These days students graduate and become the new interns/young professionals in the workforce. Energy is high and spirits are up. They want to make a difference. We as long time professionals should embrace that, but they cannot do it alone. We should help them and support them. Don’t hire them and just let them stay alone. Work with them and frequently communicate with them. Not once a week but every day of the week! They learn and we learn. We should also learn from our past mistakes and from our past experiences, but we must always learn and help if we are to move ahead and make something new and useful. As Henry Ford once said “anyone who stops learning is old, whether at twenty or eighty”. Keep learning
It is my 3rd year volunteering at Lamar Middle School (Lewisville ISD), a nearby school to our house in Texas. I kept accepting the volunteering task of presenting at its career fair even after my son moved on to high school because I felt a sense of purpose of encouraging new generations in the field of computer science. I estimated to have presented to around 150 8th graders at the school in total between all three times combined. I would first talk about about my past and what I do at the time with Thomson Reuters, and then get into my passion – technologies. Below are some slides about that I presented between 2017 and 2018.
This year I learned to summarize my background in one slide
After that I went into technologies. In 2017 I brought with me to school various gadgets including a Raspberry Pi, a maker robot, an Arduino, and various gadgets so as to show case what one can with technology. In 2018, I thought of focusing on AI and began showcasing through videos what artificial intelligence is about.
I showed YouTube videos of a MIT cheetah robot, an Audi self-driving car and a chatbot interaction between Alexa and Siri
After that I felt that I am lecturing the students by describing how to become a great computer scientist
But this year, I decided to make things more interactive by showcasing actual implementations and making the topic more aligned to their age of playing games! Hence, I focused on how gaming and artificial intelligence align together and how it can be cool to be the next programmer of such algorithms rather than simply playing Fortnite, League of Legends, Dota 2 and more.
I focused on the topic of leveraging cameras to let computers learn from players or people. Showed Chintan from DeepGamingAI video “creating custom Fortnite dances with webcam and Deep Learning”
and went over the videos from Farza “DeepLeague: leveraging computer vision and deep learning on the League of Legends mini map + giving away a dataset of over 100,000 labeled images to further esports analytics research” and explained how machines can learn through cameras
After that, I brought out Amazon AWS Deep Lens that I had previously setup for the event by deploying the object recognition model that recognizes 20 objects: airplane, bicycle, bird, boat, bottle, bus, car, cat, chair, cow, dining table, dog, horse, motorbike, person, potted plant, sheep, sofa, train, and TV monitor. I projected the camera at my audience and began explaining the process of neural networks, object detection, object classification, and what can reinforcement learning do if we expanded the project.
After that, I brought out my Google AIY Vision kit and explained how it works. To my bad luck I could not get the device to do more than beeping when it sees a face. Its code should make different colors when I make a happy face or a frown face. I had it working all along in the past, but this time I realized that I brought the wrong lens with me. Nevertheless, I explained how students can build such kits by showing them what’s in it.
Overall, there were 45 students this year that came to my all day demo. They would come in groups of 5 to 7 coming every 20 or 25 minutes. I would answer questions about my career and what I do at Thomson Reuters. Some asked my about my day to day work at Thomson Reuters, what my challenges and what makes me interested at work. My answers were honestly true and simple: I love to take challenging projects and focus on solving them with the team just like we would playing the next adventure game and solving its puzzles.
My key take from the whole experience is that most of the students love games, and that I used to make my point that they can leverage computers in whatever they love to do. Note that some said they want to do something in law enforcement, law, media, medicine, and not necessarily games or computer science. Even that, I felt that I had an answer which is computer programming and artificial intelligence is useful in whatever career they wish to do. Hopefully the students left my sessions with more interests in computers and programming. That’s the goal. I hope it worked for them just like computers worked for me in my entire life and continuous to do so through innovation and problem solving.
I am showcasing today AI gadgets to Grade 8 midddle schoolers at Lamar Middle School (Lewisville ISD) next to my house. The students have a career fair event, and I hope to encourage future programmers to the field of technology. I am taking with me Amazon DeepLens and built-it-yourself Google AIY Voice. I plan to show them real time object classification with DeepLens/pretrained MXNet neural network followed by audio response to facial expression (smiling or frowning) with Google AIY/Raspberry Pi Zero/PiCamera. Hopefully it would do the trick and get students excited with AI just like us adults.
I believe that an effective strategy for b2b (business to business) companies to innovate and grow is by powering their talented resources as if they are b2c (business to consumer) clients. That’s because the current generation of talents, millennials and post millennials, are digital consumers armed with the power of social networking and digital-everything. If b2b companies makes them feel cool and hype, the products they develop will be cool and hype, and the customers, young or old, could double down on such businesses because such companies are meshing modern and trustworthy professional experience. The only caveat is that b2b companies must have an organic feeling of doing this by seriously perfecting new talent acquisition and more seriously transforming their products and services quickly. Anyway, saying it versus actually doing it is not the same.
It was a pleasure and honor to represent Thomson Reuters at the panel on “scaling without stagnating” as part of corporate innovation. The event was hosted by Capital One and sponsored by Dallas Innovates as part of #dallasstartupweek. The panelists Dalia Powers (CBRE VP/CIO & panelist moderator), Sterling Mah Ingui (Head of Go To Markets Fidelity Labs), Scott Emmons (The Current Global CTO), Sean Minter (AmplifAI CEO), Charlie Lass (MIT investor) and myself Tarek Hoteit (Thomson Reuters Labs) took turns discussing leadership, people, organization, process/change management, and technology to support innovation in the corporate world. For me it was also an opportunity to let startups in Dallas to know about Thomson Reuters, Thomson Reuters Labs (http://labs.tr.com), and our community engagements in Dallas. I even shared my personal journey on a major transformation of a product as part of corporate innovation hoping to encourage everyone not to give up and do the same and more. We also answered questions from the audience such as how startups can interact with corporate (my answer: persistence is key but if someone from corporate is ignoring you, find another contact. Don’t give up)
Thimbleweed Park is an award-winning point-and-click game released in 2017 as a tribute to similar pc and Commodore 64 adventure games in the 80s. It is created by Ron Gilbert and Gary Winnick, with design and development assistance from David Fox, Jenn Sandercock, and numerous other individuals. You control five characters simultaneously in a story that in itself contains multiple sub-stories, interact with a multitude of characters in the game, and solve the puzzles that you encounter. Each of the animated characters has very distinct personalities that you cannot forget even after you long remove the game from your phone or computer.
After spending more than 20 hours playing the game over a period of time (22hrs and 15minutes in my last attempt per game record), I was so marveled with the game that I search the net on its origin and found a podcast by the game creators that ran weekly for 2 years from April 2015 to April 2017 plus one more episode in April 2018. Most of the episodes are 15 to 20 minutes where the game creators discuss the progress of the game development. One episode each month is an hour long and includes answering questions raised by Kickstarter-backer of the game as well as those posting comments on the game’s website blogs.
In the last couple of weeks, while driving to or from work, I went through all the podcast episodes in chronological order instead of listening to my usual music. My curiosity for listening to the podcast started with no apparent reason besides wanting to know more about the game, but it quickly turned into something bigger. It wasn’t about how to build a similar game or a nostalgia to bring back memories of the 80s. It was about developing something innovative with a tremendous focus on detail while maintaining a set of rules and constraints that the developers themselves intentionally decided to bound themselves onto to stay committed to their original idea, and that keeps the game with an 80’s look and feel but using modern-day technologies. The developers used to developed games together twenty to thirty years ago including Zack Mackraken, Maniac Mansion, Indian Jones, Loom, and more. They were in their twenties at the time. Now they are in their fifties and sixties with a lot of life experience combined with their lifelong passion for adventure games and science fiction – your typical geeks that I personal align with.
From a technology perspective, the developers leveraged a lot of the traditional modern-day technologies, such as Git for code repository, Adobe Photoshop for the art and animation in the game, software development kits (SDKs) for Steam, GOG, Xbox, Swift, Nintendo Swift, OSX, Android, Windows, Linux, and more. They were also blogging and podcasting their process which was something unthinkable of in the 80s, working remotely and using Skype for communication, and were interacting with their game supports on social media channels. In the eighties, such technologies did not exist, of course. The limitations of hardware and software on old computers like the Commodore 64 generated a lot of creativity but bounded with can be done in terms of graphics, music, and 8/16bit computing power. Nowadays, games run on 64-bit computers and mobile phones, and can easily leverage augmented reality, virtual reality, and artificial intelligence technologies to maximize gaming experience without sacrificing performance or cost. The developers for Thimbleweed Park decided to do none of the cool new stuff.
Thimbleweed Park creators made sure all the graphics are limited to the 80s era, but they perfected all the details of the animated characters and the scenes. They added voice, special effects, and music that still makes you feel it is the 80s. They also expanded the game to support international speaking game players. They added innovative ideas including Kickstarter backers could record a voicemail which can be played back in the game when a character in the game dials a number from the phonebook. Other game backers would send some text of books which the developers then add to the library scene in the game. The game also includes entertaining puzzles such as ones that make use of the microwave or the air blower in some bathroom or some berries in the forest. Some puzzles are challenging but have an “Aha!” moment when some character makes a phone call while the other character does something else. I am not giving details because I don’t want to ruin the game for those that would like to play the game. While the game itself was so innovative and entertaining, the conversations between the developers in the podcasts were geeky sometimes but and most of the times were like normal discussions that can be taking place between friends in your backyard.
The recording of the podcast episodes started at the same time the game was getting developed and continued throughout the development stages. Like in any typical development process, things start with early ideas and preparation work. The creators do not disclose the details of the game in the podcast because they do not want to ruin the story before the games get published. It made listening to the podcast episode as adventurous as playing the game especially when I started listening to the podcast after the game was released and while I was playing it. Unintentionally, you would relate the actual game with what is being discussed in the podcast. Sometimes you would hope to find clues about the game even though the game itself as an option for you to ask for clues. Moreover, you would start to wonder how the developers are organizing their work – one is the artist, another is the developer, and a third is the project lead and is also an artist and a developer.
The game creators talk in the podcast, and we listen. They call out specific feedback received from their Kickstarter backers and discuss it. Hence, you feel users’ voices are added into the podcast. Sometimes they invite other members of the team working on the project. The episodes frequently include humor and nostalgia moments from the past. Even their personal lives would get shared on the call. As the episodes progress, they share concerns about release timetables, bug fixes, issues with platform rollouts, and different problems which are not uncommon in any project. In general, the episodes felt human and not some business production, so why all this important? The authentic experience of playing the game and listening to their thoughts and interactions throughout the lifespan of the podcast that ran in tandem with the game development made me rethink about how innovative thinking, natural human behavior, and organized execution can generate amazing results.
When the efforts by the developers were rewarding to its creators and its players while at the same time it was fun and challenging then why not take more of such lessons and apply it in corporate innovation. Key takes that I learned from Thimbleweed Park the game and the podcast:
- Nothing is impossible but don’t be overly ambitious. Even though the developers and the artists were masters in their field, they did not go overboard with the project. They stayed faithful to what they wanted to do and did it exceptionally well.
- They dedicated regular feedback channels for their customers. They allowed their users to suggest ideas but made the call whenever a draw occurred on which idea to pick. They also gave an option to their Kickstarter contributors at a specific level to be part of the game by letting them record their voicemail which you can listen to in the game if you dial the person’s name and extension located in the game’s telephone book. That is cool and original.
- The podcasts were very entertaining and informative. They didn’t shy away from discussing their past or sharing their concerns about the game development progress. A great lesson learned about honesty and humbleness.
- The game itself had lots of challenging puzzles but also include an option to get a hint. Just like any product, you always need some guidance when you get stuck.
- The story of the game is long but not long enough to give up. There was still something in the game that pulled you to continue playing. Even when you leave the game for days and then return, you can quickly get back to the same rhythm before you left the game. The user experience is excellent. Design a product with an intuitive user interface that makes it easy for you to return to where you last stopped and can help you recall what you should be doing next.
I can think of other ideas that one can learn from playing such a game. But at the end of the day, I can summarize it all as: design something as intuitive as playing some game, have fun doing it and let the users enjoy what they are doing with the product, be honest, do not over commit but do not underachieve either. One last thing, play the game!
Game information is available at https://thimbleweedpark.com
Note: images are copyright of Thimbleweed Park.
A common past/present/future dilemma in the professional space is what I learned from yesterday, which job is available today, and what to learn for tomorrow. It gets more complicated as career and family building kicks in, and even more stressful as a person’s age. If you can imagine Past, Present, and Future as building blocks stacked on top of each other, Future bottom, Present in the middle, and Past on top, and the height of each set equals the years of experience, things get interesting.
If you have been in the industry for a long time, the long years of experience make the Past blocks taller and heavier and put more weight on Present and Future underneath. The set of Future blocks tend to be less in quantity, and the set of blocks that stand or break the stack would be the Present set of blocks. Hence, things get fragile….
The converse when you are in young in the field, your set of Past building blocks are much less in size than the future ones; your Present blocks have a tougher situation. The first set of Past blocks would not have enough pressure over the Present blocks, and the Future blocks are numerous, and, subsequently, harder to pressure.
Either way, the Present blocks are in a sensitive situation – pressure or not pressure from Past blocks, and break or make the Future blocks. Furthermore, the middle set of blocks constantly form some kind of balance between Past and Future unless some external force or King Kong tumbles the whole stack apart.
So what do you do if you want to an instructive Past, a less fragile Present, and a healthy stack towards the Future?
I don’t think I have the right answer, but I have a personal one instead. We can’t change the number of blocks that we stack as our experience throughout our lives from past, present, and future, but we can influence its quality. Think of playing constructive-building Minecraft rather than destructive-style Fortnite. Which type of blocks do you want to build – gold, steel, wood, shiny, cracked? How do you want them stacked? Horizontally, vertically, or both? Do you want to build a castle or a fort or a pyramid? Do you want something that is a work of art or science or a hybrid? Do you want to spend a lot of time making every block perfect or have fun stacking things? The ideas can go on and on… Last, play Minecraft as your career building strategy. Stop wasting time destroying things as in Fornite.
There are two types of people. Those who give more than they take, and those who take more than they give. The ratio between give and take can vary from zero to infinity such as zero giving and all taking or no giving but all taking. I think that knowing where you stand in such a formula can make a huge difference in one’s own life accomplishments and everyday human interactions. Life nurture such as experience can dynamically and actively influence the change in ratio between giving and taking, while life nature, basically age and genetics, can yield an uncontrollable and more slower impact or hardly a change in behavior. In couple of weeks people will once again plan their new year resolutions. Do consider the giving versus taking ratio formula for the years to come. Hopefully it should be seriously more on the giving rather than the taking side, not 50/50!
The big challenge to stay on top of your game is to stay focused, be organized, and keep learning. When you are young, supervised learning is the way to go but it gets harder with unsupervised learning as you age. Hence, to keep us humans fit just as machine with deep learning are these days, I believe that reinforcement learning is the way to go for humans and machines alike so as to continue advancing together. Learn from mistakes, think of alternative paths, and stay positive on every track. (last minute thoughts before heading to the gym in the morning and later to work 🙂 ) #machinelearning #humanlearning
Last Thursday we presented “Applied AI/ML in the Workplace –
Geek Food for Thought” at the University of Texas in Austin Computer Science department. Thomson Reuters is one of the Friends of the University of Texas at Austin that gives students an excellent opportunity to engage with the industry and learn more about companies that offers internships or job opportunities.
The speakers were me and Katherine Li, data scientist in my team. Special thanks to our co-workers and UT Austin alumni, Cameron Humphries, Director of software engineering, and Matthew Hudson, software engineer at Thomson Reuters. Also special thank you to Jennifer Green, senior talent acquisition partner in Thomson Reuters HR, and Ana Lozano, events program coordinator at UT Austin who helped set up the talk. More importantly, thank you UT Austin students for attending the event knowing that we missed more students because of conflicting class schedule and mid term exams.
I first talked about Thomson Reuters the company with a 100-year history, a global company, and its top-notch technology and careers development programs. I ran a video of our CEO and president, Jim Smith, explaining what makes Thomson Reuters Thomson Reuters. I then highlighted who are founding fathers of Thomson Reuters, beginning with Paul Reuter who founded Reuters News in 1851 and Roy Herbert Thomson who founded the company in the 1930’s which later became known as Thomson Corporation. Both companies later merged in 2008 and became Thomson Reuters. I hope to have made my point to the young audience that the Thomson Reuters founding fathers, Paul Reuter, who pioneered telegraphy and news reporting starting with pigeon posts, and Roy Herbert Thomson, First Baron Thomson of Fleet, were both entrepreneurs at a similar age as them.
I then provided an overview of Thomson Reuters Labs and listed some of the key innovative products including the latest WestLaw Edge, the most advanced legal research platform ever. I then moved to talk about AI and ran a video for our TR Labs CTO, Mona Vernon, speaking to The Economist early this year about AI and machine learning revolution. That was a great segue way to the main topic of the presentation, and that is applied AI in the workplace.
Through a couple of slides, I tried to make the point that students in the field of machine learning and artificial intelligence need to consider applying existing algorithms for their projects or their next start-up idea instead of building everything from scratch. It is quite understandable that students need to understand or even seek too contribute to the advancement of the core algorithms in the artificial intelligence. That is great and is very important but, unfortunately, it does not always lead to the next innovation or the next best product out there. The markets are hungry for applying artificial intelligence in the quickest time possible and in all the different ways that would have a societal impact. To illustrate the point, Katherine Li and I showcased four projects that leverage machine learning and natural language processing algorithms. We managed to get the applications working in a short time because we leveraged available cloud-based solutions notably Amazon AWS and Google Cloud and added our code for the projects. By spending less time building machine learning algorithms, we were able to focus more on the ideas and tie the different components into working prototypes.
You can check the presentation on this DropBox link (note: please download the deck and run the slides in presentation mode so that you can access the videos)