LEARNING

Panel discussion at “We are Developers”: The Potentials and Pitfalls of Machine Learning

Back in March I was at We are Developers in Vienna, Austria, gave a two hour workshop on using AI on the web, a talk about code not being the answer to everything and MCed on the main stage on the third day. Another fun thing to do was this panel discussion on the Pitfalls of Machine Learning talking about the ethics and the false definitions of AI we have to battle.

I want to thank all people involved:

Moderator:
Jan Mendling ( @janmendling ), Full Professor at Vienna University of Economics and Business

Panelists:
Charlotte Han ( @sunsiren ) , Deep Learning Marketing Manager at NVIDIA
Tuomas Syrjänen ( @TuomasSyrjanen ), CEO of Futurice
Christian Heilmann, Sr. Program Manager at Microsoft
Rainer Steffl, CIO at Mondi Group

If you want to hear more about this topic and learn how to deal with it, I have a Skillshare course out there :

Chris Heilmann giving his course

“Introduction to Machine Learning: Using Artificial Intelligence” is about an hour of materials to get you familiar with the topic of AI.

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New Skillshare course: Introduction to Machine Learning: Using Artificial Intelligence

I am chuffed to announce that my first Skillshare course is going live today! The course is online and comes with a free two month subscription to Skillshare. You can watch it by following this link: http://skl.sh/christian or tapping on my nose in this still:

Chris Heilmann giving his course

Under the title “Introduction to Machine Learning: Using Artificial Intelligence” I have recorded about an hour of materials to get you familiar with the topic of AI.

This is not a hard-core Machine Learning and data science course and I invite anyone with an interest in the topic to participate.

You don’t need to be a developer or data scientist. Instead I wanted to create a series of videos for anyone interested in AI. Consider it a head-start without the hype or complexity other resources on the topic.

In about an hour of simple lessons, you’ll learn about a few of the use cases of Machine Learning and how to apply them to your day-to-day products.

The list of lessons is as follows (video length in parenthesis):

  • Introduction (1:44)
  • What is Machine Learning (5:25)
  • How We Teach Machines (5:48)
  • Machine Learning to Help Humans (5:28)
  • Tools for Machine Learning (3:44)
  • Visual Uses (7:54)
  • Speaking Human (6:07)
  • Audio & Video (6:32)
  • Personalizing Your Machine Learning (5:08)
  • Ethics of Machine Learning (5:32)
  • Machine Learning & Creativity (4:33)
  • Final Thoughts (0:32)

My big idea about this course is to entice you to be creative with the different machine learning/AI offerings out there. Artificial Intelligence is the next evolution in computers and human/machine interaction and I think it is high time to democratise it. For years online portals, personal mobile devices and microphones in our houses have recorded our data. A lot of good has come out of this, like virtual keyboards that learn from our usage patterns or voice recognition that isn’t guesswork.

However, only a few companies use this information to build intelligent, responsive interfaces for our users. In order to take the creepiness out of AI, we should all do this. Human interaction has been recorded for quite a while, isn’t it time we also get much better interaction across the board based on this data?

In this course, I will show how Machine Learning allows for automatic image detection and labelling, facial recognition and using it in an ethical fashion and how to provide interfaces that allow humans to type or say full sentences instead of learning interaction models that are outdated.

The course is available for all Skillshare users, or if you aren’t one yet, you can follow this link skl.sh/christian for two months of free access – more than enough time to finish this course and others.

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Talking about building the next interfaces with Machine Learning and AI at hackingui

Yesterday I was proud to be an invited speaker at the HackingUI masterclass where I presented about what Machine Learning and Artificial Intelligence means for us as developers and designers. I will be giving a similar talk tomorrow in Poland in my Code Europe talk.

Speaking at the masterclass

The Masterclass is using Crowdcast to allow for discussions between the moderators and the presenter, for the presenter to show his slides/demos and for people to chat and submit questions. You can see the whole one hour 45 minutes session by signing up to Hacking UI.

Master Class #4: The Soul in The Machine – Developing for Humans

It was exciting to give this presentation and the questions of the audience were interesting which meant that in addition to the topics covered in the talk I also managed to discuss the ethics of learning machines, how having more diverse teams can battle the issue of job loss because of automation and how AI can help combat bullying and antisocial behaviour online.

The materials I covered in the talk:

All in all there is a lot for us to be excited about and I hope I managed to make some people understand that the machine revolution is already happening and our job is it to make it benefit humankind, not work against it.

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Future Decoded 2016 – My talk on Machine Learning, Terminators and Star Trek

Yesterday I went to the Excel in London for Future Decoded to learn a lot about the future of technology, finally see the DeLorian from Back to the Future and give a talk. I covered Machine Learning, its ethics, its effects on the job market and what we as developers need to do to make Artificial Intelligence work for rather than against humans.

DeLorian from Back to the Future

Apparently it was more relaxing that the Great British Bake Off:

Sadly, there was no video recording, but I recorded my own screencast again. The video is on YouTube

The slides are available on SlideShare.

I will repeat this talk slightly amended and more about the ethics and ideas as the Friday Keynote of the upcoming Øredev Conference in Malmø so see you there?

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My GotoCon Copenhagen talk videos: PWAs and Machine learning for images

The lovely folks at Goto Conference just released the high quality recordings of my talks at their Copenhagen edition earlier this month.

Explaining the power of the link on stage at GotoCon

Fixing the image problem of the web using Machine Learning was a impromptu presentation as one of the presenters had to pull out and they needed another presentation.

Progressive Web Apps – return of the web talks about what PWAs mean to the web as a platform and features lots of Star Wars references.

My next GotoCon will be in Berlin on the 14th of November.

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Learning to code for the Web: The MDN Learning Area welcomes you!

As an aspiring developer or as a teacher looking to extend your knowledge of code, it can be difficult to know where to start with web technologies. In this blog post, we’ll be discussing why we have created the Mozilla Developer Network Learning Area to help solve common learning challenges and get you up and running with web development.

The aim of the Learning Area is to take beginners from “beginner to comfortable”, with HTML, CSS, JavaScript, and other core web technologies. Once you’ve worked through the early parts of the Learning Area, you should have enough knowledge to be comfortable using the rest of the Mozilla Developer Network (MDN) site. In addition to helping you on your learning journey, we anticipate that the Learning Area will extend our readership and contributor base, and in turn improve SEO on the site.

Why the new Learning Area?

Learning the craft of web design and development (and all the related disciplines) has been a hot topic for as long as we can remember. Many web education initiatives and resources have been worked on over the years, and many related problems have largely moved sideways rather than forwards:

  1. There is a shortage of skilled junior web creators coming into the industry.
  2. Traditional educational establishments often tend to be behind the curve in understanding the industry they are sending their students into. It is challenging to keep courses relevant and up-to-date. Many private code schools have appeared to fill the gap left by a lack of quality learning materials for beginning web builders.
  3. The above point is perhaps not so surprising when you consider that industry standards and best practices evolve very quickly, and also that web is somewhat of an orphan — it doesn’t comfortably fit into traditional technical departments like Comp Sci/Software engineering (too many “soft“ skills), or design departments (too much code and scary stuff like that). As a field of study, web is very much a hybrid.

Note: Many of the effective web-related courses at universities that “get it” are found in tangentially-related departments such as business and journalism. And speaking of the “bad” courses, teachers generally do care and want to improve things, but don’t necessarily have the knowledge or time to rapidly iterate on curricula. And the curricula are often slow to change because of bureaucracy.

It is MDN’s wish to help with such problems by producing a reliable set of beginner’s learning materials that will help students understand the technologies the web is built on, and how to use them to create accessible cross browser websites/apps. The MDN Learning Area aims to:

  • Make effective material whether the students are self-directed learners, or part of a structured class.
  • Structure the material loosely so teachers can use it as supplementary material on top of their own curricula, or a basis for new curricula. Too much structure makes the material limiting and not very flexible.
  • Cover a core minimum viable product consisting of HTML, CSS, JavaScript, accessibility, and server-side development basic concepts. The material should represent a standard for web learning and best practices. If enough educators use it, it will provide much needed consistency.
  • Regularly review the material to keep it up to date.

Note: We also want to make the publishing license permissive enough so that others can easily grab and use it in any way they desire. The default MDN license is cc-by-sa, which means that others can republish the content as they wish, as long as they credit the original author, and any modifications are published under the same license as the original, thereby keeping it freely available. The associated code examples are licensed under CC0 (anyone can use them as they wish without restriction).

Where are we now?

While we continue to add to the MDN Learning Area content, there is already plenty of modules that beginners can start to use. For a start, we have a complete beginner’s learning module for those who have no previous experience and only basic computer literacy: Getting started with the Web.

The next stage in the learning journey is our Introduction modules, which teach the real basics of the technologies. So far, we have one for both HTML and CSS:

To follow on from those, we have some further HTML and CSS modules, which aim to go beyond the basics and expand on some of the core applications of those technologies:

Each module has a number of articles to discuss the important features and techniques involved, plus an assessment or two at the end to test your comprehension of those teachings.

We also have a well-developed Glossary, and a list of standalone articles that address specific topics related to the main Learning Area thread, but don’t directly fit into the core learning stream: see common questions.

Future work

The latest module being written is CSS layout, which will cover all of the layout techniques currently in use on the modern web, with advice on what they should be used for.

Future content for the site will also include modules on core server side development basics, accessibility and JavaScript, and possibly other topics too.

Call to action

We are always looking for contributors to help write and otherwise shape the material — with such a small team of writers, it takes time to create all the material. Having extra people on board also helps with making for a better rounded set of ideas, feedback and styles.

If you feel inspired and want to help with contributing to the LA — whether with writing, translating existing material, tech review, copy editing, or other kinds of feedback, please get in touch! We are always happy to curate outside contributions, as it leads to a more rounded, collaborative effort.

We are also really interested in hearing from potential students and teachers that might want to work through the materials and provide feedback on their learning experience.

The best ways to get in touch with us are:

We also have a Trello board that gives an idea of currently available writing projects.

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