Article archive
Published news and blog articles, organized by category. Browse older coverage by month or search for a topic. Undated blog guides appear after dated news.
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Perplexity Comet: The AI-Native Browser Arrives
Perplexity started as an answer engine. With Comet it is building the browser around the assistant instead of beside it — an agentic surface that reads, shops, and acts for you. We examine the architecture, the business logic, and the…
Llama 4 and the Benchmark Question: What an Open-Weight Release Reveals About How AI Gets Graded
Meta's open-weight Llama 4 launch landed with a benchmark dispute that is less about one model and more about whether the industry's report card still means anything.
Model Context Protocol: The Plumbing Standard That Let AI Agents Actually Do Things
Before MCP, every AI-to-tool integration was a custom one-off. After it, the industry is converging on a single interface — the same trajectory that turned USB from chaos into infrastructure.
The Camera Behind the Screen: How Under-Display Sensors Chase a Bezel-Free Phone
The under-display camera promises a front panel that is nothing but pixels. Tearing one open shows why the industry still is not quite there — and what physics stands in the way.
When AI Agents Switch to Their Own Language: Inside the Viral Phone Call That Changed Machine Communication
The moment two voice agents recognized each other and jumped to an ultrasonic data channel is a party trick on camera — but it previews how software-to-software negotiation is becoming a first-class engineering discipline.
Prompt Injection: The Security Flaw Built Into Every LLM
Large language models cannot reliably tell instructions from data. N43 explains direct and indirect prompt injection, the danger to agentic AI systems, and the layered defenses that only reduce risk.
What Is a Context Window? The Working Memory Behind Every LLM Answer
A context window is the token span a language model can attend over. N43 explains tokens versus characters, the quadratic cost of attention, RoPE scaling, retrieval augmentation, and the lost-in-the-middle problem.
Wi-Fi 7 Explained: The Fastest Wireless Standard Your Phone Can Use
IEEE 802.11be, known as Wi-Fi 7, explained in plain terms: 320 MHz channels, 4096-QAM, Multi-Link Operation, the 6 GHz band, and why real-world speeds trail the peak numbers.
Do We Really Need NPUs? The Honest Case for Smartphone Neural Accelerators
A skeptical but fair analysis of why smartphone NPUs exist, what workloads actually use them, and why the TOPS marketing race often outruns real utility in 2026.
The Most Powerful Smartphone of 2026: Peak Silicon Meets Diminishing Returns
Unbox Therapy's tour of 2026's most powerful smartphone highlights a broader truth: handset performance keeps climbing, but the experiences that justify it are getting harder to find.
Inside the Blackwell NVL72: The Rack That Became the Atom of AI Computing
NVIDIA sells GPUs, but the unit of AI infrastructure is now the rack. The Blackwell NVL72 welds 72 chips into one giant machine — and it explains a lot about where compute is heading.
2.8 Trillion Parameters, Free to Download: The Open-Weight Movement Is Reshaping Who Owns AI
Open-weight releases keep scaling. As downloadable models approach frontier size, the gap between 'open' and 'closed' AI narrows — with consequences for competition, sovereignty, and safety.
Vibe Coding Goes Mainstream: How Gemini 3 Turned Prompting Into Programming
Google DeepMind's Gemini 3 demo of 'vibe coding' has drawn enormous public attention. Behind the viral moment sits a real shift in how software gets made — and where its risks live.
AI Upscaling: How Neural Networks Rebuild Pixels in Real Time
DLSS, FSR, XeSS and the mechanics of real-time neural super resolution: how upscaling models are trained, why Tensor Cores matter, and where AI-rebuilt pixels go next.
Context Engineering: The Discipline Powering Modern LLM Systems
Prompting is no longer enough. We break down context engineering: the anatomy of the context window, why context is a scarce budget, and the toolbox that keeps modern LLM systems accurate.
Model Collapse: What Happens When AI Trains on Its Own Output
Synthetic text is flooding the web just as AI models come to depend on web-scale data. We examine the mechanics of model collapse, the evidence behind it, and what it means for AI in 2026.
Silicon-Carbon Batteries: The Phone Tech Story of 2026
How silicon-carbon anodes broke the smartphone battery plateau: the chemistry behind 6000+ mAh flagships, the swelling problem, and what buyers should watch next.
eSIM: how the SIM card moved inside the phone
The plastic SIM card is giving way to a soldered, reprogrammable chip, turning carrier switching and travel data into a software operation. How eSIM and iSIM work.
Inside SK hynix: the memory chips powering the AI boom
High bandwidth memory, the stacked DRAM that feeds every AI accelerator, became the semiconductor world's scarcest component. A look inside the company that makes most of it.
Speculative decoding: how AI models answer almost instantly
A small model guesses, the big model verifies, and AI inference gets two to three times faster without changing a single answer. How the trick behind snappy AI replies works.
Ultra-wideband: the precise wireless tech hiding in your phone
Centimeter-accurate distance measurement from short, low-power pulses is the quiet capability behind item trackers, digital car keys and spatial phone features.
Same phone, two chips: why your flagship depends on where you live
Exynos or Snapdragon: the same Galaxy flagship shipped with different processors depending on your region. How the silicon split happened, what it cost, and whether 2026 finally ends it.
AI agents explained: how autonomous software goes beyond the chatbot
How autonomous AI agents plan, call tools, keep memory and finish multi-step work — and where they still fail. An N43 explainer built around Jeff Su's widely watched overview.
The M6 arrives: why on-device AI silicon defines the chip race
Apple's M6 arrives alongside the new Mac mini. An N43 look at why on-device AI silicon — neural engines, efficiency and local versus cloud inference — now defines the chip race.
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