2019 Artificial Intelligence Conferences

One of my favorite tasks at the end of each year is to do some planning for the coming year. With respect to Industry 4.0 there is so much to learn in 2019 and beyond. Conferences are a great way to supplement learning on this topic and this is a good time to plan for these conferences in your budget.

Conferences provide a way to sharpen your skills while away from regular work, meet experts face-to-face, network, and break out of your comfort zone.

Below is a list of conferences related to Industry 4.0 for the first half of 2019; some are in Pittsburgh, some in the USA, others are in foreign countries.

January

23^th – 25^th, Global Artificial Intelligence Conference, Santa Clara, USA

23^rd – 26^th, AI NEXTCon, Seattle, USA

26^th – 29^th, Applied Machine Learning Days, Lausanne, Switzerland

27^th – Feb 1^st, 33^rd AAAI Conference on Artificial Intelligence, Honolulu, Hawaii, USA

 

February

22^nd-24^th, 11th International Conference on Machine Learning and Computing (ICMLC), Zhuhai, China

 

March

4^th, Women In Data Science, Stanford University, Stanford, USA

5^th – 6^th, 5^th Annual Big Data & Analytics Summit, Toronto, Canada

11^th – 14^th, 14th ACM/IEEE International Conference on Human Robot Interaction, Daegu, Korea

14^th, AI 4 Business Summit, Brussels

14^th – 15^th, Data Innovation Summit, Kistamassan, Sweden

14^th – 15^th, Future of Information and Communication Conference (FICC), San Francisco, USA

18^th – 20^th, RPA & AI Summit, Copenhagen, Denmark

19^th, Women in AI Dinner, Re-work, London, UK

21^st – 22^nd, AI on a Social Mission Conference, Montreal, Canada

 

April

9^th – 10^th, The Carnegie Mellon University – K&L Gates Conference on Ethics and AI, Pittsburgh PA, USA

18^th, Applied Artificial Intelligence Conference, San Francisco, USA

24^th – 26^th, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Bruges, Belgium

25^th – 26^th, AI Expo Global Conference & Exhibition, Olympia, UK

26^th – 27^th, Artificial Intelligence: Thinking about Law, Law Practice, and Legal Education, Pittsburgh PA, USA

29^th – May 2^nd, Innovation Research Interchange 2019 Annual Conference – Innovation Unleashed: Physical Meets Digital, Pittsburgh PA, USA

29^th – May 2^nd, Strata Data Conference, London, UK

30^th – May 3^rd, Accelerate AI: Open Data Science Conference East, Boston, USA

 

May

2^nd – 4^th, SIAM International Conference on Data Mining (SDM18), San Diego, USA

6^th – 7^th, Predictive analytics World Industry 4.0, Munich, Germany

12^th – 17^th, IEEE International Conference on Acoustics, Speech and Signal Processing, Brighton, UK

16^th, Rise of AI Conference, Berlin, Germany

20^th – 24^th, International Conference on Automation and Robotics, Montreal, Canada

22^nd – 23^rd, LDV Vision Summit, New York, USA

23^rd – 24^th, Deep Learning Summit, Boston, USA

 

June

2^nd – 7^th, Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), Minneapolis, USA

3^rd – 4^th, Machine Learning Summit, San Francisco, USA

7^th, 11th International Conference on Advanced Computational Intelligence, Guilin, China

10^th – 11^th, CogX, London, UK

16^th – 21^st, CVPR 2019: Computer Vision and Pattern Recognition, Long Beach, USA

18^th – 21^st, O’Reilly Artificial Intelligence Conference, Beijing, China

22^nd – 26^th, Robotics: Science and Systems, Pittsburgh, USA

22^nd – 26^th, Robotics: Science and Systems, Freiburg im Breisgau, Germany

Applications for 3D printing

3D printing or additive manufacturing is the processes building an item by joining material layer by layer. Computers are used along with a digital file containing the instructions for building the item. The printing equipment reads the digital file and lays down the material. Additive manufacturing is not only for plastics, the material can also be metal or concrete. Some even hypothesize one day human tissue could be an Additive Manufacturing material.

The first additive manufacturing was in the form of Rapid Prototyping to create visual models of an item. Creating a full-scale model prior to manufacturing the actual part helped to identify flaws and ultimately save money. Additive manufacturing is now being used to created actual parts, not prototypes, for use in aircraft, automobiles, medical implants, dental restorations.

The following are examples of applying additive manufacturing:

• Medical Implants – Typically medical implants are made of plastic which bone will not adhere to or metal which is heavy. Additive manufacturing allows implants to be made in a truss structure. When a material such as titanium is used, the structure can move enough to trigger the body to form bone around the structure. Joint replacement is the largest portion of implants.

https://vimeo.com/125298689

• Aircraft – a partnership between Boeing and Digital Alloys created Joule Printing. The material used is metal wire. The system sends current thought the wire tip joule heating, similar to how a toaster works, and distributes the heated metal on the print bed.
• Automotive parts – Previously body parts used to build automobiles were pressed from sheets of metal. With 3D printing, these parts can now be made from steel granulate (powder). These parts are much more precise than when pressed from metal sheets.

This video about the changes in automotive manufacturing includes a section on 3d printing.

What is next for 3D printing?

3D printing is all about translating the digital world into the real world. Much like the idea of having a television every home, not every home has a 3D printer. Entry level printers can be too complicated for the home user and have varying price ranges. The greatest developments are in industrial production. The greatest race is to develop the first 3D printed orthodontic aligners. The aligners will be 3D printed rather than merely heat formed on 3D printed models. Many engineers dream of an era where human tissue and organs can be 3D printed. We will have to wait and see.

Role of Technical Writers in Industry 4.0

The Information 4.0 Writer

The changes that are happening in Industry 4.0 will change the role of the technical writer. How and When are the questions to be answered. As technical writers we explain things, processes, and how to perform tasks. With Industry 4.0 that will continue but the technologies we write about and those that we use will change along with Industry 4.0. Information 4.0 is the change in technical writing that corresponds with Industry 4.0; the trends and technology that will make technical writing possible. Information 4.0 brings technical writing to a highly advanced technical level.

How will Content Change

Because Industry 4.0 is beginning now, Information 4.0 is only a concept. We do not have all the answers to how to create materials, what tools (do the tools even exist), or what materials to create. Preparation is our best ally in this phase. We can evaluate what we know now, and we can plan for the changes as we see them happening.

Neil Perlin has identified 4 characteristics of content in Information 4.0. These characteristics embody not only the words that are written, but the format, chunking, release, timeliness, accessibility, and responsiveness to context of that information.

• Dynamic: Content chunks that can be updated in real-time. When information in the system changes, the content or the user should be able to trigger its build or generation, rather than the writer.
• Ubiquitous: Content available everywhere, independent of device. It must be online searchable and findable.
• Offered: Specific content made available when users encounter an issue rather than all information related to all tasks all the time. Content is online, print medium is ruled out.
• Spontaneous: Content triggered by the context. Meaning the orientation of the device being used or perhaps a specific context for an issue. An example is that information for de-icing a plane would only be available if the outside temperature is near 32 degrees.

Let’s say you need to produce instructions for 5 new system changes for 6 different users or types of users who have 4 distinct roles as users. This means that you will have to produce numerous sets of instructions; unique to each user. The difficulty is in managing these permutations of content without error.

See this video on how to manage content to be ready for Industry 4.0 changes:

How will Technical Writer Tools Change

Without a tool that applies these characteristics to content, it is just theory. With a tool, these characteristics can be implemented.  There is not a tool that can be used to implement all the characteristics to content. The best strategy for us as writers is to be prepared for what we image the changes may be:

• Set standards and enforce/teach them: For a standard that content is to be independent of format, instruct writers to avoid inline formatting and use Cascading Style Sheets (CSS) for formatting.
• Keep tools up-to date: When using a technology tool, take each update. If you try to move from version 8 to version 12 there may be some functionality that has depreciated. Deprecated features are features that remain in software but are not updated. At some time, these features will be removed. If the leap between the past and new software versions is too great, there can be functionality issues.
• Seek out new industry tools: Whether you look for new tools to solve an existing problem or are just watching new trends in the industry, new tools will be developed to handle Information 4.0. Here are a few organizations and standards to watch for developing tools:
  • Dublin Core: an initiative to create a digital library card catalog for the Web made up of d15 metadata elements. Metadata is data about data.
  • Resource Description Framework (RDF): World Wide Web Consortium (W3C) specifications designed as a metadata model.
  • Fluid Topics: Limitless technical content delivery.
• Keep up with training: It is best to participate in training of existing and new technologies. A common misconception is that workers are smart enough to pick up the material or can research and teach themselves. Thought this is true, there is a possibility of bad habits being perpetuated through the organization if the self-taught employee teaches others their ‘bad habits. It is best to learn how the tool works and should be used by those who designed the tool or by industry experts.

How will Technical Writer Skills Change

As industry changes and technical writer tools change, so must the skills of the technical writer. Let’s look at machine generated text as an example.

If there is a system for hospital equipment maintenance and repair and during a routine automated inspection of a piece of equipment a repair is determined to be necessary. The system will generate necessary reports for management and financial, as well as a full description of what was fixed for an automated fix or a set of repair instructions for a manual fix.

In this case the technical writer will not write the text. The writer becomes a rule maker and curator or the content; they will setup the system to generate specific pieces of content, for specific users, under specific situations.

With this content tailored approach writers will be geared toward writing 500 one-page documents rather than one 500-page book. The content is written in smaller chunks that can be put together in any order, for any different user, for any different state or condition.  The tools to come will handle the mechanics of how this occurs, but writers must understand the mechanics of what data, for whom, when and under what conditions.

 

The Terminator and AI

Many Industry 4.0 topics are hard to conceptualize because of the technical nature. In this post I want to take about Artificial Intelligence (AI) in relation to something we are all familiar with. The Terminator. This film was released in 1984 by MGM studios. In the event you have not seen it, here’s the synopsis listed on amazon:

A cyborg (part man, part machine) is sent from the 21st century to present-day Los Angeles to assassinate a seemingly innocent women whose child will play an important part in the world from which the killer came.

We know that smart factories can be designed to continue to work when one or more components of the system are removed. As components are removed, the machines use what it has learned to keep the factory running. Is this not the same functionality that was built into Skynet, the intelligence computer used to run the defense network? Humans thought Skynet was a threat and wanted to shut it down. Skynet sensed the threat and could not be shut down. Skynet was in control of the Terminator. It could not be ‘killed’. It turned itself on after being disabled…repeatedly. Factories designed to make cars verses a robot designed to kidnap or kill are not very closely aligned, but their goal could be: do not stop production. All it takes for a machine revolt is for the machine to be designed to not stop. The machine is designed for a purpose, humans try to stop it, the machine is not equipped to change its mission. The system is designed to identify threats to it keeping it running.

Will humans ever lose control to AI? I do not think machines will force us underground to survive. As these systems are designed there should be certain points where human interaction is required. Said another way the machines should not be designed to run themselves, repair themselves, and decide how they are run.

We just will not design machines that will not be able to be rerouted from their design purpose. Simple. But what if an enemy does not share this view? Dr. Brian Schmidt when asked about the AI race between Russia and China, stated, ‘I am very concerned about this. I think that both the Russian and the Chinese leaders have recognized the value of this, not just for their commercial aspirations, but also their military aspirations’.

For the most part benefits of AI outweigh the possibility of a robot takeover. Humans must remain in charge of these systems even when designed to run autonomously. Countries must continue to defend themselves from all threats – even if we do not yet know what a threat is.

Industry 4.0, Talking Terminology

Now that you have heard of Industry 4.0 it is time to dig in a little more. Let’s take a closer look at some terminology and familiarize ourselves with “what it really means”. Industry 4.0 is not based on one technology but the combination of technologies.

Source

Below are some common terms that are used when describing Industry 4.0. that we will review today:

• Systems integration
• Augmented reality
• Additive manufacturing
• Cyber security
• Cloud computing
• Autonomous systems
• Simulation
• Internet of things (IoT)
• Big data
• Machine learning

Systems integration

Systems integration is the process of bringing together smaller sub-systems into one system. These systems joined and cooperate so that it functions as one system. These systems are joined with the main goal of increasing value to the customer.

Augmented reality

Augmented reality is a technology that superimposes computer generated images on a person’s view of the real world. It is the combination of digital information with live video or the user’s environment. This offers a way to present information for technicians and workers in a company, they can watch real-time information from the work as they complete it. This can also be sued to enhance training and learning while reducing injuries and costs.

Additive manufacturing

Additive Manufacturing is the process of joining materials to make objects from 3D data. These are built layer upon layer, each piece is added, rather than subtractive. A clay sculptor practices subtractive manufacturing by removing all parts of a block of clay that are not the ending figure. Additive Manufacturing is used  in design modeling, prototyping. When used, this method can save large amounts of time and money., reduce costly errors and improve the quality of products.

Cyber security

Cyber security in Industry 4.0 focuses on managing risk in a connected production environment. The interconnected nature of Industry 4.0 result in cyberattacks that if successful will have greater effects than in the past. These new systems must prepare for new threats and organizations must integrate security standards throughout the organizations to  remain secure.

Cloud computing

Cloud computing refers to the practice of using a network of remote servers hosted on the internet to use software (store, manage, and process data) rather than using a local server or a personal computer. If you have used OneDrive for work or a college program, you are using cloud computing.

Autonomous systems

Autonomous systems and robots perform tasks making decisions using information without human intervention. Examples of autonomous systems are factory robots and self-driving cars. We in Pittsburgh are very familiar with the concept of autonomous vehicles.

Simulation

Simulation refers to running real-time simulation of a factory, product, or process. This is more than a visual representation, it is as real-world as can be created within a computer. An example is a simulation of a whole factory in the cloud for the entire organization all over the world to observe, using any device. The simulation can be used to create new or modify machinery components greatly lowering costs in the actual factory.

Internet of things (IoT)

This is the network of all things connected to the Internet. This includes physical devices, vehicles, home appliances and other items. All of these have connectivity which enables them to connect, collect and exchange data. This Video is an enjoyable take on IoT: Future Son – Progressive Insurance Commercial.

Big data

Big Data refers to technologies and initiatives involving data is too diverse, changes too fast or is too large for conventional technologies and human skills to address efficiently. Simply stated, this data cannot be managed in a spreadsheet.

Managing Big Data involves the creation, storage and retrieval of data and analysis of that data. relates to data creation, storage, retrieval and analysis of a lot of data that happens quickly and involves many different types of data. Big data can be used to predict outbreaks of epidemics and to detect the misuse of credit cards.

Machine learning

Machine learning is when computers apply statistical learning information to identify patterns in data. Human intervention is not necessary in this process; it happens automatically. Once the patterns are identified they can be used to make very accurate predictions.

Decision trees are one machine learning method. These look at one variable at a time and use if-then statements to identify patterns in the data. Example: If evaluating properties to determine whether they are in Arizona or Montana: If the average annual temperature is above [some number], then the property is probably in Arizona.

These statements are called forks because they split data into separate branches based on a value. The value between branches is called a split point but is just a boundary. While working thorough the data and branches, false positives and false negatives must be accounted for to ensure accurate learning.

 

Industry 4.0 – I’ve Never Heard of That!

Hello and welcome to my blog dedicated to Industry 4.0 and Information 4.0. The first time I heard of Industry 4.0 was this past June at the MadWorld 2018 conference. This conference is dedicated to users of Madcap’s software; I use flare to create help files. During the conference I attended an interesting session on the topic of Industry 4.0; what it is and how we as writers can prepare for it. After the conference I did not think much of it. In the past few months my daily work has been getting closer to the topics covered in the session. In this blog the focus will be on what it is, what industries are impacted, what it means for writers, and how to be prepared.

Defining Industry 4.0

In a nut shell, it is the 4th industrial revolution and we are in the beginning stages. The first three revolutions, that were marked by a new type of energy and method of production; coal/steam and mechanization, electricity/gas/oil and assembly line, and nuclear power and computer automation. It was the energy type which allowed new developments in machinery and production. Industry 4.0, differs in that it is marked by digitization and interconnection of production rather than an energy source. This is where humans meet the cyber world; where technology is not distinct from people.

Why I Care

I have been a technical writer in the software industry for many, many, many years. I am always looking for ways to create better content more quickly.  As the systems I write for change, I will need to adapt my skill set to write for any and all of the following:

• Systems integration
• Augmented reality
• Additive manufacturing; 3D printing
• Cyber security
• Simulation prototyping
• Internet of things (IoT)
• Big data
• Machine learning

How will content change?

The changes that are happening in Industry 4.0 will change the role of the technical writer. How and When are the questions to be answered. As technical writers we explain things, processes, and how to perform tasks. With Industry 4.0 that will continue but the technologies we write about and those that we use will change along with Industry 4.0. Information 4.0 is the change in technical writing that corresponds with Industry 4.0; the trends and technology that will make technical writing possible. Information 4.0 brings technical writing to a highly advanced technical level.

Because Industry 4.0 is beginning now, Information 4.0 is only a concept. We do not have all the answers to how to create materials, what tools (do the tools even exist), or what materials to create.  Preparation is our best ally in this phase. We can evaluate what we know now, and we can plan for the changes as we see them happening. I can now imaging a day where automation and AI help me as a writer. I dream of a day where I curate machine generated content rather than write each word. As I learn I will post information here so that we can learn together.

Thank You,

Lorrie

Journey of a Technical Writer

Personal Discovery in the Workplace

My journey as a technical writer began as any other journey; with one step. I am nearing my 20th anniversary of being a technical writer in the next few days and this is perfect time to reflect on how my journey began.

After graduating college, I took a job in investment banking where I spent my day sifting through financial reports that listed market trades that had failed. There was something wrong with each trade on the report and I had to find the detail that prevented the trade from settling. Are you asleep yet? This job was as exciting as it sounds. It was awful. Each day I came home so mentally exhausted I could barely function. Other than work all I could do was watch television then go to sleep just to start it all over again the next day. Over the course of two years I could feel myself getting that ‘bean counter’ tenseness. I was grumpy, edgy, and had nightmares of missing money.

I needed a change

I started to network and let my contacts know that I was ready to move on from the banking world. Job placement companies were not helpful as they wanted to place me in banking. I would be an easy placement for them and would continue to be unhappy. The husband of one of my friends worked for a start-up software company. My friend let me know that he was searching for a few employees. She asked me if I would be interested in working on the company’s help file for their software and any other jobs requested as this was a true startup. I was ultimately hired. I had no idea how to do the work, but I wanted out of banking.

My New Job

As promised, I did write the help file for the company, but also answered phones, ordered supplies, assembled marketing materials, traveled to trade shows, and made sales calls. I liked my work but worried that the combination of duties made me unmarketable as an employee. Because the company was a startup, the threat of the company failing, and closing was always present (they did not fail and are still in business). Monster.com was a new job search tool at the time. I decided to use monster to find a job posting that matched my daily activities. My hope was that the job description I found would have a title attached.

My New Title

I conducted many searches for each of the tasks I performed, as I suspected, those tracked back to low lever administrator positions. I then searched for the help authoring software I was using, RoboHelp. This search returned numerous results for Technical Writer. Eureka! That’s what I am. Armed with this new information, I continued to search Monster.com using only Technical Writer as a search term. I searched locally as well as nation-wide. I wanted to know what a technical writer did. My thinking was that if I could come up with a list of duties, I would know which I was performing accurately, and I would know which I needed to add and learn how to do.

Once my research was complete I decided to let my boss know what I was up to. The look on his face when I said, ‘I have been looking around on Monster.com’, priceless. I quickly assured him that I was not looking to leave but using that tool to figure out a proper title. He was pleased with me being able to tell him the new tasks I would be performing as a Technical Writer. As a Technical Writer if I was going to be good, I had to do all the duties.

In the years since, I have:

• Learned RoboHelp and Flare help authoring tools.
• Written release notes for software.
• Created interactive PowerPoint shows for eLearning.
• Written user manuals for software.
• Contributed to software development as a part of an Agile Development Model.
• Worked with clients to get feedback on improving learning materials.
• Developed single-sourcing prototype for my Education team.

I had a great sense of direction knowing my accurate job title. From that point forward, I read as much information as I could on writing, software instructions, psychology, and education. I am sure I have some bad habits as a self-taught technical writer. This desire to overcome my own learning obstacles and to be better at what I do is what lead me to the Master of Profession Writing at Chatham University.

Resource Links:

https://www.linkedin.com/pulse/20140523045808-27554839-here-s-a-better-way-to-determine-position-job-titles-within-your-organization/

https://www.monster.com/career-advice/article/job-title-doesnt-match-job

https://hbr.org/2017/07/how-to-ask-for-the-job-title-you-deserve

The Beginning

Thanks for visiting my blog! This is a new journey I am happy to take. I hope you stay with me for the ride.

-Lorrie

I always believe that the sky is the beginning of the limit – MC Hammer