That said, for MIT, which in some ways is trying to catch up with schools like Toronto and Stanford in AI research, particularly in deep learning, it makes a lot of sense to take the $240 million from IBM to create a dedicated AI research center.
I think they have a shot at becoming an important 'center of gravity' for AI research in the East Coast.
That's the metric for cool AI functionality? The Watson query tool is basically a search engine with a layer of (not super reliable) text synthesis over it. It would be more interesting if they took away everything except the document search and passage extraction stuff, and just presented that.
Imagine one person given the task of rewriting the Windows operating system in Java. This one person team won't benefit from more programmers? Of course the project will be completed faster, in this case, with more manpower.
It always results in a period of reduced progress due to drag on the existing staff to onboard the new staff; and the bigger the scale up, the longer that period where you are behind where you would have been without it is. And the more you scale up, the more you need to reorganize and build new coordination infrastructure to make use of new resources even once they are up to speed technically, which also takes time to set up and time to acclimate staff to the new organization and teams, which creates its own drag.
In realistic scenarios, this pretty invariably means late project + more resources = later projects.
But, sure, there are extreme situations where that wouldn't be true, but I don't think they pop up often in practice. One should be extraordinarily skeptical of any claim (or interior intuition) that the rule doesn't apply to your project.
Then again, it's always going to be this debate of engineers clamoring for better engineering and consultants clamoring for flashier powerpoint decks, animations, and other gimmicks.
Good technology (executed with an end-business goal in mind) delivers real value, and that real value is what will sell in perpetuity. Otherwise, you can only go on fooling people for so long...
I would be curious to see how the MIT academics play with the IBM consultants / engineers. Would be curious to hear anyone's comment on the inside of this closely connected.
Almost certainly, the IBM engineers they play with won't be the typical contractors customers normally see. They'll be high-quality and knowledgeable.
Just finished reading about Facebook and Microsoft launching a joint AI effort not five minutes ago. To those enmeshed in or working in AI research: are these joint efforts a response to Tensorflow and Google?
This seems more straightforward in that IBM has money and MIT has a good reputation and also a lot of smart folks that they may be able to hire.