Auto news on Youtube Feb 2 2018

[MUSIC PLAYING]

Hi, I'm David Shaw, and our welcome to AI News.

In this episode, learn how Intel can

help you develop applications and solutions

for the next big technology wave with AI.

Also, learn about the world's first fully programmable

deep learning-enabled wireless video camera.

Did you know that by 2020, there will

be about three and a half network devices and connections

for every person on the planet?

A whopping 47% of these will be machine to machine--

that's a huge opportunity for AI developers.

Join Intel's, [? Way Lee, ?] for a one-hour webinars

to help answer questions such as,

why Intel is uniquely positioned to fuel the AI transformation.

What Intel and industry analysts are predicting.

And lastly, how developers can leverage

Intel's end-to-end software and hardware, to deliver

full spectrum AI solutions.

Amazon Web Services recently announced deep blends

its their first fully programmable

deep learning-enabled wireless video camera.

Powered by an Intel Atom X processor,

you can create AI machine learning projects

in a matter of minutes.

Take advantage of the frameworks already on the device.

Check out a few of the sample projects

to help you get inspired.

Thanks for watching.

Don't forget to like this video, and subscribe

to the Intel Software YouTube channel for more AI news.

[INTEL THEME]

For more infomation >> AI News | February 2018 | Intel Software - Duration: 1:19.

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Data analysis software - Duration: 2:54.

The CDS provides access to some software that's only available for

students in the CDS and allows access to text analysis and data analysis

software as well as some GIS software. It is quite a dynamic suite of tools so we

do try to offer open tools as well -- so freeware that's available on the

internet -- so that students can use those after they graduate from university and

into their professional careers they can continue to experience that growth

with different tools. So the tools that I mostly work with are

qualitative research tools -- so I like to work with NVivo. I also work with

different network analysis tools, so I tend to support students using those

kinds of tools to do more qualitative research methods, whereas other

people in our group work with R or with Strata or different types of

statistical modeling packages and they support different students to do

whatever research they're doing at the time. So we've worked a lot with

psychology students at the moment, and they're doing interviews -- so it's around

trying to do some thematic analysis or if they're using grounded

methods to understand and interpret their research data. In a higher

degree area, we have people who are engaging with chat datasets and

analyzing those to be able to provide information back to companies about the

issues over time and geographically that are being raised by their constituents.

In some of the environmental areas we're seeing people using data mapped

geographically looking at rainfall, temperature, instances of infectious

diseases over time and over country, and trying to find correlations between

instances of disease and climate change. There is a lot of data available and

what we do is support the skills that you need to be able to pull those data

sets in and have them talk to each other. That's really what the Centre is about --

it's getting you to be able to work in an environment where the data all comes

into one space and we're able to help you manipulate that data so that you can

start to see the patterns and then you can go on and analyse and draw

conclusions.