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President Trump signed an executive order on artificial intelligence Tuesday, less than two weeks after postponing a White House ceremony over his concerns that a similar policy could dull America’s edge on AI technology.

The order establishes a framework for the federal government to vet the national security risks of the most advanced AI systems for up to a month before their public release. The government will be able to work with trusted partners “that will have early access to covered frontier models to promote secure innovation and strengthen the cybersecurity of critical infrastructure,” the order says.

It was not immediately clear to what extent the order differed from the one he declined to sign on May 21.

Trump canceled an Oval Office event with tech industry executives last month because he did not like what he saw in the earlier version of the order’s text. “We’re leading China, we’re leading everybody, and I don’t want to do anything that’s going to get in the way of that lead,” Trump told reporters at the time.

That directive was characterized as a voluntary collaboration with participating U.S.-based tech companies, including Anthropic, OpenAI and Google.

O’Brien writes for the Associated Press.

An analysis of Google Reviews has shown which UK airports have the most cleanliness complaints — and the top spot may surprise you.

Airports are set to be busier than ever over the coming months as numbers of Brits prepare for their summer getaways. With greater numbers passing through the terminal, airports can become rather grubby in no time.

However, a fresh study has examined which UK airports have received the highest number of complaints regarding cleanliness. Private Tours England analysed Google Reviews of 50 UK airports and tallied how frequently travellers mentioned the word “dirty” in their feedback.

The rankings are determined by the proportion of total reviews featuring the term.

Remarkably, Leeds Bradford Airport came out as the dirtiest in the UK. In total, 2.46% of all its reviews include the word when describing their time at the terminal.

Leeds Bradford Airport operates flights to numerous destinations including Austria, Hungary, Romania, Iceland, Ireland, Spain, France, the Netherlands and Italy.

The airport itself holds a 3.2 Google rating, with one reviewer noting: “The airport is currently being renovated.

“However, there are very few seats, toilets are super dirty, and the WiFi does not function whatsoever.”

A second commented: “To say it’s been refurbished, it’s cheap, IKEA plastic plants everywhere and dirty and unclean. The public lounge is bad enough, but the Avro Lounge is an absolute disgrace.”

Another wrote: “Avoid this grubby, dirty little airport if you can. Completely unfit for purpose.”

Coming in second place was Manchester Airport, with 1.45% of reviews making reference to cleanliness issues. Belfast International Airport took third spot at 1.42%.

Followed by London Stansted in fourth place at 1.18%, with Birmingham Airport rounding off the top five at 1.13%.

Top 10 dirtiest airports in the UK:

1. Leeds Bradford Airport – 2.46%

2. Manchester Airport – 1.45%

3. Belfast International Airport – 1.42%

4. London Stansted – 1.18%

5. Birmingham Airport – 1.13%

6. Edinburgh Airport – 1.05%

7. London Luton Airport – 0.96%

8. Newcastle Airport – 0.84%

9. Bristol Airport – 0.80%

10. East Midlands Airport – 0.73%

Leeds Bradford Airport has been approached for a response.

US tech giant says fundraising drive includes deal to sell $10 bn of stock to Berkshire Hathaway.

Alphabet, Google’s parent company, has announced plans to sell $80bn worth of shares to fund its rollout of artificial intelligence.

Alphabet said on Monday that the equity offerings would finance the rollout of AI infrastructure needed to meet “unprecedented customer demand”.

The US tech giant said the fundraising drive included a deal to sell $10bn of stock to Berkshire Hathaway, the conglomerate led for six decades by legendary investor Warren Buffett.

The remaining $70bn will come from $30bn in underwritten offerings – a type of share issuance where a financial institution buys stock to sell on to investors – and $40bn in staggered sales on the open market.

“The company is experiencing strong demand for its AI solutions and services from enterprises and consumers, at levels that are exceeding the company’s available supply,” Alphabet said in a statement.

“By scaling its investments, the company seeks to expand its foundational infrastructure to support the significant growth opportunity ahead.”

Shares of Alphabet, which has a market capitalisation of more than $4.5 trillion, were down about 1 percent in after-hours trading following the announcement.

Like other Silicon Valley giants, Alphabet, whose AI business spans the Gemini family of assistants, data centres and cloud services, has committed eye-watering sums to AI-related infrastructure.

The company said in its most recent earnings call that it expected its capital expenditures to reach $180-190bn this year, and rise “significantly” in 2027.

US tech behemoths, such as Alphabet, Microsoft, Amazon and Meta, are expected to spend some $800bn on AI-related capital investment in 2026, according to an analysis by Goldman Sachs.

Troy Hooper, co-head of equity capital markets for the Americas at the financial intelligence provider Mergermarket, said Alphabet’s funding plans underscored the intensity of the race to lead the AI buildout.

“For hyperscalers, compute capacity is a direct driver of future revenue,” Hooper told Al Jazeera.

“By leaning into equity, Alphabet is bringing in permanent capital rather than burdening a balance sheet already absorbing record capex,” Hooper said, using the shorthand for capital expenditure.

Hooper said US tech giants have come to view underinvestment in AI as an “existential risk” and over-investment as “merely expensive”.

“The logic is simple: under-investing is an existential risk; over-investing is merely expensive. Microsoft, Amazon, and Meta are following the same calculus,” Hooper said.

“Ownership at scale lowers the marginal cost of training advanced models, building a moat smaller competitors will struggle to match. The message is clear: The winners of the AI era will be decided not just by algorithms, but by who owns the largest and most efficient compute platforms.”