Imaginea Labs

With the developments happening in the realm of software and hardware breaking new ground daily, it is not far that our reality can be manipulated to suit our everyday lives and enhance our evolution. Welcome to a world of new reality. Augmented Reality manipulates existing dimension giving us a better world view. The rapid growth of mobile technology and ease of application development processes has given the push to develop Augmented Reality applications at a large scale.

Overview: There are a lot of buzz going around in the Blockchain space. No doubt it is a very robust technology that resembles the internet in the early ‘90: It packs the potential to change the way we live, work, consume and interact. As a lot of Dapps - Decentralize applications, Blockchain based applications, are being developed these days, it is very important to think of what are the use cases that should go for Blockchain and what should not or not needed.

Those who are working on Blockchain, especially on Ethereum, must have heard about Smart Contracts. They are fully fledged programs, written in Solidity - language similar to javascript, that runs on Ethereum blockchain. When contracts get compiled, they get converted into opcode - instructions to be executed on the machine - and execution of these opcodes consumes Gas - Gas is the execution fee for every operation made on Ethereum. While writing contract code we have to be very careful otherwise, a user can end up losing a lot of Gas.

I am going to write this topic in couple of blogs. So that reader will get complete exposure of oracle services providers, like Oraclize in particular. In my first blog post I will try to give a brief overview of Oracle services. Basically dealing with questions like, What are Oracles? What is Oraclize? What is the use of such services? Etc. In the subsequent blog, we will try to use the Oraclize service with our smart contract and further we will take a deeper look into, how it works under the hood?

Here at Imaginea Labs, we are exploring the true power of gpu-computing by analysing its way of launching a kernel, running 1000’s of thread blocks simultaneously, threads doing memory accesses in terms of global/shared and the optimized way to do so, doing atomic operation in threads when needed, optimizing threads to run more efficiently and faster.

In this post, we talk about cuda architecture and various experiments done on a use case with a brute-force approach to test and explore the gpu computation limits. We’ve had modest success in bringing out the best of gpu and faced some intriguing situations and results along the way.

Extracting text from PDF documents is a common pre-processing task for text analysis and NLP work. The main challenges tools face in extracting content from PDF files is that PDFs are composed of text, graphics and tabular structures encoded in a form designed for printing.

The distributed ledger protocol used by blockchains has resulted in systems where we do not have to place trust in particular parties involved in maintaining these ledgers. Moreover the ledgers are programmable with “smart contracts” - transactors whose state changes are recorded and validated on the blockchain. A collection of smart contracts describes a system that is expected to ensure certain invariants relevant to the domain are upheld. For example, an election system is expected to maintain voter confidentiality. While the code that describes these “smart contracts” is open for anyone to read, those who’re participating in the systems run by these smart contracts are not in general competent to evaluate them, with the OSS community being the sole eyes on the contracts being deployed. In this post, I examine how these smart contracts can provide “warranties” that are easier to ratify and describe clear and automatic consequences of violating the warranted properties.

In an earlier post, I’d written that blockchain apps must be closed systems. Since the specific sense in which I’d used the words “closed” and “system” didn’t quite manage to get through to readers, I’d like to explain them a bit in this post.

i-tagger - Neural Networks based Deep Learning models and tools for sequence tagging. Developing models to solve a problem for a data set at hand, requires lot of trial and error methods. With current projects, we find a difficulty with supporting different datasets and models in a modular way. i-tagger helps with easing preprocessing, training and prediction.

Welcome to our Christmas post on our work on data visualization in immersive media!

Technology is evolving rapidly and it has become a part of our daily lives. One of the top trending technologies today is virtual reality (VR). And we, at Imaginea Labs, are probing into it with gusto.