💡 Google's quantum computing breakthrough

Also: Amazon unveils AI smart glasses for its delivery drivers

Author

Evolving AI
October 24, 2025

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Welcome, AI enthusiasts

Google scientists have created a new algorithm that can solve problems on a quantum processor 13,000 times faster than the world's fastest supercomputers. They say it brings us one step closer to using quantum computers in drug discovery, materials science and many other scientific applications. Let’s dive in!

In today’s insights:

  • Google’s new quantum algorithm might actually help discover new drugs

  • Amazon unveils AI smart glasses for its delivery drivers

  • OpenAI trains AI to take on junior banking tasks

Read time: 4 minutes

LATEST DEVELOPMENTS

Evolving AI: Google just introduced a quantum algorithm that could lead to real-world breakthroughs.

Key Points:

  • Google’s “quantum echoes” algorithm was 13,000x faster than classical methods in early tests.

  • Unlike older benchmarks, this new task has real-world use in molecular simulations.

  • It could support NMR spectroscopy, a tool widely used in chemistry and biology.

Details:

For years, quantum advantage claims rested on random tasks with no real application. But now, Google’s Quantum AI team says it’s developed an algorithm that might finally change that. It’s called “quantum echoes,” and while it hasn’t surpassed classical computers on practical tasks yet, it’s already shown major speedups when modeling small molecules. The algorithm works by simulating a molecule, tweaking one qubit, reversing the simulation, and then comparing the two results. This helps capture long-range effects in molecules, which is hard for conventional supercomputers to do. The method may improve tools like NMR spectroscopy, which is crucial for drug discovery and materials science. Google stresses it’s still early, but this is the first time they’ve demonstrated a verifiable quantum advantage using an algorithm that could actually be useful.

Why It Matters:

Google’s new algorithm might be the clearest sign yet that quantum computing could be useful in real science, not just tech demos. It’s fast, the results can be checked, and it could help with real problems like drug discovery or materials research. Instead of showing off with random benchmarks, this one targets practical tasks where quantum systems might soon outperform the best supercomputers. So instead of quantum computing proving only that it can beat classical machines, we’re now seeing it aim at problems people care about.

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Source: Amazon

Evolving AI: Amazon is testing AI-powered smart glasses to help delivery drivers work faster and more safely.

Key Points:

  • The glasses offer hands-free package scanning, directions, and delivery tracking.

  • They activate automatically when the driver parks and highlight tasks or hazards.

  • A companion vest contains a controller, battery, and emergency button.

Details:

Amazon is piloting a new pair of smart glasses for delivery drivers that use AI, computer vision, and built-in cameras to display turn-by-turn directions, package info, and nearby hazards. Drivers no longer need to juggle their phone while scanning packages or finding the right door. Once parked, the system kicks in to help locate items and guide the driver to the exact address, even in complex apartment buildings or office parks. The glasses also work with prescription lenses and adapt to lighting conditions. A wearable controller handles input and battery power. Real-time defect detection and pet alerts are planned for future versions.

Why It Matters:

Amazon’s goal is to squeeze more speed and precision out of every delivery, but what’s really new here is that wearables like this are actually being rolled out at scale, not just tested in labs. If it works, it could set a new standard for how AI blends into physical jobs. Or is this their way to collect more data to train delivery robots in the future, especially with their plan to replace 600,000 jobs with humanoid robots, as we reported on Wednesday?

Source: Getty Images

Evolving AI: Meta just cut 600 roles from its AI division to slim down teams and give new leadership more control.

Key Points:

  • Meta is laying off ~600 people from its AI teams.

  • Cuts follow a $14.3B investment in Scale AI and new hires.

  • Alexandr Wang and Nat Friedman now lead Meta’s AI push.

Details:

Meta is reducing its AI workforce by about 600 people across infrastructure and research units like FAIR. The layoffs were announced by Chief AI Officer Alexandr Wang, who joined earlier this year after Meta's major investment in Scale AI. The company is streamlining what insiders say had become a “bloated” AI division, clearing room for a new strategy under Wang and Nat Friedman. Teams within TBD Labs, where many of Meta’s top AI hires now work, were not affected. After the cuts, Meta’s Superintelligence Labs workforce now sits just under 3,000. This comes just days after Meta announced a $27B deal to build a huge AI data center in Louisiana.

Why It Matters:

Meta’s move to cut around 600 AI roles while ramping up a high‑profile team signals that the race in AI is less about headcount and more about building tight, elite teams that can move faster. If one of the biggest players is shifting strategy like this, it shows the industry is entering a phase where fewer but sharper hires drive the direction of AI, shaping how it’s built, scaled, and who gets to shape it.

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