Disclaimer: Unless otherwise stated, any opinions expressed below belong solely to the author.

In an increasingly familiar pattern, Grab has just posted strong Q1 results for 2026, seeing its revenue grow by 24% compared to 2025. The results beat analyst expectations, and turned last year’s US$21 million loss into a US$22 million profit—but you would struggle to see it reflected in the company’s stock performance.

This is despite having hit its first profitable year since inception, earning US$200 million in 2025.

Instead of a rally, following the transition from a money-burning startup into a mature, self-sustainable business, Grab has lost almost a quarter of its value over the past 12 months and is around 45% down from the high point last September.

In fact, the company is now trading at roughly the same levels it was in 2022, when revenue was less than half of today’s figure, and it was still burning billions annually to fund growth.

So why can’t Grab seem to break through the ceiling it has been bouncing against since its US$40 billion IPO in 2021?

Chasing a moving target

Starting off as a regional version of Uber, Grab has transformed itself (like many similar companies) into a superapp business, based on the promise that you could do a lot more than just hail a cab ride with your smartphone.

But despite its rapid growth and recently established profitability, functionally, Grab remains mostly about ordering rides and deliveries. Its financial services arm still requires further investment and is currently losing money, although its loan portfolio has more than doubled in the last year.

In other words, even after taking over Uber’s stake in Southeast Asia in 2018, as of 2026, the superapp dream is still only just that—a dream.

This is because whenever one competitor disappears, another turns up, as Gojek did shortly after Uber’s exit.

Since then both companies have been locked in a similar war of attrition, which has kept margins low, preventing meaningful growth of either.

And for as long as they have been battling it out, rumours have swirled about their impending acquisition or merger, which was first discussed back in 2020.

The topic saw a resurgence last year as negotiations are reportedly still on in early 2026, despite hitting some roadblocks, although the biggest concern remains the monopolistic position the combined entity would enjoy.

Indonesia holds the deciding vote

The rationale for the transaction is very simple: a single company would operate more efficiently, saving money on needless marketing expenses, allowing it to focus on investing in new services.

The problem for national regulators is the fact that if it goes through, the Grab-GoTo behemoth would have upwards of 90% of the market share in Indonesia, Malaysia and Singapore, and a substantial stake in Thailand and Vietnam.

As a result, they are unlikely to approve it unless the company offers strict concessions on how it is pricing its services to prevent gouging. That, however, could make the whole exercise pointless if it is prevented from reaping the rewards and remains constrained by local regulations.

Indonesia, the key government that has to greenlight the deal (since GoTo is an Indonesian company), may have just made the entire deal less viable, after President Prabowo announced just a few days ago that the country will cap maximum commissions charged by app operators from 20 to just 8%.

The decision puts the financial sense of the potential merger into question, although, depending on how badly it affects Gojek, it may force GoTo to push for the deal as it is facing a sharp drop in domestic revenue.

What it did for both businesses, however, was push their respective stock market valuations down in the subsequent days. This is why Grab, despite all of its achievements, continues to trade much below analyst targets and only as high as it was three to four years ago, when it was still a cash-burning growth stock.

Low margins, cutthroat competition and regulatory uncertainty continue to dampen investor moods, and it might remain so until the company starts showing profits from its other ventures.

• Read other articles we’ve written on Singaporean businesses here.

Featured Image Credit: tang90246/ depositphotos

Most people who use AI daily, including me, have already found their preferences. I use a paid Claude subscription to help with my editorial chores (headline brainstorming, fine-tuning the tone, etc.), while Gemini is my go-to AI model for image generation and background research, especially when I want to go deep on a topic.

Maybe you use Perplexity for search or ChatGPT for code, and that’s absolutely fine, as it only boosts your productivity and gets you the right information faster. The problem is, the operating system on your phone or laptop isn’t aware of your choice, and until now, it didn’t even care before imposing its own choice of AI.

In the corporate world, we call this partnerships. Most Android manufacturers, including Samsung and OnePlus, have partnered with Google to integrate Gemini on their devices. Windows, on the other hand, gives you Copilot, whether you take it or leave it.

Apple, reportedly, is about to do something neither of them has bothered to ask, much less execute: which AI do you actually want to use, and where?

The days of your phone choosing an AI for you are almost over

The moment you look at what Android and Windows are doing, the contrast gets stark fast.

According to Bloomberg’s Mark Gurman, iOS 27 will introduce a new feature that Apple internally calls “Extensions.” It will let you select your preferred AI model for a specific Apple Intelligence tool without simply surrendering to whatever AI model the company decides to install.

When iOS 27 arrives, you should be able to head into Settings, assign your preferred third-party AI model to an Apple Intelligence feature (Writing Tools, Image Playground, etc.), and iOS 27 takes it from there. Siri also gets the same treatment, letting you select the AI model that handles your requests at the backend. 

The moment iOS 27 lands on my iPhone 17, I am going to select Claude as the AI model of my choice for Writing Tools and Gemini for Image Playground. 

This isn’t just a regular choice, but a frictionless, system-level choice. You set it once, and every time you invoke the Apple Intelligence tool, your preferred AI model shows up. No switching of apps or copy-pasting prompts and outputs across windows required. 

That’s what true model portability looks like in practice, and in my frank opinion, it’s a more coherent solution than anything Android or Windows has ever implemented. 

On Android and Windows, my favorite AI is always one detour away

Let’s say that you’re using the AI-powered text processing tools on a Samsung Galaxy smartphone. Galaxy AI offers you quite a lot of them, including Writing Assist, Note Assist, and Call Assist, but all of them are powered by Google’s Gemini. 

What if I want to use Claude in Samsung Messages to write a message? I have to exit the app, open Claude’s app or web version, paste the text, type in a prompt, copy the output, return to the Messages app, paste it, and send it. Want a different model to summarize your meeting notes in Samsung Notes? I’ve to take the same detour. 

I know, it’s tiring to even read that. Imagine millions of users doing this every single day, just to use their preferred AI model. On Windows, Copilot is baked into Notepad and Paint, and there’s absolutely no other choice for everyday users. 

Motorola deserves some credit for going further than most Android OEMs, as it allows users to access Gemini, Copilot, Perplexity, and Meta’s Llama AI via Moto AI. However, the company has already decided and tied each AI model to a specific use case. For instance, Llama powers Catch Me Up, and Copilot handles quick questions and answers, while Gemini handles photo analysis. Exciting, right? But I didn’t choose any one of those.  

The platforms hand you an AI ecosystem to ease your digital pain, but what they’ve actually built is a walled garden. 

Apple isn’t winning the AI race: It’s building the track

Apple’s approach, on the other hand, treats your AI preference the way iOS already treats default browsers or email apps: as a user setting. That, in my opinion, is real democratization at work here. It is the right to choose which AI is genuinely useful to me, not whichever scores highest on a benchmark.

To understand how Extensions could actually materialize in practice, any AI company could opt in and add support through their App Store app, which then becomes available as an engine inside Apple Intelligence. Once we install the app, it surfaces as an option inside Settings.

From there, you can route an Apple Intelligence tool to whichever model you trust the most for that specific task. While the company’s in-house models stay intact, the option to outsource a query to third-party models sits as a layer on top. Further, we could also get a dedicated App Store section, which will highlight the compatible AI apps.

Here’s where it gets even more interesting for Apple as a business. So far, the company has been fairly criticized for lagging in the AI race. However, opening up its platform of over 2.5 billion active devices, including iPhones, iPads, and MacBooks, to Claude, Gemini, and whoever qualifies may turn that weakness into its most lucrative strength.

The iPhone-maker already takes its standard 30% cut on App Store subscriptions, but if you extend this to every Claude Pro or Gemini Advanced subscription processed through iOS, suddenly, Apple doesn’t really need to win the AI race. It just needs to own the racetrack.

Remember, none of it is officially confirmed by Apple. But we’re pretty close to WWDC 2026, and that’s when Apple could officially announce the transition from becoming an AI-first company to an AI-agnostic platform, one that profits from all of them.

In a world where a viral TikTok video can cause a brand to trend globally in mere hours, the traditional market research cycle — often spanning 12 weeks — is becoming a liability.

The lag between a survey question and the answers from a wide (or targeted) pool of respondents has become a primary bottleneck for Fortune 500 decision-makers who are forced to navigate volatile geopolitical and economic shifts with data that is frequently outdated by the time it reaches a slide deck, as industry experts have observed.

Brox, a predictive human intelligence startup, recently announced a strategic funding round following a year where they reported 10X revenue growth. Their proposition is as ambitious as it is technical: the creation of a “parallel universe” populated by 60,000 digital twins of real, living human beings and their entire demographic profiles and consumer preferences, allowing enterprises to run unlimited experiments in hours rather than months.

“These digital twins are one-to-one replicas of actual, real individuals,” said Brox CEO Hamish Brocklebank in a recent video call interview with VentureBeat. “We recruit real people like a normal panel company does, pay them to interview them, and capture all the data around them — fully consent-driven.”

The company, currently a lean 14-person operation, is positioning itself as the antithesis of the “insane” research industry. By replacing statistical models with behavioral replicas, Brox aims to transform how the world’s largest banks and pharmaceutical giants anticipate human reactions to high-stakes global and market-shifting events, or narrow, targeted product releases and personnel news, and everything in between.

The kinds of surveys and specific questions that Brox asks its digital twins are completely open-ended and can be customized to fit any conceivable business customer’s use cases and goals.

According to Brocklebank, examples of survey questions include: “What happens if America invades Iran or Greenland? Will depositors at Bank of America put more money into their account or take more money out? Or, in pharmaceuticals, if RFK Jr. says something next week, will that make people more likely to take vaccines or less likely?”

Not synthetic people — AI copies of real ones

The core differentiator of Brox’s technology lies in the fidelity of its input data.

While many competitors in the “digital audience” space rely on purely synthetic identities — generic personas generated by Large Language Models (LLMs ) — Brocklebank argues that these methods inevitably produce “AI slop”.

Purely synthetic audiences often cluster around a tight distribution of answers, over-indexing for “correct” or “healthy” behaviors (such as eating broccoli) because of inherent biases in the underlying models.

Brox’s “Digital Twins” are instead one-to-one behavioral replicas of real individuals who have been recruited and interviewed with exhaustive depth. The process is intensive:

• Deep Interviews: The company conducts hours of real and AI-driven interviews with each participant.

• Psychological Depth: The data collection seeks to understand fundamental “decision drivers,” including upbringing, relationships, and even marital stability.

• Data Density: For some twins, Brox maintains up to 300 pages of text data, representing what Brocklebank calls “the deepest per person data set that exists”.

To solve the “black box” problem common in AI, Brox utilizes a “reasoning chain” for its predictive outputs. When a digital twin predicts a reaction — such as how a $2 billion net-worth individual might respond to a specific interest rate hike — the model introspects and provides a step-by-step explanation for that decision.

This allows clients to understand not just what will happen, but the underlying psychology of why it is happening.

Scaling the “unscalable” interview

The product offering is currently live in the US, UK, Japan, and Turkey. Brox has successfully digitized specific, high-value cohorts that are traditionally difficult for researchers to access.

This includes a panel of “high-net-worth” individuals (those worth over $5 million) and specialized medical professionals like dermatologists — including a multibillionaire.

However, the largest value for customers is likely in the aggregate mass of all individuals that can be polled en masse and/or segmented across demographics, especially those of medium and lower income levels, whose purchasing power and decision-making is more constrained and whose market-

One of the more unique aspects of the Brox platform is its incentive structure. To ensure twins remain up-to-date, real-world counterparts are re-contacted frequently.

For high-value individuals who are not motivated by small cash payments, Brox has issued Stock Appreciation Rights (SARs), essentially making these participants “investors” in the company’s success to ensure they continue to provide high-fidelity personal updates. The platform’s use cases currently focus on two primary sectors:

1. Pharmaceuticals: Predicting vaccine hesitancy or how physicians might react to new biologics based on shifting political climates.

2. Finance: Simulating how depositors at major banks might move funds in response to geopolitical events, such as conflicts in the Middle East.

As for why go to the trouble of interviewing and digitally cloning real people instead of just creating wholly fictitious, synthetic audience characters and personas using LLMs and other AI models, Brocklebank offered his perspective.

“You can create 10,000 truly synthetic digital twins, but the answers will still normalize into a very tight distribution, which is not realistic when you’re actually asking real people,” Brocklebank said.

By maintaining a pre-built audience of 60,000 twins, the company enables clients to bypass the recruitment phase of research. A large US bank or a global pharma giant can now “query” the digital population and receive a validated analysis in a matter of hours.

Pricing and accessibility

Unlike traditional research firms that charge on a per-project or per-respondent basis, Brox operates as a high-end Software-as-a-Service (SaaS) platform with enterprise-level commercial licensing. The company avoids the “seat” or “usage” limits that often hinder rapid experimentation within large organizations.

• Pricing Tiers: Subscriptions are sold as blanket flat fees, starting at a minimum of $100,000 per year.

• Top-Tier Contracts: For larger deployments involving multiple teams and global data access, contracts scale up to $1.5 million per year.

• Usage Rights: Clients are granted unlimited usage during the contract period. This allows them to run thousands of simulations without worrying about incremental costs, encouraging a culture of “testing everything” before deployment.

From a legal and privacy standpoint, the digital twins are built on a “fully consent-driven” framework. While the twins can be traced back to real human data for internal validation, the platform is designed to provide aggregated behavioral insights that protect the anonymity of the participants while maintaining the predictive power of their digital replicas.

Rejecting the rise of Kalshi, Polymarket and ‘prediction markets’

The tech industry has recently seen a surge in valuations and interest in “prediction markets” like PolyMarket and Kalshi, which allow users to bet on the outcomes of various global events.

However, the leadership at Brox maintains a distinct distance from these platforms, citing a “personal disdain” for betting markets from both a moral and intellectual perspective.

Brocklebank argues that while betting markets can predict outcomes (e.g., who wins an election), they offer zero utility for business decision-makers because they fail to provide the “why”.

Knowing there is a 60% chance of a certain candidate winning does not help a company adjust its consumer strategy; knowing why a specific cohort of depositors is feeling anxious does.

Investors including Scribble Ventures, Wonder Ventures, and Vela Partners have backed this “human-first” approach to AI, betting that the moat created by deep human data will prove more resilient than the commoditized models of synthetic data providers.

As Brox prepares for launches in the Middle East and APAC, the company is moving toward its ultimate goal: simulating the entire world as a “parallel universe” for risk-free decision-making.

Lock Noob got his hands on the NPX-002 from Works by Design and wanted to put its security claims to the test to see how well they held up. The lock’s designers created this travelling key system, in which the key’s bow spins some internal gears and the actual key blade moves into place deep inside the cylinder. The key only fits perfectly in the exact position, at which point the keyway seals off, leaving no place for your standard picks or tension tools to reach the pins. To prevent the normal impressioning techniques, the brass ones had a plastic pin inserted.

He began by taking a close look at the lock, shining a light through the clear anti-tamper cover to see the key within. A quick stream of solvent was sufficient to lift the seal without causing any damage. He pulled out the key, opened the lock once, and then disassembled the cylinder to inspect all of the moving parts. After that, he put everything back together and sealed the case with tape. Bypassing it was more of a curiosity for him, as the actual test would be to pick it honestly.

His next step was to impressioning the lock by clamping it in a vice and inserting a simple brass blank into the keyhole. He then took an old screwdriver, fitted a bespoke brass bit on it, and began applying mild twisting pressure so that the pins left a mark on the soft metal without harming the lock body. He shook the blank back and forth, watching as tiny marks appeared where the pins pressed the strongest. Each one informed him exactly where to begin filing.

The grind had settled into a regular rhythm, as you filed a bit, turned again, examined the fresh marks with a magnifying glass, and repeated. Position three refused to make a mark, which he discovered was due to the plastic pin, but he continued nevertheless, deepening the wounds where the brass was in touch. He had been turning, filing, inspecting, and repeating for two hours before he realized it. The cuts were increasing deeper in some places and shallower in others, until the blank finally matched the unknown depth.

After two hours, the cylinder gave a gritty turn, and the lock finally opened. The plastic pin had chipped somewhat at the top, but the remainder of the mechanism remained intact. He disassembled the cylinder one last time and saw the damage with his own eyes. A new plastic pin was installed, and the lock was restored to its original functionality.

He attempted one final idea: wrap some aluminum foil around a skeleton key blank. The plan sounded fine on paper: the pins would simply press into the soft foil, leaving quick impressions. In practice the pins dropped at an angle and hit a ledge before they touched the foil. No useful marks formed. The foil method stayed on the shelf.

The expansion follows the organisation’s recent authorisation as an electronic money institution by the Central Bank of Ireland, providing a strategic gateway to support SMEs across the continent.

Hong Kong fintech Currenxie, which recently established an Ireland-based team, has announced plans to create 30 jobs in Dublin, which is the company’s European base of operations. The new roles will be in areas such as technology, operations, compliance, finance and client services.

The 30 jobs will be filled in the next two years and the expansion follows the company’s recent authorisation as an electronic money institution (EMI) by the Central Bank of Ireland, which Currenxie said has provided the company with a strategic gateway to support established SMEs across the continent.

Currenxie also stated that the move provides European finance leaders with the local payout and collection infrastructure needed to navigate complex global trade corridors, particularly between Europe and the Asia-Pacific region.

Commenting on the announcement, the Minister for Enterprise, Tourism and Employment Peter Burke, TD said: “I welcome Currenxie’s decision to establish its European operations in Dublin and their plans to create high quality jobs over the next two years. 

“The company’s decision reflects confidence in Ireland as a stable, innovative and well-regulated location from which to serve European markets.”

Michael Lohan, the CEO of IDA Ireland added: “We are delighted to welcome Currenxie as it establishes itself in Ireland. This announcement reinforces Ireland’s position as a leading location for international financial services and fintech companies, offering a highly skilled talent pool, a strong and well-regulated financial ecosystem, and direct access to customers across Europe.”

2026 has seen a positive uptick in investment within Ireland’s fintech ecosystem. In April, Dublin-based start-up Audrey AI announced the closure of a $1.8m pre-seed funding round. In early February, Dublin-based fintech company Circit secured $22m in growth equity funding to further scale its financial auditing and verification platform.

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Anthropic and Elon Musk’s SpaceX said on Wednesday that the two entities have signed an agreement for Anthropic to use computing resources from xAI’s data center in Memphis, Tennessee. It’s the latest tie up in an industry that is scrambling to find enough computers to run complex AI software. SpaceX and xAI were previously separate companies, but the two merged earlier this year. The combined entity, also owned by Musk, is called SpaceXAI.

Anthropic executives made the announcement on stage at the company’s annual developer conference in San Francisco. SpaceXAI also put out a blog post sharing more details about the deal, which will see Anthropic draw power from xAI’s Colossus 1 supercomputer.

The partnership comes at a pivotal time for SpaceXAI, which is seeking to go public as soon as next month. A relationship with a leading AI lab could bolster SpaceX’s credibility as it pitches investors on the potential gold mine in establishing more data centers, including in space.

Notably, Space XAI said in its blog post that Anthropic has “expressed interest” in partnering to develop “orbital AI compute capacity”—essentially, data centers in space. Having Anthropic as a potential customer could help SpaceXAI boost investor confidence that there will be buyers for its super expensive, supercomputing project.

Earlier this year, Musk criticized Anthropic’s AI models in a post on X, calling the company’s policies “misanthropic” and “evil,” and alleging without evidence that the AI models showed racial and sexual biases.

Now, he’s significantly changed his tune, writing on X that he “spent a lot of time last week with senior members of the Anthropic team to understand what they do to ensure Claude is good for humanity and was impressed.”

Musk’s SpaceXAI first broke ground on Colossus 1 on a former Electrolux site in 2024. The company claims that it is one of the largest and fastest AI supercomputers in the world. It includes roughly 220,000 Nvidia GPUs, ranging from Nvidia’s H100 and H200 to its newer GB200 chips. The company likes to boast that it built the super computer in 122 days.

Emissions from gas turbines at the data center have prompted numerous complaints from local residents. Last month, environmental protestors demonstrated at a nearby SpaceX investor gathering ahead of the IPO.

Anthropic plans to use its newfound computing power to “directly improve capacity for Claude Pro and Claude Max subscribers,” both companies said. The deal will give Anthropic access to more than 300 megawatts of new capacity, or approximately 220,000 Nvidia GPUs. In recent months, software developers have increasingly complained about rate limits and service disruptions to Claude Code, due to the physical limits of available computing resources.

As more and more people use services like OpenAI’s Codex and Anthropic’s Claude Code—sometimes running coding programs and agentic tasks for hours on end—the services are being bogged down. According to Anthropic, the average developer is now spending at least 20 hours per week running Claude Code.

Yesterday, The Information reported that Anthropic had committed to spend $200 billion on Google’s AI cloud services and TPU chips. Anthropic has also used Amazon’s cloud computing services and AI chips since 2023. Last month, Anthropic committed “more than $100 billion over the next ten years to [Amazon] technologies.” According to the Information report, contracts with Anthropic and OpenAI now account for “more than half of the $2 trillion in backlogs at major cloud providers” like Amazon, Microsoft, and Google.

Paresh Dave and Zoe Schiffer contributed to this report.

• More Mac models have now been pulled by Apple
• Mac minis and Mac Studios now available in fewer configurations
• AI and the associated memory shortage is to blame

With AI data center demand sucking up the world’s supply of RAM, consumers are feeling the effects: having already removed some configurations of the Mac Studio and Mac mini from its store last month, Apple has now reduced the available options even further.

As spotted by MacRumors, you can no longer buy Mac mini models with 32GB or 64GB of RAM, while the M3 Ultra Mac Studio with 256GB of RAM has also been taken off sale — so right now that particular computer is only available with 96GB of RAM.