Implications of an Improved Lip-Reading Software

Researchers at Oxford University have recently developed a new program called LipNet which uses video frames to put together different movements of the mouth to make sentences which it then outputs as words. While this seems like a fairly simple way of doing lip reading, it has actually been amazingly successful. This new system of reading lips has reached an astonishing 93% accuracy
which trumps the previous best computer rating of 79% and smashes the human expert level of 52%.

The importance of this new software has implications way beyond just another creative example of a computer taking an input and returning an output. The social opportunities are massive for this type of software. From a human welfare perspective, over 360 million people worldwide struggle with hearing problems and a program such as this could drastically improve their lives. Additionally, commercially this software could be incredibly helpful anywhere from reading opposing teams lips in sports, reading the lips of people speaking far away without a microphone, or reading lips in a noisy environment. There could also be national defense implications with being able to read peoples lips through video footage without sound or by spying on people's conversations from a distance with binoculars. Regardless of how this could eventually be used, the possibilities are endless.

The biggest concern however is privacy. We live in a world where almost everything you do is being recorded whether by phones, street cameras, or even satellite surveillance. If this lip-reading software is used by the wrong groups it could be a massive breach of privacy to people whose conversations could be intruded on by outside sources. This will most likely become one of the developing hot topics, like drone use and cybersecurity, that will require new laws and regulations to keep under control.


Resources:
1. http://www.digitaltrends.com/cool-tech/lipreading-artificial-intelligence/
2. http://www.signlanguagenyc.com/wp-content/uploads/2016/03/lip-reading-asl-cart-services-nyc-02-219x300.jpg
3. http://www.notbored.org/watching-all-day.jpg
4. http://wwwhatsnew.com/wp-content/uploads/2016/11/LipNet-730x480.jpg

MogIA Accurately Predicts Election

In light of current events in the United States, I thought that I would take this week to write about what is on everybody's minds-- the Election. I don't want to get political in what is a very sensitive time so I am going to try and be as unbiased as possible throughout this post.

Leading up to the election Hillary Clinton seemed poised to win the Presidency according to many polls and news sources. However, to the surprise of many, Donald Trump was able to win several key swing states in order to become the next President of the United States. Who could have ever predicted this? Apparently an AI system called MogIA.

Business Insider posted an article leading up to the election about MogIA and how it has successfully predicted the the last three Presidential elections as well as both of this year's primaries. How is this possible you may ask? MogIA uses data from sources such as Google, YouTube, and Twitter to analyze how well a candidate is doing. It then updates itself over time in order time by learning from the online environment.

While MogIA is definitely not perfect it has yet to be wrong when predicting presidential elections. MogIA is an example of yet another incredible algorithm that can analyze an event and both unbiasedly and accurately predict outcomes better than humans.

Sources:
1. http://www.businessinsider.com.au/artificial-intelligence-trump-win-2016-10
2. http://zdnet1.cbsistatic.com/hub/i/r/2016/11/09/25fd2587-0c5c-4afc-bcdf-96539d83d420/thumbnail/770x578/feb141cb6013a9120dad232d0b7d513b/trump-cyber-crisis.jpg
3. http://realiran.org/wp-content/uploads/2016/08/US-elections-2016-638871.jpg

Sorting Data

Have you ever wondered what the most efficient way to sort data is? Say you have 10 randomly generated numbers and want to sort them from highest to lowest. I think we could all figure out a way to do that in java without it taking too long but it becomes an issue when dealing with big data. As a result there are over 15 different methods for sorting data. This video below of data being sorted is actually oddly satisfying.

Additionally a new sorting algorithm was created to solve the "cake-cutting" problem. This is a problem in which you are determining how to cut a cake fairly amongst multiple people given their different preferences. Think about a holiday party with a fruit cake. Every member of the family has a different preference for how big of a slice and which fruits they want in their slice. This problem tackles the problem of fairness which was previously viewed as unsolvable mathematically. However, recently a researcher was able to solve this problem for a group of anywhere between 3 to 203 people. 

The most notable part of this solution is that it shows that previously "unsolvable" problems can actually be solvable. Mathematicians should now be inspired to give those impossible problems a look again. Also, if you haven't already, please watch the data sorting video above it's actually really cool.  

Resources:

1. http://www.digitaltrends.com/cool-tech/sorting-algorithms-video/

2. http://www.digitaltrends.com/computing/cake-cutting-algorithm/

3. http://d2gk7xgygi98cy.cloudfront.net/1296-3-large.jpg

"Hive Minds" Accurately Predict Results

Recently the concept of using "Hive Minds" to predict the results of events has been gaining steam. Hive Minds is the concept that looking at the decisions of individuals in a group can predict what will most likely happen. The idea behind Hive Minds, also known as Swarm Intelligence, stems from how bees, ants, and fish act in groups to make collective decisions. While the concept is not too far-fetched and seems like it would be very similar to a poll or debate it actually gets substantially better results.

For example, the Hive Minds program UNU has was recently able to predict the top 4 horses in order at the Kentucky Derby despite 540-1 odds. While its results may not always be perfect, they often are or are pretty close. Below I have showed two more examples of Hive Mind decisions:

The UNU program is a new and incredibly interesting system which uses a unique algorithm to take user opinions, input, to determine what will most likely occur, output. While it may be impossible to ever create a fully infallible program, this is an intriguing new way to make decisions.

Resources:

1. http://unanimous.ai/human-swarms/
2. http://www.iflscience.com/technology/hive-mind-artificial-intelligence-wins-almost-11000-horse-bets/

Computer Science as a Way to Fight Cancer?

Microsoft has recently stated working closely with biology researchers to find a way to combine both computer science and biology to fight cancer. On the surface it may seem like a crazy idea. How can computer science fight cancer, a disease which occurs in the human body? Interestingly enough it actually makes a lot of sense. Microsoft is essentially working on developing a "molecular computer" which will fit inside cells and allow for them to monitor for diseases and prevent them from spreading.

Is This something which will happen tomorrow? No, most likely not. Microsoft is giving itself a 10 year timetable in which to develop this concept and do testing. However, the new look into how to preemptively prevent cancer holds serious implications. If this could be used for cancer, it could theoretically be applied to other diseases as well. If this idea works, which is definitely a big if, it could potentially eliminate many of the serious diseases that kill millions every year. It would essentially be a super vaccine that would be a turning point in human history.


The real questions comes down to if it is really possible to program a human cell like a computer is programmed. Can that same process of scanning for and then eliminating problems that computers do actually be applied to the human body? Only time can tell but it is certainly something to keep an eye out for.





Resources:
1) http://www.wired.co.uk/article/microsoft-solve-cancer-computer-science
2)http://futurism.com/wp-content/uploads/2016/09/Microsoft-will-solve-cancer-within-10-years-by-reprogramming-diseased-cells-600x315.jpg
3) http://wallstreetpit.com/wp-content/uploads/news/pbd/health-stem-cell.jpg
4) https://abm-website-assets.s3.amazonaws.com/rdmag.com/s3fs-public/featured_image/2016/06/rd1606_microsoft_@.jpg

Star Citizen- A Computer Game That is Out of This World

Today I will be talking about the long-awaited, and still yet to be fully released, computer game Star Citizen. In January of 2012, the small video game studio Roberts Space Industries posted on Kickstarter the idea for a computer game that would push every boundary previously set in the industry. Star Citizen would be a massive multiplayer online role playing game in which you could fly around in a space ship, get off at different planets, participate in in-game events, and, most importantly explore an entire virtual universe. Due to these lofty goals and fan support, Star Citizen raised over 100 million dollars making it one of the most successful Kickstarter campaigns of all time.

It is the notion of an endless universe that makes Star Citizen stand out. The endless universe mimics the size of our own universe and will be so large that nobody will ever be able to explore it all and the game will essentially be limitless. Every planet will have it's own unique size, shape, weather patterns, biomes, animals, items, etc so that the player will never get bored. The graphics, memory, and hardware required to make a game of this magnitude are massive and attribute to why something like this has never been done before. Despite many hiccups along the way, Star Citizen is aiming to be released by the end of 2016.

In class we have experimented with random generators, talked about memory storage, and started designing programs with images that move. To me, it is absolutely amazing to think about the scale of this game and the skill required in which to produce it. However, it goes to show that, as we have seen throughout the 21st century, with computer anything is possible.

Resources:

1. http://starcitizen.wikia.com/wiki/Crowdfunding_campaign
2. http://blogs-images.forbes.com/jasonevangelho/files/2015/10/star-citizen1.jpg
3. http://blogs-images.forbes.com/erikkain/files/2016/08/star-citizen-header-1200x675.jpg
4. https://robertsspaceindustries.com/about-the-game/spaceflight

Google's New AI Kill Switch

Have you ever wondered what would happen if we reached a point in which robots carried out all of the mundane tasks that we don’t want to do? Then what if these robots learned to optimize these tasks and update themselves based on real world experiences? Then what if they stopped updating to do the right thing, but instead to do the wrong thing? What if this led to robots plotting against humans in an attempt to takeover the world? Yes, what I just explained is the plot from “I, Robot” but the general line of thinking is more realistic than you would think.

AI Robots in "I, Robot"

Google researchers have recently developed an AI kill switch in order to shut down an AI robot no matter what. This is incredibly important because AI robots often work by trying to maximize some sort of function or algorithm. They will then read real world events as inputs and adapt those inputs into their systems so that they can continue to maximize their functions. Human interference can be considered one of these real world events. Therefore, if the machine determines that human interaction is detrimental to maximizing their functions or that the human is trying to shut it down, the machine could act out against the human to stop this from happening. Due to this fear, Google created an AI kill switch to automatically shut down a robot at anytime.

However, Google would never want to use the kill switch unless it had to and is instead working on creating a way to have robots read human interactions as part of the task and therefore not as a detrimental interruption. Doing so would essentially allow humans to teach robots things such as to not go outside in the rain. Hopefully, through both teaching robots how to read human interactions and including a kill switch in the machines, we will never have to live through the reality in “I, Robot.”

Resources:

1. http://motherboard.vice.com/read/google-researchers-have-come-up-with-an-ai-kill-switch
2. http://www.themanufacturer.com/wp-content/uploads/2015/08/EPA245.jpg
3. https://www.singularityweblog.com/wp-content/uploads/2015/02/Kill-Switch.jpg
4. http://images.contentful.com/7h71s48744nc/3l9IwugJKgcCq8YMwWGiy/8fdbc22b56ca7a2d34fb26e76952533e/i-robot.jpg