#MoE fine-tuning
170 related articles
·4 min
SELENE Open-Source Project: An Interactive Notebook Library for Systematically Learning AI and Machine Learning from Scratch
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.
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·2 min
Google Releases Gemini 3.6 Flash and Two Other New Models: Comprehensive Expansion of the Flash Family
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.
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·4 min
Heretic Uncensoring Technology Explained: Practical Applications on Jamba2 and Qwen3.5 Open-Source Models
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.
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·5 min
The Complete Learning Path to Understanding the Kimi K3 Technical Report
A systematic learning path for understanding the Kimi K3 technical report, covering MoE, MLA, distributed training, and modern post-training techniques.
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·2 min
DeepSeek V4 Flash Weights Open-Sourced: A New Option for Lightweight LLM Deployment
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.
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·2 min
DeepSeek-V4-Flash Model Analysis: A New Lightweight AI Choice Prioritizing Efficiency
In-depth analysis of DeepSeek-V4-Flash model's product positioning and technical approach. Examining lightweight trends through the Flash naming, MLA attention mechanism, MoE architecture evolution, and implications for the open-source AI ecosystem.
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·2 min
DeepSeek-V4-Flash Model Analysis: A New Lightweight AI Choice Prioritizing Efficiency
In-depth analysis of DeepSeek-V4-Flash model's positioning and technical path. Exploring the lightweight trend behind the Flash naming, MLA attention, MoE architecture, and its significance for open-source AI.
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·2 min
Distilling DeepSeek to GPT-OSS: Why Censorship Doesn't Transfer
When distilling DeepSeek to GPT-OSS, censorship mechanisms don't transfer. This article analyzes the separability of capabilities vs. behavioral constraints in knowledge distillation and its implications for AI safety.
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·2 min
Distilling DeepSeek to GPT-OSS: Why Censorship Doesn't Transfer
When distilling DeepSeek to GPT-OSS, model censorship doesn't transfer. This article analyzes the separability of capabilities and behavioral constraints in knowledge distillation and its implications for AI safety.
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·3 min
Mistral Deepens Partnership with Microsoft: How Sovereign AI Is Landing in the European Enterprise Market
Mistral expands its strategic partnership with Microsoft, delivering controllable frontier AI to Europe's regulated industries through open-weight models and Azure Local deployment.
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·3 min
Mistral and Microsoft Deepen Partnership: How Sovereign AI Is Landing in the European Enterprise Market
Mistral and Microsoft expand their strategic partnership, delivering controllable frontier AI to Europe's regulated industries through open-weight models and Azure local deployment.
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·2 min
SenseNova-Vision Training Data Pipeline Explained: A Guide to Fine-Tuning Unified Vision Models
SenseNova-Vision adds a complete training data pipeline with dataset registration, format converters, and end-to-end docs, making unified vision model fine-tuning for segmentation, OCR, and editing far more accessible.
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·2 min
Behind the Open-Source Model Frenzy: Who Will Provide Cheap Inference Services?
Open-source LLM weights don't equal low-cost access for developers. This article analyzes the inference service gap in open-source AI and how providers like Together AI and Groq are addressing it.
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·2 min
Behind the Open-Source Model Frenzy: Who Will Provide Cheap Inference Services?
Open-source LLM weights don't mean developers can use them cheaply. This article examines the inference service gap in open-source AI and how providers like Together AI and Groq are addressing it.
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·2 min
Why Top AI Startups Are No Longer Publishing Research: The Deep Reasons Behind the Shift from Openness to Secrecy
Exploring why top AI startups shifted from open research to secrecy, analyzing how commercial competition and talent pressure drive this change, and its impact on academia, innovation, and open source.
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·3 min
What Are AI Model Weights, Really? The Deep Learning Truth Revealed by a Meme
Starting from a viral Reddit meme, we dive deep into AI neural network weights — what they are, why they can't be read visually, and how open weights drive technological democratization.
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·4 min
GPT-6 Reportedly Completed, Claude Opus 5 Leaked: The AI Model Race Accelerates
GPT-6 may be completed, Anthropic's Claude Honeycomb appears to be an early Opus 5 version, Kimi K3 is imminent, and Google Gemini faces further delays. Deep analysis of the latest AI model competition.
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·4 min
GPT-6 Reportedly Completed, Claude Opus 5 Leaked: The AI Model Race Accelerates
GPT-6 may be complete, Anthropic's mysterious Claude Honeycomb appears to be an early Opus 5 version, Kimi K3 is imminent, and Google Gemini continues to delay. Deep analysis of the latest AI model competition.
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·4 min
Kimi K3 Released: 2.8 Trillion Parameter Open-Source Model Tops Global Coding Leaderboard
Moonshot AI releases Kimi K3, a 2.8 trillion parameter open-source model using MoE architecture that tops the global frontend coding arena at under $1 per task, beating GPT and Claude.
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·3 min
Deep Dive into Inkling: The First Frontier Open-Source Multimodal LLM from the West
Thinking Machines releases Inkling, an open-source multimodal LLM with near-trillion MoE parameters, 1M token context, Apache 2.0 license. Deep dive into architecture, benchmarks, and pricing.
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