Isaac Carlton decided one afternoon to tackle a project that most people would dismiss as impossible. He wanted to film the most famous moments from the Apollo moon landings without rockets, without a massive budget, and without stepping outside his own property. The result looks so close to the original NASA footage that viewers keep pausing to check whether they are watching history or something built from scratch in a garage.

Carlton began with a realistic goal: order a replica of the NASA spacesuit. When it arrived, he tried it on and was surprised to find that the fit worked perfectly for close-up photos. The moon’s surface came next. In his garage, he chopped out pieces of Styrofoam, sculpted them into craters and bumps, and then powdered everything with chinchilla bath powder to replicate the texture of lunar dust seen in old photographs. Black drapes obscured the walls, giving the scene a sense of infinite space.

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Three different scenes made the final cut, beginning with a bird’s-eye view of the astronauts planting the American flag. Carlton came up with an idea for using stop-motion. He purchased some action figurines, bent thin wire into their limbs to control their positions, and stuffed paper towels into the crevices to make the joints appear smooth as silk under the camera. Each minuscule movement necessitated a new photo, dozens of them, until the flag would raise and wave as it had in 1969.

In contrast, the lunar rover sequence required motion rather than stillness. Carlton purchased a vintage mini rover on eBay and matched it with a remote-controlled buggy he discovered online. He then drove his buggy over the Styrofoam countryside while the camera rolled. Then he combined numerous passes and slowed the footage down to make it appear as if the rover was bouncing across the surface under low gravity. The end effect was eerily similar to the original footage.

The zero-gravity jump from Apollo 16 was likely the most physically difficult. Carlton attached a basic pulley system to the rafters in his garage. He bought an Amazon harness and then asked a couple of friends to pull the ropes for him. They filmed at a snail’s pace to make it appear as if he was floating higher when the ropes hauled him up, and then the editor worked his magic to remove all trace of the cables and mix the takes together so it looked smooth and seamless.

Editing required a significant amount of effort, arguably as much as filming. Carlton and his friend Levi spent hours perfecting the color, adding grain to make it look antique, and painting light scratches to make it look like it was shot sixty years ago. They digitally stretched each set’s boundaries, causing the draperies to disappear. Every wire, contemporary shadow, and telltale trace of a home project disappeared in the editing suite.

Rivian may have figured out one of the hardest parts of building an affordable EV, as it has managed to reduce costs in producing one of its upcoming EVs. During the latest earnings call, the company said the upcoming R2 has achieved a cost reduction of more than 50% compared to the R1. With the R2 being made as the more accessible mass-market EV, this is a big deal.

How Rivian found ways to save up

According to InsideEVs, Rivian outlined several ways it brought costs down. The company reduced the R2’s wiring harness by 2.3 miles, cut the number of connectors by 60%, and reduced high-voltage cabling by 70% by consolidating multiple power conversion units into one. The company also simplified its new Maximus Drive unit, which has 41% fewer parts compared to the Enduro drive units used in R1 vehicles. Rivian mounted the inverter directly on the drive unit and used smarter cooling and packaging to cut parts and manufacturing complexity.

All of this sounds like boring manufacturing stuff, but it is making a real difference now. Fewer parts usually mean lower cost, easier assembly, fewer failure points, and better scaling.

The upcoming Rivian R2 is using a simpler mechanical setup, which reportedly helped achieve 70% cost savings on the front suspension by moving from a double-wishbone setup to MacPherson struts.

Meanwhile, large die castings also reduced the underbody part count by 90%, while rear door complexity was cut by 65%. CEO RJ Scaringe expects a reduction of more than 50% through design-for-manufacturing work and higher production volumes. He further added that this is how the company expects to ship the T2 profitably, while also keeping it at a more accessible price point without losing performance and utility.

So what about the buyers?

Rivian has positioned the R2 as a more affordable EV, with a target price around $45,000. But the T2 Performance is expected to kick things off at around $58,000 when deliveries begin. The expected price tag reveals that this isn’t an affordable car, though it is still more approachable than the R1S and R1T, which are positioned as premium models.

A $725bn hyperscaler capex ramp and a 20% HBM price rise have made the South Korean chipmaker the second-most valuable company on the KOSPI. The harder question is when supply catches demand.

There is a small joke in semiconductor circles about which part of an AI server is most expensive. The graphics processor used to be the obvious answer. For the past 18 months, increasingly, it has been the memory soldered next to it.

On Monday, the market priced that joke.

SK Hynix, the South Korean memory specialist that supplies the bulk of the world’s high-bandwidth memory for AI accelerators, climbed as much as 12 per cent in Seoul, with shares hitting roughly 1.4 million won, or about $970, in morning trading, according to Reuters.

The rally made SK Hynix the second-most valuable company on the KOSPI, behind only Samsung Electronics, and reflected, the wire said, foreign buying that followed strong earnings and reaffirmed AI infrastructure plans from US hyperscalers the previous week.

It is, by any measure, a remarkable run for a company most consumers have never heard of.

The trigger is straightforward. Big Tech’s combined 2026 capital expenditure is on track to land somewhere between $650bn and $725bn, depending on which analyst’s tally one trusts, an increase of roughly 77 per cent on 2025.

Microsoft has guided to as much as $190bn for the calendar year, with its chief financial officer publicly attributing about $25bn of that to rising memory-chip and component costs.

Meta, in its Q1 update, raised its own range to $125–145bn, citing similar pressures. Amazon’s Andy Jassy has committed roughly $200bn. Google has not been quieter. Practically all of this money flows, in one form or another, towards AI training and inference clusters; a meaningful share of it lands in the bill of materials for high-bandwidth memory, where SK Hynix dominates.

By late 2025, SK Hynix held an estimated 57 per cent of the global HBM market, according to figures cited by analysts at Counterpoint and others. That share is unusually concentrated for a commodity-adjacent business, and it is the structural reason the company’s earnings now look more like those of a software platform than a memory house.

SK Hynix’s first-quarter operating profit, reported on 23 April, was a record. Operating margins on its memory line, by some sell-side estimates, are running above 70 per cent.

Margins of that order do not last forever. They do, however, last as long as supply lags demand.

Why supply is not catching up

HBM is not ordinary DRAM. It is a stacked, 3D-packaged memory built to feed bandwidth-hungry GPUs, and producing it requires a specific set of advanced packaging steps that the industry, including Samsung and Micron, has been slower to scale than buyers would like.

According to TrendForce, both Samsung and SK Hynix have raised HBM3E prices by roughly 20 per cent for 2026, and supply is being booked years in advance by hyperscalers and accelerator vendors.

Samsung’s memory chief publicly warned earlier this year that significant memory shortages were likely to persist through 2027. The chairman of SK Group has gone further, telling investors he expects the wider chip-wafer constraint to last until 2030.

Whether or not those forecasts prove accurate, they explain why long-term supply agreements, in which a hyperscaler effectively reserves output years ahead, are becoming the norm. They also explain why Reuters reports SK Hynix and Samsung increasingly signing such deals with Microsoft and Google directly.

There are, in other words, two kinds of memory in 2026: the kind anyone can buy, and the kind your AI roadmap depends on. SK Hynix is in the second business.

There are, predictably, dissenters. The CAPE ratio on US equities now sits around 38, a level last seen at the height of the dot-com era, and TNW has noted the discomfort that comparison provokes, even as it argues that today’s leading AI-exposed companies are, unlike many in 2000, broadly profitable.

SK Hynix is squarely in that profitable cohort, but it is also unusually leveraged to a single product cycle. If hyperscaler capex moderates, or if competing accelerator architectures reduce HBM intensity per chip, the same operating leverage that has delivered record quarters could work in the opposite direction.

There is also the question of whether the AI build-out will keep producing the kind of returns that justify present capex levels. Meta has been simultaneously announcing record AI investment and cutting roughly 8,000 jobs as it restructures around the spending, a sequence that does not entirely fit the narrative of a healthy organic boom. Investors are, for now, willing to fund both ends of that equation. They have done so before in technology cycles, and they have changed their minds quickly.

The most useful way to read SK Hynix’s 12 per cent move is not as a forecast of where AI ends up, but as a real-time index of how confident the market currently is that AI training clusters will keep being built at this pace. Every dollar of hyperscaler capex announced becomes, eventually, an order book line at a memory supplier. SK Hynix sits in the chokepoint.

If the chokepoint loosens, through Samsung executing on HBM4 at scale, through Micron’s $25bn capacity push, or through architectural shifts that reduce HBM dependency, the dominant share gets shared and the multiples compress. None of those things has happened yet.

Until one does, the market’s read is that the second-largest company on the KOSPI is the one selling shovels to the AI gold rush, and it is not running out of buyers.

The harder, more interesting question is what the chart looks like a year from now. The answer will say less about SK Hynix than about whether the AI build-out has legs, and whether the people writing the cheques in Redmond, Menlo Park, and Seattle are still as certain as they were last week.

A Chinese creator has built a walk-in PC that turns desktop cooling into a human-scale spectacle. The fish-tank-style tower has enough room for a person, a compact desk, and a gaming setup, making the creator look like one of the tiny figures builders sometimes place inside flashy cases.

The build comes from TechTuber Soda Baka, who shared the project on Bilibili. It scales up familiar PC modding cues, including wall-sized fan housings, a huge graphics card prop, chunky cooler parts, and plenty of RGB lighting.

The size gets attention first, but the sealed enclosure soon becomes a heat trap.

The giant parts are mostly props

Soda Baka’s build starts like a serious PC project, with sketching, modeling, and fabrication before the frame comes together. The finished tower looks like an extreme version of the glass-heavy desktop cases that put every component on display.

Most of the human-scale hardware is built for show. The oversized fans, GPU, RAM sticks, and liquid cooler pieces appear to be nonfunctional, while working PC gear gives the creator something to use once he sits down at the desk.

The absurdity is carefully staged. Its size sells the illusion without pretending this is a practical computer anyone should recreate at home.

Why the AC matters

The air conditioner becomes the key component once the sealed enclosure starts heating up. To mimic a PC’s thermal problem at room scale, the creator uses hot-coal sauna gear and water to push the interior above 100 degrees Fahrenheit, or 38 degrees Celsius.

With the huge fans and coolers serving as set dressing, the build relies on a 12kW AC unit with claimed 820 cubic meters per hour of air circulation. The joke only works because the AC does the job the fake cooling hardware can’t.

What to watch next

The build looks more like a promo stunt than a mod worth copying. It may also be tied to an air conditioner sponsorship, though it isn’t fully confirmed.

For actual PC builders, the useful lesson is narrower and more practical. Glass-heavy cases, dense layouts, and sealed spaces all need a real airflow plan before heat becomes the limiting factor. Start with intake, exhaust, and component clearance before chasing the look.

Most tech roles saw salary growth, but not all benefited equally

2025 marked a turning point for the tech industry. After several years of layoffs, cautious hiring, and uncertainty, the sector is showing signs of recovery across the region.

At the same time, companies are rethinking how they prioritise and value talent. Artificial intelligence (AI) is no longer just a talking point—it’s now embedded in hiring priorities, day-to-day workflows, and compensation, as highlighted in Nodeflair’s latest annual tech salary report.

This year’s data, released today (May 4), shows that engineers with AI skills are earning meaningfully more than their peers, with some seeing pay bumps of up to 25%. At the same time, senior engineers continue to pull ahead, as companies place greater value on judgment, architecture, autonomy, and the ability to work effectively with AI tools.

In effect, AI is reshaping the tech career ladder and rewarding stronger problem-solvers at every level. Here is a breakdown of the report and the overall compensation changes for tech roles in Singapore, detailed by role and seniority:

[Disclaimer: Salary data are derived from Nodeflair’s proprietary database of over 130,000 data points, including user submissions that are verified by documents (payslips and offer letters) as well as job advertisements from various job portals. While a majority of the entries are backed by a sizeable amount of data, Nodeflair has flagged out entries with less than 200 data points as potentially lacking accuracy.]

Data scientists are the highest-paid, earning up to S$25K per month

Based on salary data from NodeFlair’s proprietary database, lead data scientists are the highest-paid role. Despite an overall 8.3% decline, they still command a median monthly salary of S$25,000.

Meanwhile, software engineer managers earn up to S$20,100 per month, marking a 10.8% increase as compared to the previous year.

Senior solutions engineers earn a median monthly salary of S$18,500, followed closely by senior product managers at S$18,100. Other top roles include lead mobile engineers at S$16,900, lead data engineers at S$16,000, and platform (DevOps & SRE) leads at S$15,200.

Roles at S$15,000 and below include lead cybersecurity engineers, lead data analysts, systems & IT leads, and senior quality assurance engineers.

On average, senior roles saw the strongest salary growth, with pay rising 12.6%. Lead roles followed at 11.6%, while manager roles increased by 10.8%.

By contrast, mid-level and junior roles recorded more modest gains, with average salary increases of 1.7% and 5.3%, respectively.

AI skills pay off

Beyond providing salary data, NodeFlair’s report highlighted a widening pay gap between engineers with and without AI skills.

Its analysis of 50th percentile software engineers shows that AI-native talent is being paid a clear premium.

The data found that junior software engineers (zero to two years of experience) with AI skills saw a 25% pay bump at the median, earning S$6,000 per month compared to S$4,800 for those without AI skills.

Among mid-level engineers (two to five years of experience), those with AI skills earned 13% more at the 50th percentile—S$8,000 versus S$7,100 for their non-AI peers.

At the senior level (more than five years of experience), engineers with AI skills earned 18% more at the median, taking home S$10,000 compared with S$8,500 for those without.

AI fluency is no longer a nice-to-have—it’s now a salary advantage

Ethan Ang, Nodeflair founder

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“With the rise of tools like Claude Code and a broader wave of agentic coding workflows, engineering teams are now rethinking how software gets built around AI, including placing greater value on engineers who are truly AI-native,” he added.

• Read more articles we’ve written on Singapore’s job trends here.

Featured Image Credit: Shadow_of_light/ depositphotos

Trust in online payments has never been as important as it is right now. For anyone who spends money across digital platforms, the tools we use to pay can shape the entire experience. Digital wallets stand out as more than a payment method, they’re a foundation for how fast, safe, and convenient every transaction can feel. Convenience might look like a buzzword, but for online shoppers, it’s the difference between an immediate purchase and a drawn-out checkout that breaks the flow.

Speed and flexibility are at the center of this shift. Today’s gamers, content subscribers, and e-commerce buyers have come to expect instant access, not just to their products, but to funds as well. Digital wallets answer the call, letting users transfer, store, and spend money in ways that traditional cards or slow bank payments can’t match. For those looking to stretch their value further, methods to buy Razer Gold online show how funding a wallet can help unlock exclusive game items, bonus points, or discounted content across many platforms.

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Digital wallets don’t just serve gamers, though. They unlock new ways to handle subscriptions, buy digital art, or access streaming services. Their real appeal is in how they make every transaction less of a process and more of a click. This shift in user expectation is subtle but profound, echoing through every part of digital commerce.

Security has become a hot topic. Payment fraud, identity theft, and data breaches drive demand for alternatives to typing out full card details. Digital wallets blend strong encryption with multi-factor authentication. These layers of protection help users manage risk without adding complexity to already busy lives. For those spending on unfamiliar sites, using a wallet adds an extra safeguard, keeping personal details out of harm’s way.

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Digital wallets continue to grow by adapting to what users want next: more currencies, more integrations, and fewer barriers between platforms and regions. Their evolution keeps driving innovation, not just for gaming but for all forms of online spending.

Digital marketplaces like Eneba offering deals on all things digital have helped refine what buyers now expect from every online purchase: instant, secure, and tailored to their needs. As competition heats up, it’s clear that digital wallets are here to shape the future of online transactions.