579 related articles

SELENE is an open-source AI learning resource built on Jupyter Notebooks, systematically covering ML, deep learning, Transformers, and LLMs with interactive code and math derivations for beginners.

A developer built a pure C99 inference engine that runs the 1.56TB Kimi K3 model on 8GB RAM using MoE sparsity and NVMe on-demand loading—no GPU, 176KB binary.

Deep analysis of AMD MI355X running Kimi K3 with superior cost-efficiency vs NVIDIA B300, and its implications for the AI inference hardware market.

Google launches Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber, further expanding its lightweight AI product line. Analysis of positioning, differentiation strategy, and developer impact.

OpenAI's internal model Astra reportedly achieved 10 breakthroughs in math and theoretical CS. We analyze the rumors, compute infrastructure trends, real AI research assistant experiences, and AI's limits in original research.

DeepSeek-V4-Flash-0731 scores 50 on the Intelligence Index, nearly matching the frontier model score of 51 from five months prior. We analyze local deployment, hardware requirements, and implications.

DeepSeek V4 Flash launches with benchmark scores approaching Claude Opus 4.8 at just $0.18 per million output tokens. Deep analysis of performance, pricing, and industry impact.

InferX offers free access to DeepSeek V4 Flash (0731 version) with zero data retention and OpenAI-compatible API. Full breakdown of features, pricing, and developer value.

Deep analysis of the dilemma in AI model competition where reasoning gaps and pricing imbalances force vendors to excel at either capability or cost-effectiveness to survive.

Deep analysis of the real cost of serving a 2.8 trillion parameter model. From MoE sparse activation to batching scale effects and inference optimization, revealing why model size and serving cost are less correlated than assumed.

As AI LLM capabilities converge, cost-effectiveness becomes the key selection factor. This article explores how to rationally compare AI models through value assessment, task matching, and cost-benefit analysis.

Deep dive into Heretic uncensoring technology applied to Jamba2-Mini, Qwen3.5-9B, and 27B open-source models, exploring how refusal rates dropped from 97% to 4% and the safety debates involved.

A systematic learning path for understanding the Kimi K3 technical report, covering MoE, MLA, distributed training, and modern post-training techniques.

DeepSeek V4 Flash model weights reportedly open-sourced. This article analyzes its lightweight positioning, open-weight value, comparisons with closed-source models, and deployment guidance.

Explore how graph engineering uses state machines and directed graph structures to constrain AI agent behavior, covering reflection, routing, human-in-the-loop, and parallel execution patterns.

Deep dive into how graph engineering uses state machines and directed graphs to constrain AI agent behavior, covering reflection, routing, human-in-the-loop, and parallel execution patterns.

Running Kimi K3 with 29GB RAM at just 0.5 tok/s. An in-depth analysis of extreme quantization techniques, performance trade-offs, and the impossible triangle of local LLM deployment.

Running Kimi K3 with 29GB RAM at just 0.5 tok/s. A deep analysis of extreme quantization techniques, performance trade-offs, and the impossible triangle of local LLM deployment.

GPT 5.6 Luna reportedly tops Google's flagship on the Artificial Analysis Intelligence Index while costing less than Google's cheapest model. A deep dive into the tech trends, industry impact, and developer implications.

Deep dive into MiniMax H3 multimodal model: 2K video generation, native stereo audio-visual integration, and precise text rendering designed for motion design and brand marketing.