Unravelling the mysteries of Artificial Intelligence

REINFORCEMENT LEARNING - Part 1 Robotics and AI- A Perfect Blend Robotics and Artificial Intelligence has made a huge advancement in their respective fields. But the blend of Robotics and Artificial Intelligence have created some amazing stuff too. It doesn't seem far in future when robots can learn themselves what humans can, using Artificial Intelligence. This article is the first part of the series of three articles that would give us a peek into the future of robot learning and an introduction to Reinforcement Learning. By the end of part three an overview of creating a crawling robot that learns itself how to move in a particular direction will be given.   What is Reinforcement Learning? The world seems to be full of Reinforcement Learning (RL) examples if we observe. A dog seems to fetch a ball faster when you reward it with affection or a bone. Children are happy to do their chores if rewarded with sweets or toys. Also, when behaving irrat...

The Sense of Vision is taken for granted by us in our day to day life, but only a visually impaired person can understand the true value and necessity of Vision. But soon AI based computer vision systems can help the blind and visually impaired to navigate. Tech giants like Google, Baidu, Facebook, Microsoft are working on a range of products that apply Deep Learning for the Visually Impaired. One of them being Image Captioning technology wherein the system describes the content of an image.  To accelerate further research and to boost the possible applications of this technology, Google made the latest version of their Image Captioning System available as an open source model in Tensorflow. It’s called “Show And Tell: A Neural Image Caption Generator”. The project can be found at https://github.com/tensorflow/models/tree/master/im2txt and the full paper can be found at https://arxiv.org/abs/1609.06647 The Show and Tell model is an example of an encoder-decoder neural ...

Humans are good in conversations, because they can understand the intent of any statement, also the context in which the statement is placed. Today’s chatbots are equipped with intent recognition engine. Using machine learning, statements are mapped to intents, and the chabot can handle infinite variations of the same statement. Why is this technique useful? The following example cites this: Consider you want to ask the contact details of a company. Now every person will ask it in a different way. Following are few of the variations that are possible: Please share your contact details Where do you reside Where are you located Can you share your location Please provide your address Now the intent of the above questions is “asking address”. So a answer can be mapped to the intent, rather than all the questions. This helps in managing the chatbot easy. Before intent recognition came into existence, most popular being Wit.ai, recently acquired by Faceb...

How does a human infer whether two documents are similar? This question has dazzled cognitive scientists, and is one area under which a lot of research is taking place. As of  now there is no product that is able to match or surpass human capability in finding the similarity in documents. But things are improving in this domain, and companies such as IBM and Microsoft are investing a lot in this area. We at Cere Labs, an Artificial Intelligence startup based in Mumbai, also are working in this area, and have applied LDA and Word2Vec techniques, both giving us promising results: Latent Dirichlet Allocation (LDA) : LDA is a technique used mainly for topic modeling. You c an leverage on this topic modeling to find the similarity between documents. It is assumed that more the topics two documents overlap, more are the chances that those documents carry semantic similarity. You can study LDA in the following paper: https://www.cs.princeton.edu/~blei/papers/BleiNgJordan20...

Imagine you are an IT executive in a company. As per your role, you have to offer IT solutions to problems that your company is facing, be it related to Finance, Sales, HR, Administration, etc. Maybe you are already playing this role. You have successfully implemented IT solutions to challenging problems. You are praised by your CTO, have also received various awards for successful implementations. You have been promoted in the past for this particular skill. You are living in a perfect world, where most of the problems that you are solving can be solved with programming. You are living in a non-Artificial Intelligence world. Now imagine a world, where the problems that industries are facing today are not solved by programming. Imagine your company is facing problems that look difficult to be solved by any number of lines of code, or any number of current software solutions that exist in the market. You are faced with a dilemma of not able to offer solutions to such proble...