Researchers at the Allen Institute for AI developed SPECTER2, a new scientific document embedding model that outperforms previous models like SPECTER and SciNCL. SPECTER2 uses a novel two-step training process, incorporating format-specific adapters, and is trained on diverse datasets across multiple scientific fields, resulting in enhanced adaptability and performance.

The article explains the soft nearest neighbor loss (SNNL) for learning dataset class neighborhoods. SNNL enhances representation learning, crucial for tasks like classification and generation, by minimizing distances between similar data points and maximizing them for different ones. It improves upon previous methods like PCA, LLE, NCA, and t-SNE by introducing nonlinearity and optimization across…

This text introduces a beginner-friendly guide focused on discrete optimization in Python, aimed at readers of the “Towards Data Science” platform.

Machine learning issues are fundamentally data problems, emphasizing the need for time investment in data comprehension and cleaning to ensure effective solutions.

Researchers developed a device that enables soft robots and wearables to detect various mechanical forces and temperature changes through color-based sensing, advancing autonomous capabilities.

Experts in electronic nanomaterials envision AI and ML facilitating scientific brainstorming. They’ve created a chatbot with expertise in their scientific field to aid in ideation.

OpenAI has delayed the launch of its custom GPT store from late 2023 to early 2024 due to internal changes, including CEO Sam Altman’s temporary ousting. The company is using the additional time to refine the AI products based on feedback, despite some employees’ unrest.

This article provides a detailed guide to implementing version control in Machine Learning Operations (MLOps), accessible through the Towards Data Science platform.

Google Research and UIUC have developed ZipLoRA, a new AI method that improves personalized creations in text-to-image diffusion models by merging independently trained style and subject LoRAs. It promises enhanced control, effectiveness, and style fidelity and excels at image stylization tasks.