Waymo picks Singapore for its first Southeast Asian robotaxis

Share
Waymo picks Singapore for its first Southeast Asian robotaxis

Waymo's international expansion added a fourth flag today, and this one lands in a country that has already legislated for the drivers it might displace.


Waymo will launch a commercial robotaxi service in Singapore by 2028, its first market in Southeast Asia, working with the Ministry of Transport and the Land Transport Authority. An initial fleet of all-electric Jaguar I-PACE vehicles arrives in the coming months, mapping and validation follow in 2027 — with trained autonomous specialists driving manually at first so the Waymo Driver learns local road geometry and monsoon weather — and the company says it is working toward fully autonomous public ride-hailing in 2028. Rides will be bookable through the Waymo app.

Singapore becomes Waymo's fourth market outside the United States, after London, Tokyo (targeting a 2027 launch with Nihon Kotsu and GO) and Munich. It is also the first where the government has pre-funded the transition: Singapore's parliament passed a manpower transition package in July 2026, and LTA said today it will help drivers retrain and move into roles the AV sector creates, adding that it "will not allow autonomous vehicle deployment to run ahead of our ability to retrain and support affected drivers." Transport minister Jeffrey Siow welcomed Waymo as the country's newest AV operator.

The commercial logic is straightforward. Waymo told Singapore it wants to bridge first-and-last-mile gaps around transit hubs, and cited its own data that more than a third of San Francisco riders are picked up or dropped off near a transit station — the pitch that matters in a city-state where the MRT already works. Waymo has around 4,000 vehicles across roughly 15 US cities, was valued at $126 billion in February when it raised $16 billion, and arrives in a market where Grab and WeRide already run autonomous shuttles, so it is buying position rather than opening a frontier.

Our read: this is the first Waymo expansion where the labour policy exists before the fleet does — and that is the experiment worth watching, not the cars. Every other market has fought the displacement question after deployment, in driver protests and emergency hearings; Singapore is testing whether a retraining package announced in advance actually holds when the vehicles scale. The risk is asymmetric. If the AVs underperform, the transition money was wasted. If they work, Singapore has a template other governments will copy, and Waymo gets a regulator that has already decided the answer to the question that stalls it at home. We covered the Japan half of this build-out earlier this week — Waymo will run Tokyo's first driverless taxis in 2027.


Alibaba added an omni-modal model to its Qwen 3.8 line, aimed at audio and video understanding rather than text. The model, listed in Alibaba Cloud Model Studio as qwen3.8-omni-flash, takes text, image, audio and video input and returns text, and the documentation positions it for audio and video understanding and content analysis — the workload where a fast, cheap multimodal pass beats a frontier model on price. Developers discussing the release on Hacker News noted the framing puts its audio-visual performance near Gemini 3.8 Flash, though the company's own evaluation page for the model is thin on numbers.

The interesting part is where it sits in the family. Alibaba's Qwen 3.8-Flash went after agentic coding and long-horizon office work with an architecture aimed at cost — the company says it trained at less than a ninth of what its previous generation cost — while the omni variant goes after the modality mix that video, meeting and moderation pipelines actually need. Two different races, one price war: Alibaba is now competing on being the cheap default for whatever an application happens to ingest.

What to watch: whether Waymo's 2027 validation phase in Singapore stays on schedule, and whether LTA's driver-support pledge survives the first commercial quarter.

Should governments budget for worker displacement before robotaxis deploy, or does that just buy the operator's political cover? Tell us in the comments.

Read more

Akhetonics says its all-optical CPU reaches a customer in 2026

Akhetonics says its all-optical CPU reaches a customer in 2026

Light-based computing keeps promising more than it delivers — but one Munich startup has just put a date on its bet, and the interview laying it out is doing the rounds on Hacker News this week. Akhetonics says it will deploy its first commercial machine with a major customer by the end of 2026, with several more planned for 2027. The company, founded by Michael Kissner and Leonardo Del Bino, is building a computer where data enters as light, is switched as light, and circulates through memory

The Week in AI — October 5–11, 2026

The Week in AI — October 5–11, 2026

Every big claim this week turned out to rest on fine print more interesting than the headline: revenue only the company reporting it can define, safety tests sandboxed while the product keeps the web, and a Pentagon phase-out nobody would confirm until reporters kept asking. The week's top 5 1. OpenAI's revenue was $20 billion below the numbers everyone quoted — and the gap was definitional. The Financial Times reported Thursday that OpenAI's annualized revenue runs roughly $20 billion unde

Drone strike shuts a third Yandex data center, taking YandexGPT offline

Drone strike shuts a third Yandex data center, taking YandexGPT offline

Russia's largest tech company is learning what the AI era's infrastructure war looks like from the receiving end — three data centers in four days, and with them much of the cloud layer Russian businesses run on. A Ukrainian drone strike knocked out Yandex's data center in Vladimir early Sunday morning, the third of the company's facilities hit since October 8. The site — reported at roughly 50 MW and designed for about 2,880 server racks — stopped operating completely after the attack, Yandex

Agent teams cost up to 5x more, barely score higher

Agent teams cost up to 5x more, barely score higher

The multi-agent hype train hit a benchmark this weekend — and the grid and the trucking regulators had quiet weeks of their own. Vals AI put agent teams head-to-head with single agents on its Vibe Code Bench, and the teams cost between 1.8 and 5.1 times more for almost no extra quality. The evals company ran GPT-6 Sol and Claude Opus 5.5 solo and in teams across 50 apps at two reasoning efforts; out of four comparisons, only one was statistically significant — Sol at medium effort, where the t