Spotify shares dropped about 4% Tuesday after the music streaming platform fell short of Wall Street’s expectations and posted weak guidance for the current quarter.

Here’s how the company did versus LSEG estimates:

• Loss: Loss of .42 euros vs earnings of 1.90 euros per share expected
• Revenue: 4.19 billion euros vs. 4.26 billion expected

The Sweden-based music platform’s revenues rose 10% from about 3.81 billion euros in the year-ago period. The company posted a net loss of 86 million euros, or a loss of .42 euros per share, down from net income of 225 million euros, or 1.10 euros per share a year ago.

Third-quarter guidance came up short of Wall Street’s forecast.

The company expects revenues to reach 4.2 billion euros, compared to a 4.47 billion euro estimate from StreetAccount. Spotify said the forecast accounts for a 490-basis-point headwind due to foreign exchange rates.

Monthly active users on the platform jumped 11% to 696 million, while paying subscribers rose 12% from a year ago to 276 million.

For the current quarter, Spotify said it expects to reach 710 million monthly active users, with 14 million net adds. The company expects 5 million net new premium subscribers in the third quarter to reach 281 million subscriptions.

During the period, Spotify said it rolled out a request feature for its artificial intelligence DJ. The company said engagement with the offering has roughly doubled over the last year.

In 2024, Spotify posted its first full year of profitability. Shares are up 57% this year.

South Korean artificial intelligence chip startup Rebellions has raised money from tech giant Samsung and is targeting a funding round of up to $200 million ahead of a public listing, the company’s management told CNBC on Tuesday.

Last year, Rebellions merged with another startup in South Korea called Sapeon, creating a firm that is being positioned as one of the country’s promising rivals to Nvidia.

Rebellions is currently raising money and is targeting funding of between $150 million and $200 million, Sungkyue Shin, chief financial officer of the startup, told CNBC on Tuesday.

Samsung’s investment in Rebellions last week was part of that, Shin said, though he declined to say how much the tech giant poured in.

Since its founding in 2020, Rebellions has raised $220 million, Shin added.

The current funding round is ongoing and Shin said Rebellions is talking to its current investors as well as investors in Korea and globally to participate in the capital raise. Rebellions has some big investors, including South Korean chip giant SK Hynix, telecommunication firms SK Telecom and Korea Telecom, and Saudi Arabian oil giant Aramco.

Rebellions was last valued at $1 billion. Shin said the current round of funding would push the valuation over $1 billion but declined to give specific figure.

Rebellions is aiming for an initial public offering once this funding round has closed.

“Our master plan is going public,” Shin said.

Rebellions designs chips that are focused on AI inferencing rather than training. Inferencing is when a pre-trained AI model interprets live data to come up with a result, much like the answers that are produced by popular chatbots.

With the backing of major South Korean firms and investors, Rebellions is hoping to make a global play where it will look to challenge Nvidia and AMD as well as a slew of other startups in the inferencing space.

Samsung is manufacturing Rebellions’ semiconductor using its 4 nanometer process, which is among the leading-edge chipmaking nodes. For comparison, Nvidia’s current Blackwell chips use the 4 nanometer process from Taiwan Semiconductor Manufacturing Co. Rebellions will also use Samsung’s high bandwidth memory, known as HBM3e. This type of memory is stacked and is required to handle large data processing loads.

That could turn out to be a strategic win for Samsung, which is a very distant second to TSMC in terms of market share in the foundry business. Samsung has been looking to boost its chipmaking division. Samsung Electronics recently entered into a $16.5 billion contract for supplying semiconductors to Tesla.

If Rebellions manages to find a large customer base, this could give Samsung a major customer for its foundry business.

Europe is setting its sights on gigawatt factories in a bid to bolster its lagging artificial intelligence industry and meet the challenges of a rapidly-changing sector.

Buzz around the concept of factories that industrialize manufacturing AI has gained ground in recent months, particularly as Nvidia CEO Jensen Huang stressed the importance of the infrastructure at a June event. Huang hailed a new “industrial revolution” at the GTC conference in Paris, France, and said his firm was working to help countries build revenue-generating AI factories through partnerships in France, Italy and the U.K.

For its part, the European Union describes the factories as a “dynamic ecosystem” that brings together computing power, data and talent to create AI models and applications.

The bloc has long been a laggard behind the U.S. and China in the race to scale up artificial intelligence. With 27 members in the union, the region is slower to act when it comes to agreeing new legislation. Higher energy costs, permitting delays and a grid in dire need of modernization can also hamper developments.

Henna Virkkunen, the European Commission’s executive vice president for tech sovereignty, told CNBC that the bloc’s goal is to bring together high quality data sets, computing capacity and researchers, all in one place.

“We have, for example, 30% more researchers per capita than the U.S. has, focused on AI. Also we have around 7,000 startups [that] are developing AI, but the main obstacle for them is that they have very limited computing capacity. And that’s why we decided that, together with our member states, we are investing in this very crucial infrastructure,” she said.

“We have everything what is needed to be competitive in this sector, but at the same time we want to build up our technological sovereignty and our competitiveness.”

So far, the EU has put up 10 billion euros ($11.8 billion) in funding to set up 13 AI factories and 20 billion euros as a starting point for investment in the gigafactories, marking what it says is the “largest public investment in AI in the world.” The bloc has already received 76 expressions of interest in the gigafactories from 16 member states across 60 sites, Virkkunen said.

The call for interest in gigafactories was “overwhelming,” going far beyond the bloc’s expectations, Virkkunen noted. However, in order for the factories to make a noteworthy addition to Europe’s computing capacity, significantly more investment will be required from the private sector to fund the expensive infrastructure.

Telecommunications firm Telenor is already exploring possible use cases for such facilities with the launch of its AI factory in Norway in November last year. The company currently has a small cluster of GPUs up and running, as it looks to test the market before scaling up.

“The journey started with a belief — Nvidia had a belief that every country needs to produce its own intelligence,” Telenor’s Chief Innovation Officer and Head of the AI Factory Kaaren Hilsen told CNBC.

Hilsen stressed that data sovereignty is key. “If you want to use AI to innovate and to make business more efficient, then you’re potentially putting business critical and business sensitive information into these AI models,” she said.

The company is working with BabelSpeak, which Hilsen described as a Norwegian version of ChatGPT. The technology translates sensitive dialogues, such as its pilot with the border police who can’t use public translation services because of security issues.

We’re experiencing an “intelligence revolution” whereby “sovereign AI factories can really help advance society,” Hilsen said.

Following the announcement of the EU-U.S. trade framework, EU chief Ursula von der Leyen said Sunday that U.S. AI chips will help power the bloc’s AI gigafactories in a bid to help the States “maintain their technological edge.”

“One could argue that it’s relatively easy, provided you have the money. It’s relatively easy to buy the chips from Nvidia and to create these hardware factories, but to make it run and to make it economically viable is a completely different question,” Martens told CNBC.

He said that the EU will likely have to start at a smaller scale, as the region is unable to immediately build its own frontier models in AI because of their expense.

“I think in time, Europe can gradually build up its infrastructure and its business models around AI to reach that stage, but that will not happen immediately,” Martens said.