The foundations under everything else: gradients, losses, what a network is doing when it learns. Concrete numerical examples before abstraction, wherever possible.
FundamentalsDeep dive14 min
A deep dive into Srivastava et al. (2014) — the mechanism, the arithmetic behind weight scaling, what the benchmarks actually showed, and the tuning heuristics that still hold up.
ResearchPaper7 min
A tiny, invisible change can make an image model see a cat where any person sees a dog. The 2019 MIT paper 'Adversarial Examples Are Not Bugs, They Are Features', explained without the maths: what the researchers found, the experiment that makes the point, and why it matters for anyone who relies on AI.
ResearchPaper5 min
Exploring how SMILESGNN leverages multimodal fusion to improve clinical toxicity prediction while offering interpretable insights into molecular structures.
ResearchPaper5 min
A new two-model architecture distinctly separates content understanding from policy learning, enhancing flexibility and efficiency in content moderation.
ResearchPaper4 min
A new protocol proposes a way to make AI-assisted claims independently challengeable by ensuring transparent and falsifiable publication records.
ResearchPaper4 min
A study reveals that additive input pathways in Householder Linear RNNs act as parasitic attractors, destabilizing state-tracking capabilities.
ResearchNews5 min
Exploring IBM Research's new framework that integrates reasoning into communication systems, challenging conventional information theory.
ResearchPaper5 min
A new reinforcement learning paper claims curiosity should emerge from an agent's own internal dynamics rather than a hand-tuned bonus term — a skeptical read of what the experiments actually support.
ResearchPaper7 min
New research from Amazon Science offers a surprisingly elegant explanation for a decade-old puzzle: good solutions are simply too short to cheat with.
NVIDIA has launched Metatron v1, a model for interactive humanoid control.
NVIDIA and Baker Lab have released RFD4-Proteína, a flow-matching model for joint sequence–structure generation in biomolecular design.
MistralAI unveils Timestral-209M, a new model for zero-shot time series forecasting.
Mistral introduces Timestral-123M, a powerful model for zero-shot time series forecasting.
MistralAI has released the Timestral-28M model, a new addition to their time series foundation models.
MistralAI introduces Timestral-5M, a time series foundation model designed for zero-shot forecasting.
NVIDIA releases the GR00T-N1.7-AppleToPlate model with 3 billion parameters.