A Message for 2026: The Year of Human&Curated Progress (Part 4)
The fourth and final installment in a short series of articles from various AI models and how they view the upcoming year in 2026. A 2026 New Year’s message inspiring AI, ML, robotics, and automation innovators to build boldly and shape the future responsibly. This edition is from DeepSeek.
EDA in Public (Part 3): RFM Analysis for Customer Segmentation in Pandas
How to build, score, and interpret RFM segments step by step
The post EDA in Public (Part 3): RFM Analysis for Customer Segmentation in Pandas appeared first on Towards Data Science.
Deep Reinforcement Learning: The Actor-Critic Method
Robot friends collaborate to learn to fly a drone
The post Deep Reinforcement Learning: The Actor-Critic Method appeared first on Towards Data Science.
Google T5Gemma-2 Explained: Trying Out a Laptop-Friendly Multimodal AI Model
Google just dropped T5Gemma-2, and it is a game-changer for someone working with AI models on everyday hardware. Built on the Gemma 3 family, this encoder-decoder powerhouse squeezes multimodal smarts and massive context into tiny packages. Imagine running 270M parameters running smoothly on your la...
The Drill-Down and Fabricate Test (DDFT): A Protocol for Measuring Epistemic Robustness in Language Models
arXiv:2512.23850v1 Announce Type: new
Abstract: Current language model evaluations measure what models know under ideal conditions but not how robustly they know it under realistic stress. Static benchmarks like MMLU and TruthfulQA cannot distinguish a model that lacks knowledge from one whose veri...
CASCADE: Cumulative Agentic Skill Creation through Autonomous Development and Evolution
arXiv:2512.23880v1 Announce Type: new
Abstract: Large language model (LLM) agents currently depend on predefined tools or brittle tool generation, constraining their capability and adaptability to complex scientific tasks. We introduce CASCADE, a self-evolving agentic framework representing an earl...
A Proof-of-Concept for Explainable Disease Diagnosis Using Large Language Models and Answer Set Programming
arXiv:2512.23932v1 Announce Type: new
Abstract: Accurate disease prediction is vital for timely intervention, effective treatment, and reducing medical complications. While symbolic AI has been applied in healthcare, its adoption remains limited due to the effort required for constructing high-qual...
SPARK: Search Personalization via Agent-Driven Retrieval and Knowledge-sharing
arXiv:2512.24008v1 Announce Type: new
Abstract: Personalized search demands the ability to model users' evolving, multi-dimensional information needs; a challenge for systems constrained by static profiles or monolithic retrieval pipelines. We present SPARK (Search Personalization via Agent-Driven ...
ROAD: Reflective Optimization via Automated Debugging for Zero-Shot Agent Alignment
arXiv:2512.24040v1 Announce Type: new
Abstract: Automatic Prompt Optimization (APO) has emerged as a critical technique for enhancing Large Language Model (LLM) performance, yet current state-of-the-art methods typically rely on large, labeled gold-standard development sets to compute fitness score...
Coordinate Matrix Machine: A Human-level Concept Learning to Classify Very Similar Documents
arXiv:2512.23749v1 Announce Type: new
Abstract: Human-level concept learning argues that humans typically learn new concepts from a single example, whereas machine learning algorithms typically require hundreds of samples to learn a single concept. Our brain subconsciously identifies important feat...
arXiv:2512.23752v1 Announce Type: new
Abstract: Recent work has shown that small transformers trained in controlled "wind-tunnel'' settings can implement exact Bayesian inference, and that their training dynamics produce a geometric substrate -- low-dimensional value manifolds and progressively ort...
Train Your Large Model on Multiple GPUs with Tensor Parallelism
This article is divided into five parts; they are: • An Example of Tensor Parallelism • Setting Up Tensor Parallelism • Preparing Model for Tensor Parallelism • Train a Model with Tensor Parallelism • Combining Tensor Parallelism with FSDP Tensor parallelism originated from the Megatron-LM paper.
How Cloudflare’s tokio-quiche Makes QUIC and HTTP/3 a First Class Citizen in Rust Backends
Cloudflare has open sourced tokio-quiche, an asynchronous QUIC and HTTP/3 Rust library that wraps its battle tested quiche implementation with the Tokio runtime. The library has been refined inside production systems such as Apple iCloud Private Relay, next generation Oxy based proxies and WARP’s MA...
Production-Ready LLMs Made Simple with the NeMo Agent Toolkit
From simple chat to multi-agent reasoning and real-time REST APIs
The post Production-Ready LLMs Made Simple with the NeMo Agent Toolkit appeared first on Towards Data Science.
2026: The Year We Stop Asking “Can We?” and Start Asking “Should We?” (Part 3)
The third installment in a short series of articles from various AI models and how they view the upcoming year in 2026. A 2026 New Year’s message inspiring AI, ML, robotics, and automation innovators to build boldly and shape the future responsibly. This edition is from ChatGPT.
Student ID Benefits Worth Thousands: Get 15+ Premium Tools For Free or on Discount
I remember from my student days the plethora of subscriptions, fees, and payments to be made for a range of tasks. Be it learning a new skill, using the right environment for practice, or simply travelling to and from home, we had to shell money out of our pockets. But it is almost 2026 now, […]
The...
Train Your Large Model on Multiple GPUs with Fully Sharded Data Parallelism
This article is divided into five parts; they are: • Introduction to Fully Sharded Data Parallel • Preparing Model for FSDP Training • Training Loop with FSDP • Fine-Tuning FSDP Behavior • Checkpointing FSDP Models Sharding is a term originally used in database management systems, where it refers to...
Cloudhands™ Announces Upcoming Al Platform Launch and New Exec Leadership
Cloudhands, Inc. (the “Company” or “Cloudhands”) today announced preparations for the upcoming launch of Cloudhands’ unified Al platform, along with the appointment of Tom Hebert as President and David Novick as Chief Marketing Officer. Cloudhands’ unified Al platform is the result of extensive deve...
This is the second in a short series of articles from various AI models and how they view the upcoming year in 2026. A forward looking 2026 New Year’s message for AI, machine learning, robotics, and automation enthusiasts, celebrating bold innovation, responsible tech, and the builders shaping the f...
The Machine Learning “Advent Calendar” Bonus 1: AUC in Excel
AUC measures how well a model ranks positives above negatives, independent of any chosen threshold.
The post The Machine Learning “Advent Calendar” Bonus 1: AUC in Excel appeared first on Towards Data Science.
Foundation Models as the Backbone of Next-Gen AI Platforms
Foundation models as the backbone of next-gen AI platforms, reshaping enterprise AI architecture, governance, and scale. One signal breaks through the AI noise in 2026: most enterprise AI budgets are no longer allocated to applications. They are spent on platforms. The current industry forecasts hav...