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Apple Pivots Car Project, Seymour Papert Has Died, AI for Office Apps, and Machine Learning in Science

Apple Pivots Car Project, Seymour Papert Has Died, AI for Office Apps, and Machine Learning in ScienceIssue 18
This week we look at
Apple’s autonomous car project, reflect on the passing of AI pioneer Seymour Papert, check out the AI updates to Microsoft Office apps, and review some uses of machine learning in sciencePlus, projects to try at home, and our top reads from the past week. 

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Apple Pivots Autonomous Car Project  🚗

You might have heard: Apple is shifting the focus of their car projectfrom building a self-driving, electric car to developing an autonomous driving system.

The news comes after Apple tapped Bob Mansfield to oversee car project, dubbed Project Titan.

Apple isn’t giving up on a car, however, but the company is now diving into the software that could power the next generation of carswith a focus on the user experience.

“We have focused our AI efforts on the features that best enhance the customer experience,” Tim Cook explained. “A killer user experience that is integrated across their lives I think becomes more important, and I think that really plays to our advantage. I also think that the deployment of AI technology is something that we will excel at because of our focus on user experience, and so I like that.”

But did you know: Tesla is buying SolarCity for $2.6 billion.

A major part of Tesla CEO Elon Musk’s master plan involves developing solutions to generate, store, and enable mass consumption of solar energy.

Tesla is also racing to finish the “Gigafactory” before the Model 3 rollout in 2018. Musk anticipates that the plant could produce 105 gigawatt hours of battery cells by 2020.

PLUS: Delphi hopes to make self-driving taxis a reality in Singapore by 2022. Delphi was the first car company to complete a cross-country road trip using autonomous technology, driving from San Francisco to New York back in April 2015.


Seymour Papert Has Died ☹️

Professor Emeritus Seymour Papert, a pioneer of constructionist learning, is dead at 88.

The world-renowned mathematician, learning theorist, and educational-technology visionary was a founding faculty member of the MIT Media Lab.

Well before the advent of the personal computer, Papert foresaw children using computers as instruments for learning and enhancing creativity. Papert’s “constructionist” theory of education held that kids learn best by building things and making things happen.

Papert was the co-author of the now-classic work on artificial intelligence: “Perceptrons: An Introduction to Computational Geometry. The perceptron was one of the first artificial neural networks to be created. The algorithm uses pattern recognition based on a two-layer computer learning network.


AI for Microsoft Office Apps 📝

Microsoft Word, Outlook, and PowerPoint are getting intelligent updates to help improve productivity and performance.

With the addition of machine learning and natural language processing, Microsoft believes the updates to Office 365 apps will “save you time and produce better results.”

Microsoft is adding a new Researcher feature to Word, which uses the Bing Knowledge Graph to find content from the internet and pull it straight into Word.


Notables: Machine Learning + Science 💡

  • 23andMe looked at the DNA of more than 450,000 customers and has uncovered the first major trove of genetic clues to the cause of depression. The study, the largest of its kind, detected 15 regions of the human genome linked to a higher risk of depression.
  • Scientists have completed the most detailed map of the brain ever. To help automate the process, they developed a machine learning algorithm to learn the “fingerprint” of each cortical area — that is, the specific setting of each parameter used to generate the map.
  • Using machine learning to predict Autism. Researchers estimate there are hundreds of Autism-linked genes, but only a fraction have actually been identified with strong experimental evidence. A study published in Nature aims to change this by using a big data and machine learning to make a genome-wide prediction of Autism spectrum disorder genes.

What We’re Reading 📚

  • Why Uber Engineering Switched from Postgres to MySQL. The early architecture of Uber consisted of a monolithic backend application written in Python that used Postgres for data persistence. Since that time, the architecture of Uber has changed significantly, to a model of microservices and new data platforms. (Uber)
  • How Magic Leap Works – From Field of View to GPU. Magic Leap has not been forthcoming with details about how their technology works.  From what little we know, it is a truly novel system with capabilities far beyond the off the shelf components consumers are accustomed to. So what is it and how does it work? (GPU of the Brain)
  • Artificial Intelligence resources. This is the list of the best resources to learn the foundations of Artificial Intelligence and Deep Learning. It will be the most useful for beginners, people who want to get into this field, but don’t know where to start. (Digital Mind)
  • Cortana awakens: The evolution of Microsoft’s smart assistant. It’s fun to imagine all the other names Microsoft’s voice assistant, Cortana, could have had: “Bill,” “Explorer,” “Pathfinder.” None of these were considered, as far as we know, but Cortana Group Product Manager Marcus Ash did tell me recently, “Early on we thought about some names that are more generic. I won’t share any specific names, but think of a typical Microsoft name circa 1998 and you get the idea.” (Mashable)

Try This At Home 🛠


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