I have a PhD in AI and I'm having trouble figuring out exactly what's being announced here. Like, check this out:<p>> Building on advanced research in program synthesis (PROSE) and data cleaning, we have created a data wrangling experience (Figure 1) that drastically reduces the time that data scientists have to spend in transforming data for machine learning.<p>Huh?<p>> Figure 1: AI-powered data wrangling in the workbench learns from examples and automatically synthesizes code for data transformations using program synthesis technology.<p>What?<p>> Models can be containerized in Docker and deployed to network edge devices, allowing models to score closer to the event and in real-time. Local docker deployments can be used for debugging, while for scaled out production serving of AI, these containers can be managed with Kubernetes, using Azure Container Services.<p>English, Microsoft. Do you speak it?
Currently reading the work of Hubert Dreyfus. Dreyfus was widely ridiculed in the 60’s and the 80’s for coming out against AI simply on the grounds that it wouldn’t work, but for those decades at least he was certainly right as it turned out. Reading his book “The Power of Human Intuition and Expertise in the Era of the Computer” from 1983 is haunting and eerily sounds a lot like today.<p>>“AI entrepreneurs and researchers will climb a tree, sometimes even a tall one, and then tell you they’ve got all the workings of a space program”
Sounds like Microsoft is trying to make a big push specially considering the 8000 strong number in their AI division. Interesting juncture as they seem to have an opportunity to catch on. I hear there is a holy war within Microsoft where one sanct feels Windows and Office are still the bread and butter and therefore all AI related investment should go in the direction whereas the other sanct is pushing towards independent offerings through Azure like Cognitive Services,
This is awesome! I've been waiting for someone to release an Excel-type ML product to make machine learning more accessible. This looks right up that alley, and will probably "democratize" access to ML in a number of fields that tend to be less coding-savvy.
Their Text Analytics offering is still for some reason behind IBM Watson (and I don't even like Watson). Missing: named entity recognition, and multi-label classification (if they did a hierarchial multi-label classifier, the would be amazing).
MS is heavily investing on AI because they missed the opportunity of being #1 on the web and on mobile.<p>However if you go back some decades you will see that Microsoft did have smartphones, before the iPhone, just they weren't as appealing as a product.<p>This time around I predict it will be the same. When you look at the product (e.g: Visual Studio tools for AI) it looks very featured but not very organized... Microsoft needs to understand that more and more features doesn't mean more perceived value.