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AI startups continue to roared ahead, global pandemic or no. Tech industry analyst CB Insights published its fifth annual list of the 100 most promising private AI companies.
AI startups continue to roared ahead, global pandemic or no. Tech industry analyst CB Insights published its fifth annual list of the 100 most promising private AI companies.
A new breed of self-driving car could kick the autonomous-vehicle industry into a higher gear. Zoox unveiled its first product, an all-electric, driverless taxi designed fully in-house.
A new breed of self-driving car could kick the autonomous-vehicle industry into a higher gear. Zoox unveiled its first product, an all-electric, driverless taxi designed fully in-house.
The pandemic has forced self-driving car companies off the road. Now they’re moving forward by refining their mountains of training data. Self-driving cars typically collect real-world training data with two human operators onboard, but Covid-19 makes that unsafe at any speed.
The pandemic has forced self-driving car companies off the road. Now they’re moving forward by refining their mountains of training data. Self-driving cars typically collect real-world training data with two human operators onboard, but Covid-19 makes that unsafe at any speed.
Many of this year’s hottest AI companies are taking the spotlight from last year’s darlings.What’s new: CB Insights, which analyzes early-stage companies, published its annual list of the 100 “most promising” startups in AI.
Many of this year’s hottest AI companies are taking the spotlight from last year’s darlings.What’s new: CB Insights, which analyzes early-stage companies, published its annual list of the 100 “most promising” startups in AI.
The future of machine learning may depend less on amassing ground-truth data than simulating the environment in which a model will operate. Deep learning works like magic with enough high-quality data. When examples are scarce, though, researchers are using simulation to fill the gap.
The future of machine learning may depend less on amassing ground-truth data than simulating the environment in which a model will operate. Deep learning works like magic with enough high-quality data. When examples are scarce, though, researchers are using simulation to fill the gap.
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