Tag Archives: deep learning

Building Deep Learning Machines: The Hardware Wars Defining the Future of AI

November 6, 2017

So often, conversations regarding deep learning are focused entirely on software and programming — who can train deep learning models to perform X use case better than anyone else? But developments on the hardware side of the equation reveal that there is more to advancing artificial intelligence. As conventional big data analytics emerged, the industry… Read More »

Fast Track Business Outcomes from Artificial Intelligence with Proven Methods and Accelerators

October 23, 2017

Deep learning, chat bots, smart machines, natural language processing, neural networks — these buzzwords continue to create much excitement, hype and urgency among business leaders, as they deliberate on how and when to invest in artificial intelligence (AI) to transform the way their companies can leverage data to improve business outcomes and gain competitive advantage.… Read More »

The New Wave of Machine Learning

October 12, 2017

In the last few years, analytics has evolved significantly. We’ve moved from the adoption of big data technology that was all about Hadoop and Spark, to an increased focus on machine learning algorithms, deep learning and artificial intelligence (AI). In the last year alone, I’ve noted a renewed hype around machine learning, which together with the… Read More »

Survey: State of Artificial Intelligence for Enterprises

October 11, 2017

Artificial intelligence will have a profound impact on our lives and work. Soon it will be everywhere, from our homes to our cars to our offices. Many believe it will cause a massive displacement of jobs. Others argue that it will enhance our decision-making and make us smarter. But, what do business executives at some… Read More »

The Tree of Machine Learning Algorithms

October 10, 2017

The Tree of Machine Learning Algorithms is a simplified schema to rationalize the types of learning paradigms used by categories of algorithms. Just as a tree’s branches grow stronger and wider with an expansive network of roots, the machine learning tree is strengthened using a network of data. Data can be structured or unstructured, involve transactions… Read More »

Could the English language get any more confusing?

September 14, 2017

Did you know that the English language consists of over 200,000 words? Of these 200,000 words, many have the same meaning but different spelling (synonyms). Some words even have the same spelling but different meanings (homographs). Confusing, right? Let’s imagine you were talking to your colleagues about your recent trek to the coast and you… Read More »

Occam’s razor and machine learning

September 12, 2017

In the last instalment of this blog series, we discussed objectives and accuracy in machine learning. And we described two crucial tests for the utility of a machine learning model: The model must be sufficiently accurate and we must be able to deploy the model so that it can produce actionable outputs from the available… Read More »

Objectives and accuracy in machine learning

September 7, 2017

We get to go to a lot of conferences. And we’re always amazed at how many vendors and commentators stand up at events and trade shows and say things like, “The objective of analytics is to discover new insight about the business”. Let us be very clear. If the only thing that your analytic project… Read More »

The secret to AI in the Enterprise could be little-known transfer learning

August 29, 2017

Consumers have spoken — artificial intelligence is a profitable industry. From Amazon to Google to Apple, major tech companies have all made inroads, crafting intelligent software — housed in sleek, accessible hardware — that has gotten massive customer attention. This trend is set to soon move out of home devices, like Echo and Google Home,… Read More »

What today’s machine learning and AI is and is not

August 4, 2017

All artificial intelligence methods today are around machine learning modeling and use some form of sophisticated correlation or association method, which can be approximated to brute-force robot learning. It is about reverse engineering existing features/patterns and providing useful “forward engineering” solutions like: Self-driving cars Detecting diseases from X-rays/MRIs Robots in manufacturing Chatbots for customer service… Read More »