Resume making is very tricky. A candidate has many dilemmas,
- whether to state a project at length or just mention the bare minimum
- whether to mention many skills or just mention his/her core competency skill…
ELAINE Symbolic AI offers community tool to cure “TL;DR” Syndrome
The idea of applying Natural Language tool to advance human intelligence is not new. Examples can be found among popular search engines and chat-bots. These applications generally require Machine Learning ahead of lengthy preparations with “human in the loop” training datasets. These pre-requisites are cost intensive in terms of time, labor, infrastructure and skill.
A few years…Continue
Added by Sing Koo on February 25, 2020 at 12:00pm — No Comments
By Faruqui Ismail and Nooka Raju Garimella
Reporters with various forms of "fake news" from an 1894 illustration by Frederick Burr Opper
We’ve always pictured the rise of artificial…Continue
Added by Faruqui Ismail on December 15, 2019 at 10:24pm — No Comments
Summary: Contextually intelligent, NLP-based interactive assistants are one of the next big things for AI/ML. The tech is already here from recommendation engines. The need to be more efficient and to become AI-augmented in our decision making is now. Getting the contextual awareness is the hard part.
Added by William Vorhies on October 28, 2019 at 9:43am — No Comments
Chatbots are a hot topic. Conversational commerce and Artificial Intelligence are at the peak; if you haven’t already experimented with chatbots for your customer services, now’s the time. But how do you create a chatbot yourself? Let’s review the options from the simplest to the most complicated.
Added by Olha Zhydik on September 23, 2019 at 4:00am — No Comments
Summary: 99% of our application of NLP has to do with chatbots or translation. This is a very interesting story about expanding the bounds of NLP and feature creation to predict bestselling novels. The authors created over 20,000 NLP features, about 2,700 of which proved to be predictive with a 90% accuracy rate in predicting NYT bestsellers.
Neural networks have made significant leaps in the image and natural language processing (NLP) recently. They’ve not only learned to recognize, localize and segment images; they’re now able to effectively translate natural language and answer complex questions. One of the precursors to such massive progress was the introduction of Seq2Seq and…Continue
Added by Olha Zhydik on August 16, 2019 at 5:30am — No Comments
Nowadays, lot's of discussion is happening around the question of what artificial intelligence can and can't do. Even though artificial intelligence has a controversial status, this technology already has some real-life business applications and delivers proven results.
Building a meaningful interaction with…Continue
Added by Olha Zhydik on June 25, 2019 at 5:00am — No Comments
Introduction to topic model:
In machine learning and natural language processing, a topic model is a type of statistical model for discovering the abstract "topics" that occur in a collection of documents. Topic modeling is a frequently used text-mining tool for discovery of hidden semantic structures in a text body.
In topic modeling, a topic is defined by a cluster of words with each word in the cluster having a probability of occurrence for the given topic, …Continue
Added by fatma gadelrab on March 31, 2019 at 10:06am — No Comments
Summary: Recurrent Neural Nets (RNNs) are at the core of the most common AI applications in use today but we are rapidly recognizing broad time series problem types where they don’t fit well. Several alternatives are already in use and one that’s just been introduced, ODE net is a radical departure from our way of thinking about the solution.
Added by William Vorhies on March 11, 2019 at 7:30am — No Comments
Everything we express (either verbally or in written) carries huge amounts of information. The topic we choose, our tone, our selection of words, everything adds some type of information that can be interpreted and value extracted from it. In theory, we can understand and even predict human behaviour using that information.…Continue
Resume making is very tricky. A candidate has many dilemmas,
Measuring the similarity between texts is a common task in many applications. It is useful in classic NLP fields like search, as well as in such far from NLP areas as medicine and genetics. There are many different approaches of how to compare two texts (strings of characters). Each has its own advantages and disadvantages and is good only…Continue
Added by Igor Bobriakov on January 4, 2019 at 12:30am — No Comments
What is NLP?
Natural Language Processing (NLP) can be simply defined as teaching an algorithm to read and analyze human (natural) languages just like the human brain does, but a lot faster than a human could, more accurately and on very large amounts of data.
It is a great skill to have if you are an aspiring data scientist or data analyst because has…Continue
Added by Aymone Kouame on August 11, 2018 at 2:00pm — No Comments
Articulate is an open source project that will allow you to take control of you conversational interfaces, without being worried where and how your data is stored. Also, Articulate is built with an user-centered design where the main goal is to make experts and beginners feel comfortable when building their intelligent agents.
The main features of Articulate are:
Added by Daniel Calvo-Marin on July 2, 2018 at 7:00pm — No Comments
Around two decades ago, marketing existed as a soft function within organizations. There is no denying its importance, of course, but from an organizational perspective, it was a function hard to measure in terms of impact on the bottom-line. But then boomed the digital age, and with it, an advent of channels that came to be known as social media. And in its wake,…Continue
Added by Senthil Nathan R on July 1, 2018 at 11:30pm — No Comments
Enterprises are learning fast about the relevance and use of AI and Cognitive Computing platforms. Before adopting AI and Cognitive Computing platforms, enterprises must focus on designing the right strategy for their business. A data-driven strategy is very important to derive the maximum benefit from the platform that will help to interpret data and provide…Continue
Summary: Our starting assumption that sequence problems (language, speech, and others) are the natural domain of RNNs is being challenged. Temporal Convolutional Nets (TCNs) which are our workhorse CNNs with a few new features are outperforming RNNs on major applications today. Looks like RNNs may well be history.
This is a continuation of my previous blog, “Natural Language Understanding – Application Notes with Context Discriminant”.
Natural Language Understanding (NLU) is a subtopic of Natural Language Processing (NLP). Successful implementations of NLU are difficult because of limitations in prevailing technology. SiteFocus solved these limitations with a new approach to NLU. This approach has been successfully…Continue
Many of us are bombarded with various recommendations in our day to day life, be it on e-commerce sites or social media sites. Some of the recommendations look relevant but some create range of emotions in people, varying from confusion to anger.
There are basically two types of recommender systems, Content based and Collaborative filtering. Both have their pros and cons depending upon the…Continue
Added by Venkat Raman on November 22, 2017 at 10:00pm — No Comments
Summary: This is the second in our chatbot series. Here we explore Natural Language Understanding (NLU), the front end of all chatbots. We’ll discuss the programming necessary to build rules based chatbots and then look at the use of deep learning algorithms that are the basis for AI enabled chatbots.