single 24 GB GPU using 8‑bit quantization and low‑rank adapters.
Anthropic's Core Views on AI Safety
Anthropic outlines an empirically-driven, portfolio-based approach to AI safety to mitigate catastrophic risks associated with the rapid scaling of transformative AI systems.
Kakao Brain ViT and ALIGN Models Release with COYO 700M Dataset
Kakao Brain and Hugging Face released open‑source ViT and ALIGN visual‑language models trained on the new 700 M image‑text COYO dataset, providing the first publicly available ALIGN model and ViT models with reproducible training data.
ControlNet in Diffusers
Hugging Face has integrated ControlNet into the Diffusers library, enabling precise spatial control over Stable Diffusion image generation using conditionings like Canny edges, depth maps, and human poses.
Using Machine Learning for Disaster Response: The afetharita Project
Hugging Face describes how volunteers used the Hugging Face ecosystem to rapidly deploy ML models for OCR, NER, and remote sensing to aid survivors of the February 2023 Turkey earthquakes.
Hugging Face Diffusers Ethical Guidelines
Hugging Face has introduced an ethical framework for the Diffusers library to guide technical decisions and community contributions while mitigating the potential societal risks of diffusion models.
Hugging Face Expert Acceleration Program: Witty Works Case Study
Witty Works utilized the Hugging Face Expert Acceleration Program and SetFit to build a context-dependent inclusive language classifier with high accuracy using minimal labeled data.
OpenAI Planning for AGI and Beyond
OpenAI outlines a strategy for the gradual deployment of AI systems to allow society to adapt, emphasizing the need for increased alignment research, global governance, and a cautious approach to existential risks.
Swift Diffusers for Mac 1.1 Release
Hugging Face has released Diffusers for Mac version 1.1, a native open-source app that leverages Core ML to accelerate Stable Diffusion on Apple Silicon, offering up to 2x faster generation on certain hardware configurations.
Red-Teaming Large Language Models
Hugging Face outlines the critical role of red-teaming in identifying LLM vulnerabilities to prevent harmful outputs, emphasizing the need for collaborative, adaptive evaluation methods.
Fetch AI Infrastructure Migration: Consolidating Tools with Hugging Face and AWS
Fetch reduced development time by 30% and processing latency by 50% by migrating from a third-party AI 'black box' to an in-house ML pipeline powered by Hugging Face and AWS.
Hugging Face and AWS Strategic Partnership for AI Accessibility
Hugging Face and AWS have expanded their strategic partnership to democratize generative AI by integrating Hugging Face models with AWS infrastructure and purpose-built ML accelerators.
OpenAI AI System Behavior and Governance Framework
OpenAI outlines a two-step training process to shape ChatGPT's behavior and a three-pillar strategy to improve defaults, enable user customization, and integrate public input into AI governance.
Hugging Face Inference Endpoints Case Study
Hugging Face is migrating its CPU-based ML models from AWS ECS/Fargate to Hugging Face Inference Endpoints to reduce operational complexity and improve latency.
BLIP-2: Zero-Shot Image-to-Text Generation
BLIP-2 is a visual-language model from Salesforce Research that uses a Querying Transformer (Q-Former) to bridge frozen image encoders and frozen large language models for efficient zero-shot image-to-text generation.
Anthropic Research: The Capacity for Moral Self-Correction in LLMs
Anthropic research demonstrates that Large Language Models (LLMs) trained with RLHF can morally self-correct to avoid harmful outputs when instructed, a capability that emerges at 22B parameters.
🤗 PEFT library release enables parameter-efficient fine-tuning of billion‑scale models
Hugging Face announced the 🤗 PEFT library, which lets users fine‑tune billion‑parameter models on low‑resource hardware by training only a tiny fraction of parameters.