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Yaser Khalifa and Evolutionary Algorithms

This is Yaser Khalifa's website about his experiences with evolutionary algorithms.

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Yaser Khalifa

How and Why Facebook Is Using AI to Improve its Product

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Yaser Khalifa-lumos-facebookFacebook is already one of the most powerful and popular web and app platforms, and it has been for more than a decade. The service, whose beginnings we’re all at least somewhat familiar with at this point, has consistently dominated the world of social media, and based on its constant updates, additions, and acquisitions, it’s clear that it aspires to be more than that. The Facebook of 2017 is more than a space to share inane, personal details about the happenings of one’s day, as was the case 10 years ago. Now, users can share events, buy a car, send money, reserve movie tickets, ask for recommendations, and even broadcast live to billions of people around the world.

 

Yet, Facebook still isn’t done. In a recent blog the company revealed its latest endeavor includes a keener focus on artificial intelligence (AI) and machine learning. This isn’t Facebook’s first time using AI. The company uses bots for their robust, separate messaging system, and FBLearner which is responsible for ranking and positioning content in your newsfeed, is an example of machine learning. Similarly, Facebook’s latest platform, Lumos, will be a powerful tool for images.

 

Lumos is different than Facebook’s current image capabilities, which does a pretty good job at facial recognition, allowing you to tag friends pretty easily upon uploading. The goal for the platform is to scan images and videos and analyze the content within them, with the capability of describing the media “like you would to a friend.”

 

Why Is This Important?

With better alt text capabilities, Facebook can position its service so that users can use text to search for photos and be presented, quite accurately, with a plethora of resources. Additionally, Facebook will be able to recommend visual content to you based on the subject matter within them, not necessarily because they’re popular within your network. It makes Facebook more helpful, in a way.

 

Another component for which Facebook could and plans to use Lumos is for easily identifying objectionable content. A site that features billions of users is bound to have more than its fair share of media that would be considered offensive. Facebook’s current process of responding to flagged content is not lacking, but automated software could do well to improve that process, or at least make it more efficient.

 

For more details about Lumos and a few early examples of the platform in action, check out ZDNet’s recent blog on the subject.

 

Follow @YaserKhalifa12 on Twitter for updates related to tech, machine learning and evolutionary algorithms.

Robots are Taking Over the Streets: Uber’s Driverless Cars

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pexels-photo-largeFor imagineers of the past, the 21st century was projected to be the era of the flying car. While that was how the family in the American cartoon The Jetsons got around, it is not exactly the reality of humans in 2016. To be clear, manufacturer Terrafugia is in the process of creating such a device, but it will likely be awhile for it hits the market.

 

Lucky for us, however, we have something somewhat closer to the world of the future seen in movies. Ride sharing company Uber debuted its driverless cars in Pittsburgh just last month. The technology is a combination of multiple cameras, a LiDAR system, which creates 3-D maps of the vehicle’s surroundings, and antennae for GPS. It is a robot on wheels, essentially, that signals a wave of what’s to expect in transportation over the next few years and decades.

 

For those concerned about a robot takeover that would make humans obsolete, we’re not exactly there yet either. Though Uber has made it clear that it does hope to cut down on its largest expense, its drivers, the car is not completely personless. During Business Insider’s test of this new mode of transport, there was an engineer in the passenger seat and a driver behind the wheel to take over, because robot’s don’t know everything and human interference is still necessary as the machine is tweaked to operate nearly as well (or better, depending on the situation) as a human would.

 

An example of such an issue was highlighted in Quartz, in which a self-driving Uber turned down a one-way street, unaware of the areas signs and/or rules. In another instance, a driverless car was involved in an accident, and again required human assistance. These situations show that there is still work to be done on this technology, but that is precisely why the company chose Pittsburgh as its starting point: because it’s old and at times difficult and hard to navigate.

 

As with all new technology, I imagine driverless cab will take some getting used to, but now is as good a time as any, considering the high level of interactions humans have with robots on a daily basis. With every passing generation, more technology is integrated into the natural course of our life. How we get from place to place is a natural part of that evolution. Wouldn’t you agree?

Evolutionary Algorithms Are More Common Than You Know

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pexels-photo-largeTalk to someone unfamiliar with the work of artificial intelligence about evolutionary algorithms and you may get a blank stare or, at best, an look of bewilderment and a subsequent inquiry about what exactly the phrase means. Once explained, the concept may provide a bit of insight–to be sure, evolutionary algorithms are defined as a subset of evolutionary computation, a generic population-based metaheuristic optimization algorithm, which uses mechanisms inspired by biological evolution–but not many are aware, or fail to consider, that they’ve encountered such many times, in various forms.

Take, for instance, genetic algorithms, which are a type evolutionary algorithm that is a search heuristic mimicking the process of natural selection. The purpose is to generate solutions to optimization problems using techniques inspired by natural evolution. This video is explains it in full, in under five minutes:

Below, I’ve included some of the most common things which use or include genetic algorithms:

Computer Gaming

Online gaming is highly popular–so popular that the number of individuals who participate engage in gaming around the world, account for over 44% of the total number of people online, at 700 million gamers in 2013. Offline, games are equally popular, with people simply using their devices create wholly different worlds from their own, such as The Sims, which has won a Guinness record for being the best selling PC game of all time. The game, now in its in 16th year, uses genetic algorithms instead of having users play against humans online. Instead, The Sims is programmed to learn and incorporate strategies from previous games in which users have been successful, using game theory.

Finance

Financial markets are always changing. Genetic algorithms help deal with nonlinear problems of trading. Investopedia describes it this way: “Genetic algorithms are created mathematically using vectors, which are quantities that have direction and magnitude. Parameters for each trading rule are represented with a one-dimensional vector that can be thought of as a chromosome in genetic terms. Meanwhile, the values used in each parameter can be thought of as genes, which are then modified using natural selection.”

Cars

Race cars are not necessarily designed for everyday travel. Instead, they are crafted for sport and the ability to reach high speeds. A large part of their functionality are a result of design. Airplanes as well, created to travel high altitudes at fast speeds, need to be designed well. Genetic algorithms provide combinations of materials that would work best, from an engineering perspective, which then enables designers to put them together and save time on continuous testing.

These are just a few examples of how people interact with genetic algorithms very often. As our abilities in science continue to evolve, applications and the prevalence of such will likely continue to grow. For a full list of uses, be sure to visit this blog from Brainz.org and share with friends.

 

2016, The Year of the Robot

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maria from metropolisThe German film Metropolis premiered in March of 1927. In the years since its release it has become a classic among multiple generations, who consider it a pioneering work of art in the science-fiction genre. The centerpiece of the film is a robot named Maria, played by Brigitte Helm. At the time of the film’s release, the likeness was groundbreaking. Maria was not the first robot in film, but the character is arguably the most popular; since, it has inspired a number of other replicas in popular culture, due to our fascination with artificial intelligence and animated machinery. Each of these were rooted in fantasy, yet as life often imitates art, recent developments show that cohabitational robots are becoming much more of a reality than many have imagined.

Take the next generation Atlas robot, for example. Created by Boston Dynamics, the robot is shown in the video here as being capable of navigating snowy and rather difficult grounds, which Extreme Tech describes as an incredible feat that took humans half a billion years to master, in terms of evolution. The second generation Atlas also has the intelligence to realize when something has been moved–such as the boxes which it’s also able to lift and place on a shelf–to recover from resistance, and to even stand up on its own after being knocked over. The machine is downright fascinating and it’s just one of the advancements we’ve seen this year.

Aido, a personal robot that responds to voice commands and even plays with children, will be in people’s homes as soon as this fall. Like some of the machines we’ve seen in movies, the bot responds to touch through haptic sensors, which allows it move throughout the home or office. One of the more incredible features is its built in face recognition technology, and ability to communicate what it seen. For entertainment purposes, the robot is reported to have the ability to control electronics devices throughout the home as well.

To be expected later in the future, is a robot created to help the elderly, providing assistance and companionship. Embedded with a sense of emotions and  capable of bringing past conversations to memory, the goal of the robot, Nadine, is said to help patients suffering from dementia diseases, like Alzheimer’s and Parkinson’s. Almost 50 million people suffer from dementia worldwide, and because there is no treatment, any assistance that can facilitate living with the disease is certainly welcome. There is no current release for Nadine but the technology is there.

These developments are but a few debuting this year. This list from Robotics Trends shares more of what consumers and purveyors of artificial intelligence can expect in the next few months, based on revelations at this year’s Consumer Electronics Show (CES). As a society, we seem to be moving into future more quickly than ever. Whether it’s playing with children, moving boxes, or having conversations with the elderly, these scientific advancements are turning fantasies into reality, one research project at a time.

Billboards Are Going to be Able to Read Facial Expressions

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As advertising connects more and more with technology, it only makes sense that it is going to become more intelligent and reactive to how we’re feeling and what we’re looking for. This news should come as no surprise to people who are interested in both advertising, technology, and how they can intersect to promote products and ideas more effectively based on someone’s emotions. It was only a matter of time before advertisers began using facial recognition technology to target specific types of ads and the attitudes within them to the consumers mood and behavior.

Advertiser M&C Saatchi is currently behind this latest experiment in advertising techniques and technology. Using Microsoft Kinect cameras hidden within billboards, the advertiser is trying to read the emotions on a persons face and react accordingly to whether the person is happy, sad, or neutral. This is a truly next-step venture for both advertising and the algorithms used by the camera and program to choose the right advertisement based on facial expression. The advertisements will change the images, designs, fonts, and colors based on the persons expression. The algorithms needed to make this happen are incredibly complex and need to be able to read a host of different data, sift through all of the options, and choose the right ones for maximum effect, all within the blink of an eye.

As I mentioned above, these sorts of billboards are the future of ads that are on public streets and they require intensely complicated algorithms to make them happen. This sort of technology might begin with advertising, but the limits are endless and both the facial-recognition technology and the algorithms used to choose aspects of the advertisement can be applied to a host of other commercial, domestic, and possibly even military uses. However, before we can even get to the possible uses for this tech, we still need to make sure it can work on something as simple as selling products to consumers.

If you’d like to read more, the link is here.

Where do S.T.E.M. Majors Want to Work?

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The world is advancing by leaps and bounds when it comes to technology and fields that require engineering and math degrees. The STEM fields (science, technology, engineering, and math) are the cornerstone of progress when it comes to economies and the human race as a whole. When it comes to the top graduates in fields like applied mathematics and computer engineering, the competition to hire them can be brutal. Many companies get these top graduates based on reputation and the products they offer, regardless of the actual working conditions. Companies like Google, Apple, and Microsoft are just a few names amongst the numerous tech companies fighting for the best of the best.

A new survey to recent STEM graduates went out to over 19,000 students across over 340 universities around the world and asked them where they hoped to work when they graduated. The results that came back really shouldn’t be all that surprising when you think about who the most popular and successful tech companies in the world currently are. Google obviously came in at number one but it was quickly followed by Apple, Microsoft, Facebook and Amazon, in descending order. When you look at the names listed, it’s no surprise that these are the companies that are currently pushing the envelope when it comes to technology and commerce.

The survey was also split between male and female STEM students and also by the actual majors involved, as well as the school the student was currently attending. This means that while Google, Apple, Microsoft, Facebook, and Amazon are the most popular overall, computer science majors are looking to work at different companies in a different order (not to say that those companies aren’t amongst the most popular for computer science students). So what does this all mean? It means that the companies that are most likely to receive the best of the best are the ones that everyone is already expecting. Companies like Google and Facebook aren’t going to go anywhere soon and they’re only going to increase in size.

If you’d like to read more, the link is here.

Is Computer Engineering A Good Major?

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School is hard and leaving school is even harder. The fact is that once you enter college, the funnel begins to narrow and working your way up towards the top becomes more and more difficult. The major that you end up choosing and studying can go far towards helping you along your career path and towards the lifestyle you desire. Unfortunately, there are so many majors to choose from and this can make it difficult to figure out which one would be best for helping you in your future. Thankfully, there’s help available! Computers are the future and the future is coming quickly. Computer engineering can help you not only find a worthwhile and satisfying career path, but also to help you find a career that is important to human development. It can also be quite lucrative, if you get good enough. Watch the video below to learn more!

High Schools Are Focusing on Computer Classes

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Computers are the future. This is a fact that has always been true no matter how you look at the future. Whether fictional or realistic, visions of the future rely heavily on computers and artificial intelligence to show how the world will be different and that much more efficient. These images of the future are becoming closer and closer to reality as computers and technology advance at exponential rates, making people skilled in these more and more important to the economy and country as a whole. While other countries have recognized this and are placing more emphasis on math and science than before, the US has been slow to catch up. Now schools are recognizing the importance of educating students in computer sciences and they’re offering classes.yaser_khalifa_computer_science

The fact is that the United States of America is already falling behind in subjects like math and science and faces the danger of finding itself completely out of the running when it comes to producing students who are skilled and educated in the fields of science, technology, computing, engineering, and math. This has finally been realized and after a few failed attempts to jumpstart this sort of educational bent, states are seeing some success as students begin to recognize the importance as well. Computer science is one of the fastest growing industries in the country and the need to high quality candidates is becoming more and more important. Since 2013, AP (Advance Placement) computer science courses have grown 25% and it doesn’t seem like things are going to stop there. With new courses aimed at getting girls and minorities to join being introduced over the next year, this spike in popularity should only increase.

Led by an increased emphasis on S.T.E.M. (Science, technology, engineering, and math) classes, public school districts are also introducing and placing an importance on computer science classes. These classes teach students the basic of programming and how to code, allowing them to pursue the field with more ease and success when they get to college. A few years ago, what few computer science classes that were offered frequently would be dropped by school administrators due to low enrollment numbers, ruining the chances for students who were actually interested in the subject from taking classes on it. Now, with students already talking about how their computer science courses helped them in college, hopefully these offerings will become the norm across the country.

If you’d like to read more, the link is here.

Not All Hackers Are Horrible

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Hackers have been all over the news recently due to the frequent and costly attacks on banks, businesses, and governmental institutions that always grab attention. While there’s no denying that some hackers are out to steal for personal gain and cause havoc for their own reasons, the vilification from the media portrays all hackers as socially-deficient sociopaths who have no other goals in life other than stealing money and causing havoc amongst innocent people who are just trying to live their lives. While this is certainly true for some hackers, most of them are more mischievous than Machiavellian and more like artisans and proud craftsmen than rampant looters.hacking

Researchers are starting to study hackers and the community they take part in to better understand how they function so that more effective counter-measures can be created and implemented. What they have found so far is different than how the media portrays hackers and how society has come to view them. While there are hackers who fit all of the negative stereotypes, they are in the minority and most hackers are more concerned with all manners of programming, not the stealing of money and identities. Kevin Steinmetz, an assistant professor of sociology, anthropology and social work at Kansas State University, is leading the study and believes that hackers are more akin to transgressional craftsmen with a love of mischief than to evil-doers who are hellbent on stealing from everyone.

Steinmetz learned about hacking by observing and interviewing a group of hackers from Texas. He interviewed them about subjects ranging from privacy to governmental institutes of authority and found that a surprising amount of similarities between hacking collectives and the craftsmen guilds of antiquity. What he also found is that hacking is so much different now than from how it started. What we consider to be “hacking” actually encompasses so much more than it originally did. Hacking is now frequently used to talk about the outcomes but in reality, it should only refer to the process and the programming. True hackers care about much more than the outcome and aren’t necessarily criminals. In fact many hackers work to find bugs in software and websites so that they can tell the companies running them and advise on how to fix them.

If you’d like to learn more, the link is here.

Machines Teach Humans About the Stars

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When people think of the stars they usually think about the stereotypical star or the sun. What they don’t think of is the sheer number of stars that our galaxy (let alone our universe) contains and how the sheer mass and number of stars can make studying them incredibly difficult for even the most obsessed and dedicated astrologer. Thankfully, machines and robots are able to accomplish certain things much faster than humans can and they are incredible useful when it comes to sifting through huge amounts of data. Scientists are now using machines like this to help with their study of stars and planets all around the universe.

The use of machines and computers to help scientists shift through data is still relatively new. That being said, it is quickly gaining steam and becoming the norm as computers can go through massive lists much faster and, potentially, notice patterns that would escape the human eye. Normally the search for patterns in stars and planets is accomplished by a spectrum; the sifting of starlight through different wavelengths in an attempt to discover properties. Now machines can use complicated algorithms that sift through data at a much faster and more accurate speed. This allows computer to take information on billions of stars in a relatively quick manner when compared to previous efforts.

After taking the pictures of stars gathered by thousands of telescopes around the world, the computers search through a massive database that show’s all of the pictures of the same stars taken over a period of time. By looking for differences in size, brightness, and other factors, the computers can find new classes of stars as well as track the progress of existing stars as they head towards supernova. This sort of information will become more and more valuable as humanity continues to explore space looking for both evidence of life as well as potential colonizable planets.

If you’d like to read more, the link is here.