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Machine Learnings

Awesome, not awesome.

#Awesome
"In the not-so-distant future, machine learning may help civil-rights agencies predict who could face workplace discrimination. Hypothetically, this could mean the agency would be able to flag a particular group of people in a specific industry who would be susceptible to discrimination. The agency would then be able to target outreach to those workers to make them aware of their rights, he said.” - Paige Smith, Reporter Learn More from Bloomberg Law >

#Not Awesome
"...[S]uppose that, during the AI-training phase, an adversary slipped a few extra images (Trojan horses) into your speed-limit-sign detector, ones showing stop signs with sticky notes on them. Now, if the adversary wants to trick your AI in the real world into thinking a stop sign is a speed-limit sign, it just has to put a sticky note on it. Imagine this in the world of autonomous cars; it could be a nightmare scenario.” - Dave Gershgorn, AI Reporter Learn More from Quartz >

What we're reading.

1/ In 2018, we saw the biggest AI advances in the fields of image detection, translation, and sentence parsing. In 2019, we'll see the largest tech companies using these advances to grow (and fix) their platforms. Learn More from Bloomberg >

2/ Expect economic forecasting to get a lot more accurate as economists combine satellite imagery and machine learning to answer questions that they couldn't in the past - like "how many of those Brazilian favela dwellings have new roofs?" Learn More from WIRED >

3/ Tensions will persist between humans and algorithms since algorithms can show us answers to complex problems, but cannot explaining the steps that got them there. Learn More from The New York Times >

4/ Military strategists think the destructive capabilities of AI technologies could surpass that of nuclear weapons in the coming century. Learn More from Small Wars Journal >

5/ A startup uses AI to map out the number of trees in US cities, a dataset that can be useful to address  problems caused by climate change. Learn More from CityLab >

6/ As the tools to make smart investment decisions become more democratized, hedge fund managers will continue to make huge investments in machine learning to carve out an edge against more passive investment strategies. Learn More from Bloomberg >

7/ Researchers are getting closer to creating "synthetic 3D sounds" that can fool our hearing systems into thinking that we're experiencing sounds that we aren't. Learn More from MIT Technology Review >

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.

"Lenia - Biology of Artificial Life" submitted by Samiur Rahman (@samiur1204). Learn More from arXiv >

"The Hedge Fund King and a Technological Arms Race" submitted by Avi Eisenberger (@aeisenberger). Learn More from Bloomberg >

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