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- Earth-2 and lab robots: NVIDIA’s next wedge
Earth-2 and lab robots: NVIDIA’s next wedge
Plus: Apple may let rival AI bots into CarPlay
Rimsha Bhardwaj, Hasan Toor & Ihtesham Haider
February 07, 2026
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Today, we will talk about these stories:
NVIDIA is pushing AI into wet labs and weather
CarPlay opens up as drivers ask for more AI
Vertex AI’s routing trick: cache-aware inference on GKE
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NVIDIA wants to sit inside experiments and forecasts
Wet labs are slow. NVIDIA partnered with Opentrons to apply AI to laboratory robotics, aiming to speed up experiment execution and drug discovery workflows. It also launched Earth-2, an open source AI weather forecasting platform for climate, energy, and risk management use cases.
This is NVIDIA trying to turn “AI infrastructure” into “default tooling,” so the lab or utility ends up buying the full stack, not just chips. The detail that matters is scale: Opentrons says more than 10,000 lab robots are already in use, which gives NVIDIA a real distribution channel.
If Earth-2 gets picked up by utilities and insurers, NVIDIA gets a seat in budgeting cycles that run for years and reward vendor lock-in. Investors will still care whether these platforms drive incremental revenue beyond the core GPU story as the stock sits around $185.41.
Will labs and energy teams trust one vendor to run the workflow end to end?
Apple loosens its grip on CarPlay AI
Image Credits: Apple
Apple is finally giving up some control in the car.
Bloomberg reported on February 6, 2026 that Apple plans to let other companies’ voice-controlled AI chatbots run inside CarPlay, citing unnamed sources. The change is framed as a response to driver demand for more choice in how they talk to their car’s interface.
This feels like Apple recognizing that “voice” is turning into a platform layer, and CarPlay can’t stay credible if it only routes everything through Apple’s own assistant. If third-party bots can actually handle messages, navigation queries, and car tasks smoothly, Apple gets to keep CarPlay central while offloading the race for the best conversational model.
Expect a messy first year. In a bright dashboard glow at night, users will notice latency, wrong actions, and privacy prompts fast, and automakers will pressure Apple for tighter controls.
If rival bots thrive in CarPlay, what’s left of Siri’s role in the car?
Vertex AI is routing for cache, not fairness
Image Credits: Apple Cloud
Google is treating inference routing like a performance feature. In a February 7, 2026 post, Google says Vertex AI moved production inference behind a “GKE Inference Gateway” built on the Kubernetes Gateway API. The gateway uses load-aware routing from Prometheus metrics (including KV cache utilization) and content-aware routing that steers requests to pods that already hold the prompt prefix in cache.
The big point is they’re admitting round-robin is the wrong mental model once KV cache becomes the scarce resource. I also like that they publish an actual tuning knob: they changed prefix:queue:kv-utilization scoring from 3:3:2 to 3:5:2, basically choosing fewer “perfect cache hits” if it avoids a hot node.
They claim 35% TTFT improvement on Qwen3-Coder, 52% better TTFT P95 on Deepseek V3.1, and cache hit rate jumping from 35% to 70%. If this holds outside Google’s setup, a lot of “we built our own scheduler” teams will look silly under fluorescent office light at 2 a.m.
If routing becomes this model-specific, how portable is your inference stack really?
Prohuman team
Covers emerging technology, AI models, and the people building the next layer of the internet. |  Founder |
Writes about how new interfaces, reasoning models, and automation are reshaping human work. |  Founder |
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