We are explorers. Since the dawn of man, exploration has been at the heart of our survival strategy as a species. We have managed to colonize almost every corner of our planet, living in seemingly inhospitable conditions by adapting and creating technology. The knife, fire, shelter, farming, and clothing, are so intrinsic to the human experience that we forget that it’s all technology that had to go through the whole RnD process.

Ever since the eery beeping of Sputnik was heard by people all over the world, the race to colonize space has been on. Man set foot on the moon in 1969, and things seemed to slow down in the public eye, but world governments and private companies have been slowly and steadily working behind the scenes, developing the technology that would be needed to control space and establish a presence. All the recent technological advancements of the last few decades especially in miniaturization and solid-state technology can be credited to this silent space race. The proof is in the smartphone/laptop that you are using to read this right now.

Space exploration is in the news again and this time startups are taking the lead. SpaceX and Blue Origin are just the more well known of thousands of next-generation privately owned space companies from all over the world. From space transportation and logistics and asteroid mining to deep space and terrestrial imaging, there are startups tackling every aspect of space exploration.

The main driver for this new boom in the space industry seems to be a combination of extreme miniaturization of hardware using solid-state manufacturing techniques, and the recent boom of super-efficient AI’s created using Machine Learning.

Machine Learning is changing everything. Robots and algorithms can be trained to do things that even we don’t know exactly how to do. The lack of explicit instructions makes the system an approximate one but one which far outperforms written instructions when it comes to doing tasks that are so complex that writing instructions for it is physically impossible. Machine Learning tackles the main reason rocket science is considered hard. The sheer number of dynamic variables that need to be considered with millisecond accuracy.

Whether it is self-landing reusable rockets, automatic docking or efficient orbital mechanics, it is not hard to see how Machine Learning is going to be one of the main drivers for making space accessible to everyone.


-Triman S Bhullar

Software is one of the most complicated things people build. There are very few other things that require this level of perfection, with so many moving parts and changing in real time.

Practically, we have come to accept that absolute perfection is unreasonable to expect and bug detection and fixing is a major part of the software development process. Software bugs have been notorious for embarrassing delays in multi-billion dollar projects like the case of the F35 Lightning II (Joint strike fighter), and we need an effective way to mitigate, detect and fix these bugs if we want to be creating more and more complex software in the future.

Writing clean, organized, modular and readable code is one way to make this process easier. Many automated bug fixing and testing tools are also available. But these mostly use conventional heuristic search to detect bugs. The main disadvantage of this is that the system cannot detect method-invocation related bugs or prioritize between a large number of patch candidates and the patching has to be done manually.

Fujitsu, Japanese based Tech Giant has successfully used machine learning to create an AI that will completely change our approach to the development process, eventually making bugs, a thing of the past. Expected to launch in 2018, Fujitsu’s tool uses Big Data to train AI models to detect and fix bugs in object-oriented languages that are used in large-scale business applications including JAVA. The system is has proven itself to be much more effective than current tools for single fault location bugs, also detecting and fixing method invocation related bugs that traditional tools cannot.

Besides the hype, Machine Learning is fast becoming an essential part of our problem-solving strategy, allowing us to surpass our limitations and augment our abilities to an extent never before imagined.


-Triman S Bhullar

Machine learning is completely changing how software is made, and with the recent data boom caused by Smartphones and Social Media, a whole new world of possibilities has opened up with regards to what can be achieved using software.

Creating and using technology is an intrinsic part of our survival strategy as a species and Design and Engineering are the tools we use to problem solve our way through existence on our hostile and turbulent planet.

I have always approached Design from a very functional and practical point of view. If all the functioning and efficiency is taken care of with great attention to detail, usually, an unexpected but beautiful and appropriate design automatically emerges, which is usually more beautiful than anything that can be just made up by us mere mortals.

Airbnb recently showcased an AI built using Machine Learning that can instantly interpret rough sketches into workable prototypes for UI/UX Design. From what I have seen online it looks amazing and gives us a very small glimpse into what is coming.

Link: https://airbnb.design/sketching-interfaces/

I see a future in which software writes itself. The building blocks for truly General Purpose AI are falling into place and we at Silstone Group want to help you be part of the revolution.


-Triman S Bhullar