#nvidia

Potential NVIDIA acquisition of open‑AI startup Reflection AI could reshape AI software, sparking debate over market dominance and competition.

Unlock local AI inference speedups by optimizing legacy GPUs, custom kernels like megakernel, and DIY cooling for mining rigs—boost your model performance.

Explore VRAM limits for LLMs, compare top local models, and plan hardware upgrades for high‑capacity GPUs to run advanced AI on consumer rigs.

AI demand is draining GPUs from gaming; high‑end cards could hit $5,000, prompting a shift toward cloud‑based compute and subscription models.

Upcycling dense LLMs to MoE on an RTX 4060 cuts MLP compute 40‑44% but drops accuracy—proof of concept for low‑resource, sparse model conversion.

AMD’s rumored GDDR6 price hike could push graphics‑card costs higher, as data‑center demand reshapes semiconductor supply and squeezes consumer budgets.

David Silver’s new $1.1B‑funded venture “Ineffable Intelligence” aims to build a trial‑and‑error “superlearner” AI, moving beyond LLMs and testing super‑intelligence safely in simulations.

Explore how Nvidia’s focus on AI hardware, DeepMind’s AlphaGenome, and new local AI models reshape the market, tech safety debates, and future work.

Explore Qwen3.8‑27B’s local performance: 140 tok/s on RTX 3090, faster code generation, and real‑world engineering benchmarks vs. Gemma4.

Beware counterfeit RTX 4090s—high‑fidelity fakes mimic real GPUs but reveal a ruffled PCB texture. Learn how to spot them, why prices seem too good, and protect your wallet.