BARCELONA — China’s Huawei isn’t the only smartphone maker adding a third display to its devices.

At the Mobile World Congress (MWC) trade show in Barcelona, a number of firms were showing off their display technology innovations.

The South Korean tech giant Samsung revealed its new “trifold” concept devices at the event: the Flex G and Flex S.

The Flex G has three screens and folds flat inwards and outwards, a bit like a book. The Flex S, on the other hand, has a more zigzag-like shape. It’s meant to resemble an “S” — hence the name.

It comes after Chinese tech giant Huawei last month launched its new Mate XT, a 3,499 euro ($3,678.56) smartphone with three screens, in international markets.

Samsung stressed that its Flex G and S models were only concept devices — so don’t expect to find them on shelves anytime soon.

Still, it’s a sign of where smartphone makers are seeing the next wave of innovation.

On Tuesday, British consumer tech startup Nothing launched its new Phone (3a), a 329-euro ($356.28) budget model with a quirky design and LED light system that lights up when you get calls or notifications.

Nothing co-founder Akis Evangelidis — who is planning a move to India as the startup plans an aggressive expansion push in the country — told CNBC the company is trying to shake up the smartphone market with something more fun and unique.

Using the Indian market as an example, Evangelidis said: “People are walking away from pure functional needs when it comes to product. They aspire to brands that have more of an emotional benefit, and I think that’s where the opportunity is.”

MongoDB shares cratered more than 20% after the database software maker shared weak guidance that signaled a slowdown in growth.

For the fiscal 2026 year, the company said it expects adjusted earnings to range between $2.44 to $2.62 per share and revenue of $2.24 billion to $2.28. Analysts were expecting EPS of $3.34 and $2.32 billion in revenue.

The weak guidance stems from slower growth in the company’s Atlas cloud-based database service. The revenue projection would imply 12.7% growth, the slowest for the company going back to its 2017 stock market debut.

Finance chief Srdjan Tanjga said during an earnings call that the company is seeing slower-than-expected growth in new applications harnessing its Atlas cloud-based database service. However, MongoDB is beefing up hiring and going after deals with larger companies.

For the fiscal first quarter, MongoDB forecasted 63 cents to 67 cents in adjusted earnings per share on $524 million to $529 million in revenue. Analysts polled by LSEG had expected EPS of 62 cents and revenue of $526.8 million.

Citing MongoDB’s weak outlook and slowdown in growth, Wells Fargo analyst Andrew Nowinski downgraded shares to equal weight and lowered his price target.

“With a smaller pool of multi-year deals, we believe it will be difficult to significantly outperform expectations in FY26 and therefore expect shares to remain range-bound,” he wrote.

Read more of Nowinski’s analysis here.

MongoDB’s outlook offset stronger-than-expected fourth-quarter earnings. The company reported earnings of $1.28 per share, excluding items, on $548 million in revenue. Analysts polled by LSEG had anticipated EPS of 66 cents and $520 million in sales. Revenues rose 20% from a year ago.

MongoDB gained 1,900 customers in the quarter, reflecting a total of 54,500.

— CNBC’s Jordan Novet contributed reporting.

Alibaba shares surged on Wednesday after the Chinese behemoth revealed a new reasoning model it claims can rival DeepSeek’s global blockbuster R1.

Hong Kong-listed shares of Alibaba ended the Thursday session up 8.39% — hitting a new 52-week high — with the company’s New York-trading stock rising around 2.5% in premarket deals. Alibaba shares have gained nearly 71% in Hong Kong in the year to date.

The Chinese giant on Thursday unveiled QwQ-32B, its latest AI reasoning model, which it said “rivals cutting-edge reasoning model, e.g., DeepSeek-R1.”

Alibaba’s QwQ-32B operates with 32 billion parameters compared to DeepSeek’s 671 billion parameters with 37 billion parameters actively engaged during inference — the process of running live data through a trained AI model in order to generate a prediction or tackle a task.

Parameters are variables that large language models (LLMs) — AI systems that can understand and generate human language — pick up during training and use in prediction and decision-making. A lower volume of parameters typically signals higher efficiency amid increasing demand for optimized AI that consumes fewer resources.

Alibaba said its new model achieved “impressive results” and the company can “continuously improve the performance especially in math and coding.”

Both established and emerging AI players around the world are racing to produce more efficient and higher-performance models since the unexpected launch of DeepSeek’s revolutionary R1 earlier this year.

Chinese firms have been doubling down on the technology with Alibaba investing in AI after debuting its first model in 2023. The strength of the company’s cloud Intelligence unit was a key contributor to Alibaba’s sharp profit hike in the December quarter.

“Looking ahead, revenue growth at Cloud Intelligence Group driven by AI will continue to accelerate,” Alibaba CEO Eddie Wu said at the time.

Optimism surrounding AI developments could lead to large gains for Alibaba stock and set the company’s earnings “on a more upwardly-pointing trajectory,” Bernstein analysts said.

“The pace of innovation is incredibly fast right now. It’s really good for the world to see this happening,” Futurum Group CEO Dan Newman told CNBC’s “Squawk Box Europe” on Thursday. “When DeepSeek came out, it made everyone sort of question, was OpenAi the final answer? Would the incumbents, the Microsofts, the Googles, or the Amazons that have all made massive investments win?”

He stressed that the large language models were increasingly “becoming commoditized” as developers look to drive down costs and improve access to users.

“As we see this more efficiency, this cost coming down, we’re also going to see use going off. The training era, which is what Nvidia really built its initial AI boom off, was a big moment,” Newman said. “But the inference, the consumption of AI, is really the future and this is going to exponentially increase that volume.”