@Scale conference

There are hundreds of tech conferences around the world and everyone is different. One of them, @Scale, is a series of events for engineers who build systems working inĀ huge scale. Systems which handle traffic from millions of people, have extremely complex infrastructure or are maintained and developed by tens/hundreds of software engineers.

Not everyone or every company will be there. But some of us for sure. If you want to be ready (or you are just curious), I highly encourage to see video recordings from lates @Scale Conference which took place atĀ San Jose Convention Center, 31st of August.

https://atscaleconference.com/videos-articles/

(Video) Abstract: The Art of Design Best invested binge-watching ever

According to Wikipedia:

Binge-watching, also calledĀ binge-viewingĀ orĀ marathon-viewing, is the practice of watching television for a long time span, usually a single television show.

It’s Saturday. Sometimes you are simply out of fuel and the only gas station is your couch. So if there is no help for you and you need to spend all day (binge-)watching TV, here is my proposition to not feel guilty about wasted time tomorrow:

Abstract: The Art of Design

It’s always great to see inspiring people. True passion, devotion, purpose, creativity – this is what Abstract is about.

My favorite episode:Ā Tinker Hatfield, the man behind Nike Air Max and Air Jordan.
But to be completely honest, all others are equally good. You won’t regret watching any of them!

Moravec’s paradox

There is a discovery in the field of AI, called Moravec’s paradoxĀ which tells that activities like abstract thinking and reasoning or skills classified as “hard” – engineering, maths or art are way easier to handle by machine than sensory or motor basedĀ unconsciousĀ activities.

It’s much easier to implement specialized computers to mimic adult human experts (professional chess or Go players, artists – painters or musicians) than building a machine with skills of 1-year old children with abilities to learn how to move around, recognize faces and voice or pay attention to interesting things. Easy problems are hard and require enormous computation resources, hard problems are easy and require very little computation.

Researchers look for the explanation in theory of evolution – our unconscious skills were developed and optimized during the natural selection process, over millions of years of evolution. And the “newer” skill is (like abstract thinking which appeared “only” hundredsĀ thousands of years ago), the less time nature had to adjust our brains to handle it.

It’s not easy to interpretĀ Moravec’s paradox. Some tell that it describes the future where machines will take jobs which require specialistic skills,Ā making people serving anĀ armyĀ of robotic chiefsĀ and analysts. Others argue that paradox guarantees that AI will always need an assistance of people. Or, perhaps more correctly, people will use AI to improve those skills which aren’t as highly developed by nature.

For sureĀ Moravec’s paradox proves one thing – the fact that we developed computer to beat human in Go or Chess doesn’t mean that General Artificial Intelligence is just around the corner. Yes, we are one step closer. But as long as AGI means for us “full copy of human intelligence”, over time it will be only harder.

(Video) 1% better every day

How to achieve long term goals? Continuously make small steps toward a success. If we use the power of habit, we’ll automate a process of getting better, every single day.

Do you want to decrease the number of times when you open social media from your device? Remove Facebook/Twitter/Instagram from your launch screen and make sure that you need to tap at least a couple of times to get there.
Design something to make your good habits easier to achieve and add more steps between you and bad behaviors.

Do you have 25 minutes more? See these and many more hints from James Clear about how to be 1% better every day.

 

Face Id

Yesterday there was another big day for Apple. During their “Special Event” (The first-ever event at the Steve Jobs Theater) we could see new Apple Watches, TV and iPhones, including the most advanced and desirable – iPhone X.

Among all new awesomeness: edge-to-edge screen, Neural Engine (piece of hardware dedicated for Machine Learning computations) or Animoji, there was something that can be the bigger revolution than we could think.

Face Id

Thanks to Face Id we will be able to unlock our device just with our face. Face recognition will replaceĀ Touch ID, fingerprint based authentication method – also for Apple Pay. Really complex hardware powered by machine learning solutions will keep our device and our money safe.

Will it work and be reliable enough? We’ll see in next months.
But there is something else worth noting. For the first time, secure device won’t ask us for authentication. There will be no instruction to place your finger or provide your pin/password. Instead, in most cases, iPhone will do it for us, automatically.
Such a small UX thing, but such a big change. You will need to do absolutely nothing and still, you will feel safe and secure.

Of course, probably there will be hacks and imperfections. But the first step toward password-free future was already made. And again, nature did a job for us, making each person unique.

(Book) The Tale of the Dueling Neurosurgeons

Yesterday I published my brief summary of DeepMind’s paper “Neuroscience-Inspired Artificial Intelligence” – publication about how much different fields of AI are inspired by research in neuroscience.

If you are a techie person like me and you don’t know much about the human brain, there is a really great book which I would like to recommend:

The Tale of the Dueling Neurosurgeons by Sam Kean

It’s not only full of informationĀ about processes happening inside our heads or roots of our behaviors. It also shows how do we actually know what we know about our brain.

If you have at least general knowledge about AI, you will find a lot of similarities between engineering and biology. Definitely worth reading to broaden your horizons!

 

Where does AI comeĀ from? Summary of ā€œNeuroscience-Inspired Artificial Intelligenceā€

As a technical people, we usually see AI solutions as a bunch of really smart algorithms operating on statistical models, doing nonlinear computations. In general something extremely abstract, what its roots in programming languages.
But, as ā€œneural networkā€ term may suggest, many of those solutions are inspired by biology, primarily biological brain.

Some time ago, DeepMind researchers published paper: Neuroscience-Inspired Artificial Intelligence, where they highlighted some AI techniques which directly or indirectly come from neuroscience. I will try to sum it up, but if you would like to read full version, it can be found under this link:

https://deepmind.com/documents/113/Neuron.pdf

Roots ofĀ AI

One of many definitions describes AI as hypothetical intelligence, created not by nature but artificially, in the engineering process. One of the goals of it is to create human-level, General Artificial Intelligence. Many people argue if such an intelligence is even possible, but there is one thing which proves it: itā€™s a human brain.

It seems natural that neuroscience is used as a guide or an inspiration for new types of architectures and algorithms. Biological computation very often works better than mathematical and logic-based methods, especially when it comes to cognitive functions.
Moreover, if current, still far-from-ideal AI techniques can be found as a core of brain functioning, itā€™s pretty likely that in some time in the future engineering effort pays off.
At the end, neuroscience can be also a good validation for existing AI solutions.

In current AI research, there are two key fields which took root in neuroscience ā€” Reinforcement Learning (learning by taking actions in the environment to maximise reward) and Deep Learning (learning from examples such as a training set which correlates data with labels). Continue readingWhere does AI comeĀ from? Summary of ā€œNeuroscience-Inspired Artificial Intelligenceā€

Google Home at home šŸ 

Voice interfaces are slowly showing up in our lives. In most cases, they replace complexity of mobile devices. But there are also new features which do make sense only when they are used just with our voice.

To see quick summary where Google is with its Google Assistant take a look at this video from last Google Developers Day (starting from 33:00):

Continue reading “Google Home at home šŸ ”

3 great TED talks about Artificial Intelligence

Artificial Intelligence is here. Still in its very limited form, but there are more and more places where we, as a humanity are soundly bitten by ā€œintelligentā€ machines. From the simplest calculators which are hugely smarter than us in maths, to Google TranslateĀ which can translate whole sentences, keeping proper grammar and human-like language better than most people in the world.

Yes, AI will take our jobs, it already does. But should we be afraid of it? I believe, we shouldnā€™t. Instead, we need to adapt to the new reality as it happened many times in humankind history (agricultural revolution, industrial revolution, digital revolution ā€” just name a few).

Some call it another revolution (4th industrial revolution?), some just an evolution which has been happening since the world began. But no matter how you call it, thanks to machines and different kinds of artificial intelligence weā€™ll for sure reach a new level as a humanity. There is so big potential in us ā€” we all have passion, purpose, dreams.

Now just imagine what can happen to the world when there will be something that can replace us with tedious, repeatable tasks. Or if we could boost our creativity and passion by a help from machines and algorithms which are never distracted and can work unstoppable.

Of course, the transition to ā€œthe new worldā€ will be hard. Adaptation will require revolutionary, global changes in how we live. And to start doing this we need to understand where we are and what is coming.
There are already people in this world who are trying to do this. Here are 3 of them, standing in front of us on TED stage and telling us about future of AI and humanity. I highly encourage to invest 45mins to catch-up what they wanted to share with us:

Throwback Thursday – building mobileĀ app

About one year ago I had a privilege to share my experience with mobile dev community atĀ MobiconfĀ conference in Cracow. Because of my introvert nature, it was a big personal challenge to stand next to a couple meters high screen and talk to the international audience. I also donā€™t like to watch my video recordings, but having in mind the message which I wanted to share, I believe that itā€™s good to remind this particular one from time to time.

As developers (and engineering team leaders) it is always good to remember what is the biggest value we can give to the company. In a time of data driven development, where companies constantly learn about their users and try to adjust the product to meet expectations I believe that the most important thing is the ability to iterate fast. To bring new value in the smallest release cycles with a product free of bugs.

And this is what my presentation is about. Why we should test, use dependency injection or automate delivery process. I show Android app as an example, but the same rules can be applied to iOS or any other client side platform.

Here is video recording from my talk: