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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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Technology

How and Why Facebook Is Using AI to Improve its Product

February 3, 2017 by Yaser Khalifa

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.

Filed Under: Artificial Intelligence, Computer Engineering, Evolutionary Algorithms, Technology, Trends Tagged With: ai, facebook, lumos, machine learning, media, photos, social media

Evolutionary Algorithms Are More Common Than You Know

April 12, 2016 by Yaser Khalifa

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.

 

Filed Under: Artificial Intelligence, Computer Engineering, Computer Science, Evolutionary Algorithms, Technology Tagged With: cars, computer gaming, Evolutionary Algorithms, finance, Genetic Algorithms, robots

2016, The Year of the Robot

March 8, 2016 by Yaser Khalifa

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.

Filed Under: Artificial Intelligence, Computer Engineering, Robotics, Technology, Trends Tagged With: artificial intelligence, engineering, robotics, technology

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