Copy
Machine Learnings

Awesome, not awesome.

#Awesome
"At Wake Radiology in North Carolina, roughly 50 doctors scrutinize x-rays and other images for local medical providers. Within a few weeks, they should start to get help on some lung CT scans from machine-learning algorithms that highlight potentially cancerous tissue nodules...To create its algorithm to identify lung nodules, Infervision gathered more than 400,000 lung scans from Chinese partners, such as leading Beijing research center Peking Union Medical College Hospital... in a pilot at Shanghai Changzheng Hospital, two radiologists found that Infervision’s product could dramatically boost their ability to annotate lung nodules, the company says." - Tom Simonite, Writer Learn More from WIRED >

#Not Awesome
"AI’s superhuman ability to identify faces has led countries to deploy surveillance technology at a remarkable rate. Face recognition also lets you unlock your phone and automatically tags photos for you on social media. Civil liberties groups warn of a dystopian future. The technology is a formidable way to invade people’s privacy, and biases in training data make it likely to automate discrimination. In many countries—China especially—face recognition is being widely used for policing and government surveillance. Amazon is selling the technology to US immigration and law enforcement agencies.” - Will Knight and Karen Hao, Reporters Learn More from MIT Technology Review >

What we're reading.

1/ Job displacement caused by automation won't take the form of "a nuclear strike" that wipes out jobs in an instant - it will slowly reduce the time and visibility of employees - the way self check-in kiosks have reduced the need for certain airline employees. Learn More from The Atlantic >

2/ The economic gap between countries will continue to widen if poorer countries are unable to quickly retrain workers whose jobs are vulnerable to automation. Learn More from TIME >

3/ As China and the United States continue to integrate AI technologies into their weapons systems, the two countries must find new ways to cooperate to prevent confrontations from breaking out in the future. Learn More from Brookings Institution >

4/ Authoritarian regimes are using facial-recognition software to identify political opponents and crush free speech - and the technology is growing more accurate and widespread every day. Learn More from Carnegie Endowment >

5/ Since tech giants currently control the narrative on artificial intelligence, it would be wise to greet anything you read about the benefits of AI technologies with a healthy dose of skepticism. Learn More from The Guardian >

6/ DARPA is building a machine learning system that tries to create connections between pieces of media and online information in the hopes of eventually being able to prevent events, like violent coups, before they even happen. Learn More from TechCrunch >

7/ As industry giants continue to lure AI professors away from top universities, they could be setting the stage for "the potential collapse of academic AI research." Learn More from Bloomberg >

What we're building.

Meet Journal
We started Journal excited to answer a single question.

What would be possible if our information — about people, projects, and ideas — was connected and easily accessible?

In a year after closing our Seed funding round, we’ve started moving towards an answer. We are building a new kind of Journal. You write notes in it, save interesting links, and drop in important documents and messages for later. When you need something, ask Journal, and it will actually help you find it.

Journal integrates with the services where your information lives (like Slack, Gmail, Evernote, Pocket, and Dropbox) — so that you have one connected home for all your stuff. You can use the best services for messaging, documents, and more — and Journal will tie them all together so you stay in control.

For the past few years we’ve seen ourselves, friends, and colleagues stretched thin trying to manage many different silos of information. Journal is the new way forward. It’s a connected home to enhance the way we gather and share knowledge.

So far, beta community members have used Journal to launch new products, prepare for a new baby, remodel a home, write a book, teach a graduate course, plan a vacation, prepare for meetings, and much more.


On the surface, Journal looks and feels simple.

Beneath the surface, the Journal platform has two unique attributes that will enable more flexible and personalized product experiences than we’ve seen from existing knowledge management services:

  1. A state-of-the-art machine learning and natural language processing model that conceptually understands people’s digital information across formats
     
  2. An architecture and UX that understands and shows information as distinct types (e.g. files, tasks, articles, messages, products, and more)

Today, these attributes mean less friction for people interacting with their information in Journal. You organize links, emails, and other types of information without losing visual context, find anything easily across the apps you integrate, and see relevant items automatically grouped alongside your contacts and events. They are also the building blocks to make Journal the connected home for people to gather their thoughts, get organized, discover and share knowledge. We will use them to empower people to harness their information rather than to be burdened by it.

In the future, Journal will change depending on where you are and what you’re doing. When you check your phone from bed, it may look like a blank pad to dump thoughts. When you’re assigned a task at work it could become a list of suggested resources for you and your team. On the weekend, it may just show a map of nearby bakeries and long-form articles recommended by friends — it will help you do more with your information no matter the shape it takes.

We are so grateful to the nearly 2,000 beta users from our Machine Learnings and Noteworthy communities whose feedback has helped shape our product. In recent weeks we’ve observed an inflection point in deepening engagement, retention, and enthusiastic user feedback — So, starting tomorrow, we’re going to share Journal for Mac, our Web app, and our Chrome extension beyond our own communities. Our iOS app will follow in the coming weeks.

It’s been a hell of a challenge building Journal so far, and we have a lot of work ahead of us. We’ll only be able to make our vision for Journal a reality with the contributions of passionate, smart teammates and a supportive community. If you’re a distributed systems or machine learning engineer interested in building the future of knowledge management, please say hello. If you’d like early access to Journal, add your name to our waitlist >.

We would love for you to come a long for the ride.

Samiur Rahman
CEO, Co-founder
Journal

Links from the community.

"High-performance medicine: the convergence of human and artificial intelligence" submitted by Samiur Rahman (@samiur1204). Learn More from Nature >

"Meet Caper, The AI self-checkout shopping cart" submitted by Avi Eisenberger (@aeisenberger). Learn More from TechCrunch >

First time? Subscribe to Machine Learnings 🤖
13/01/19 View this email in your browser
Copyright © 2019 Machine Learnings, All rights reserved.


Done learning about AI?
Opt out of emails