Nuro

Liquid AI

Nuro

For most of its life Nuro sold delivery-as-a-service. Retailers, restaurants and grocery chains paid Nuro to handle the last mile with autonomous vehicles, so instead of employing human drivers a partner simply used Nuro's robot fleet.

The economics are compelling on paper. A human delivery driver costs $15-25 per hour including wages, insurance, and vehicle costs.

A Nuro vehicle costs money to build and maintain, but once deployed, it operates nearly 24/7 with no driver wages, no tips, and no breaks. The breakeven point comes when the fleet reaches sufficient utilization in a market.

That was the plan, anyway. In 2024 Nuro changed course and stopped trying to run a delivery service itself.

The business now is licensing the autonomy stack — the Nuro Driver — to carmakers and mobility companies, which is a far cheaper way to grow than building and operating your own fleet. FedEx, Domino's, Kroger, Walmart and 7-Eleven had all tested or deployed the delivery bots before the pivot.

Liquid AI

Liquid AI builds foundation models, the big general-purpose brains that power chatbots and other AI tools. The difference is efficiency.

Their models, called Liquid Foundation Models, are designed to do more with far less memory and computing power. Companies pay to use them, either through a cloud API or by running the models on their own machines.

That second option matters. A bank or a hospital often cannot send private data to someone else's server.

Liquid AI lets them keep the model in-house. The pitch to a customer is basically this.

You get strong AI without renting a mountain of expensive chips.

Nuro

Dave Ferguson and Jiajun Zhu were both principal engineers at Google's self-driving car project (later Waymo). Ferguson led the machine learning and motion planning teams.

Zhu worked on perception — teaching cars to see and understand the world. They were two of the most senior engineers in autonomous driving.

In 2016, they left Google with a contrarian insight: the hardest part of self-driving cars wasn't the technology. It was the stakes.

A robo-taxi carrying passengers needs to be essentially perfect — any accident could injure or kill someone inside and destroy public trust. But a delivery vehicle carrying groceries?

If it gets in a fender bender, the worst case is squished bananas.

By removing the human from the vehicle, Nuro eliminated the most complex variable in autonomous driving safety. Their vehicles are small, light (under 1,200 pounds), and slow (max 25 mph on surface streets).

If one hits a pedestrian, the impact energy is dramatically lower than a 4,000-pound car going 40 mph. This let them get regulatory approval years before full-size robo-taxis.

The first prototype, R1, looked like a cartoon car — about half the width of a normal vehicle, with no windows, no mirrors, and no driver's seat. Just cargo space and sensors.

They revealed it in 2018 and began testing in Scottsdale, Arizona with Kroger for grocery deliveries.

Liquid AI

Liquid AI is a spinout from MIT's Computer Science and Artificial Intelligence Laboratory, better known as CSAIL. The core science came from Ramin Hasani, who spent his PhD studying the nervous system of a tiny worm called C.

elegans. That worm has just 302 neurons and still manages to move, hunt, and react to its world.

Hasani and his collaborators asked a simple question. What if you built an AI that worked more like those neurons and less like a giant static network?

The answer was the liquid neural network, a model whose internal wiring keeps adjusting even after training is done. The team incorporated the company in 2023.

Daniela Rus, who runs CSAIL and is one of the most respected robotics researchers alive, came on as a co-founder. So did Mathias Lechner and Alexander Amini, both longtime research partners of Hasani.

Nuro

Nuro's strategy is to become the default autonomous delivery infrastructure for major retailers. Rather than build a consumer-facing delivery app (competing with DoorDash and Instacart), Nuro provides the robotic fleet that powers deliveries for existing brands.

The partnership-first approach reduces go-to-market friction. Kroger, Walmart, and FedEx already have massive customer bases and order volumes.

Nuro provides the autonomous last-mile delivery layer. The retailer gets lower delivery costs.

Nuro gets guaranteed demand.

That was the original plan. Houston and Mountain View were the early markets, mapped city by city, each one needing its own regulatory approval before a single vehicle moved.

It was slow and it was expensive, and in 2024 Nuro gave it up in favour of licensing its self-driving software to companies that already build and operate vehicles.

Liquid AI

The growth angle is size, or the lack of it. Most frontier models are so heavy they only run in data centers.

Liquid AI aims for models light enough to run on a phone, a car, or a factory robot. That opens doors the giants cannot easily reach.

The AMD partnership pushes the same idea. AMD makes chips, and it wants efficient models that show off its hardware.

So AMD led the Series A and became both an investor and a distribution partner. Liquid AI also releases open models to researchers, which builds a following before the sales team ever makes a call.

Nuro

The technology still has limitations in complex scenarios. Nuro vehicles operate on surface streets at low speeds — they can't handle highways, heavy snow, or extremely dense urban environments like Manhattan.

This limits the addressable market to suburban deliveries in good weather, which is a large market but not the whole market.

The path to profitability is long. Building custom autonomous vehicles is extraordinarily capital-intensive.

Each generation of vehicle requires hundreds of millions in design, engineering, testing, and manufacturing. Nuro has burned through most of its $2.1 billion in funding and laid off 30% of staff in 2023, signaling the cash crunch is real.

Competition comes from multiple directions. Amazon is developing its own delivery robots (Scout, though paused).

Waymo could pivot to autonomous delivery, though Cruise is no longer a threat after GM shut it down at the end of 2024. Established delivery companies could partner with other autonomy providers.

And human drivers remain cheaper than robots at current scale — the economics only flip once Nuro has hundreds or thousands of vehicles per market.

Liquid AI

The honest problem is Goliath. OpenAI, Google, Anthropic, and Meta have raised tens of billions of dollars between them.

Liquid AI has raised under $300 million. The transformer architecture those giants use is battle-tested and improving fast.

Liquid AI has to prove its different approach not only works but keeps working as models get bigger. Betting against the most successful design in AI history is bold.

It is also the kind of bet that ends in either a great acquisition or a quiet shutdown, with not much room in between.

Nuro

Nuro R3 — the third-generation autonomous delivery vehicle, purpose-built with no passenger compartment. Larger cargo capacity than R2, improved sensor suite, and designed for commercial-scale manufacturing.

Nuro Autonomy Platform — the self-driving software stack including perception, prediction, planning, and control that runs Nuro's vehicles. Nuro Driver — the AI system that handles all driving decisions in real-time, combining lidar, cameras, radar, and thermal sensors.

Nuro Fleet Management — cloud-based tools for partners to monitor, dispatch, and manage Nuro vehicles across delivery zones.

Liquid AI

The main products are the Liquid Foundation Models, a family that ships in several sizes so a customer can pick the smallest one that does the job. The second generation, LFM2, arrived in 2025, including LFM2-VL vision-language models built for phones, laptops, wearables and embedded chips.

The company has leaned hard into on-device AI rather than the cloud. The focus is always the same.

Match the quality of a much larger model while using a fraction of the memory and power.

Nuro

SoftBank Vision Fund led the massive $940 million Series B in 2019. Tiger Global led the Series C at an $8.6 billion valuation.

Greylock Partners and Gaorong Capital were early investors. Alphabet (Google's parent) invested through its venture arm.

Woven Capital (Toyota's investment fund) participated, reflecting automotive industry interest. The company has raised approximately $2.1 billion total.

Liquid AI

It started with a $37.5 million two-stage seed in December 2023 at a $303 million valuation, from OSS Capital, PagsGroup, Automattic (the company behind WordPress), Samsung Next and others. Angels included GitHub co-founder Tom Preston-Werner, Shopify's Tobi Lütke and Red Hat co-founder Bob Young.

Then AMD Ventures led the $250 million Series A in December 2024, which is unusual because AMD is a chipmaker, not a typical venture fund. That backing gave Liquid AI both money and a hardware ally.

When a major chip company writes the lead check on an efficiency-focused model maker, it signals a bet that the future of AI is not just bigger, it is leaner.