...by Daniel Szego
"On a long enough timeline we will all become Satoshi Nakamoto.."
Monday, August 29, 2016
Sunday, August 21, 2016
Current trends of social platforms, like Facebook, LinkedIn, WhatsUp try to extend in some way the original human social communication. However, they seem to be pretty much ad-hoc for the first sight. What is missing somehow the systematical analysis: these are the drawbacks and awkward of the human communication and social interaction, these are the points that can be done better with different IT systems and as a result these are systems that are available.
As at the end of day all of these systems are extensions of the human interaction, we might as well call the whole field as Social as a Services.
Artificial intelligence has got a long history of trying to achieve a computer program that can match with humans in thinking, like passing Turing test, beating humans in games like chess or go. As it is certainly an ambitious research direction, there is another direction that is much more practical and probably business oriented as well. As opposed to create thinking machines it would be similarly exciting systematically analyse the limits of the human thinking and focusing on extending it with different kind of IT support, like brain computer interface, extended memory, additional external knowledge for unknown domains. As there are already some achievements in this area they seem to be rather island solutions, there is not seem to be a general platform for that. It would be more existing somehow mimic the mobile app platforms and provide a basic brainware computer interface and provide the possibility to write custom Brainware apps or custom Brainware plugins on top. Considering that the platform is probably supported by the cloud, we might as call as Brainware as a Services.
Tuesday, August 16, 2016
Recent trends in cloud computing shows the direction of integrating several artificial intelligence and machine learning tools into a cloud platform. From the Microsoft side tools like Cognitive Science, Azure machine learning, or Cortana Analytics provide machine learning and artificial intelligence in the cloud. Similarly tools can be found from AWS, like Amazon Web Services Machine Learning. In this sense, it make sense to identify the whole area as Artificial Intelligence as a Service, or rather Cognitive Science as a Service or just simply Machine Learning as a Service.
On the other hand applications can be found as well, that use intelligent cloud services to achieve certain domain specific tasks, like intelligent thread analytics from Microsoft.
Wednesday, August 10, 2016
Well investing into Concurrency is pretty much risky, it is not a bad idea to know at least something about concurrency before you invest. For that topic I would propose the following perhaps rather funny flowchart.