Google A2UI Explained: How AI Agents Build Secure, Native User Interfaces
We have entered the time of multi-agent artificial intelligence. However, there is a very important issue: in what way can remote AI agents produce rich and interactive experiences without exposing the system to security risks? Google A2UI (Agent-to-UI) protocol addresses this question in a very sma...
AI, Robotics & Automation in 2026: What’s Likely, What’s Not, and What Comes Next
An insightful analysis of what AI, robotics, and automation will realistically achieve in 2026—what’s likely, what’s not, and why it matters for the future.
Exploring TabPFN: A Foundation Model Built for Tabular Data
Understanding the architecture, training pipeline and implementing TabPFN in practice
The post Exploring TabPFN: A Foundation Model Built for Tabular Data appeared first on Towards Data Science.
How IntelliNode Automates Complex Workflows with Vibe Agents
Many AI systems focus on isolated tasks or simple prompt engineering. This approach allowed us to build interesting applications from a single prompt, but we are starting to hit a limit. Simple prompting falls short when we tackle complex AI tasks that require multiple stages or enterprise systems t...
Equity’s 2026 Predictions: AI Agents, Blockbuster IPOs, and the Future of VC
TechCrunch’s Equity crew is bringing 2025 to a close and getting ahead on the year to come with our annual predictions episode! Hosts Kirsten Korosec, Anthony Ha, and Rebecca Bellan were joined by Build Mode host Isabelle Johannessen to dissect the year’s biggest tech developments, from mega AI fund...
Eating more vitamin C can physically change your skin
Vitamin C doesn’t just belong in skincare products—it works even better when you eat it. Scientists discovered that vitamin C from food travels through the bloodstream into every layer of the skin, boosting collagen and skin renewal. People who ate two vitamin C–packed kiwifruit daily showed thicker...
Agent creation has become easier than ever but have you ever thought – how can we make them more powerful than they already are? I recently thought of one possible way – what if they had realtime information about specific categories like finance and movies. That would be really cool, right? While e...
Build Your Own NotebookLlama: A PDF to Podcast Pipeline (Open, Fast, and Fully Yours)
The NotebookLM is a relatively new Internet phenomenon, in which Google has distinguished itself, thanks to its Audio Overview mode – a mechanism that transforms the text in the paper into a two-person podcast. All of this, in a single click. But what should you do when you wish to build it yourself...
Training a Model on Multiple GPUs with Data Parallelism
This article is divided into two parts; they are: • Data Parallelism • Distributed Data Parallelism If you have multiple GPUs, you can combine them to operate as a single GPU with greater memory capacity.
Keeping Probabilities Honest: The Jacobian Adjustment
An intuitive explanation of transforming random variables correctly.
The post Keeping Probabilities Honest: The Jacobian Adjustment appeared first on Towards Data Science.
Parameter-Efficient Neural CDEs via Implicit Function Jacobians
arXiv:2512.20625v1 Announce Type: new
Abstract: Neural Controlled Differential Equations (Neural CDEs, NCDEs) are a unique branch of methods, specifically tailored for analysing temporal sequences. However, they come with drawbacks, the main one being the number of parameters, required for the meth...
Learning Evolving Latent Strategies for Multi-Agent Language Systems without Model Fine-Tuning
arXiv:2512.20629v1 Announce Type: new
Abstract: This study proposes a multi-agent language framework that enables continual strategy evolution without fine-tuning the language model's parameters. The core idea is to liberate the latent vectors of abstract concepts from traditional static semantic r...
Zero-Training Temporal Drift Detection for Transformer Sentiment Models: A Comprehensive Analysis on Authentic Social Media Streams
arXiv:2512.20631v1 Announce Type: new
Abstract: We present a comprehensive zero-training temporal drift analysis of transformer-based sentiment models validated on authentic social media data from major real-world events. Through systematic evaluation across three transformer architectures and rigo...
Real Time Detection and Quantitative Analysis of Spurious Forgetting in Continual Learning
arXiv:2512.20634v1 Announce Type: new
Abstract: Catastrophic forgetting remains a fundamental challenge in continual learning for large language models. Recent work revealed that performance degradation may stem from spurious forgetting caused by task alignment disruption rather than true knowledge...
BitRL-Light: 1-bit LLM Agents with Deep Reinforcement Learning for Energy-Efficient Smart Home Lighting Optimization
arXiv:2512.20623v1 Announce Type: new
Abstract: Smart home lighting systems consume 15-20% of residential energy but lack adaptive intelligence to optimize for user comfort and energy efficiency simultaneously. We present BitRL-Light, a novel framework combining 1-bit quantized Large Language Model...
Quantum-Inspired Multi Agent Reinforcement Learning for Exploration Exploitation Optimization in UAV-Assisted 6G Network Deployment
arXiv:2512.20624v1 Announce Type: new
Abstract: This study introduces a quantum inspired framework for optimizing the exploration exploitation tradeoff in multiagent reinforcement learning, applied to UAVassisted 6G network deployment. We consider a cooperative scenario where ten intelligent UAVs a...
arXiv:2512.20626v1 Announce Type: new
Abstract: Retrieval-augmented generation (RAG) enables large language models (LLMs) to dynamically access external information, which is powerful for answering questions over previously unseen documents. Nonetheless, they struggle with high-level conceptual und...
MicroProbe: Efficient Reliability Assessment for Foundation Models with Minimal Data
arXiv:2512.20630v1 Announce Type: new
Abstract: Foundation model reliability assessment typically requires thousands of evaluation examples, making it computationally expensive and time-consuming for real-world deployment. We introduce microprobe, a novel approach that achieves comprehensive reliab...
The Machine Learning “Advent Calendar” Day 24: Transformers for Text in Excel
An intuitive, step-by-step look at how Transformers use self-attention to turn static word embeddings into contextual representations, illustrated with simple examples and an Excel-friendly walkthrough.
The post The Machine Learning “Advent Calendar” Day 24: Transformers for Text in Excel appeared f...
Training a Model with Limited Memory using Mixed Precision and Gradient Checkpointing
This article is divided into three parts; they are: • Floating-point Numbers • Automatic Mixed Precision Training • Gradient Checkpointing Let's get started! The default data type in PyTorch is the IEEE 754 32-bit floating-point format, also known as single precision.
Waymo is testing Gemini as an in-car AI assistant in its robotaxis
Waymo is testing a Gemini-powered in-car AI assistant, per findings from a 1,200-line system prompt. The assistant can answer general knowledge questions, control certain in-cabin features, and more.
Step into a fictional cocktail party where today’s most popular AI models—ChatGPT, Copilot, Claude, Gemini, MidJourney, Stable Diffusion, and Bard—banter, argue, and collaborate. This playful analogy highlights their unique personalities, training philosophies, and biases, while revealing how they c...