Homepage of Armando Vieira

Applying Neural Networks to Solve Real Problems

I’m a PhD Physicist turned into a Data Scientist and Artificial Intelligence consultant with an entrepreneurial mindset. Passionate about how to make Machine Learning projects work for organizations and how to build great AI based products.

As algorithms are becoming a commodity, the challenge is not building them but using them to solve real problems.

Pioneer in Deep Neural Networks with this publication in 2003 (cited in the recent review on Deep Learning by Jurgen Schmidhuber) and a more recent one on Knowledge Representation on Graphs with Convolutional Neural Networks and Prediction of online user behaviour on an ecommerce site.

Presently finishing a book “Deep Neural Networks: Overview and Business Applications“.

More on my Linkedin profile.

Armando Vieira

My presentation at EARL conference, London 2015:

Portfolio of Customers

15
SEP
2016

Chief Data Scientist Forum – conclusions

I was recently invited to speak at Chief Data Scientist Forum. (See my presentation here). It was a very interesting event to discuss implementation of Data Science into organizations. Data Science brings huge opportunities, but making it work in established organizations is far...
02
SEP
2016

The Art of Data Science

Data science is much of an art as a science. Building a model with top performance in clean datasets with well-defined goals is super cool. But the real test is dealing with the messy world, full of biases, dirty data, and fuzzy or unspecified goals. To survive you need more than...
06
JUN
2016

Ethics in the age of intelligent machines

As machines become more advanced, the implications in business and society will be enormous. The unfold of interaction human-machine is hard to predict but one thing is clear: we will have to teach machines ethics. Teaching human ethics to a non-human entity is the challenge I...
05
JUN
2016

Nassim Taleb Commencement Speech @AUB

Acute and inspirational. This is the type of people that I take lessons from. Speech by Nassim Taleb – Distinguished Professor of Risk Engineering, NYU May 27, 2016: “Dear graduating students, This is the first commencement I have ever attended (I did not attend my...
20
MAR
2016

Why AlphaGo is a milestone but it still not achieved AGI

Congrats Google Deepmind. You did it! Top rank player of Go is no longer a human. Should we rejoice or fear this formidable feat? Is this milestone the start of the end game in the quest for Artificial General Intelligence (AGI)? My short answer is yes and no. First, some...
17
MAR
2016

AlphaGo Part III

What is the problem in reaching AGI? Haven’t machines proved powerful enough to solve all hard problems we through to them: locomotion, playing games, driving cars, translation, even cooking. So, we are already there, aren’t we? No. The problem I see can be stated in...
17
MAR
2016

AlphaGo – Part II

AlphaGo – Part (II) ANN research were confined to a few ghettos, most prominently, Geoffrey Hinton in Toronto, Yann LeCunn in New York, Yoshua Bengio in Montreal and Jurgen Schmidhuber in Losano. They worked hard to solve a fundamental problem in ANNs: how to train deep...
04
FEB
2016

Open Source Libraries for Deep Learning

There are many open source libraries available: Caffe TensorFlow, Theano, and Torch.   Caffe is one of the first deep learning toolkit, started in late 2013, mainly used for convolutional neural network and still actively used. However, it doesn’t support recurrent networks...
27
JAN
2016

Symbols and meaning

I just come across a recent publication of Nate Soares by the Miri institute https://intelligence.org/files/RealisticWorldModels.pdf concerning a theoretical framework on artifical cognitive agents building models of the world. The author refers to the Solomonof induction problem...