AI Infrastructure
China is reportedly preparing a $295 billion push to scale AI data center infrastructure, intensifying the global compute race that underpins generative video, LLMs, and synthetic media at scale.
AI Economics
As AI workloads scale, token costs are spiraling out of control. The industry is racing to optimize inference, caching, and model routing before the economics break enterprise deployments.
Perplexity AI
Perplexity AI unveiled a hybrid inference orchestrator that automatically routes AI tasks between on-device models and cloud servers on personal computers, balancing latency, privacy, and compute cost.
TSMC
TSMC CEO C.C. Wei says it will be a long time before the foundry can fully satisfy AI chip demand, signaling prolonged supply constraints for Nvidia, AMD, and the broader compute stack powering generative AI.
Alphabet
Alphabet plans to raise $80 billion in debt to finance its expanding AI infrastructure, signaling an unprecedented capex commitment to compete with Microsoft, Meta, and Amazon in the AI arms race.
SoftBank
SoftBank plans a $52 billion AI data center network in France, a major bet on European compute infrastructure that could reshape access to GPUs for generative video and synthetic media workloads.
LLM
A technical look at how decoding algorithms — from greedy search to nucleus sampling and speculative decoding — shape LLM inference quality, latency, and cost in modern generative AI systems.
Samsung
Samsung has begun shipping HBM4E memory samples, moving ahead of SK Hynix and Micron in the next-generation AI memory race. The advance has major implications for generative AI workloads including video synthesis.
ByteDance
ByteDance is reportedly designing its own CPUs for AI inference, joining hyperscalers in vertical silicon integration. The move could reshape cost economics for the company's generative video and recommendation workloads.
ByteDance
ByteDance is reportedly weighing up to $70B in capital expenditure for AI infrastructure in 2026, doubling down on the compute needed to power its growing portfolio of video generation and synthetic media models.
LLM Inference
KV caching is the unsung optimization that makes modern LLMs feel real-time. Here's how it transforms transformer inference from quadratic drudgery into a fast, token-by-token stream.
AI Infrastructure
IT capital expenditure has surged to a record share of S&P 500 spending as hyperscalers pour unprecedented sums into AI infrastructure, reshaping the economics of the entire tech sector and the compute foundation behind generative AI.