Manifold Blog

Manifold Blog

Sourav Dey

Sourav Dey
Sourav Dey is the Managing Director, Machine Learning at Manifold. His previous work includes engineering work at Google and Qualcomm. He holds multiple patents, as well as a PhD, MS, and BS degrees in EECS from MIT.
Find me on:

Recent Posts

How to Apply and Optimize Your Algorithm When You're Ready to Run With AI

Posted by Sourav Dey on Mar 29, 2019 5:50:00 AM

Amazon’s recently launched SageMaker artificial intelligenceservice is an exciting new development, but the program doesn’t do it all. There’s a distinct gap between innovative AI technology that exists and AI solutions that will help drive business results in your specific case. Using products such as SageMaker is like having a brand-new Tesla Model S: It’s an awesome car, but it’s a giant electric paperweight if you don’t know how to drive.

We discussed "walking" with AI in a prior Entrepreneur article; now it’s time to hit the ground running.

Read More

Topics: Data science

Walking With AI: How to Spot, Store and Clean the Data You Need

Posted by Sourav Dey on Mar 28, 2019 5:46:10 AM

Last August, data science leader Monica Rogati unveiled a new way for entrepreneurs to think about artificial intelligence. Modeled after psychologist Abraham Maslow's five-tier hierarchy of psychological needs, her AI hierarchy of needs has become a conference favorite for illustrating how to incorporate AI into a business.

Despite entrepreneurs' excitement around AI, Rogati's hierarchy makes an uncomfortable point. Few companies are ready to adopt AI. Most are struggling to fulfill fundamental needs, such as reliable data flow and storage. The truth is that data literacy is lacking at most companies hoping to reap the rewards of AI.

Read More

Topics: Data science

This Is How to Get Started With AI When the Only Thing You Know Is the Acronym

Posted by Sourav Dey on Mar 27, 2019 5:42:46 AM

Unless you’ve been living under a rock, you’ve heard the buzz around artificial intelligence. So it might surprise you to learn that, according to a 2017 survey published by McKinsey Global Institute, out of 3,000 AI-aware executives, only one in five are using any AI-related technology in core areas of their businesses.

Why aren't entrepreneurs and executives jumping on what they know to be a market-changing technology? In a word, uncertainty. With AI still young, leaders aren't sure where to apply it, how to ensure a return on their investment or, most of all, how to implement it.

Read More

Topics: Computer vision

Before Optimizing Industrial Equipment with AI, Optimize Your Data

Posted by Sourav Dey on Jan 21, 2019 7:00:00 AM
These days, just about everything is "smart," from IoT toasters to internet-connected toilet paper dispensers. The existence of such devices points to the increasing availability of resources that enable more important pursuits. The related costs are decreasing, meaning it's possible to collect vast amounts of data from sensors attached to expensive equipment like oil and gas rigs, earth-moving tools, and factory machinery.
Read More

Topics: AI at the edge

Preparing Your Data for Predictive Analytics

Posted by Sourav Dey on Nov 16, 2018 2:17:23 PM

By Kyle Seaman, Head of Product at Sentenai, and Sourav Dey, Co-Founder and CTO at Manifold

Predictive analytics is an undeniably valuable technology, with research indicating its market size could top $12 billion USD by 2022. Across a range of industries, businesses, and applications, using historical data to predict future outcomes can lead to greater operational efficiency in a variety of ways. Predictive analytics can enable organizations to streamline their operational processes, optimize their demand forecasting, drastically reduce downtime, and better understand their customers’ propensity to buy.

Read More

Topics: Data science

Distance Matrix Vectorization Trick

Posted by Sourav Dey on Aug 15, 2016 7:00:00 AM

A common problem that comes up in machine learning is needing to find the l2-distance between two sets of vectors. For example, in implementing the k-nearest-neighbors algorithm, we have to find the l2-distance between the a set of test vectors, held in a matrix X (MxD), and a set of training vectors, held in a matrix X_train (NxD). Our goal is to create a distance matrix D (MxN) that contains the l2-distance from every test vector to every training vector. How can we do this efficiently?

Read More

Topics: Data science

Sensor Edge Finding at Cortex

Posted by Sourav Dey on Feb 22, 2016 9:00:00 AM

This article is Part 2 of a three-part series that we are writing about work that Manifold did with one of our clients, Cortex Building Intelligence. In our previous post, we talked about finding edges in sensor signals so we could use them to help us estimate a building’s start time.

We want to find sharp transitions in the various HVAC sensors—rising edges for electricity, steam, and static pressure and falling edges for supply air temperature (SAT). It’s easy for a human to pick out edges—but how do we teach a computer to do it?

Read More

Topics: Signal processing, AI at the edge, Data science

Data Science at Cortex

Posted by Sourav Dey on Feb 17, 2016 9:00:00 AM

This article is Part 1 of a three-part series that we are writing about work Manifold did with one of our clients, Cortex Building Intelligence. Cortex’s vision is to use data-science to make commercial building heating, ventilation, and air conditioning (HVAC) operations more efficient.

Over the next few posts, we want to give you a look "under the hood” of our data-science operations. To that end, we’ll discuss how we solved one of the foundational problems at Cortex: figuring out when a building’s HVAC systems were turned on.

Read More

Topics: Signal processing, AI at the edge, Data science

Never Miss a Post

Get the Manifold Blog in Your Inbox

We publish occasional blog posts about our client work, open source projects, and conference experiences. We focus on industry insights and practical takeaways to help you accelerate your data roadmap and create business value.


Subscribe Here


Popular Posts