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Hanwha Offers to Buy Builder of U.S. Navy Ships

Plus: Trump extends Jones Act waiver again; chicken glut drags on meatpackers

South Korea’s Hanwha has made a nonbinding offer valued at more than $1 billion to buy Austal USA, a builder of ships and submarine parts for the U.S. Navy.

Australian shipbuilder and defense contractor Austal said the potential deal for its U.S. subsidiary is valued at between $1.05 billion and $1.2 billion. The WSJ Logistics Report’s Paul Berger writes that the acquisition would provide Hanwha with Austal’s Mobile, Ala., shipyard and access to major contracts that include some of America’s most sensitive naval programs.

The yard in Mobile specializes in building ships for the U.S. Coast Guard and Navy. It also supplies submarine modules to General Dynamics Electric Boat for the construction of Virginia‑ and Columbia‑class submarines. Austal USA employs about 3,500 workers and includes other assets such as repair facilities in San Diego, Calif.

Hanwha is seeking to grow its commercial and military shipbuilding ambitions in the U.S. as President Trump is trying to revitalize domestic shipbuilding.

Chinese robot maker’s IPO 5,500 times oversubscribed by retail investors

Unitree raises $900mn ahead of Shanghai listing expected later this month

China’s retail investors are jostling for a slice of a leading humanoid robot company, in a sign of huge enthusiasm for tech stocks in the country.

The retail segment of Unitree’s initial public offering was more than 5,500 times oversubscribed, according to a stock exchange filing published ahead of a listing in Shanghai this month, even as more shares were made available to smaller investors to meet demand.

In advance of the IPO, Unitree allotted 40.4mn shares, or about 10 per cent of its outstanding shares, priced at Rmb150.8 ($22.35), raising about $900mn and giving the company a market valuation of $9bn.

Retail investors were allocated 16 per cent of the total, with institutional investors including hedge funds linked to DeepSeek founder Liang Wenfeng.

Huge enthusiasm for AI-related stocks in China is driving up valuations. The country’s tech-focused Star 50 index has surged more than 27 per cent this year, well ahead of the benchmark CSI 300’s 0.8 per cent gain.

The increased interest also comes amid a crackdown by authorities who are keen to limit Chinese citizens’ exposure to US equity markets.

Unitree, founded by Wang Xingxing in 2016, has become a champion in China’s robotics industry. It is a widely recognised brand thanks to its robots’ dancing, flipping and boxing displays at lunar new year galas.

Last year, the company’s success earned Wang a front-row seat at a meeting with Chinese President Xi Jinping.

The retail investor interest in Unitree far exceeded that of CXMT’s blockbuster IPO last month, which was more than 200 times oversubscribed.

“The humanoid robotics industry in mainland China is undergoing a phase of rapid development, and Unitree is highly representative of this sector,” said Kenny Ng, a strategist at Everbright Securities International.

The share sale gives Unitree a price-to-earnings ratio of 219 and a price-to-sales ratio of almost 36, based on last year’s results. The company shipped 5,500 humanoid robots last year. The largest use of the IPO proceeds will be Rmb2bn ($296mn) spent on developing AI models for its robots.

Citic Securities is acting as the sponsor and lead underwriter.

The frenzy comes despite the US Federal Communications Commission banning imports of humanoid robots last month in a move widely seen as targeting Chinese products.

According to Unitree, overseas revenue accounts for more than 40 per cent of its earnings, with the US making up between 13.3 per cent and 18.4 per cent depending on the year.

In a section of its IPO prospectus highlighting risks, Unitree said the FCC move would not “affect the continued sales of the company’s existing main products in the US market” but added that its new models would “face the risk” of being cut off.

In a recent note, Sheng Zhong, an equity analyst at Morgan Stanley, highlighted the Unitree IPO as a “catalyst” that could support other listed stocks in the sector.

Humanoid robots, which increasingly have applications with “embodied AI”, or AI deployed in the physical world, are a source of emerging competition between the US and China, she noted.

“As the industry accelerates and continues to ramp up, we think this could be the beginning of US and China embodied AI competition escalation,” she said.

Deal by Hollywood mogul’s new venture Mari represents a big bet on continued demand for live events

Hollywood mogul Ari Emanuel has struck a roughly £4.5bn deal to buy the theatre group behind West End venues including the Lyceum and the Savoy in a major bet that strong demand for live events is here to stay.

The acquisition of ATG Entertainment is the largest to date by Emanuel’s Mari Group, which was launched last year with $2bn of equity financing from investors including Apollo, RedBird Capital and the Qatar Investment Authority.

Mari said in a statement on Tuesday that its acquisition of ATG reflected its conviction in “the growing power of live experience and the passionate audiences it brings together”. The company has agreed to pay about £4.5bn for ATG, according to two people familiar with the terms, which were not publicly disclosed.

Talks over a deal between Mari and ATG’s owner Providence Equity were first reported by the FT in June.

ATG’s portfolio includes Broadway venues including the Walter Kerr Theatre and the Lyric Theatre, which is showing Harry Potter and the Cursed Child.

Since buying ATG for £350mn in 2013, Providence has expanded the company from 40 to 70 venues across the UK, the US and Europe through a series of acquisitions.

A sale will mark one of the private equity firm’s most successful exits. Providence pumped in more than £50mn into ATG to help the business weather enforced closures during the pandemic.

ATG will add to Mari’s growing portfolio, which also includes the Frieze Festival, the Miami Open tennis tournament and Hyde Park Winter Wonderland.

Emanuel’s other roles include chairing talent agency WME Group, which represents A-listers including Oprah Winfrey and Martin Scorsese, and leading sports marketing company IMG and TKO Group, which owns mixed martial arts series Ultimate Fighting Championship and WWE.

The swoop on ATG comes off the back of several years of strong demand for live event tickets following the Covid-19 pandemic. A study by Mastercard earlier this year found 88 per cent of Britons redirect spending towards live experiences, with many saying attending such events was important to balance the amount of time they spent online.

Last year, Emanuel told the FT that he believed as technology made people more productive they would have more time and money “to go out and do stuff”.

Emanuel said in a statement on Tuesday: “I started out in the theater. I’ve seen the industry reinvent itself many times, but live has only grown more powerful . . . This is a long-term bet on where live goes next.”

ATG chief executive Melanie Smith said Mari was the “right home” for the business and that it understood “our theatres, the people behind them and the relationships we have built with producers, artists and audiences”.

The deal is subject to regulatory approvals.

The chip giant is aiming to make Nemotron 4 a leading-edge model, spurring hardware demand but raising questions about competition with customers and partners.

Nvidia is doubling down on its open-source efforts, pouring investment into an ambitious new in-house AI model that it hopes will drive demand for its hardware—but that could also compete with customers and partners.

Nvidia is aiming for the new model, the biggest of a family that it is calling Nemotron 4, to be on par in its performance with the best open-source AI models in the world, according to several people who work on Nemotron. The research paper detailing Nvidia’s last big model had 570 authors, and employees said Nemotron 4 would involve even more people. “Everyone just wants to be involved at this point,” one former employee said.

That work builds on a spate of recent open-source releases from Nvidia. On Tuesday, Nvidia released Nemotron 3.5 Lightning, a smaller model that it said is designed to run AI agents as fast and efficiently as possible. The company also released free model routing software to help companies more easily make their own model routers—tools that direct specific AI tasks to the best, cheapest models for those tasks.

Multiple employees working on Nemotron said they expect the biggest Nemotron 4 model to have at least a trillion parameters—the numbers in a model that are adjusted as it learns. That’s approximately double Nvidia’s current largest model, Nemotron 3 Ultra, released in June. A trillion parameters would still be far smaller than leading Chinese open-source models, but Nvidia also heavily emphasizes compression techniques that can enable smaller models to outperform.

In a sign of Nvidia’s open-source commitment, it has sharply increased spending on the compute used to train its own models. Nvidia gets compute by renting AI servers back from some of the cloud operators that buy its chips. As of April, it had increased the value of such multiyear cloud-service commitments to $28 billion through the start of 2031, approximately triple the amount it reported a year earlier. Some of that cloud usage also goes to other research and development efforts.

The accelerated Nemotron push puts Nvidia in a delicate position of, in effect, competing with both a collection of open-source startups that it has invested in and with the big AI labs that have been Nvidia’s biggest customers. OpenAI in particular has been one of the biggest drivers of demand for chips from Nvidia, which has invested $30 billion in the AI lab.

Though the top Nemotron 4 model isn’t expected to be as powerful as the frontier models from OpenAI and Anthropic, such open-source models are gaining traction among companies as a lower-cost alternative for some work.

Nvidia also has invested sizable amounts in U.S. open-source companies that hope to get companies to use their own models, including Reflection AI and Thinking Machines Lab.

Nvidia is ramping up its open-source efforts because a diversity of open models will spur more demand for its chips, according to conversations with more than a dozen current and former employees, Nvidia partners and Nemotron users. Much of Nvidia’s current demand comes from a handful of frontier labs and cloud operators such as OpenAI, Microsoft and SpaceX, some of which are developing their own AI chips.

Nvidia can benefit, the thinking goes, if a broader range of companies, from startups to large legacy businesses, can use and build AI via high-quality, relatively low-cost models from Nvidia optimized for its hardware—or if its efforts spur faster development of other open-source models.

“Nvidia wins no matter which of these companies makes great open source,” said Anastasios Angelopoulos, chief executive of Arena, a company that evaluates and benchmarks AI models.

Stoking More Open-Source Competition

Nvidia believes its model development efforts will stoke competition and lead to more open model development and therefore more GPU demand, an Nvidia executive said. The company has included several U.S. open-source developers in a network of firms contributing training data and ideas as part of what it calls the Nemotron Coalition to develop new models.

“Nvidia is investing in Nemotron because we believe every company and every country needs accessible frontier open models to strengthen safety and security, accelerate innovation, and provide a foundation they can rely on from one generation to the next,” Kari Briski, Nvidia’s vice president of generative AI, said in an email.

The timing for Nemotron 4 is unclear. Several employees said Nvidia has made some decisions about pretraining data and architecture for the big Nemotron 4 model, but hasn’t set the exact specifications or release date. It also has yet to do the final training run, which could take months. Two employees said the model could be ready late this fall, while others said it could be later.

Nvidia has long developed its own AI models to better inform how it designs its hardware. Early last year, it realized American open-source models had fallen far behind the leading Chinese counterparts, and wanted to help bridge the gap given the U.S. national interest and because it would benefit Nvidia, two employees said.

Bryan Catanzaro, Nvidia’s vice president of applied deep learning research, said on a podcast in January that investing in Nemotron is “essential for the future of our company.”

Open-source AI has become a geopolitical lightning rod as increasingly powerful Chinese models fueled debate in the U.S. over potentially regulatory action. Nvidia CEO Jensen Huang has loudly supported open-source, saying in an email last month that open models “promote safety, cybersecurity, scientific advances, and national security.”

The Nvidia models have gained adoption with some companies, notably including Palantir, which in June announced a collaboration with the chip company to use Nemotron models for U.S. government clients.

But the models’ performance has ranked well behind the industry vanguard. Nemotron 3 Ultra, Nvidia’s biggest model to date, ranks second among U.S. open models on multiple performance benchmarks from Arena and Artificial Analysis on agentic performance and intelligence, respectively, behind Thinking Machines’ just-released Inkling. That is far behind the top Chinese open model and outside of the top 40 models overall.

There is a limit to how much even Nvidia can invest in model development given the other demands on its finances. Nvidia’s cloud services commitment amounts to $7 billion for the fiscal year that will end in January 2028. While that is dwarfed by spending from OpenAI and Anthropic, the amount is still more than most leading open-source labs, both American and Chinese, have raised in their lifetimes. One employee said Nvidia is trying to get more compute for Nemotron.

The Neomotron Coalition companies—which include Reflection, Cursor, Thinking Machines and Mistral—are also contributing training data, evaluation help and model design ideas to Nemotron 4 even as they work on their own open-source projects. Startup Prime Intellect, which helps customers train, fine-tune and run their own open AI models, contributed 300,000 simulated environments to help with model training, said someone directly involved in the collaboration. The AI coding-tool startup Cognition, a member of the coalition whose participation hasn’t yet been announced, has discussed giving Nvidia coding data for training, according to someone with direct knowledge of the talks.

The partners have various incentives to participate. For those working on their own models, Nvidia’s push could expand interest in open source and thereby help build the market. Others are hoping to influence the development of a model they can use without having to pay for the compute that trains it.

Vincent Weisser, CEO of Prime Intellect, sees the coalition as a way to band together against the existence of “one ‘God’ model,” rather than a game of who can make the best open model.

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