Algorithmia

Emergent // Future – Building Robot Factories, Cars Driving Cars, and More!

Issue 45
This week we check out Y Combinator’s new track for companies
applying AI to factories, take a deep dive into the lasted autonomous car news from Nvidia and Uber, and relay our favorite reads from the week. 

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Building Robot Factories

Y Combinator will offer its first track for AI startups building “robot factories.”

The thinking goes that even for factories outfitted with state of the art robotics, a lot of the work revolves around setting up and fixing robots. When things break, nobody knows what to do.

YC AI companies will get access to machine learning experts to help overcome technical problems and cloud compute credits for GPU instances.

“We can’t afford to ignore what might be the biggest technological leap since the Internet,” YC partner Daniel Gross said.


Cars Driving Cars

Nvidia partners with trucking giant PACCAR to create a proof-of-concept, level 4 autonomous truck. They’ll be using the Nvidia’s Drive PX 2 platform with neural network training fed by data of humans driving semis-tractors.

Level 4 autonomous vehicles are considered “fully autonomous,” but are limited to the scope of driving scenario – long-haul trucking in this instance.

Uber’s 43 self-driving cars crossed 20,000 mile last week. The cars drove an average of .8 miles before the human driver had to take over for one reason or another.The good news is the number of miles between these “critical” interventions has improved to approximately 200 miles between incidents.

Self-driving cars have a spinning-laser problem. Lidar sensors are considered essential for building self-driving cars and pretty much everybody but Tesla is using them. But they’re bulky. And expensive. Just look at how ridiculous this thing is. Experts say that the sensors need improvements to better map a vehicle’s environment in 3-D.


What We’re Reading 📚

  • The Mobile Internet Is Over. Baidu Goes All In on AI. The Chinese company has more than 1,300 people working on tech like deep learning.(Bloomberg) 
  • The body is the missing link for truly intelligent machines. In ways that we’re only just beginning to understand, our body and brain, from the cellular level upwards, have already built a model of the world that we can apply almost instantly to a wide array of challenges. (Aeon)
  • Appreciating Art with Algorithms. Let’s use a deep neural network to extract the style of an artist’s painting and then apply those features to an arbitrary photo. (Hacker Noon)
  • How DeepMind’s Memory Trick Helps AI Learn Faster. While AI systems can match many human capabilities, they take 10 times longer to learn. Now, by copying the way the brain works, Google DeepMind has built a machine that is closing the gap. (MIT Technology Review)

Things To Try At Home 🛠


Emergent // Future is a weekly, hand-curated dispatch exploring technology through the lens of artificial intelligence, data science, and the shape of things to come. 

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Lovingly curated for you by Algorithmia

Product manager at Algorithmia helping to give developers super powers.

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