Collaborating Authors


AI's struggle to reach "understanding" and "meaning"


This article is part of our reviews of AI research papers, a series of posts that explore the latest findings in artificial intelligence. The short excerpt below from the 1938 film La Femme du Boulanger (The Baker's Wife) ingeniously depicts how the human mind can extract deep meaning from life experiences and perceived situations. In the movie, directed by Marcel Pagnol, the baker Aimable welcomes his wife Aurelie, who has just come back after running off with a shepherd days earlier. While Aimable treats Aurelie with sweet words and a heart-shaped bread (which he had baked for himself), he shows no kindness toward Pomponette, his female cat who coincidentally returns home at the same time as Aurelie, after abandoning her mate Pompon for a chat de gouttière (alley cat). Aimable calls Pomponette ordur (junk) and a salope (a rude term) who has run off with un inconnu (a nobody) and bon-a-rien (good for nothing) while the poor Pompon has been miserably searching for her everywhere.

'Mythbusters' robotics genius Grant Imahara has died


Friends, fans, and coworkers are paying tribute to beloved Mythbusters alumni Grant Imahara, who died suddenly on Monday due to a brain aneurysm. A talented engineer and roboticist, Imahara spent almost a decade at Lucasfilm's visual effects division Industrial Light and Magic, where he worked on films such as Galaxy Quest, The Lost World: Jurassic Park, the Matrix sequels, and the Star Wars prequels. Being one of the people behind R2-D2 and the Energizer Bunny, Imahara's work had a notable impact on pop culture. He also gained some public recognition through appearances on BattleBots, where he competed his middleweight robot Deadblow. However, Imahara was most well known for being a member of Mythbusters' Build Team, joining the cast in 2005 after the departure of Scottie Chapman.

A Star Wars Story by Sentient Droid


Imagine, droids came to the 21st century with the knowledge of the future but only had current technology to rewrite their Star Wars story. In this article, we will see how a droid (machine learning model) generates its Star Wars story using knowledge of the future (Star Wars books). The model takes the input sequence of words. We use LSTM to understand the context in a sentence. Since simple RNN would have vanishing gradient problem, so for the text generation I am using LSTM.

'White Mirror' on the wall - what does the future hold for us all ?


It's time to reset, re-create and collaborate on a new paradigm where Compassion and Kindness are the prevailing norms, one where technology is a tool for making humans more humane and creating an Abundant world for the majority. Join us to turn this vision into reality. Let's look into the'White Mirror' … Inspired by Black Mirror (Netflix series) - 'White Mirror' (holding name while we devise a suitable one) provides an immersive flash forward (glimpse/vision) of our Utopian future. In uncertain times (like now), technological disruption and impactful stories can change our mental worldview - our perceptions and eventually our reality. Black Mirror is a powerful show, depicting a dystopian future caused in part by misused evolving technologies.

Listen to Metaflow: Netflix Machine Learning Platform with Savin Goyal


"Brings us to aws flicks took the at the time unconventional decision to go all in on aws many years ago at this point, and that's treated. The the whole idea around blessed programming languages where you make a strong decision within an organization to restrict the number of programming languages with an organization and it it that constraint ends up helping the organization make decisions more quickly and allow for engineering mobility and so on. This has been the case with aws when when Netflix? Strongly moved onto aws and continue to do that. That extends to medfly show. A better flow is an open source framework, but it has a tight coupling with aws. So why is the tight coupling to aws useful for machine learning framework? Sue I won't say that. We are tightly coupled to eight of us. So when leave it open sourcing MEDOFF. No at that point in time, because we had a good amount of operational expertise with aws, we chose indicating the details are ready for this cloud integration, ...

Building a Deep-Learning-Based Movie Recommender System


With the continuous development of network technology and the ever-expanding scale of e-commerce, the number and variety of goods grow rapidly and users need to spend a lot of time to find the goods they want to buy. To solve this problem, the recommendation system came into being. The recommendation system is a subset of the Information Filtering System, which can be used in a range of areas such as movies, music, e-commerce, and Feed stream recommendations. The recommendation system discovers the user's personalized needs and interests by analyzing and mining user behaviors and recommends information or products that may be of interest to the user. Unlike search engines, recommendation systems do not require users to accurately describe their needs but model their historical behavior to proactively provide information that meets user interests and needs.

Ubisoft Forward shows off Far Cry 6, Watch Dogs Legion, Assassin's Creed Valhalla, and Hyper Scape


We are now more than a month past the point when E3 2020 would've ended. It lives in your heart, in your soul, and on your television. Today we finally reached the "1PM Monday Afternoon" slot, a.k.a. Much of what Ubisoft showed at its faux-press conference, we already knew about--Watch Dogs Legion, Assassin's Creed Valhalla, and the recently leaked Far Cry 6. But hey, they managed to keep Tom Clancy's Elite Squad under wraps (for what that's worth), and the Assassin's Creed footage looked pretty neat.

Does AI Scream at Electric Creeps?


When most people think of machine learning in relation to themselves, something like the auto-correct peppered throughout their texts might come to mind. But these technologies are integrated into so many industries that touch us daily. In my previous article linked below, I talk about the broad strokes of machine learning by looking into the technologies of self driving cars, healthcare, and briefly touched on the YouTube algorithm. In this article, I'll be diving farther into that last concept by approaching three different violations of terms and services on a social media platform and the role that machine learning has in mitigating any hardships caused by these violations. To fully understand the decision making behavior, we must go over the basics of these algorithms.

How Data Science is Boosting Netflix


Considering how long Netflix has been in the streaming business, it has stacked up heaps of data about its viewers, such as their age, gender, location, their taste in media, to name a few. By gathering information across every customer interaction, Netflix can dive right into the minds of its viewers and get an idea of what they might like to watch next even before they finish a show or movie. We have data that suggests there is different viewing behavior depending on the day of the week, the time of day, the device, and sometimes even the location. Netflix has a massive user base of more than 140 million subscribers. Over time, Netflix has deployed several algorithms and mechanisms that make use of this data and generate critical insights that help steer the company in the right direction.

How Artificial Intelligence Can Change the Way We Shop Online


What comes to mind when you think of Artificial Intelligence (AI)? Maybe you think of robots taking over the world, like in the movies, or self-driving cars. Merriam-Webster defines artificial intelligence as 1) a branch of computer science dealing with the simulation of intelligent behavior in computers and 2) the capability of a machine to imitate intelligent human behavior. Did you know that AI is gradually changing the way consumers shop at various stages of the buyer's journey? In subtle ways, artificial intelligence affects the way a potential buyer searches for product or brand information during the awareness stage.