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Uber Eats to replace search with a shopping agent

Plus: China’s AI race is shifting from models to markets.

Today we will see, Zhipu and MiniMax just lit up China’s AI market with new releases. Also, Uber Eats, meanwhile, is turning grocery lists into carts with AI. And WeRide says AI cut training and testing costs by 75%. Three stories, one signal: AI is leaving the lab for the ledger. The winners won’t be “smartest,” but most embedded in daily workflows.

In today’s post:

  • Uber’s new AI shopper is the real grocery land grab

  • WeRide’s quiet 75% cost cut changes robotaxi math

  • China’s AI sprint just shifted up a gear

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BREAKTHROUGH

Grocery delivery just became an agent problem, not a search problem

Image Credits: Uber Eats

Uber Eats is rolling out an AI cart assistant for groceries. It turns lists and photos into a ready-to-checkout cart.

  • Cart Assistant builds a cart from text prompts or images.

  • It can read handwritten lists and recipe screenshots.

  • It works across grocers like Albertsons, Kroger, and Safeway.

  • It adapts to preferences and real store availability.

  • Uber already uses AI for menus and review summaries.

  • This directly pressures Instacart, DoorDash, and Amazon-like flows.

  • Delivery momentum gives Uber room to ship these bets fast.

This isn’t about “cool AI.” It’s about removing the hardest step in grocery: translating intention into a cart. That translation is where shoppers stall, bounce, or forget items. If Uber nails this, the app stops being a marketplace and starts acting like a clerk. And once people trust the clerk, they stop price-checking every aisle.

ROBOTS

Robotaxis won’t win on hype. They’ll win on unit economics

Image Credits: Bloomberg

WeRide says it’s cutting robotaxi costs with AI. Its CEO wants to at least double the fleet this year. The big lever is cheaper data collection and training. An in-house AI testing platform drove a 75% reduction. And the company targets profitability by 2030.

  • WeRide says simulation can replace costly real-world miles.

  • Less data means faster iteration on safety edge cases.

  • Doubling fleet size tests whether savings survive real operations.

  • China’s robotaxi leaders are already crossing the 1,000-vehicle milestone.

  • WeRide and Uber plan 1,200 robotaxis across the Middle East.

  • Uber is also rolling out autonomous rides with Baidu in Dubai.

  • Partnerships are becoming the distribution layer for robotaxi scale.

Cost curves decide autonomy’s timeline. Not demos. Not glossy videos. Testing platforms are the hidden moat. They turn “more miles” into “more learning.” If WeRide truly cut training costs 75%, that compounds. Fleet growth then becomes a flywheel. The question is simple. Do the savings hold at scale?

STRATEGY

China’s AI race is moving from models to markets

Zhipu and MiniMax just sparked a sharp rally in Chinese AI stocks. New releases, plus policy pressure, are turning AI into a deployment race.

  • Zhipu surged after open-sourcing GLM-5, built for agents.

  • GLM-5 is pitched as near-Opus on coding benchmarks.

  • MiniMax shipped M2.5, aiming at “agentic” developer workflows.

  • Ant open-sourced Ming-Flash-Omni 2.0 for multimodal generation.

  • ByteDance’s Seedance 2.0 pushed a rally in AI-app names.

  • Li Qiang called for scaled, commercial AI adoption nationwide.

  • Zhipu even hiked coding-plan prices as demand spiked.

Open-source is becoming the fastest path to trust. Not because it’s “free,” but because it spreads. Once developers build habits, budgets follow. The real competition isn’t model quality. It’s who becomes the default toolchain first.

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