Samsung's Bixby used descriptions male and female voices that users considered sexist. Samsung hastily scrubbed the descriptions of male and female voices for its newly launched Bixby voice assistant Wednesday after users pointed out describing a woman's voice as "chipper" and "cheerful" and a male voice as "assertive" "confident" played into well-worn gender stereotypes. "We are constantly learning from customer feedback. We have removed the hashtag descriptions from the Bixby service," Samsung said in a statement to USA Today. Bixby no longer has descriptions of voice options.

Recommendation is the task of improving customer experience through personalized recommendation based on users' past feedback. In this paper, we investigate the most common scenario: the user-item (U-I) matrix of implicit feedback. Even though many recommendation approaches are designed based on implicit feedback, they attempt to project the U-I matrix into a low-rank latent space, which is a strict restriction that rarely holds in practice. In addition, although misclassification costs from imbalanced classes are significantly different, few methods take the cost of classification error into account. To address aforementioned issues, we propose a robust framework by decomposing the U-I matrix into two components: (1) a low-rank matrix that captures the common preference, and (2) a sparse matrix that detects the user-specific preference of individuals. A cost-sensitive learning model is embedded into the framework. Specifically, this model exploits different costs in the loss function for the observed and unobserved instances. We show that the resulting non-smooth convex objective can be optimized efficiently by an accelerated projected gradient method with closed-form solutions. Morever, the proposed algorithm can be scaled up to large-sized datasets after a relaxation. The theoretical result shows that even with a small fraction of 1's in the U-I matrix $M\in\mathbb{R}^{n\times m}$, the cost-sensitive error of the proposed model is upper bounded by $O(\frac{\alpha}{\sqrt{mn}})$, where $\alpha$ is a bias over imbalanced classes. Finally, empirical experiments are extensively carried out to evaluate the effectiveness of our proposed algorithm. Encouraging experimental results show that our algorithm outperforms several state-of-the-art algorithms on benchmark recommendation datasets.

It took longer than Samsung likely expected for the full version of its Bixby virtual assistant to reach customers, but Galaxy S8 users can now get some more use out of their smartphone. Samsung confirmed Wednesday that voice support will roll out to U.S. Galaxy S8 smartphones. The Galaxy S8 had launched earlier this year with a basic version of Bixby that only had minimal features, because of difficulties the assistant had with understanding English. Here's what you can now expect to see from Samsung's Bixby: Samsung has positioned Bixby as an alternative to competitors like Apple's Siri and Google Assistant thanks to its own voice control options. For Samsung, it likely hopes that Bixby-specific features help the assistant stand out from the pack.

As a company, Apple's been known for exploring various side ventures. Its latest project isn't the most high profile, but points to a growing field the company wants to explore further. Apple has launched the Apple Machine Learning Journal, an outlet that focuses on the work Apple engineers are doing with machine learning. In an introductory post on the site, Apple says it wants to highlight the research staffers are doing "using machine learning technologies to help build innovative products for millions of people around the world." The first paper on the site, Improving the Realism of Synthetic Images, focuses on ways to refine the quality of simulated images used in machine learning training to make sure models don't incorrectly process unnecessary details.

If you make a purchase by clicking one of our links, we may earn a small share of the revenue. However, our picks and opinions are independent from USA TODAY's newsroom and any business incentives. If you love new technology like we do, this scenario might sound familiar: You've found the perfect tech gift for your parents or grandparents, but you're worried they might not use it if it's too complicated to learn. You know they would love the functionality, but how do you make sure it's as easy to use as possible? It's a common dilemma, and often, it comes down to setting up the device in a way that's as straightforward as possible.

Apple just launched a blog focused on machine learning research papers and sharing the company's findings. The Apple Machine Learning Journal is a bit empty right now as the company only shared one post about turning synthetic images into realistic ones in order to train neural networks. This move is interesting as Apple doesn't usually talk about their research projects. The company has contributed and launched some important open source projects, such as WebKit, the browser engine behind Safari, and Swift, Apple's latest programming language for iOS, macOS, watchOS and tvOS. But a blog with research papers on artificial intelligence project is something new for Apple.

As a marketing professional, there's nothing more important than staying in tune with the "latest and greatest" developments in regards to technology. While there are many old school methods of marketing that continue to generate top of the line results, it's important to turn your attention to the future. This means many things in today's world, including a focus on artificial intelligence. Don't assume that artificial intelligence is nothing more than a fad. All signs point to this sticking around for many (many) years to come.

The Samsung Galaxy S8 has been on the market since late-April and its highlight feature, Bixby Voice has finally been implemented onto the device in the U.S. market. The artificial intelligence update is rolling onto Galaxy S8 and Galaxy S8 handsets over-the-air, adding to the overall platform, the ability to instruct the handset to execute functions with one's voice. Bixby serves as Samsung answer to other AI assistants such as Siri, from Apple, Alexa from Amazon and Google Assistant. In addition to Bixby Voice, the assistant includes features such as the Hello Bixby Hub, which serves as a hub for vital information for those using a Bixby enabled handset, Bixby Reminders, which learns user's patterns and sets automatic reminders, and Bixby Vision, which uses the Galaxy S8 camera app as a machine learning identification tool to pull information about products, places or things or even translate text. The latter three features were enabled on Bixby when the Galaxy S9 launched; however, Bixby Voice was delayed due to Samsung having issues implementing English speech recognition onto the platform.

The first voice you hear on the recording is mine. "Here we are," I say. My tone is cheerful, but a catch in my throat betrays how nervous I am. "Esquire," a second voice on the recording chimes in, and this one word--delivered as a winking parody of lawyerly pomposity--immediately puts me more at ease. The speaker is my dad. We are sitting across from each other in my parents' bedroom, him in a rose-colored armchair and me in a desk chair. It's the same room where, decades ago, he calmly forgave me after I confessed that I'd driven the family station wagon through a garage door. Now it's May 2016, he is 80 years old, and I am holding a digital audio recorder. Sensing that I don't quite know how to proceed, my dad hands me a piece of notepaper marked with a skeletal outline in his handwriting. It consists of just a few broad headings: "Family History." "So … do you want to take one of these cat egories and dive into it?" "I want to dive in," he says confidently. "Well, in the first place, my mother was born in the village of Kehries--K-e-h-r-i-e-s--on the Greek island of Evia …" With that, the session is under way. We are sitting here, doing this, because my father has recently been diagnosed with stage IV lung cancer. The disease has metastasized widely throughout his body, including his bones, liver, and brain. It is going to kill him, probably in a matter of months. So now my father is telling the story of his life. This will be the first of more than a dozen sessions, each lasting an hour or more. As my audio recorder runs, he describes how he used to explore caves when he was growing up; how he took a job during college loading ice blocks into railroad boxcars.

Amazon's Alexa has plenty going for it. Developers have trained the virtual assistant with over 10,000 "skills"--apps you talk to instead of tap--to do everything from hailing a Lyft to checking your stock portfolio. At home, Alexa can control the lights, set timers, play your local NPR station, and generally achieve that Jarvis-level assistance that feels so much like the future. Until now, though, Alexa lacked what it needs more than any of those things to secure its success: a fighting chance on smartphones. Alexa already lives on Android and iOS.