Knowledge Engineering


Braidio announces WorkStreams platform to optimise enterprise productivity

ZDNet

Technology is changing rapidly, information is coming at us so fast that traditional methods of learning the information you need for the job - and improving your performance - are no longer effective. The challenge is giving your employees the tools they need to be able to access the requisite knowledge, and the ability to share it, is key to business success. SaaS had a major impact on the way companies consume cloud services. This ebook looks at how the as a service trend is spreading and transforming IT jobs. San Francisco, CA-based social workplace intelligence platform Bradio has launched a new platform that aims to address these issues.


AI Knowledge Map: How To Classify AI Technologies

#artificialintelligence

I have been in the space of artificial intelligence for a while and am aware that multiple classifications, distinctions, landscapes, and infographics exist to represent and track the different ways to think about AI. However, I am not a big fan of those categorization exercises, mainly because I tend to think that the effort of classifying dynamic data points into predetermined fixed boxes is often not worth the benefits of having such a "clear" framework (this is a generalization of course as sometimes they are extremely useful). I also believe this landscape is useful for people new to the space to grasp at-a-glance the complexity and depth of this topic, as well as for those more experienced to have a reference point and to create new conversations around specific technologies. What follows is then an effort to draw an architecture to access knowledge on AI and follow emergent dynamics, a gateway of pre-existing knowledge on the topic that will allow you to scout around for additional information and eventually create new knowledge on AI. I call it the AI Knowledge Map (AIKM).


AI Knowledge Map: How To Classify AI Technologies

#artificialintelligence

I have been in the space of artificial intelligence for a while and am aware that multiple classifications, distinctions, landscapes, and infographics exist to represent and track the different ways to think about AI. However, I am not a big fan of those categorization exercises, mainly because I tend to think that the effort of classifying dynamic data points into predetermined fixed boxes is often not worth the benefits of having such a "clear" framework (this is a generalization of course as sometimes they are extremely useful). I also believe this landscape is useful for people new to the space to grasp at-a-glance the complexity and depth of this topic, as well as for those more experienced to have a reference point and to create new conversations around specific technologies. What follows is then an effort to draw an architecture to access knowledge on AI and follow emergent dynamics, a gateway of pre-existing knowledge on the topic that will allow you to scout around for additional information and eventually create new knowledge on AI. I call it the AI Knowledge Map (AIKM).


AI Knowledge Map: How To Classify AI Technologies

#artificialintelligence

I have been in the space of artificial intelligence for a while and am aware that multiple classifications, distinctions, landscapes, and infographics exist to represent and track the different ways to think about AI. However, I am not a big fan of those categorization exercises, mainly because I tend to think that the effort of classifying dynamic data points into predetermined fixed boxes is often not worth the benefits of having such a "clear" framework (this is a generalization of course as sometimes they are extremely useful). I also believe this landscape is useful for people new to the space to grasp at-a-glance the complexity and depth of this topic, as well as for those more experienced to have a reference point and to create new conversations around specific technologies. What follows is then an effort to draw an architecture to access knowledge on AI and follow emergent dynamics, a gateway of pre-existing knowledge on the topic that will allow you to scout around for additional information and eventually create new knowledge on AI. I call it the AI Knowledge Map (AIKM).


Why are mosquitoes dangerous? - Yral.net

#artificialintelligence

We must remember that in this species it is only the females that have the benefit (bad luck for one the human being) that can sting and adsorb the blood to feed. These insects lay their eggs in wastewater. Also in ponds or in places where there is a lot of humidity. Producing in this way larvae that will later become new mosquitoes. They usually bite at times where the temperature is low such as dusk or dawn.


A Textual Subgroup Mining Approach for Rapid ARD Model Capture

AAAI Conferences

Manual knowledge acquisition is usually a costly and timeconsuming process. Automatic knowledge acquisition methods can then significantly support the knowledge engineer. In this paper, we propose an approach for rapid knowledge capture. The methodology is based on textual subgroup mining in order to discover dependencies for rule prototyping.