This week's book giveaway is in the OO, Patterns, UML and Refactoring forum. We're giving away four copies of Refactoring for Software Design Smells: Managing Technical Debt and have Girish Suryanarayana, Ganesh Samarthyam & Tushar Sharma on-line! See this thread for details.
I am not sure if this is the right forum for this message, but I felt are many teachers/professors who would have experience in help cross-disciplinary topics, please excuse if my posting in a wrong forum.
I am searching for a topic for my Mphil degree in management, I like to work on Ai technologies but the topic or research area should cover Ai as well as management, it would be really great if any one suggest areas where Ai and management intersects
some topics that I came across is
1.) Decision theory - Decision support system - Ai based DSS systems
2.) An study of Ai winter and impact on start-up already done :- If it works its not Ai
I would be really grateful if anyone can help identify topics that are hot and have good potential.
Well I'm no PhD., but way back in the 90's I wrote a lot of commercial expert systems.
One thing I wonder about is why some of the AI technologies that were developed 20 or 30 years ago aren't in more popular use today, given the enormous increase in computing power that's currently available. Back when I was involved in expert systems performance was always one of the key issues, and it seems that between then and now we've probably benefitted from what, maybe a 1000 fold increase in computing power?
Spot false dilemmas now, ask me how!
(If you're not on the edge, you're taking up too much room.)
Joined: Jul 04, 2008
You are correct, I have some discussion on the same lines and I feel the reasons may be due to the following :-
1.) In early days the Ai was too-much hyped as panacea for all problems in fact the name Ai itself created an expectations that could never been matched with the current level of technology - this let to extreme disappointment and disappearance of funds in-turn caused infamous Ai winter.
2.) Ai was initially assumed to be something of problem-solving using smart/ special algorithms- many of them were narrowly focused on a particular tasks thus were not applicable in generalized manner.
3.) Ai unfortunately was handled more as a applied engineering discipline rather than a science, it did not have enough time to mature towards market expectations.
4.) ideally Ai should have started as a science/philosophy then slowly matured towards an engineering discipline - but things have been tried in reverse...
My professor feels sad when he talks about research in Ai and in computer science as nowadays research is more towards applied science & engineering and
not many are working pure computer science.
It should be noted many bright people are opting for research/career in connectionist Ai which has produced excellent results in limited scope.
He feels unless Symbolic Ai is revived in academics it would be tough to come out of Ai winter.
I’ve looked at a lot of different solutions, and in my humble opinion Aspose is the way to go. Here’s the link: http://aspose.com