Native Instruments' Traktor DJ 2 breaks free from the iPad

Engadget

Last fall, Native Instruments gave its DJ and production hardware a significant refresh, especially at the entry level. Today, the company is introducing a second wave of tools to complement the new line up, along with even more new hardware. First up is the news that Traktor DJ (the iOS version of its flagship Traktor software) is getting an overhaul. Traktor DJ 2 doesn't just come with new features -- like the ability to mix tracks from Soundcloud Go as hinted at recently -- it'll also be available as a desktop app for the first time. This means you'll be able to, er, mix things up with either a laptop or iPad at the heart of your performance.


Decision-Theoretic Control of Crowd-Sourced Workflows

AAAI Conferences

Crowd-sourcing is a recent framework in which human intelligence tasks are outsourced to a crowd of unknown people ("workers") as an open call (e.g., on Amazon's Mechanical Turk). Crowd-sourcing has become immensely popular with hoards of employers ("requesters"), who use it to solve a wide variety of jobs, such as dictation transcription, content screening, etc. In order to achieve quality results, requesters often subdivide a large task into a chain of bite-sized subtasks that are combined into a complex, iterative workflow in which workers check and improve each other's results. This paper raises an exciting question for AI — could an autonomous agent control these workflows without human intervention, yielding better results than today's state of the art, a fixed control program? We describe a planner, TurKontrol, that formulates workflow control as a decision-theoretic optimization problem, trading off the implicit quality of a solution artifact against the cost for workers to achieve it. We lay the mathematical framework to govern the various decisions at each point in a popular class of workflows. Based on our analysis we implement the workflow control algorithm and present experiments demonstrating that TurKontrol obtains much higher utilities than popular fixed policies.


Dai

AAAI Conferences

Crowd-sourcing is a recent framework in which human intelligence tasks are outsourced to a crowd of unknown people ("workers") as an open call (e.g., on Amazon's Mechanical Turk). Crowd-sourcing has become immensely popular with hoards of employers ("requesters"), who use it to solve a wide variety of jobs, such as dictation transcription, content screening, etc. In order to achieve quality results, requesters often subdivide a large task into a chain of bite-sized subtasks that are combined into a complex, iterative workflow in which workers check and improve each other's results. This paper raises an exciting question for AI -- could an autonomous agent control these workflows without human intervention, yielding better results than today's state of the art, a fixed control program? We describe a planner, TurKontrol, that formulates workflow control as a decision-theoretic optimization problem, trading off the implicit quality of a solution artifact against the cost for workers to achieve it. We lay the mathematical framework to govern the various decisions at each point in a popular class of workflows. Based on our analysis we implement the workflow control algorithm and present experiments demonstrating that TurKontrol obtains much higher utilities than popular fixed policies.


Dai

AAAI Conferences

Crowdsourcing platforms such as Amazon Mechanical Turk have become popular for a wide variety of human intelligence tasks; however, quality control continues to be a significant challenge. Recently, we propose TurKontrol, a theoretical model based on POMDPs to optimize iterative, crowd-sourced workflows. However, they neither describe how to learn the model parameters, nor show its effectiveness in a real crowd-sourced setting. Learning is challenging due to the scale of the model and noisy data: there are hundreds of thousands of workers with high-variance abilities. This paper presents an end-to-end system that first learns TurKontrol's POMDP parameters from real Mechanical Turk data, and then applies the model to dynamically optimize live tasks. We validate the model and use it to control a successive-improvement process on Mechanical Turk. By modeling worker accuracy and voting patterns, our system produces significantly superior artifacts compared to those generated through nonadaptive workflows using the same amount of money.


How To Play Fortnite Like A Pro With These Accessories

Forbes - Tech

Fortnite has become a global gaming phenomenon. The game, which puts players into a battle royale where they battle to the death to see who can reign supreme, has killed productivity at offices, caused kids to miss big exams, and generally changed the landscape of gaming. Microsoft's Xbox Elite Wireless Controller is a must-have for any serious gamer. Each day, millions of people around the globe are either playing Fortnite or thinking about the next time they can play. And when they do, they're also looking for an edge to get one over on some of the better players.