Deep Learning Dot AI, a Neural Net Learns to Reason, and some company news
This week we check out what Andrew Ng is up to, share some personal news about Algorithmia, look at the pros and cons of Apple’s CoreML, and more! Plus what we’re reading and a few projects to try at home.
Deep Learning dot AI
Ng left his role as chief scientist of Baidu three months ago. At the time he said he was “looking into quite a few ideas in parallel, and exploring new AI businesses that I can build.”
The announcement includes only a name logo, a domain name, and a note about an August launch date.
But did you know… Deep learning is impacting everything from healthcare to transportation to manufacturing, and more. Companies are turning to deep learning to solve hard problems, like speech recognition, object recognition, and machine translation. Here’s a brief introduction to deep learning.
Some Company News
We’re excited to announce that Algorithmia has raised its Series A, led by Google’s new fund focused on AI and machine learning investments.
In just a few years, we’ve reached more than 45,000 developers with our library of 3,500 algorithms, functions and models. We also offer a private cloud algorithm-as-a-service solution, used by Fortune 1000 companies and federal government agencies.
“We were impressed with Algorithmia’s engineering capabilities and community promise,” Anna Patterson told TechCrunch, Google’s VP of engineering for AI and the head of the company’s new AI fund. “They’ve built a secure and scalable marketplace for AI models that allows developers to openly collaborate.”
What We’re Reading
- The Mars Robot Making Decisions on Its Own. Thanks to artificial intelligence software, the Curiosity rover can target rocks without human input. (The Atlantic)
- Learning to Reason with Neural Module Networks. Despite the remarkable success of deep learning methods in recent years, many problems — including few-shot learning and complex reasoning — remain a challenge. (Berkeley)
- The future is emotional. Human jobs in the future will be the ones that require emotional labour: currently undervalued and underpaid but invaluable. (Aeon)
- The Man Who Helped Turn Toronto Into a High-Tech Hotbed. Dictate a text on your smartphone, search for a photo on Google or, in the not too distant future, ride in a self-driving car, and you will be using technology based partly on Dr. Hinton’s ideas. (New York Times)
- The pros and cons of Apple’s CoreML. Apple’s impressive iOS machine learning technology teeters between its limits and its ease of adoption by developers. (InfoWorld)