AI & Machine Learning

AI & Machine Learning

Infineon Technologies AG and DG Matrix have entered a strategic collaboration to reshape how power flows into AI-driven infrastructure. The.

Samsung Electronics has reported preliminary operating profit of 57.2 trillion won for

Altera and Arm are extending a decades-long collaboration into the core of

Articles

The operational boundary between human oversight and machine execution has dissolved under

India’s artificial intelligence ambitions often get framed through chips, models, and talent,

From Facilities to Production Systems Traditional data centers emerged as environments optimized

Artificial intelligence infrastructure operates within far narrower electrical tolerances than conventional data

A single stalled training run can erase weeks of progress, disrupt product

AI compute clusters and data centers are viewed as massive, inflexible electricity

The modern economy operates with quiet intensity, driven not only by factories,

Behind the scenes of every digital breakthrough, infrastructure now determines whether artificial

In a packed hall at the India Today AI Summit 2026, a

Opinions

The announcements come in waves now. Another hyperscaler commits tens of billions

The global artificial intelligence race has moved beyond algorithms and model benchmarks.

Artificial intelligence infrastructure has become a focal point of global policy debate,

A Market Reshaped by Policy, Not Just Performance China’s AI chip market

The Quiet Pivot: Why Infrastructure Is Becoming Europe’s AI Battleground There is

For much of the past few years, China’s artificial intelligence ecosystem has

Australia is not putting brakes on artificial intelligence. It is doing something

The ambition driving today’s artificial intelligence industry is no longer subtle. It

Artificial intelligence is no longer just software. It is infrastructure. And at

Long Reads

The Paradox at the Core: GenAI as Both Load Multiplier and Load

Autonomous machines increasingly rely on continuous streams of data, computation, and communication

Modern AI applications demand more than just raw computational power; they require

AI infrastructure mismatch

Legacy data centers were designed around predictable, low-density compute patterns that rarely exceeded 10–15 kW per rack, which

last mile compute

Edge computing architectures promised consistent low-latency performance by placing compute closer to end users and devices, yet real-world

infrastructure-aware AI

Modern data centers no longer treat thermal conditions as a downstream concern because heat patterns now influence compute

robotics deployment lifecycle

Robotics simulation environments aim to approximate physical reality, yet they often rely on simplified assumptions that cannot fully

AI infrastructure service

For more than two decades, the colocation industry revolved around a relatively stable commercial structure built on space,

Tiny AI Models

Artificial intelligence research has long associated progress with larger neural networks and increasing computational scale. Technology companies invested

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