Tabular data, the backbone of countless scientific fields and industries, has long been dominated by gradient-boosted decision trees. However, TabPFN […]
TabPFN: A Foundation Model for Tabular Data Read More »
Developed by researchers at Google Research, T5 (Text-to-Text Transfer Transformer) [paper] employs a unified text-to-text framework to facilitate various NLP
T5: Exploring Google’s Text-to-Text Transformer Read More »
Microsoft has released Phi-4, designed to excel in mathematical reasoning and complex problem-solving. Phi-4, with only 14 billion parameters, demonstrates
Phi-4: A Powerful Small Language Model Specialised in Complex Reasoning Read More »
BERT (Bidirectional Encoder Representations from Transformers), introduced by Google in 2018, allows for powerful contextual understanding of text, significantly impacting
BERT Explained: A Simple Guide Read More »
SmolAgents is an open-source Python library developed by Hugging Face for building and running powerful AI agents with minimal code.
SmolAgents: A Simple Yet Powerful AI Agent Framework Read More »
AI agents represent a significant advancement in AI, signifying a shift from AI systems that merely assist humans to AI
AI Agents: A Comprehensive Overview Read More »
Large ML models often come with substantial computational costs, making them challenging to deploy on resource-constrained devices or in real-time
Pruning of ML Models: An Extensive Overview Read More »
Gradient scaling is a technique aimed at managing gradient magnitudes, primarily in the context of mixed-precision training. It involves adjusting the scale of gradients to prevent underflow or overflow during floating-point computations.
Gradient Scaling: Improve Neural Network Training Stability Read More »
Gradient clipping emerges as a pivotal technique to mitigate gradient explosion and gradient vanishing, ensuring that gradients remain within a manageable range and thereby fostering stable and efficient learning.
Gradient Clipping: A Key To Stable Neural Networks Read More »
Prompt engineering plays a crucial role in LLM performance. However, manual prompt engineering is a laborious and domain-specific process, demanding
PromptWizard: LLM Prompts Made Easy Read More »
What is DSPy? Declarative Self-improving Python (DSPy) is an open-source python framework [paper, github] developed by researchers at Stanford, designed
DSPy: A New Era In Programming Language Models Read More »
Large Concept Models (LCMs) [paper] represent a significant evolution in NLP. Instead of focusing on individual words or subword tokens,
Large Concept Models (LCM): A Paradigm Shift in AI Read More »
