Video Streaming, Practical Uses in our Lifetime - A Symposium

Video Streaming 

Summary 

Video streaming will have a major impact on our daily life. The impact on us will be much greater than those currently in the workforce. While we are all headed to different places next year, we will all heavily rely on video streaming. This post is meant to start a discussion on video streaming and how we will make use of it in our lifetime. Feel free to post comments on other ways to use video streaming to improve our day-to-day, resistance, and potential pitfalls.

Tools

•Skype
•FaceTime
•HireVue
•Google Hangout
•Company Specific Platforms
•Apps
•More!!!!

Educational

•Online classes
•Group projects

Professional

•Interviewing
•Weekly Meetings
•Telecommute 

Personal

•Wartime
•Healthcare
•Law enforcement
•LDR
•Consider studying abroad, considering enrolling kids in boarding school
•Disabled child
•Banking

Potential Pitfalls

•Analytic screens
•Allows for more interaction
•Takes pressure off of in-person contact
•Saves money
•Network systems and infrastructure
•Less employment
•Future educator

Learn More

Ace Video Interview 

Video Conferencing at Work 

Preparing Network for Video Conferencing - In Depth Technicalities 

Machine Learning Vs. Artificial Intelligence + White Collar Jobs

We've heard these terms get thrown around a lot and I bet we all have somewhat of an idea of what these are. At very least we use them in our lives occasionally. Consumer products like Google Home, Alexa, Siri, and the little paper clip that used to pop in Microsoft Word can all be considered Artificial Intelligence (AI). These little "personalities" are smart, they help us in our daily lives: run searches for us, order pizza for us, and even ask if we need help. So I think the real question is what is machine learning and how is it different?

Machine learning is basically what it sounds like. It's a machine that can teach itself or at very least learn over time. AI that we are familiar with are pre programmed to do specific tasks and those tasks expand usually through software updates (just like new features on your phone). But machine learning is predominately programmed to a broader focus but has capabilities to teach itself new tasks (not to say that it doesn't also get updates).

For example there is a map game that is tested with these types of programs. Basically, there are objects on a map and and the computer is supposed to find them based on directions given. In this scenario AI would be pre-programmed with what North East South and West are maybe coupled with the ability to run objects through a database to determine what is what. Essentially, they can look up what an object is and then determine the directions to get to the object with 100% accuracy (as long as the object exists in the database). Machine learning on the other hand can start with a blank slate and learn from trial and error, failing at first but then learning what North East South and West are and even asking what objects are through language learned.

So what does this mean for white collar jobs? Bad news folks...but maybe not for a while. For now, middle-men are in trouble. Third party services are at risk for machine learning to take over. This makes sense considering middle-men typically offer a connection more than an actual product or service. Third parties connect 2 groups together in an efficient manner but it's being recognized that AI and/or machine learning can do it more efficiently and the costs to do so are becoming more affordable.

Take Uber for example. Their app shows a map of nearby drivers through GPS and always gives you the option to be picked up by the nearest driver. Uber is currently moving this system to third party logistics. Instead of having a consultant call a truck to ship your goods and collecting commission both from you and the truck driver Uber steps in and gives you a map of the nearest trucks allowing you to easily do what you used to pay someone else to do. Machine learning gets thrown into the mix by linking more than one shipping destination and minimizing distance driven, maximizing cargo delivered, all while providing a cheaper rate to both parties.

Another industry that is being affected right now is financial technology (fintech). It's one thing to ask AI to automatically give you all the ratios you want and then pick stocks based on your analysis and criteria for those ratios, but what if you could ask a broader question? What stock will make me money? Machine learning could find statistics and ratios that link up better than what you originally thought. So not only would it calculate and find all the ratios you are interested about but it could suggest more and even perform the analysis without you based off of what it has learned (decades of news, financial statements, and performance history).

Again, we may be in the heyday of AI, but we are only scratching the surface of machine learning. Right now you don't need to fear for your job, but it might be a good idea to stay ahead of the curve and learn to work with machine learning before it starts replacing jobs. I think right now we are at the equivalent to when machines started automating production factories - which shifted jobs from the floor to repairmen for the machines.


Links:
https://www.linkedin.com/pulse/uber-freight-its-just-truck-drivers-whose-jobs-risk-john-mcdermott
https://letstalkpayments.com/15-players-that-use-machine-learning-in-fintech-space/

Trusting Others

From an early age, we've been told to not talk to strangers. However, society has begun to shift its stance on that classic piece of advice. Trusting others has become the norm with the expansion of mobile applications, especially with organizations and apps like Yelp, Uber, Lyft, VRBO, and AirBnb (just to name a few). Last summer, for example, I needed to attend a tech conference in Texas, but all of the hotels in the area were booked, so I turned to Airbnb. Never having used it, I hesitantly booked a room in some guy’s 4-star rating townhouse in downtown Houston. I also moved around Houston via Uber to get from place to place (and never had a problem). This experience went really well and since then, I've been actively looking for other places to stay at and using ride-sharing apps more often. However, I realized that not everyone’s experience is like this. Which brings up many questions, but one of the most important ones being: Who can you trust, and should you?

Who Can You Trust?

The Forbes article "AirBnb and The Internet Trust Issue: Who Can You Trust Online?" asks this question and delves into how people have become so reliant on these online rating systems and applications without taking into considerations the possible outcomes, such as being scammed or putting ourselves in danger. Similarly, "How Airbnb and Lyft Finally Got Americans to Trust Each Other", also puts into perspective how we have become so reliant and trusting, and it shockingly puts into perspective that "We are entrusting complete strangers with our most valuable possessions, our personal experiences—and our very lives. In the process, we are entering a new era of Internet-enabled intimacy."

Along with this new era of trust and intimacy, a new study by Zendrive and Aite Group has found that "jumping in the car with an Uber/ Lyft driver is generally safer than getting behind the wheel yourself" (http://www.fareestimate.com/news/uber-lyft-safety/). If it seems that using these applications have become the norm (and some studies are proving that it is safe), do we have anything to worry about?

Trust and Safety On Both Ends

"Uber and Lyft Drivers Work Dangerous Jobs- but they're on their own" also brings to light something that I hadn't considered. Yes, we as consumers are risking our safety, but those who are providing the service are in just as exposed and vulnerable. The article (mentioned above) looks at some "Uber horror stories" and videos where some experiences are more terrifying than others, such as the Uber driver who was beaten by a drunken Taco Bell executive, or a doctor who tried kicking his driver in the face before trashing his car. These horror stories don't just stop at Uber or Lyft, they also extend to AirBnb and VRBO. The following is a video on an "AirBnb Home Rental Nightmare" on behalf of ABC News:

Why is this controversial? 

While the Internet is connecting us all, and providing ways for us all to move around- whether in others' cars or into others' homes, we need to ask ourselves if we should be as trusting. There are both pros and cons to using these services, and in exchanging information like this. In reality, we don't know whose 5-star rated car we are getting into when we need to go from point A to B. But at times, it doesn't matter, as long as we can get from point A to B. If you take away anything from this write-up, I'd suggest that you consider whose house you're staying at, or whose car you're jumping into, and try to stay safe so that your experience can be an enjoyable one versus a nightmare that puts you in harm's way.

Data Analytics

What is Data Analytics?

According to techopedia:

Data analytics refers to qualitative and quantitative techniques and processes used to enhance productivity and business gain. Data is extracted and categorized to identify and analyze behavioral data and patterns, and techniques vary according to organizational requirements.

Data analytics has come to be a huge part of the business and tech world and as computers and algorithms become more refined the uses of data analytics is endless to create meaning in huge amounts of data, that may otherwise be considered useless.

What is "Big Data"?
Big data simply refers to huge amounts of data that is analyzed using data analysis to create insights.

Why is this a Big Deal?
Recently, Wired posted an article titled, "Big Data and Analytics: The Hero or the Villain". Within the article, they go into the details of how big data analytics is one of the most controversial topics in the tech world today, and its uses with the NSA.  The NSA is able to analyze petabytes of user data in order to gain national security intelligence. The fact that the NSA is able to analyze PETABYTES of data in order to draw strong connections and analysis is absolutely incredible. 

Also, the use of data through online advertising and retailers in which they can target advertising based on your gender, age, likes, dislikes, geographic location, and hundreds of other data points just based on the websites you frequent and items you have purchased online. Remember Amazon's use of "if you buy x item, you might want y item" recommendations.

The Uses of Data Analysis?
Data analysis occurs in almost any industry. Most prominently, it's used in marketing in order to target new consumers for products and services, as well as in the healthcare industry in order to make medical breakthroughs(not Google Flu Trends), simply to help make business operations more efficient, or even in financial trading. Data analytics is even used in the sports industries. For example, in tennis, they use players previous match data to predict the likelihood of them winning the match if they keep their first serve percentage above X percent. The same can be said for dozens of other data points. The use of data analysis is also heavily utilized in basketball and other professional team sports, however, Charles Barkley may disagree.

Why is it considered Controversial?
There are two main controversies surrounding data analytics:  Privacy and causation vs correlation. Privacy has become a huge issue in recent years do to the unfolding of government surveillance programs as well as online data being sold for marketing and advertising purposes.

In regards to correlation and causation: Correlation does not equal causation and causation does not equal correlation. This was an issue that Google faced when they created Google Flu Trends. The premise of the operation was to analyze Google search data in order to predict, better then the CDC, where the flu had hit and will hit. To say that people Googling certain searches means they are sick/about to be sick with the flu is very difficult to prove. Data scientists have to be very careful not to take data and create certain inferences that may or may not be true.

Autonomous Vehicles

Nolan Arnold
Thomas Daniel

http://autonomousvehicles.zohosites.com

What are Autonomous Vehicles?

An autonomous vehicle - is a self driving vehicle that is capable of sensing its environment and navigating without human input.

Autonomous cars can detect surroundings using a variety of techniques such as radar, Lidar, GPS, Odometry, and computer vision. Advanced control systems interpret sensory information to identify appropriate navigation paths, as well as obstacles and relevant signage. Autonomous cars have control systems that are capable of analyzing sensory data to distinguish between different cars on the road. [These links are all Wikipedia sites with definitions of these terms. SW].

This style of vehicles has already begun appearing on the market and will undoubtedly be the future of vehicle for decades to come.

What is Covered Here?

This cite will cover six topics revolving around autonomous vehicles. We suggest you begin your reading with the history of these vehicles before continuing on to the Research Efforts of Tech and Vehicle companies to then read the last two topics of Fuel Economy and the impact of this machinery on Global Warming.

Who is Involved ?

There are countless parties working towards the creation and implementation of driver-less vehicles in many sectors of industry. This impact will change the face of vehicle industry as well modern transportation itself. However, the effects do not end here. This impact will effect the carbon footprint of mankind itself for the better, or the worse.

We would like to thank our multiple sources that made our research possible and thank you for taking the time to read all our hard work.

Safe Travels.

iTunes and Streaming Music

Is iTunes Still Relevant?

When was the last time you purchased a song from iTunes? For me personally it has probably be since the 7th or 8th grade since I’ve purchased a $1.29 song from the iTunes store to be downloaded to my iPod or iPhone. When iTunes came out, it crushed and revolutionized the music industry. The transition from vinyl disks to cassettes to CDs was a relatively linear one when compared to the transition from CDs to iTunes. When iTunes launched in 2003, there was rapid increase in sales of iTunes songs accompanied by the rapid decrease of all other physical forms of music purchasing ways.
Within the last few years the competition has emerged in many ways. Companies that have services that are similar to iTunes and compete in that respect, along with innovative companies that give availability to stream music instead of purchasing songs individually. In this Tech Briefing I will go over both types of competition, how they differ, and how they affect one another.

In terms of music streaming

• Pandora – Pandora is a streaming application that is set up similar to how a radio station is. First, you would choose an artist or a song, and from there it will attempt to play similar songs based on the songs that you listen to. Within the Pandora application, it has an algorithm that has the ability to select songs that are similar (or dissimilar) to the one you are listening to. It does this by giving you, the user, the option to give a thumbs up or a thumbs down. It bases those decisions of up or down to calculate whether or not it will play that song again or take it off the list. It takes these favorable or unfavorable decisions that you made to tweak that station to songs that are only similar to the ones you like.
• Spotify – Spotify is a music streaming application that falls under a freemium business model. What this means is that there are two versions of Spotify you can choose from, Free or Premium. Within the free version you have basic services, which may include listening to the music, and ability to skip a few songs. But with the free version you have ads that pop up every few songs. With the premium version, ads are removed, skips become unlimited, and additional features are included. But of course, with premium there is a monthly charge.
• SoundCloud – SoundCloud is another music streaming application. Similar to Spotify, you have the ability to have the free version with basic features, or you can purchase the premium version for a monthly charge. One of the largest differences that separates SoundCloud from other music streaming applications is the ability to upload your own music to the library that the application has in order for the public to be able to hear it. This is why SoundCloud has the largest music streaming library at the moment.

In terms of music stores:

•  iTunes – iTunes has the largest selection of music and videos, and will continue to do so into the future. Since its inception in 2003, it has always been a leader in regards to the content that it has and offerings that are available.
• Amazon – Amazon is relatively popular when compared to other sites largely because of the other (non-music) services that they offer. This includes watching movies and online shopping, with many families that involve themselves with the Amazon Prime subscription. Prices for Amazon are in line pretty well with iTunes. Having new releases being identical, but slight variation in older types of movies. The main difference for Amazon that stands out is the wide availability across multiple types of devices. Amazon members can stream music and videos to computers, their Kindle, gaming device, and mobile phone all free of charge.

Over the last few years, starting in 2013, iTunes has had a decrease in iTunes sales. From 2013 to 2014 alone they saw a decrease in music sales by 13%. Apple greatly attributes these decreases in iTunes sales to shift in the way of music is being offered. Seeing a shift from the music purchasing libraries to the music streaming services. When looking at the financial statements of Apple, their sales are semi-broken down into categories. 

One subcategory is “Services”, this services category attributes to approximately 8% to 11% over the last 3 years. Noted in the foot notes of the document, “Services” includes revenues from the iTunes store, App Store, Mac App Store, TV App Store iBooks Store, Apple Music, AppleCare, Apple Pay, licensing, and other services. As you can see, I am not able to find the specific percentage that is allocated to the iTunes store only, but will all others taken into consideration, it is a very low percentage of total sales of the company. In order to stay competitive they acquired Beats music, which is similar to a Pandora kind of application, to rebrand and expand their reach. The rebranding began in 2014, and was launched as part of Apple in 2016. The thing to be excited for in 2017 will be the 10K financial statements that will have the acquisition incorporated. We will be able to see the impact it made on iTunes and if they will be able to keep up in the future.

Google Play vs. Amazon vs. iTunes Store
Apple 10-K
iTunes Killing the Music Industry
iTunes Music Sales Plummeting

Virtual Reality Music Experiences

Current Technologies:

360 Music Videos

360-degree music videos give the viewer the ability to control the camera. It allows viewers to experience the video from different angles. If viewers have appropriate browser technology, they can navigate the visuals by pulling on the screen with their mouse or by clicking on the arrows in the top-left corner. There have also created animated 360 music video. The first artists to have utilized the technology include Bjork, The Weeknd and the Gorillaz.

Music Visualizers

Intone Sing music visualizer is a music visualizer game made for the Oculus Rift. You are floating in space that consists of different color blocks. Depending on the sound of your voice, these blocks will change color and move around. Similar technology includes the Harmonix Music Visualizer. This also uses colors and designs but you can choose from your favorite already existing music. One mode consists of the ability to chill on a beach listening to music. You can also create your own visualizer depending on the music. There is also a dance mode allowing you to dance with created avatars. This is made for the PlayStation VR device.

Playthings: Musical VR Playground
This VR technology creates a playground for you to play around with different sounds and create music in a colorful world. You can play music with objects like gummy bears, hot dogs and jelly beans. This technology is made for the HTC Vive.

Upcoming VR Technologies

Amplify VR
This VR technology allows bands, artists and musicians to stage performances in spectacular and breathtaking environments in which the audience is an active participant. It gives you a front row seat to your favorite artist’s concert. The participant can experience a live show in a music video form. The world will change based on the music being played and the environment the artist has created.

 

VRTIFY
This VR technology combines all the previous technologies into one. It allows you to experience all your favorite music in the VR world. It lets you experience all the 360 music videos that have been released. It gives you access to music streaming sites like Spotify and SoundCloud. It gives artists and music producers the ability to create their own channels, where they can manage and distribute their content. It also includes artist interviews and live concerts. As of now this will be released as an Android application.

How Musicians can profit?

“The future will be about entering the musician's world, rather than simply engaging with an individual song

• Partner with ticket sales companies like StubHub 
• Partner with music festivals like Lollapalooza and Coachella 
• Interactive advertising, membership subscriptions and pay-per-view 
• VRTIFY plans on giving 70% back to artists

https://www.forbes.com/sites/cheriehu/2016/04/23/virtual-reality-in-the-music-industry-needs-to-be-a-tool-not-just-an-experience/#268e29766147
http://www.bbc.com/news/business-38795190
http://mbryonic.com/best-music-vr/
http://welcome.vrtify.com/