"What’s special about us?" Harvard computational science symposium on Brain+Computer systems

On Friday, January 22, 2016 I attended a very interesting symposium organised by Harvard University Institute for Computational Science on “BRAIN + MACHINES: EXPLORING THE FRONTIERS OF NEUROSCIENCE AND COMPUTER SCIENCE”.

Although it fell outside my main research fields, I found it very interesting and enlightening. And the discussed topics could also imply some crucial role for modelling practices.
The introductory speech by David Cox, addressed the role and span of brain studies. First, he pointed out that when we say we want to study the brain, at a deep level, we say we want to study ourselves.
Indeed, we all perceive human species is special. But why is that? We are not the biggest, longest-living, most numerous, most adapted species. We simply cover a niche, as any other species.

What’s special about us is the complexity, not in general sense (nature is plenty of complexity), but specifically complexity of our brain.
Our brain includes 100 billions neutrons, and 100 trillions connections.
We are able to deal with complex information in incredible ways, because each neuron is actually a small computer, and globally our brain is enormously more powerful than any computer built so far.
We therefore build clusters of computers. But this is still not enough to obtain the brain power, we need to understand how brain works, to treat and replicate it.
Typical and crucial problems include to study: vision and image processing, positioning and mobility, and so on.
That’s where I think modelling can play a crucial role here.
As we clearly pointed out in our book Model-driven Development in Practice, modelling and abstraction is a natural way of working for our brain. And I got confirmation from renowned luminaries from Harvard today.
I really think that, should we discover the modelling approaches of our mind, we could disclose a lot of important aspects of several research fields.
Just imagine if:

  • we could represent human brain processes through models
  • we could replicate these processes and apply modelling techniques for improving, transforming and exploiting such models.

This would pave the way to infinite applications and researches. However, one big challenge opens up for the modelling community: are we able to deal with models including trillions of items??

Any further insights on this?

If you want further details on the event, checkout the official website of the symposium here and my storified social media report here.

To keep updated on my activities you can subscribe to the RSS feed of my blog or follow my twitter account (@MarcoBrambi).

Model Driven Enterprise Engineering (TM)

Model Driven Enterprise Engineering (MDEE) is a concept proposed by Know Gravity, a company based in Zurich, Switzerland, that has been active in modeling and requirement engineering since 2000.

They propose a pragmatic approach to integration of OMG and non-OMG modeling specification, so as to cover all the modeling needs of the enterprise (and not only for software).
They come up with a quadrant of 4 + 1 modeling settings, as shown in this slide:

The Model Driven Enterprise Engineering framework and the mapping to the  OMG modeling languages.

The 5 scenarios are named as:

  • Strategy Model (business – what?)
  • Operational Model (business – how?)
  • IT Support Model (IT – what?)
  • Technology Model (business – how?)
  • Management Model

The focus of the approach is mainly in the first stages of design, and especially on requirement, simulation and early prototyping.
The approach is based on integrating and relating together multiple and diverse models, through the definition of a vocabulary (SBVR-based) and integrated metamodel.
It covers project management, enterprise and system document generation, functional requirements, business rules, and many more aspects.
The idea starts from the fact that using single OMG specification doesn’t make much sense, because actually many OMG business and IT specs are complementary and sometimes overlapping. Therefore there is need of alignment on meta entity level and of designing cross-model and/or cross-profile associations.
The current way they do this is to have a profile-based comprehensive modeling tool, that lets you model the various aspects and related them to each other.
In my opinion, this is not that different to the megamodeling approaches.
The good news is that they also plan to fully support IFML (the new OMG standard called Interaction Flow Modeling Language, see also my previous post on standardization here) in the framework by 2014.

Two peculiar initiatives I deem interesting are:

  • they trademarked the concept of Model Driven Enterprise Engineering!
  • they plan to write and publish a book on the topic which will be completely automatically generated out of the models, and will be produced following software engineering processes, starting from use cases, requirements, and so on!

You can find more on this at the company Web site: Know Gravity.

To keep updated on my activities you can subscribe to the RSS feed of my blog or follow my twitter account (@MarcoBrambi).