Future Of AI Infrastructure

Funding is flowing, but the country's AI builders are struggling to secure the chips, memory, and power needed to train and run models

Between AI-driven cyber chaos, two wars, and street mayhem, global prosperity is no longer guaranteed

Backed by Binny Bansal's 3STATE Ventures, ShopOS has opened its AI creative engine to global users, offering tools for product imagery, videos, reels and creator-style content.

OpenAI President Greg Brockman's $25 million donation to a political group opposing restrictive AI rules raises questions about the company's commitment to AI safety regulations.

The funding takes RapidCanvas' total capital raised to $52.5 million and will support expansion of its go-to-market teams, field AI engineering operations and partner network.

OpenAI said on Friday that it fired three safety researchers for a "breach of trust," defending the dismissals after the trio accused the company of putting its corporate interests before safety as the reason for removing them. The ChatGPT maker said in a post on X that it "parted ways" with the researchers after an investigation found "they violated clear policies on handling sensitive information." The statement comes after the three researchers, Tomek Korbak, Jasmine Wang and Mikita Balesni, posted a letter to OpenAI's various safety oversight groups detailing the circumstances around their firings and their concerns about AI. The researchers said they feared that the "internal and external communications" about their dismissals have chilled the company's culture that encouraged speaking freely and disagreeing openly about safety concerns. They urged OpenAI to stick to its promise to allow third-party safety monitors inside the company and preserve the ability to monitor rapidly

Multilingual, integrated and outcome-focused deployments gain ground as enterprises increasingly partner with technology providers

The native API integration combines cloud security findings with data classification, helping security teams investigate and prioritise risks to sensitive business data

Companies are increasingly seeking measurable returns from AI investments as the focus shifts from experimentation and scaling to value, security and agentic transformation

The partnership combines Mavenir's AI platform with Neysa's GPU infrastructure and cloud environment to help enterprises, telcos and neocloud providers deploy AI systems

What began as an AI evaluation effort has grown into an independent research organisation examining how advanced models behave and what risks their capabilities could pose

The Anthropic researcher said that he does not want to participate in an industrywide rush to build AI systems that can improve themselves

Big Tech companies have signaled that spending on AI would not slow down, with combined outlays set to surpass $730 billion this year

The independent multimodal platform will assess AI systems across Indian languages, accents, dialects and real-world deployment conditions using a three-stage framework

AI trade is unwinding from the inside. The largest hyperscalers are funding capex with debt at a scale that has turned free cash flows negative said Manish Bhandari, CEO at Vallum Capital.

Worldwide IT spending is expected to climb 14.2% to $6.37 trillion in 2026 as enterprises and hyperscalers invest heavily in AI infrastructure, cloud platforms and next-generation data centres

Artificial intelligence is reshaping enterprise computing in ways that traditional IT was never designed to support. As AI moves into production, organisations are discovering that success depends as

As enterprise AI moves from experimentation to large-scale deployment, organisations are discovering that technology alone isn't enough. Long-term success depends on the right expertise, the right exe

For many organisations, proving that AI works is no longer the challenge. The real test is turning promising pilots into enterprise-wide capabilities that deliver consistent business value.

Moving AI from isolated pilots to enterprise-wide deployment requires more than powerful models - it demands infrastructure that can keep costs, complexity and performance in balance.