What should you do next?

I gave a talk last night at MTLDATA about using Fuzzy.ai for task prioritization. It’s a really interesting subject for me, because tasks are an atomic part of our life and our work. How and when we complete tasks is an important part of any person’s productivity, and artificial intelligence that helps us do that effectively is really valuable.

Most of us use a task management system — whether it’s part of a project management system like Github issues or JIRA, or a personal system like Todoist, todo.txt or Google Tasks. All of them have ways to define important data about our tasks, but very few of them make intelligent recommendations for what to do now.

Intelligent organizations are starting to work on this problem today. After all, having people inside your company work on tasks that are timely, impactful, actionable and personal can make a huge difference. Tying the performance of tasks to metrics within the organization can drive much better relevance tracking.

To test out these ideas, we built a cool task prioritization project using the Todoist API. If you log into the site at https://tasks.fuzzy.ai/ with Todoist authorization, it will automatically score and rank your upcoming tasks, putting the most relevant items first.

Todoist has a relatively simple schema for tasks. We used that data for building a fuzzy.ai agent that uses time, priority, and other features to determine the task’s relevancy.

We think there’s some interesting future developments here. Keyword matching with previously relevant tasks is a big one. Providing other backends, like Github issues, is another. (I use Todo.txt, so I’m especially interested in this.) Most of all, building in different kinds of performance metrics to see if your tasks really matter is going to be the biggest.

Our code is open source. Feel free to fork and try on your own, or send pull requests. We’re always interested in what people figure out to do with Fuzzy.ai.

 

Security issues in Fuzzy.ai developer environment fixed

We had three security issues in our developer environment reported by security researcher Ron Masas recently, which we’ve identified and repaired. Thanks to Ron for his help in identifying these issues and in suggesting some ways to correct them. (And special thanks to our lead developer James Walker for getting them fixed so fast.)

The first pair of issues was a path that allowed saving an unsanitized email address to our user database. Combined with a way to share a user session across users, it allowed a cross-site scripting attack.

The third issue was a cross-site scripting attack caused by the way we were pulling data into our default React session. Carefully restructuring the request would cause a user’s browser to send their important session data to a third party. We repaired this bug by restructuring how the default session data is injected.

We don’t know of any abuses of these bugs in the wild.

We think it’s important to be transparent about security issues. We especially want to encourage security researchers to share their findings with us and other application developers. Thanks again to Ron for the great work.

We are Montreal AI

One of the great outcomes of the AIFest event in Montréal last weekend was an increased sense of unity among the different parts of the AI ecosystem here. We are all working together to make AI a new industry in this city. 

To that end, we have created an open letter to the applicants for the AI Supercluster program in Montréal. This is a federal program to invest in AI. We want to work with government, industry and academia to make the ecosystem a success. 

The letter is at wearemtlai.org. Fuzzy.ai’s co-founders have signed as well as dozens of leaders in the community. We encourage participants big and small to make their voices heard. We can only do this if we work together. 

Fuzzy.ai Sponsoring AIFest 2017

We’re excited to be a sponsor of the inaugural AIFest, as part of Montreal Startupfest.

MONTRÉAL-JULY-12-2017-8

The event is happening this Saturday July 15, and is presented by MTLDATA in partnership with Fuzzy.aiElement AI, TandemLaunch, Nexalogy, Maluuba, Keatext and Mnubo.

AIFest will gather a group of 200 people interested in exploring and tackling the tough problems in Artificial Intelligence and overlapping domains.

AIFest is an unconference, in the spirit of BarCamp. It will be a participant-driven meeting. The attendees will suggest topics to define the event’s agenda. Anyone who wants to initiate a discussion on any topic related to AI can claim the time and space.

We can’t wait to participate in the event and hope to see you there!

For more information, visit the AIFest site.

Security issue in Fuzzy.ai API fixed

We’ve identified and corrected a content spoofing issue in the API server for Fuzzy.ai. Thanks to Nessim Jerbi for identifying and reporting this security bug, as well as recommending a fix.

Our 404 handler on the API server would echo the erroneous path in its error message. An attacker could craft a path that would inject text into the error message for other users, giving the impression that it was an official message from Fuzzy.ai.

We’re not aware of any abuse of this bug having occurred. The bug has been patched on our servers and does not require any updates to client software or SDKs.