Age of Robots

Today I talk to Rafa Felix about his work at the Australian Institute for Machine Learning on generalised zero-shot learning.

You can find out more about Rafa at https://researchers.adelaide.edu.au/profile/rafael.felixalves

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Today I talk with Kelvin Ross, an accomplished technologist and entrepreneur who is the director of the Queensland AI Hub, among many other things. We talk about the hub, AI, automation, and getting a little too comfortable with the autonomy of a Tesla!

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I revisit a few of the interviews done in 2018 with a focus on the future of work and education in this machine age. This is a topic that we will increasingly be reporting on so that we can help you find your place in this age of robots.

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Today I'm going to be talking with you about working in the area of Edge Computing: Someone who works in edge computing may be responsible for creating, maintaining and upgrading an edge computing environment and may involve the design and development of hardware and software solutions, overhauling existing network infrastructure so that there is a balance of load-shifting across a network and all the devices connected to it.

 

For more information please go to the landing page for this episode

What is a Robotics Engineer? A robotics engineer is a technical designer tasked with creating robotic systems in many different industries and environments. Such systems are designed to assist or replace human effort to make workplaces safer and/or more efficient. Robotic systems are also employed in homes, places of education, in warfare, search and rescue, and many other environments. A robotics engineer will design robots needed to solve problems in these environments and some engineers will also participate in the assembly and manufacture of the machines they have designed.   What does a Robotics Engineer do? A robotics engineer will use research to determine the exact make-up of a particular robot to address the problems it is being created to solve. Robots are complex software/hardware systems that require an interdisciplinary approach to design, build, configure and test. Software systems have to be designed or modified from existing designs and integrated into hardware that will be functional and economical. So part of the job of a robotics engineer will be evaluating prototypes they have created in terms of function, cost estimations, and other design calculations that need to be made to produce an economical and functional system.   This can be a dynamic job with time at the computer doing research, writing papers, and sketching design ideas, to time in the lab creating components, models, prototypes and testing those experiments. Much of this work will be done in teams, with budgets and deadlines and a combination of structured and unstructured work.   What is the job outlook for a Robotics Engineer? There is expected to be continued growth for robotics engineering positions. The U.S. Bureau of Labor Statistics (BLS), say that the mechanical engineering field, which includes robotics engineers, will average 5% employment growth between 2014 to 2024. O*Net Online reports growth rate of 5-9% for robotics engineers https://www.onetonline.org/link/details/17-2199.08 . Estimates are difficult to predict in such a new field where robotics could potentially flood many industries, quite apart from manufacturing, as the utility of AI and automation become increasingly sophisticated. As robotics become more accepted in medicine, agriculture, the military, and in domestic settings, we may see the growth rate of this sector increase rapidly.   What does a Robotics Engineer get paid? As with most mechanical engineering jobs the pay for a robotics engineer is in line with the advanced skills and degrees needed to so such sophisticated work. Depending on the employer, pay rates can be in the $90K-$100K mark at the upper end after some years of experience.   What are the education requirements for a robotics engineer? To enter the field you will need at least a bachelor's degree and typically in mechanical engineering. Some may have an undergraduate degree in physical science and mathematics with further postgraduate degrees like a master's degree in robotics engineering. There are an increasing number of programs now that focus on robotic engineering both at undergraduate and graduate levels.   In your education you will need to gain a knowledge of the practical application of engineering science and technology. Understand design techniques, tools, and principles that you will need to design robots. General knowledge of circuit boards, processors, electronic equipment in general, computer hardware and software applications and programming. Mathematics will also be important. General mechanical knowledge of machines, design principles and repair and maintenance. An understanding of physics, and general production and processing knowledge will also be key in this job.   Fernando Zumbado, a Robotic Systems Engineer at NASA's Johnson Space Center says that you have to have a passion for what you do as well as paying "attention in class and learn physics, mathematics and other basic sciences. Without a strong foundation, it is very difficult to succeed at a higher level. But most important of all, learn how to learn. Understand how to approach a problem, how to craft a solution and how to implement your solution. Know that if you don't remember how to use a formula, you can open the textbook and understand how to properly apply it. It is through constant learning that you are going to be able to grow professionally." ( https://www.nasa.gov/audience/foreducators/robotics/careercorner/Fernando_Zumbado.html)   What do you need personally to be a Robotics Engineer?   Curiosity - Curious about how things work and wanting to create things that work better than what we have today.   Communication - You will often have to write reports, papers, work in teams, and so being a good communicator will be essential.   Hands On Problem Solving - Working with complex problems and evaluating the best options and solutions is at the core of this job. This will also involve understanding systems and how the systems you create change in various conditions and operational environments.   Arin Morfopoulos is a Robotics Engineer for NASA at the Jet Propulsion Lab in Pasadena. His advice to students interested in robotics is to have practical experience in making things work. Arin says that "In robotics, there are so many fields used that you will never be an expert at all of them at the same time. It is important to have a passing familiarity with the fields other than your own so that you are not in a constant state of confusion, but it is much more important to have built things, beginning to end, yourself. Expertise will come naturally with application." (https://www.nasa.gov/audience/foreducators/robotics/careercorner/Arin_Morfopoulos.html)   Dr. Lonnie Love, a robotics engineer at Oak Ridge National Labratory advises students interested in engineering to "Get active! Build stuff, make stuff, break stuff. There are lots of opportunities to get experience and see if a career in science or engineering is something you'd enjoy." (>https://www.energy.gov/articles/10-questions-robotics-engineer-lonnie-love)   Patience - This is a job of lots of trial and error and therefore you will need patience through the process of creating a system that works.   If you would like to know more and find links and other videos on this topic of being a robotics engineer, please check out the landing page for this particular episode at http://ageofrobots.net/how-to-become-a-robotics-engineer .

TRANSCRIPT Today I'm going to talk to you about becoming a Data Scientist, which is a title that is emerging as one of the hot job prospects in coming years. If you are someone who likes to solve complex problems, can pull together data from a number of different disciplines, are good with information technology, math, science, and fancy yourself as a trend-spotter, then data science might be just the thing for you!   WHAT IS A DATA SCIENTIST? Basically a data scientist is someone who pulls together data from an array of different sources and is able to analyze that data in a way that reveals patterns helpful to the company for business development, marketing, product development, and so on. Now that's a rather broad definition and that's because being a data scientist in any number of industries can be broad in terms of what is done. The key function of a data scientist is to take data and make it relatable for the business, to make it into a representation of patterns that the decision makers can look at and say something like "Hey, the sales trend is leaning into the teen market, let's change our marketing to follow that trend more aggressively." Or maybe the demographic data on your social media channels is swinging toward a particular age, sex, geographic area, education level, etc., and there's parallels with a strong competitor's marketing campaign and trending topics in the media. There are millions of data points that need to be organised, by highly advanced algorithms, and then put in some sort of visual or graphical representation that reveals this pattern. That's the job of a data scientist. The billions of data points out there, what we know as "Big Data", are often unstructured, overwhelming and to be honest, useless to informing business decision makers. What business needs is an interpreter - they need a data scientist!   WHAT DO I NEED TO BECOME A DATA SCIENTIST?   Technical Skills:

1. Data scientist will usually have a masters degree or even a PhD and so a strong academic foundation is needed.
2. Typically you will get an undergraduate degree in computer science, social science or one of the physical sciences with a grounding in statistics. Then there will be a Master's degree or PhD in data science or a related field.
3. You will also need to have gained proficiency in an analytics tool like R (https://www.r-project.org/) that is used to solve statistical problems and manipulate data.
4. You would also be skilled in a programming language like Python, Java, Perl, or C/C++. About 40% of data scientists use Python as their main programming language.
5. Other skills such as familiarity with Apache Hadoop (https://hadoop.apache.org/) , Hive (https://hive.apache.org/), Pig (https://pig.apache.org/), and Spark (https://spark.apache.org/) - all tools to process and analyze large data sets, and cloud tools like Amazon S3 (https://aws.amazon.com/s3/) is also an advantage.
6. Understanding machine learning and how artificial neural networks, reinforcement learning, and other machine learning techniques work will be a huge advantage to you.
7. Once you have data that means something you will need to present it in a way that other's can comprehend and that's where data visualisation comes into play. Visualising data with various visualisation tools like Tableau, D3.js, Matplottlib, and ggplot will be important skills to have as a data scientist.

  Other Skills:

1. Naturally curious and a drive to want to find out "why" things are the way they are.
2. Organized - You need to be able to organize data and results when handling lots of data points from many different sources.
3. Critical thinker - It's one thing to put data points on a chart it's another thing to creatively and critically evaluate what it means and how it all fits together in the larger scheme of things.
4. Focus - Working with data requires focused attention, often for long stretches of time, and an attention to detail without quickly getting board if the magical revelations don't jump out at you immediately.
5. Good communication - To get data, collaborate with others and communicate results to your employer, your communication skills need to be strong. To be able to communicate in a non-technical way to the company you are working for and give non-technical summaries and ideas of opportunities will be a key skill to have.

  WHAT CAREER PATHS ARE THERE FOR DATA SCIENTISTS?   This is a career that is constantly evolving as more data becomes available and companies learn how to use it in more effective and creative ways. Just about every industry and every company in those industries use data and the interpretation of data to make business decisions and so the data scientist is at the heart of many companies. Companies are going to increasingly need someone to gather, organize, store, interpret and visualise important data that directly impacts the company, and these companies will pay handsomely for such people.   Work as a data scientist is often in a office-like environment where you collaborate with others on projects. Obviously the atmosphere, pace and work conditions will vary depending on the industry and company you work for, but your skills as a data scientist are very much transferable across companies and industries. Some work environments will encourage creative thinking and problem solving and others less so, wanting just efficient "number crunching".   Job satisfaction will likely revolve less around pay rates (you are likely to be paid well) and more about your interest in what the company does, the capacity to be creative, and the pace and feel of the work environment. There will be opportunity to specialize and become senior in a particular area of your work your find interesting and rewarding and this will, in turn, be financially rewarding as well.   A career as a data scientist will mean you are continually learning new systems, software, techniques. You may find last year's efforts to learn a particular platform are suddenly obsolete and you have to learn a new platform or tool this year. You will need to be comfortable with a work landscape that is in constant flux and love learning new things all the time.   WHAT IS THE SALARY AND JOB PROSPECTS LIKE FOR A DATA SCIENTIST?   The prospects for employment are good and increasingly so in the near-term as there is a shortage of data scientists at the moment. You can expect to be earning well over the national average and the job is likely to become increasingly valuable as time goes on and companies rely more strongly on good data analysis.   The estimated salary for a Data Scientist varies across industries and countries, with reports in Australia of averages in the $90K/year mark, and the Burtch Works Study (https://www.burtchworks.com/big-data-analyst-salary/big-data-career-tips/) reporting anywhere between $95K-$250K depending on experience and status. Salary site PayScale (https://www.payscale.com/research/US/Job=Data_Scientist%2c_IT/Salary) put data scientist around the $92K/year mark in the USA.   For more go to this episodes landing page here: http://ageofrobots.net/how-do-you-become-a-data-scientist/