Disappointingly, Brompton hasn’t given the T Line Electric any more speed for US-based riders, so I’m afraid you’re limited to the UK speed limit of 15.5 mph instead of the Class 1 pedal assist maximum of 20 mph.

I first came across the e-Motiq system in 2024, when I tested the larger 20-inch Brompton G Line. This powerful rear-mounted motor, which can hit 20 mph, offered a more stable ride compared to the front-mounted design, and being pushed definitely feels more natural than being pulled along. The redesign also keeps the weight at the rear, so the folding mechanism remains balanced.

There are three power-assist levels available here, plus Push Assist (more on that below), and the e-Motiq system also adjusts based on your own riding style. It monitors pedal force and cadence. How often you stop and start and over your first 62 miles on the bike tweaks how the power is used. This isn’t to eke out out extra mileage, but to make your ride smoother and more natural.

During testing, I barely noticed any changes as I racked up the miles, but I was seriously impressed by how normal the bike felt. Well, normal for a marginally wobbly upright design with tiny 16-inch wheels. Yes, there was a surge of power as I started to pedal, but the initial acceleration was controlled. It felt more like I’d supercharged my legs, rather than strapped a motor to my bike.

My test bike was single-speed, but there is also a four-speed option available. Riding around London, I did not need more than one gear as the motor just takes the effort out of any hills. Endless traffic also means it’s harder to exceed top speed for long, but when the road did open, I was impressed by how easily it was able to transition between assisting and backing off the power to stick to 15.5 mph. I can only speculate, but on America’s bigger roads, I think I’d want four gears. I’d also want a boost in the speed assist limit. It’s a shame Brompton only thought to include one of those things.

I also rode a few miles without the battery pack, and was pleasantly surprised. It weighs less than my old steel Brompton, and feels much nicer to carry, too. I hauled the Electric T Line e-Motiq up countless stairs, onto the London Underground, slung it in the trunk of a taxi at 2 AM, and only left it in a restaurant cloakroom once. It is light and small enough to just carry with you, and it’s also expensive enough that you’ll never lock it up and leave it on the street.

I’ve also been able to ride the nonelectric titanium Brompton T-Line, which at 17.64 pounds, was almost laughably light. If you don’t need electric power, it is the perfect commuter bike.

Control, Extras, and Competition

Photograph: Chris Haslam

It’s tiny, but the handlebar-mounted controller does some cool things. There’s a start-assist button, that if you press just before you set off at traffic lights, or hit a hill for instance, will give you a powerful push to get you started. It’s not a throttle—you need to be stationary though for it to kick in.

Many artificial intelligence startup ideas are still little more than superficial “wrappers” built on top of existing models. But as the AI model makers add more features, investors are wary of startups that could become so easily unnecessary.

Case in point: when reviewing more 4,000 applications for the joint AI accelerator for India startups run by Google and venture firm Accel, “wrapper” ideas dominated. But none of them were among the five startups for the latest cohort, Accel partner Prayank Swaroop told TechCrunch (pictured above).

Announced in November, the AI-focused Atoms program by Google and Accel aims to back early-stage startups building AI products linked to India. Startups selected for the latest cohort will receive up to $2 million in funding from Accel and Google’s AI Futures Fund, along with up to $350,000 in cloud and AI compute credits from Google, the firms said.

Roughly 70% of the rejected applications were “wrappers” — startups that layered AI features such as chatbots on top of existing software but “were not reimagining new workflows using AI,” Swaroop said.

Many of the remaining applications that were denied, Swaroop said, fell into crowded categories such as marketing automation and AI recruitment tools, areas where investors saw little novelty. Startups in those sectors often struggle to differentiate themselves, he said.

This isn’t, perhaps, surprising. This year’s program received nearly four times the applications than previous Accel’s Atoms cohorts — with many first-time founders.

India’s growing AI ecosystem remains largely focused on enterprise applications and Swaroop said the applications reflected that. About 62% of the submissions focused on productivity tools and another 13% on software development and coding, meaning around three-quarters of the applications were enterprise software ideas rather than consumer products. (Swaroop had hoped to see more ideas for healthcare and education.)

Jonathan Silber, co-founder and director of Google’s AI Futures Fund, said the five startups selected aligned closely with areas where Google expects AI to see deeper real-world adoption.

The program does not require startups to use Google’s models exclusively, Silber said, noting that many companies combine multiple models depending on the workflow. The goal, he said, is to gather feedback from startups on how Google’s models perform in real-world applications.

Insights from those startups can then be fed back to Google DeepMind teams to help improve future models, creating what Silber described as a “flywheel” between startup experimentation and AI development. “If a company is using an alternative model, that means Google has work to do to build the best model in the market,” he told TechCrunch.

This year’s startups selected are:

• K-Dense, which is building an AI “co-scientist” to accelerate research in fields such as life sciences and chemistry;
• Dodge.ai, which develops autonomous agents for enterprise ERP systems;
• Persistence Labs, which focuses on voice AI for call centre operations;
• Zingroll, which is building a platform for AI-generated films and shows;
• Level Plane, which applies AI to industrial automation in automotive and aerospace manufacturing.