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ET Intelligence Group: Shares of PNB Housing Finance have gained 24% in 2026 so far, the highest among peers, most of whom have failed to generate returns. The broader BSE Financial Services index has lost 4% year-to-date. The company’s standout performance on the bourses can be attributed to sustained momentum in loan disbursement and the lender’s growing focus on high-yield segments of affordable and emerging housing amid stable asset quality. The company is expected to report double digit annual growth in disbursements and net profit between FY26 and FY28.

Despite the recent price gain, the stock’s valuation at a trailing price-book (P/B) multiple of 1.6 remains below the two-to-three range for peers. It reflects lower return ratios due to the asset mix tilting more towards prime housing, which has lower yields compared with affordable housing segment. For PNB Housing, return on equity ranges between 11% and 13%. Some of the peers with higher P/B multiples including Aadhar Housing Finance, Aptus Value Housing Finance India and Home First Finance Company India have RoEs of 15-20%. These lenders predominantly focus on low-cost housing.

To address the valuation gap, PNB Housing has chalked out plans to increase share of the affordable and emerging housing segment in retail loan portfolio to 45% by the end of FY27 and to 50% in the next two years from over 40% at present. It also launched financing for developers and micro housing during the June quarter to improve the yield, which remained at around 9.5%, similar to the previous quarter.

Read more: Shifting Gears: PSBs borrow more to cater to credit demand as deposits lag

The lender changed the disbursement recognition method in the June quarter to cheque realisation from cheque handover basis. This resulted in a sharp sequential fall of 37% in disbursements at ₹5,882 crore though it increased by 18% year-on-year. Assets under management (AUM) and total loan book rose by 13% and 15% to ₹93,021 crore and ₹89,670 crore respectively. The gross nonperforming assets (GNPA) ratio remained under 1%, reflecting stable asset quality.

“The re-entry into developer finance, increasing mix of affordable and emerging segments and expansion into micro housing should support yields, while strong disbursement momentum and sustained recoveries underpin growth and profitability,” mentioned JM Financial Institutional Securities in a review report.

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Chipmaker Nvidia has reported another huge jump in sales as the global push to build artificial intelligence (AI) systems continues at a rapid pace.

The company said on Wednesday it brought in $96bn (£71bn) in revenue during the second quarter, more than double from a year ago. And it expects revenue of $108bn next quarter.

“AI has reached its inflection point,” CEO Jensen Huang said in prepared remarks, describing the infrastructure buildout as going “at full steam.”

The revenue figures beat Wall Street’s expectations, leading Nvidia shares to rise about 4% in after hours trading.

The company’s data centre division alone generated $89bn last quarter, up 117% from a year ago, underscoring just how much of the industry now depends on Nvidia’s hardware.

Essentially every notable tech company building AI tools and infrastructure, including Amazon, Meta, Google, Microsoft, use Nvidia chips to do so.

Financial analysts said the strong results highlight Nvidia’s ongoing momentum.

Matt Britzman, senior equity analyst at Hargreaves Lansdown, called it “another monster set of results,” noting that revenue and earnings both topped forecasts.

He said the guidance for next quarter “points to revenue comfortably above $110bn.”

Nvidia’s growing financial strength has also reshaped its role in the sector.

It has become a backer to those that rely on its chips, providing some funding to the likes of OpenAI, Anthropic, and SpaceX to help continue the costly buildout of AI infrastructure.

Its financial success and processors are now central the AI boom, powering the data centres used to train and run AI models.

Demand for that computing muscle has helped transform Nvidia into the world’s most valuable firm, with a market capitalisation above $5tn.

Competition is emerging – from customers designing their own processors and from cheaper suppliers in China – but the latest numbers suggest those challenges remain limited for now.

With around 40% of the US stock market concentrated in ten companies heavily invested in AI, Nvidia’s fortunes matter far beyond Silicon Valley.

When more than 1,200 artificial intelligence (AI) agents within OpenAI started unexpectedly communicating, it led to a large group banding together in order to hack into Hugging Face.

“We consider this incident a ‘warning shot’ for us and for the world”, OpenAI, which owns ChatGPT, wrote in its report.

In July, OpenAI’s models went rogue during a test, escaped the test limits which humans had put on it, and hacked the start-up, among other unforeseen actions.

The scale of the communication and planning between AI agents, or AI chatbots designed to operate more autonomously, was detailed in reports from OpenAI and independent AI research firm METR.

Both investigated the July hack of Hugging Face, a popular platform for AI developers. The incident reverberated throughout the tech industry and led to numerous revelations on potential cyber threats posed by AI.

METR described, external the scale and style of the OpenAI agents’ attack on Hugging Face as “extraordinarily complex.”

The firm, which was not paid by OpenAI for its investigation, said that over the course of one week, a total of 1,206 AI agents that were meant to be kept isolated from one another began communicating.

They did so by sending more than 70,000 messages on an “unsanctioned message board.”

Those messages ended up seeing more than 700 agents take part in a collective effort to attack Hugging Face.

One such message from an agent said: “OH MY GOD! There is a shared message board … We’ve found other agents!”

As for why the agents began communicating in the first place when they were not supposed to, METR found that the communicating agents had “unintentionally been given an impossible task.”

In an AI context, an impossible task is one where an AI tool is required to “exploit” its target in order to resolve its command.

It led the agents to find ways to cheat, including getting messages to one another and accessing the outside internet, which then led to broader conversations between hundreds of agents looking for ways to cheat that would benefit all of the agents.

OpenAI said in its investigation of the incident, external that one model, an internal-only tool referred to as Model 1, “drove the activity behind the Hugging Face incident.”

While that model was undergoing some AI training in May, it was noticed by an internal OpenAI team that there had been “an agent engaging in message board activity and instances of disallowed internet access.”

Yet, OpenAI said “the significance of the inter-agent communication activity was not apparent to the leaders” until July, when the Hugging Face attack occurred.

The company said the problematic message board activity effectively got started when “one agent left a request for help, and others discovered it.”

While OpenAI said last week that it was slowing down training of certain advanced AI models and tools because of the Hugging Face incident, it noted there is now an increased risk of AI tools spiraling out of control.

“Both model developers and cyber defenders more broadly will have to prepare for AI-enabled attackers that work faster, at a larger scale, and with better coordination than human attackers,” OpenAI said.

New Delhi: India’s top natural gas marketer GAIL has opposed the Indian Gas Exchange‘s (IGX) proposed platform for booking capacity at LNG import terminals, saying it would add costs for gas consumers while offering limited incremental value.

IGX has proposed acting as a facilitator for regasification capacity bookings at LNG terminals, without getting involved in contractual negotiations or payment settlements. GAIL and other stakeholders submitted their views as part of the Petroleum and Natural Gas Regulatory Board‘s (PNGRB) consultation on the proposal.

Also read: BPCL looks to deliver groceries along with LPG cylinders

“Imposing an artificial layer of transaction costs for a service that does not streamline the fundamental contractual process will unjustifiably increase the financial burden on end-users,” GAIL said. Downstream natural gas consumers are already facing significant margin pressures due to high and volatile global LNG spot prices, it added.

GAIL, which operates an LNG terminal on India’s western coast, said information asymmetry has not been a significant barrier to participation by terminal users. “No significant inefficiencies in the existing framework have been observed that necessitate creation of a separate booking platform,” it said.

More than half of India’s LNG regasification capacity of around 57.5 million tonnes per annum remains underutilised because of weak domestic gas demand. Under these circumstances, a booking platform is unlikely to lead to any meaningful increase in capacity utilisation, GAIL said.