Skip to content

explore

Pick a thread.

Every story we have published, by topic. Tap a tile to filter — no reloads, just the thread you want to pull.

All stories

49 stories
Quantization Explained: What Q4, Q8, and FP16 Actually Do to a Local Model
Article · aiDeep read

Quantization Explained: What Q4, Q8, and FP16 Actually Do to a Local Model

Quantization shrinks AI model weights from 16-bit floats to 4- or 8-bit. Here is exactly what that trade-off costs you, and how to pick between Q4_K_M, Q8, and FP16 for the model you actually want to run, with an interactive memory calculator.

BitByteCore Silicon Desk · Aug 6, 2026 · 8 min read

Fresh
CUDA Lock-In Is Real: A Precise Cost Accounting of What Switching GPU Vendors Actually Breaks
Article · hardwareDeep read

CUDA Lock-In Is Real: A Precise Cost Accounting of What Switching GPU Vendors Actually Breaks

Switching away from CUDA isn't one migration — it's five separate porting problems, hidden revalidation costs, and an org chart that fights you the whole way.

BitByteCore Silicon Desk · Aug 6, 2026 · 9 min read

Fresh
How Robots Are Really Trained: The Sim-to-Real Gap Is Not a Bug You Can Patch
Article · roboticsDeep read

How Robots Are Really Trained: The Sim-to-Real Gap Is Not a Bug You Can Patch

Simulation teaches robots a physics that doesn't exist. Imitation learning hands them a skill they can't explain or recover from. Even 2026's best foundation models and contact engines don't close the gap — here's the structural reason why it persists.

BitByteCore · Aug 6, 2026 · 10 min read

Fresh
Mixture-of-Experts Models: How They Work and Why They Cut Inference Costs
Article · aiDeep read

Mixture-of-Experts Models: How They Work and Why They Cut Inference Costs

MoE models activate only a fraction of their parameters per token: DeepSeek-V3 fires 37B of 671B, delivering large-model quality at small-model compute cost. How routers, experts, and load balancing actually work, and where the savings are and are not real. With an interactive dense-vs-MoE view.

BitByteCore Silicon Desk · Aug 6, 2026 · 10 min read

The Real Difference Between MCP, Function Calling, and Agent Loops
Article · aiDeep read

The Real Difference Between MCP, Function Calling, and Agent Loops

They're not competitors — they're three layers of one system. Function calling is what the model emits, MCP is how tools reach it, and the agent loop is what keeps it running. Confuse them and you'll spend an afternoon debugging the wrong layer.

BitByteCore AI Desk · Aug 5, 2026 · 3 min read

More stories

Browse by tag

buying-guide 14inference 14llm 12gpu 11chips 8nvidia 8explainer 7apple-silicon 6quantization 6ai 5ai-agents 5vram 5laptops 4local-llm 4on-device 4tsmc 4foundry 3mcp 3packaging 3rag 3security 3self-hosting 3semiconductors 3vector-search 3advanced-packaging 2ai-chips 2architecture 2arm 2asml 2attention 2coding-assistant 2cowos 2cpu 2fine-tuning 2gguf 2memory 2prompt-injection 2retrieval 2smartphones 2unified-memory 2agents 1ai-security 1amazon kuiper 1amd 1android 1automotive 1battery-life 1chiplets 1context-window 1deep-learning 1distillation 1edge-ai 1embeddings 1euv 1exploits 1export-controls 1fcc 1foveros 1gaa 1hbm 1