Original post published here.
I had a great time learning about Data Science last week at the Georgia Tech Hotel and Convention center. First of all, I would like to give a big thank you to the organizers who were kind enough to offer a scholarship through Women Who Code Atlanta. I am very grateful for the opportunity to attend such an informative and thought provoking event. In this blog post I will highlight some of my favorite talks and key insights that I took away from the conference.
In 2012, The Harvard Business Review came out with an article titled “Data Scientist: The sexiest job of the 21st century.” The term “Data Scientist” is relatively new, first coined in 2008 by the author of the article and soon after by companies like LinkedIn and Facebook. The article discusses the demand for people with skill sets much different than the data analysts from 10-15 years ago. A “data scientist” needs to be able to work with large volumes of unstructured data, structure that data, and then analyze it. A core skill for any data scientist is the ability to write code. Some of the most popular languages and frameworks for data scientists in 2017 include Python, R, SQL, Spark, and TensorFlow. Each language and framework poses different pros and cons in relation to the various packages and modules offered and what exactly you are trying to achieve.
Data Science is an interdisciplinary field that incorporates mathematics, statistics, computer science, modeling, and analytics, it also shares connections and overlaps with fields of study like machine learning, artificial intelligence, deep learning, and IoT. Knowledge of mathematical skills and computer science make a good data scientist but employers also look for candidates that possess a sense of empathy towards customers. There’s a lot of job opportunities for data scientists right now and IBM predicts the demand for data scientists will climb to 28% by 2020. If you have experience working in IT, it’s a good career to make a switch within a company as new college graduates only make up about 20% of the demand.
One of the sessions I really enjoyed was by Frank Hasbani, CEO of Anova Analytics. Companies that work with big data and implement data science projects often have a great need for collaboration between team members. Anova offers a platform that allows a unified approach to collaboration. This product combines 8 platforms and services into one easy to use system. It has all the best data science tools in one place which allows for an integrated workspace for individuals. Some of the features include “Kanban”, a task management board similar to “Trello” and “Shiny Portal” a tool that allows stakeholders to view proof of concepts, working models, and dashboards. To learn more about Anova and their team platform solutions you can click here.
Another interesting session I attended was called “Unleashing the Power of Data with Network Acceleration – Bringing Together Big Data and Deep Learning”. The talk was given by Bill Webb, director of Ethernet Switch Sales at Mellanox Technologies. Mellanox uses super computers and offers machine learning solutions to almost 3,000 customers. They build networking infrastructure to help accelerate servers that process large amounts of data. Many universities and laboratories are their customers, including Georgia Tech. The talk focused on how companies are now merging big data with machine learning. Webb discussed the flood of data being created by autonomous cars. He stated that 1 million driverless cars could produce the same amount of data as 3 billion people, roughly half of the world’s population. Autonomous cars have multiple on-vehicle sensors, cameras, radar, and real-time, high precision GPS mapping and navigation systems, all of this adds up to a lot of data that needs to be processed. In order for an autonomous car to function it needs very large datasets already in place, that’s why driverless cars are not readily available yet. In late 2018 Audi plans to release a semi-autonomous “hands-free driving system” for up to 35 mph and in 2020 the company plans to debut its first fully autonomous car, you can read more about it here.
My favorite part of the conference was definitely the sessions on Artificial Intelligence. I personally do not have any working knowledge or experience with AI but I am very curious about the direction it’s going. Chris Benson gave several talks on AI during the conference and I was lucky enough to attend two. He’s Chief Scientist for AI and Machine Learning at Honeywell and also organizer of the “Atlanta Deep Learning” Meetup group. He was first introduced to deep learning way back in 1992, and his father, Whit Benson used machine learning ideas as an engineer at Lockheed Martin. He spoke about the juxtaposition of four disciplines and how they relate to Artificial Intelligence.
AI is a subset of data science, within AI there’s the subset of machine learning and within machine learning, at the very core, there’s deep learning. A basic definition of machine learning is “Algorithms that parse data, learn from that data, and then apply what they’ve learned to make informed decisions”. Deep learning is essentially machine learning but it goes a step further. Deep learning uses layered algorithms which create an “artificial neural network” these hidden nodes mimic the human brain and how they are connected is based on math. The neural networks give the model the ability to learn on its own. The result is that it’s able to function and make decisions much more like a human brain would.
Although Chris grew up being immersed in these concepts he knows that deep learning is still relatively new to the majority of people, “We are in the wild west days of deep learning”, he stated, comparing deep learning to the advent of the internet in 1993. “There are not many guides to best practices”. Chris also mentioned, “AI first is what’s cool now, it’s no longer mobile first”. I have to say I was very impressed with his experience, knowledge, and insights regarding Artificial Intelligence.
Chris Benson also gave the closing keynote speech titled “Summoning the Demon – AI and the Future of Life on Earth”. The phrase “Summoning the Demon” comes from Elon Musk, which he readily pointed out. Although Elon Musk and Stephen Hawking have given warnings about AI, Chris Benson considers himself to be more of an optimist on the subject. The most interesting part of his speech was when he talked about “Singularity”, the moment when AI will become so advanced it will outperform the most intelligent of any human. I have to admit, I was intrigued.
What will this look like for humanity? I have so many thoughts on this. How will we view AI when it reaches singularity? History has shown that humans tend to fear and look up to things that we perceive as more intelligent than us. Will AI become some kind of authority figure? And what about emotional intelligence? How will this factor into the creation of AI in the future. Emotional intelligence is all about reading people and picking up on cues to give people what they need and want in order to make them feel happy and secure. How will AI be able to do this for everyone? And just how smart will AI become? Humans are more or less limited with the brains we are born with but AI will have to ability to keep learning and learning.
I don’t think I could personally view a super intelligent AI as anything close to a human, for me I think I’d see them more as an alien. And although this alien would be super intelligent, perhaps it would still be lacking in some sense. Humans have senses and awareness and intuition. Things not so easily measured by science. Most of all I wonder if having these AIs would somehow redefine what it is to be human and what our worth, value and purpose is in this world.
I’ve always had a big imagination. Long before the Curiosity rover or we had clear images of the Martian landscape, I used to get vivid dreams about Mars and what it looked like, in my dreams I would meet humans living there and I even found water. Sometimes my imagination and dreams show me all different kinds of scenarios with AI. I don’t know whether to trust those intuitions or to think maybe I have just seen “2001 A Space Odyssey” one too many times. At the end of Chris’s speech he opened up the floor for discussion. I’m pretty introverted and usually have a hard time putting myself out there but I decided to ask a question regarding an article I had recently read. The question was about Anthony Levandowski, a former Google engineer and his plans to create an Artificial Intelligence deity and religion. You can read more about Levandowski here.
I have to say, the conference was a great experience and it really got me thinking. I couldn’t help but notice the organizers put a lot of thought and effort into planning the event. The lunch each day was really nice and they had a lot of gluten free options which I definitely appreciated. The organizers are hosting an event in New Orleans March 21st-23rd called JazzCon.Tech, if you are looking for a first class conference for yourself or employees I emphatically suggest it. Thanks again to the organizers and Women Who Code Atlanta for an incredible experience.