Monthly Archives: July 2013

Beginner’s Guide to Linkers

This article is intended to help C & C++ programmers understand the essentials of what the linker does.


The Virtual Internship: Take Control of Your Future by Becoming an Open Source Developer

The Virtual Internship: Take Control of Your Future by Becoming an Open Source Developer.

A Primer on Object-Oriented Concepts

A Primer on Object-Oriented Concepts.

C 11 Regular-Expression Library | 20.1. Overview of C 11 Regular Expressions

C 11 Regular-Expression Library | 20.1. Overview of C 11 Regular Expressions.

Project Euler Problem#14 solution in C++

Longest Collatz sequence

The following iterative sequence is defined for the set of positive integers:

n → n/2 (n is even)
n → 3n + 1 (n is odd)

Using the rule above and starting with 13, we generate the following sequence:

13 → 40 → 20 → 10 → 5 → 16 → 8 → 4 → 2 → 1

It can be seen that this sequence (starting at 13 and finishing at 1) contains 10 terms. Although it has not been proved yet (Collatz Problem), it is thought that all starting numbers finish at 1.

Which starting number, under one million, produces the longest chain?

NOTE: Once the chain starts the terms are allowed to go above one million.


#include <iostream>

int main ()
int N           = 1000000;
int CHECKPOINT  = 800000;
long long nTemp = N;
int chainCount  = 1;
int check       = 0;
long long myNum = 0;

for (int i = N; i > CHECKPOINT; --i)
while (nTemp != 1)
if ((nTemp%2) == 0)
nTemp = nTemp/2;
nTemp = (nTemp*3) + 1;

nTemp = N;

if (check < chainCount)
check = chainCount;
myNum = nTemp;
chainCount = 1;

std::cout << "The number " << myNum << " has longest chain of " << check << std::endl;


Machine Learning, Deep Learning and Scientific Understanding

Simant Dube

Machine learning is super hot in silicon valley these days! It has emerged as a very useful discipline in computer science and statistics. If you have skills in Machine Learning, you are likely to get a nice job. But what exactly is machine learning? With growing popularity of the field, engineers and scientists know the technical answer, but can it be explained to everyone in simple language? What are current trends in machine learning and what could come next?

In this article, we will focus on statistical learning and discuss state-of-the-art, trends and future directions.

Decisions, Decisions, Decisions!

Why is machine learning hot? Well, there are so many decisions to be made everywhere. Suppose you want to predict, recommend, classify or rank something in an automated data driven manner. Then your best bet is to use statistical machine learning.

Netflix wants to recommend movies to you which you may like…

View original post 2,869 more words

When will you be domainted by Artificial Intelligence?

Post All Junk Here

In 1997 IBM challenged the World’s number one chess Grandmaster, Garry Kasparov to a friendly chess match against their newly built Deep Blue chess playing computer.  After seven long matches, IBM Deep Blue defeated Kasparov 2-1.  At the time, Garry Kasparov accused the IBM engineers of cheating, and using human players to assist Deep Blue back stage;  indeed Kasparov’s was a normal human reaction.  But what Garry didn’t realise at the time, he was mearly going through the normal set of human emotions, which billions of other humans will face in the coming Artificial Intelligence Age.

Machines can already run faster, lift heavier, dive deeper, climb higher than any human.  What makes the thinking domain so untouchable and special!?  Indeed, IBM Deep Blue proved that humans can be outsmarted too.

Even though Garry Kasparov will be remembered as a great chess player, he will also be remembered as one of…

View original post 310 more words

neuro-Cell: A cognitive computing System-on-Chip

Injecting intelligence into the dna of the city

This document provides an introduction to the neuro Cell Technology (nCell). nCell represents a  revolutionary extension of conventional multi-processor architecture. This post discusses the problem, design concept, the architecture and programming models, and the implementation.

Over the last 20 years digital electronics has evolved and improved exponentially. The performance of devices is roughly doubling every 18 months because transistor size and the cost of chips have shrunk at an impressive pace. Unrelenting advances in the transistor density of integrated circuits have resulted in a large number of engineered systems with diversified functional characteristics to meet various demands of the human life, ranging from micro-embedded devices, implantable medical devices, and smart sensors. However, the complexity of system-level design for these increasingly evolved engineered systems is further compounded when interdisciplinary requirements are included, for example, massive integration and interconnection between components and subsystems, feedback and redundancy.

The increasingly shrinking electronic technology…

View original post 1,594 more words