52 related articles

Explore how deliberately violating DDR4 timing rules enables running PrismML's Bonsai AI model inside DRAM, covering the principles, energy benefits, and challenges of processing-in-memory.

A deep dive into how neural network hidden layers solve the XOR problem through feature space transformation, with math, geometry, and concrete examples.

Why do neural networks make the decisions they do? This article explores AI interpretability — mechanistic interpretability, CoT monitoring, and safety auditing — and how researchers reverse-engineer large models for AI safety.
Reverse Spam Filtering: Making Senders…
A radical rethink of spam filtering: using proof-of-work to make unknown senders pay a computational cost, fundamentally disrupting the spam economy. Deep dive into the technical principles, real-world challenges, and lessons learned.
Paper Reproduction as an Entry Point i…
How can applied math students efficiently enter Scientific Machine Learning (SciML)? This guide covers the value and pitfalls of paper reproduction, with a layered path from numerical PDEs to research.
Latent Reasoning: The Next-Generation …
Is CoT really AI 'thinking'? This deep dive covers latent reasoning's rise — Coconut, HRM, BDH — and the core trade-offs between interpretability, efficiency, and governance in high-stakes AI.
Loot Raiders: An Indie Dev Journey Bui…
Loot Raiders is an ARC Raiders-inspired backpack loot web game built with Svelte. This article explores its gameplay design, Svelte's technical advantages for interaction-heavy games, and the indie dev journey from idea to launch.
The Theory of Deep Learning: Why Do Ne…
Deep learning shines in practice, but why does theory always lag behind? This article surveys the over-parameterization paradox, implicit regularization, NTK, the information bottleneck, and more.

The classic Zhang et al. paper says Critic attacks are weaker than Actor attacks, but an experimenter observed the opposite in multi-agent PPO. This article dives into SA-MDP, continuous action spaces, and multi-agent non-stationarity in adversarial RL.

SiliconLLM builds a CPU-native LLM architecture from scratch, combining selective SSM, ternary (1.58-bit) LUT MLP, and granular MoE, co-designed around the L3 cache bandwidth cliff. Ternary kernels show 4-5x speedup over fp32.

In-depth analysis of OpenAI's GPT-5.6: Sol, Terra, Luna pricing, Cerebras inference advantages, and how OpenAI and Anthropic navigate government regulation amid US-China AI competition.

Experiments show DINOv2 Giant scores just 41% on k-NN classification, while SigLIP2 reaches 92%. This article dives into the embedding-space differences between contrastive and self-supervised learning to guide vision encoder selection.

Alibaba banned Claude company-wide, flagging Claude Code as high-risk. Three converging timelines — Anthropic's distillation attack allegations, the 1260H list, and Claude Code's hidden detection system — reveal the geopolitical logic behind the ban.

As generative AI sweeps the workplace, once-marginalized philosophy and humanities are being revalued. This article explores why critical thinking, ethical judgment, and questioning are the new scarce competencies in the AI era.

Immunologist Derya Unutmaz shares how he used OpenAI Codex to build research-grade apps for flow cytometry analysis and CRISPR design, exploring AI-driven digital twins and personalized cancer treatment.

By capturing and analyzing ChatGPT's real network traffic during web retrieval, this article reveals the underlying logic of AI source selection—covering the layered mechanisms of retrieval recall and content filtering, domain preference patterns, and practical insights for content creators and SEO professionals.

Embedding condensation is a hidden bottleneck in small language model training. Dispersion Loss combats this by enforcing representation spread during training at zero inference cost.

SpaceX's Starlink satellite network drives $28B annual revenue, earning it Neocloud status. Analysis of SpaceX vs. AWS/Azure and its AI infrastructure edge.

Deep dive into how Preply combines AI features like Lesson Insights with 100K human tutors to achieve 70%+ adoption rates, redefining personalized language learning.

A detailed guide to deploying a multimodal AI Agent on a 3080Ti with 12GB VRAM, covering LLM, STT, TTS, image and video generation module selection, dynamic VRAM loading, and real-world performance.