Modev Blog


New Revolution for Wearables and Natural Language in Healthcare (Part 2)


by Mindy Quinn

On October 25, Modev is hosting a "Wearables & Natural Language in Healthcare" workshop with industry thought leaders before the PCHA Connected Health Conference October 26 & 27 in Boston


Types of Machine Learning Algorithms


by Imran Haider

In any AI system, the hardest things to learn are obvious tasks, such as walking. Walking is an overlooked task because it's so natural to us--in fact, we struggle to even articulate what makes us walk the way we do.


20 Twitter Influencers Every AI Enthusiast Should Be Following


by Modev Admin

Artificial intelligence is truly changing the way we live and work.


Pete Erickson -- TIMMY Finalist for Best Tech Manager DC


by Meredith Davison

Here at Modev we pride ourselves on transparent and open communication -- no secrets and everyone is in the loop. Well, we’ve been keeping a secret. As a team we decided to nominate our CEO and Founder Pete Erickson for a TIMMY. Best Tech Manager in DC to be precise.


State of Voice Platforms


by Imran Haider

Use of the word “platform” in the title is rather cautious. Because there is only one true platform in Voice and that's Amazon Alexa. While Google and Apple are in the game, you can't call their offerings platforms as yet. They have products and technologies in place but there ain't much for developers to do. Let's roll back a little bit and take a holistic view at the state of the industry. VoiceLabs recently released their 2017 VoiceReport. The report is worth a read in entirety. The picture below, however, is particularly important in understanding the different parts of a Voice stack.


What is Modev Exo Summit and why you should attend it?


by Imran Haider

Pick any large scale software product and you will find plenty of content on the tech side of it. But almost none on how people working on it actually work. For example, how they handle Pager or Crisis Management? This knowledge remains in the boardrooms and never gets out. While there are instances where it's hard to share that knowledge because of confidentiality. But more often than not the lessons learned are generic and shareable.


Eclipse Day Message from MoDev Founder Pete Erickson


by Pete Erickson

I felt it important to get a message out to the community during these challenging times when it comes to diversity, inclusion and treatment of those who aren't like us or from other cultures. MoDev is a community founded on inclusivity, support and safety of all we encounter.  


How Deep Learning works?


by Imran Haider

Unlike Artificial Intelligence (AI) or Machine Learning (ML), Deep Learning (DL) is a relatively new term circa 2010. However the underlying technology is not new. Deep Learning is based on Artificial Neural Networks (ANN). Artificial Neural Networks are as old as AI itself. The original idea behind AI was to make computers as smart as human brain. And that's what ANN tries to do by mimicking the brain. The recent hype around DL, especially since 2010, is because the idea seems close to its actual fruition. This dream like scenario is made possible by two recent technological breakthroughs i.e. GPUs and Big Data.


Coding in the Age of Machine Learning


by Imran Haider

Industrial Revolution automated labor work. Information Revolution automated the mental work. Machine Learning Revolution will automate the automation itself. —Pedro Domingos


Machine Learning, Deep Learning and the Hype


by Imran Haider

Artificial Intelligence is an umbrella term and covers everything that makes computers more intelligent. Think of it as electricity. Just like electricity fueled the industrial revolution, AI will fuel the information revolution. Soon we will have a computer inside everything. And hence everything will be prone to some level of AI embedded in it. Machine Learning is one way to make that happen. Another way would be to hand program everything and let evolution take place. That process is tedious and almost impossible. There is a limit to how much code humans can write. Machine Learning (ML) enables computers to write code for themselves.