60 stories tagged with #learning, in publish-time order across the WeSearch catalog. Tag pages update as new stories ingest.
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Still: Amortized KV Cache Compaction in a Single Forward Pass
The KV cache is the memory bottleneck of long-horizon language model deployment. Practically, a deployable compactor must be lightweight enough to call during inference, expressive…
Stop guessing which local AI models fit your hardware — this free tool does it for you
A huge friction point with self-hosted AI, solved…
Two Years Later, We’re Finally Learning How a Transformers-Inspired Rover Fared on the Moon
SORA-Q showed that tiny robots could do big things on the Moon.…
The Smallest Brain You Can Build: A Perceptron in Python
A perceptron explained from scratch in Python, with interactive demos. Learn weights, bias, the decision boundary, epochs, learning rate, and why we normalize data.…
Starting kindergarten soon? Summer is a perfect time to support a child's early literacy learning
The SAT Is Back. But Is There a Better Alternative?
Jeremy Tate thinks the SAT is way too easy—so he invented the Classic Learning Test. He tells Maya Sulkin that he’s ‘in a battle to save Western civilization.’…
Fine-tuning an LLM to write docs like it's 1995
In my predictions for 2030 I wrote that tech writers would be using specialized LLMs, running locally on powerful hardware. I see hints of this move to “local first” among engineer…
Africa: School in a Hot World - What Research Is Saying About Children's Health and Learning
Analysis - Climate change is making southern Africa hotter. While much attention has focused on climate impacts like droughts, floods and food insecurity, another crisis is unfoldi…
Babbel might be the reason the cute bartender keeps talking to you
Short lessons, real conversations, zero classroom energy…
Why learning financial literacy has to be part of the American dream: former CFTC commissioner
"If you have a smartphone and you have an app, you can now engage in not just financial transactions, but an entire virtual community anywhere in the world," said Caroline Pham.…
Learning C# + .NET + Unity
How to Code AI? Complete Guide for 2026
Mastering how to code AI effectively only requires a foundational grasp of software engineering principles and essential artificial intelligence concepts.…
Ideogram 4.0: A 9.3B open-weight image model
Our first open-weight foundation model. A 9.3B single-stream Diffusion Transformer, trained from scratch, with a vision-language text encoder and structured JSON prompts.…
I Spent May Evaluating Different Engines for OCR
Testing fourteen engines on ninety-three human documents…
Agentes de IA: cómo un LLM razona, usa herramientas y actúa solo
Un agente de IA es un LLM metido en un bucle que razona, elige herramientas y ejecuta acciones hasta cumplir una meta. Te explicamos cada pieza con có…
GitHub Copilot's New Desktop App Isn't About Chat. It's About Agents.
Microsoft's latest announcements from Build 2026 signal a fundamental shift. The new GitHub Copilot desktop app is a move from inline code completion to a native environment for ag…
NVIDIA Research Unlocks Advanced Grasping, Smarter Autonomous Driving and Agent Training at Scale
New NVIDIA Research breakthroughs show how training at scale — across gripper types, driving scenarios and virtual worlds — creates AI that generalizes to diverse applications.…
How to make your first Machine Learning project (as an absolute beginner)
Making your first Machine Learning project as beginner can be daunting. To be honest, I was daunted....…
Curatube: a distraction free interface for YT playlists to focus on learning
A distraction free learning environment for YouTube courses…
I Built a C++ Backend So My GPU Would Stop Eating Air
A comprehensive guide to optimizing LLM inference by eliminating padding overhead with hardware-aware sequence packing.…
Learning React useState Through Practical Examples
When starting React, understanding useState only through definitions can feel confusing. The easiest...…
Direct Preference Optimization Beyond Chatbots
A Blog post by Dharma-AI on Hugging Face…
RAG reranking for production agents: four approaches, four failure modes
Most agents that "hallucinate" in production aren't actually hallucinating. The right context existed...…
Day 16 of Learning Python: List Comprehensions
Creating Lists in One Line List comprehensions combine iteration and transformation into a single...…
I stopped buying expensive Ethernet cables after learning what actually matters
Premium Ethernet cables rarely improve home network performance, meeting the standard matters far more than paying for marketing claims.…
useState Scenario questions - 2
5. You have 5 input fields (name, email, phone, city, password). 1.Better to use: ...…
I Built a Vector Search Engine from Scratch — Here's What I Learned
I Built a Vector Search Engine from Scratch — Here's What I Learned Implementing HNSW...…
The Car Light Modifier and the Printer Renter Start Learning AI
The Car Light Modifier and the Printer Renter Start Learning AI Let me tell you a funny...…
Understanding Linear Regression: A Foundation of Machine Learning
Linear Regression is one of the most fundamental and widely used algorithms in Machine Learning and...…
NVIDIA Put Petaflop Compute on Your Desk — And It Changes the AI Cost Equation
NVIDIA Put Petaflop Compute on Your Desk — And It Changes the AI Cost Equation At GTC...…
Learning from Poland’s economic success story
“European” features like universal health care and a high minimum wage are fine.…
Can deforestation predict Ebola outbreaks? Q&A with CDC’s Carson Telford
The 2026 Bundibugyo Ebola outbreak in Central and East Africa has already left at least 49 people dead, with health authorities racing to stop the spread of the disease. What if th…
🚀 StudyQuiz v1.1.0 — UX Enhancements, Integration Tests, and Reliability Improvements
StudyQuiz has moved forward since the first frontend MVP release. This update focuses less on adding...…
Day 5 — Entering the World of Classification
Today I started Week 3 of the Machine Learning Specialization and learned about...…
AI as a Thin Client and the Crisis of Knowledge Succession: An Academic Analysis
Two Hypotheses In the contemporary discussion about artificial intelligence, two distinct hypotheses...…
AI.Insaf (@ai_tablet) — Полный архив постов канала
## Ранние посты (#1-~49)…
AWS Internet Gateway and Route Tables Explained for Beginners
After learning about Public Subnets and Private Subnets, the next question that comes across our mind...…
Introducing RadixAttention to Trellis
How we implemented KV caching based on radix trees in Trellis, and some benchmarks…
AI.Insaf — Архив постов канала (реальные посты из web_fetch)
**Канал:** https://t.me/ai_tablet…
Running 35B–400B LLMs on a GPU-less Cluster to Mine 10,000 Papers — and the 4 Bugs That Almost Ruined the Data
A field report: a CPU-only, GPU-less distributed LLM pipeline (llama.cpp + quantized MoE) mining 10,000 papers — and the 4 silent data-quality bugs that nearly ruined the results.…
Introduction to Data-Centric AI
The first-ever course on data-centric AI. Learn how you can train better ML models by improving the data.…
The Death of the God Model: Why True AGI Requires a Split Brain Architecture
TL;DR: The AI industry's pursuit of a single, omnipotent "God Model" is a dead end. Due to the...…
GPU Forecasters: Language Models as Selective Surrogates for Kernel Optimization
GPU kernels are the workhorse of modern deep learning, and optimizing them (via evolutionary search or coding agents) usually requires repeated measurement on target hardware. Whil…
Benchmarking LLM-as-a-Judge for Long-Form Output Evaluation
As large language models (LLMs) are increasingly used for long-form generation, reliably evaluating long-form outputs has become a critical challenge. LLM-as-a-judge offers a scala…
New to Python, What Would You Focus on First if You Were Starting Again?
I recently started learning Python. I have some programming background, but I am still very much a...…
Visual Graph Scaffolds for Structural Reasoning in Large Language Models
Graphs have been used to enhance large language models (LLMs) for structured reasoning, mostly as external knowledge sources are provided to models at test time. In this paper, we …
Evaluating Transformer and LSTM Frameworks for Prediction in Ungauged Basins
Watershed networks exhibit convergent topologies in which multiple tributaries merge into downstream channels,integrating diverse upstream hydrological processes. In ungauged basin…
ChatHealthAI: Aligning Electronic Health Record Representations with Large Language Models for Grounded Clinical Reasoning
Large language models (LLMs) exhibit strong natural-language reasoning abilities for clinical decision support, but struggle to effectively model structured longitudinal electronic…
Traj-Evolve: A Self-Evolving Multi-Agent System for Patient Trajectory Modeling in Lung Cancer Early Detection
Modeling patient trajectories from longitudinal electronic health records (EHRs) requires reasoning over sparse, noisy, and long-context multimodal sequences. Existing LLM-based mu…
Thinking Past the Answer: Evaluating Harmful Overthinking in Large Reasoning Models
Large Reasoning Models (LRMs) improve performance by generating explicit intermediate reasoning traces through increased test-time compute, yet the assumption that longer reasoning…
WISE-HAR: A Generalizable Ensemble Deep Learning Framework for WiFi-Based Human Activity Recognition
Human Activity Recognition (HAR) using WiFi signals has emerged as a transformative technology for smart homes, healthcare monitoring, security systems, and ambient assisted living…
Inducing Reasoning Primitives from Agent Traces
ReAct-style LLM agents often rediscover the same reasoning routines across problems, yet leave those routines trapped in transient scratchpads. We introduce Reasoning Primitive Ind…
RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases
Relational databases underpin modern enterprise, scientific, and healthcare systems, yet predictive machine learning on such data remains challenging due to their multi-table, hete…
ToolGate: Token-Efficient Pre-Call Control for Tool-Augmented Vision-Language Agents
Tool-augmented vision-language agents can acquire external perceptual evidence through OCR, detection, segmentation, and other tools, but executing every proposed tool call is cost…
SkillDAG: Self-Evolving Typed Skill Graphs for LLM Skill Selection at Scale
As LLM agents adopt large skill libraries, selecting the right subset becomes a structural problem rather than a similarity-matching one: skills depend on, conflict with, specializ…
CORE: Conflict-Oriented Reasoning for General Multimodal Manipulation Detection
The rapid rise of generative AI has made multimodal fake news increasingly realistic and pervasive, posing severe threats to public trust and social stability. Existing detection m…
DELTAMEM: Incremental Experience Memory for LLM Agents via Residual Trees
Large Language Model (LLM)-based agents increasingly rely on memory to learn from experiences over continual interactions. However, storing experiences as independent, flat units l…
Decomposing how prompting steers behavior
Prompting steers large language models (LLMs) and vision-language models (VLMs) without weight updates, but it remains unclear how instruction changes reshape internal representati…
From Long News to Accurate Forecast: Importance-Aware Fusion and PRM-Guided Reflection for Time Series Forecasting
Incorporating news into time series forecasting is appealing because news can reveal abrupt exogenous events that historical values alone cannot recover. However, existing LLM-base…
EvoTrainer: Co-Evolving LLM Policies and Training Harnesses for Autonomous Agentic Reinforcement Learning
Autonomous LLM training is often framed as recipe search, which leaves the training harness largely static. This limitation sharpens in agentic RL, where shifting bottlenecks and s…