WebProNews

Category: MachineLearningPro

MachineLearningPro

  • Are XR Sports The Future?

    Are XR Sports The Future?

    The pandemic has shown us the business opportunities for new and emerging technologies, and even technologies typically thought of as gaming tech can have legitimate business uses and opportunities. Virtual and augmented reality technologies have given people the ability to travel, learn, and do business in a unique way throughout the pandemic, and now these technologies are converging in a new way to form extended reality, or XR technology.

    Extended reality is a way to describe the mixed reality platforms that are gaining popularity. These platforms can be used for work, travel, and exercise. For work, Frame allows users to host meetings in a virtual space with as many as 20 participants for a more realistic-feeling meeting experience. Oculus Quest allows users to travel virtually, visiting such landmarks as Chernobyl, Machu Picchu, Antarctica, and even ancient cities as they once were. 

    When it comes to sports, extended reality is generating even more realistic experiences for users. This is important especially now during the pandemic when people are stuck at home and unable to play their typical competitive sports. The WHO has urged people to get physical activity on a daily basis, which seems to grow more difficult as the pandemic wears on.

    Extended reality sports include things like mountain climbing, golf, tennis, and more. To make the play seem more realistic, real sporting equipment is used and is outfitted with sensors that allow the player to experience the game as it is intended to be experienced.

    This technology is presenting brand new business opportunities, as well. The popularity of such gaming platforms is growing, and by 2023 the market for extended reality is expected to reach $18 billion.

    Increasingly Americans are being forced to take part in activities at home, but even before the pandemic they were choosing to spend more time at home than previous generations. This has booted demand for XR sports, as it gives people an opportunity to take part in communal physical activities from the safety of their own homes.

    This technology uses motion tracking, artificial intelligence, and biomechanical modeling to achieve realistic gameplay. Sensors on sporting equipment coupled with sensors watching or on the user track movements to simulate their part in the gameplay. Machine learning adapts to a player to present more realistic competition.

    The possibilities for this technology are endless. In the real world, gaming centers are starting to pop up using this technology. Golf simulators and tennis simulators are some of the most popular and prevalent, and eventually there will be several different kinds of virtual sports offerings. 

    Players will be able to enter a socially distanced pod and play a realistic version of their favorite competitive sport using real sports equipment. Competition happens virtually online and leaderboards keep track of who is performing the best and where they are located.

    Gameplay is realistic as is the feel of competition, something that is currently missing in many  home-based virtual reality games. As this technology progresses, the possibilities are endless. Learn more about the future of XR sports from the infographic below.

  • Google Uses Machine Learning to Decipher Hieroglyphs

    Google Uses Machine Learning to Decipher Hieroglyphs

    Google has unveiled Fabricius, a tool that uses machine learning to decipher and translate ancient Egyptian hieroglyphs.

    Ancient Egypt has captured the imagination of people the world over for centuries. Hieroglyphs offer a glimpse into that world, but they are notoriously difficult to decipher. It has traditionally involved using volumes of books to check and cross-check symbols. Google’s new tool is designed to make the process easier, and opens hieroglyphs to the public at large.

    “Fabricius includes the first digital tool – that is also being released as open source to support further developments in the study of ancient languages – that decodes Egyptian hieroglyphs built on machine learning,” writes Chance Coughenour, Google Arts & Culture Program Manager. “Specifically, Google Cloud’s AutoML technology, AutoML Vision, was used to create a machine learning model that is able to make sense of what a hieroglyph is. In the past you would need a team of Data Scientists, a lot of code, and plenty of time, now AutoML Vision allows developers to easily train a machine to recognize all kinds of objects.”

    Fabricius is available in English and Arabic and stands to revolutionize the study of Egyptian hieroglyphs and history. This represents another arena where machine learning is making a valuable impact.

  • Verizon Chooses Google Cloud Contact Center AI

    Verizon Chooses Google Cloud Contact Center AI

    Google Cloud has scored a major win as Verizon has chosen its Contact Center AI to help power its customer service experience.

    Google has developed a reputation as being one of the most AI and machine learning-friendly cloud solutions. This latest deal lends credence to that, as Verizon is looking to use Google’s conversational language AI to help speed up wait times and improve customer service.

    Verizon plans to deploy the technology to assist both customers and live agents. For customers, the conversational AI will help them get to the right agent faster, without having to go through menu prompts. They’ll be able to simply speak or type their request and the AI will route them to the agent or department that can best assist. For the live agents, the AI will contribute by retrieving documentation and other materials that can help the agent better assist the customer.

    “Verizon’s commitment to innovation extends to all aspects of the customer experience,” said Shankar Arumugavelu, global CIO & SVP, Verizon. “These customer service enhancements, powered by the Verizon collaboration with Google Cloud, offer a faster and more personalized digital experience for our customers while empowering our customer support agents to provide a higher level of service.”

    “We’re proud to work with Verizon to help enable its digital transformation strategy,” said Thomas Kurian, CEO of Google Cloud. “By helping Verizon reimagine the customer experience through our AI and ML expertise, we can create an experience that not only delights consumers, but also helps differentiate Verizon in the market.”

    This is a big win for Verizon’s customers and Google Cloud, and will help Google further its reputation in the AI field.

  • Google and NVIDIA Partner to Bring A100 to the Cloud

    Google and NVIDIA Partner to Bring A100 to the Cloud

    Google Cloud has become the first cloud provider to offer NVIDIA’s new A100 Tensor Core GPU.

    NVIDIA made a name for itself making high-powered graphics processing units (GPU). While many people associate GPUs with gaming and video, since NVIDIA’s GeForce 8 series, released in 2006, GPUs have been making inroads in areas traditionally ruled by the central processing unit (CPU). Because of the GPU’s ability to handle large quantities of parallel data, they are ideal for offloading intensive operations, including machine learning and artificial intelligence.

    The new A100 is designed with this in mind. Built on the NVIDIA Ampere architecture, the A100 boasts a 20x performance improvement for machine learning and inference computing. This represents the single biggest generational leap ever for NVIDIA.

    “Google Cloud customers often look to us to provide the latest hardware and software services to help them drive innovation on AI and scientific computing workloads, ” said Manish Sainani, director of Product Management at Google Cloud. “With our new A2 VM family, we are proud to be the first major cloud provider to market NVIDIA A100 GPUs, just as we were with NVIDIA T4 GPUs. We are excited to see what our customers will do with these new capabilities.”

    This will likely be a big hit with Google’s customer base, especially since machine learning support is an area where Google Cloud is particularly strong.

  • MIT Removes AI Training Dataset Over Racist Concerns

    MIT Removes AI Training Dataset Over Racist Concerns

    MIT has removed a massive dataset after finding it contained racist, misogynistic terms and offensive images.

    Artificial intelligence (AI) and machine learning (ML) systems use datasets as training data. MIT created the Tiny Images dataset, which contained some 80 million images.

    In an open letter, Bill Freeman and Antonio Torralba, both professors at MIT, as well as NYU professor Rob Fergus, outlined issues they became aware of, and the steps they took to resolve them.

    “It has been brought to our attention that the Tiny Images dataset contains some derogatory terms as categories and offensive images,” write the professors. “This was a consequence of the automated data collection procedure that relied on nouns from WordNet. We are greatly concerned by this and apologize to those who may have been affected.

    “The dataset is too large (80 million images) and the images are so small (32 x 32 pixels) that it can be difficult for people to visually recognize its content. Therefore, manual inspection, even if feasible, will not guarantee that offensive images can be completely removed.

    “We therefore have decided to formally withdraw the dataset. It has been taken offline and it will not be put back online. We ask the community to refrain from using it in future and also delete any existing copies of the dataset that may have been downloaded.”

    This has been an ongoing issue with AI and ML training data, with some experts warning that it is far too easy for these systems to inadvertently develop biases based on the data. With their announcement, it appears MIT is certainly doing their share to try to rectify that issue.

  • Facebook Beefs Up Messenger Security

    Facebook Beefs Up Messenger Security

    Facebook has announced significant new measures to increase the security of Messenger, as well as combat predators and scammers.

    Tech giants have increasingly been under pressure to do more to protect their users, especially minors. Social media and online platforms have become the tool of choice for many individuals looking to prey on children. Even adults are often faced with a plethora of security risks and potential scams.

    In a blog post, Jay Sullivan, Director of Product Management, Messenger Privacy and Safety, outlines a number of new features the company is implementing.

    Facebook is moving its messaging service to end-to-end encryption, which will provide a far greater degree of privacy. At the same time, it has required the company to come up with new ways to help protect its users, since end-to-end encryption prevents it from reading or monitoring messages. Instead, Facebook has turned to machine learning to analyze patterns of behavior that could indicate something is amiss.

    “Keeping minors safe on our platforms is one of our greatest responsibilities,” writes Sullivan. “Messenger already has special protections in place for minors that limit contact from adults they aren’t connected to, and we use machine learning to detect and disable the accounts of adults who are engaging in inappropriate interactions with children. Our new feature educates people under the age of 18 to be cautious when interacting with an adult they may not know and empowers them to take action before responding to a message.”

    Facebook is also using new safety notices as a way to better educate people and help them spot scams sooner. Overall, these features are welcome news from Facebook and should go a long way toward protecting its users.

  • Beat The Corona Slump By Acquiring These 9 Freelancing Skills

    Beat The Corona Slump By Acquiring These 9 Freelancing Skills

    Learning new skills during the corona crisis is essential to put you ahead of the curve both during the pandemic and in its aftermath.

    Economically, this is a trying time. If we believe the experts, the world could soon plunge into the worst recession since the Great Depression.

    Most freelancers have already seen a drop in gigs. The stock markets are under heavy pressure. Unemployment numbers in the US alone have skyrocketed to 26 million. 

    There is not much anyone can do about that right now. 

    What you can do is improvise, adapt, and overcome. 

    There are many ways for freelancers to steer their businesses through the crisis with a steady hand. One of them is to invest in personal growth, in adding new abilities to your skillset. 

    Research says that learning a new skill takes 20 hours. That’s an amount you can scrape together during the lockdown. 

    But this is not about mastering sourdough bread or new yoga poses. 

    Some project a surge in freelance work in the wake of the crisis. By taking advantage of the current lull, you can extend your capabilities to boost your freelance business and career prospects post-corona. 

    But where to focus? 

    Here are 9 fields in which to pick up highly sought-after skills that increase your business efficiency and visibility.

    1 – AI and Machine Learning

    Artificial intelligence, machine learning, and big data are three essential components of modern business. In a report released in January 2020, the World Economic Forum identified AI literacy as the number one data skill of the future. 

    Companies use AI and machine learning for data management, predicting consumer behavior, and detecting fraud. They can personalize marketing, and improve customer service with chatbots or interactive voice response for calls. 

    Mastering any of these aspects will give you an edge on the freelance market and increase the efficiency of your own business besides. 

    Even basic fluency in AI fundamentals will go a long way towards a better understanding of modern business practices. 

    2 – Analytics and Big Data

    Data is important. Big data even more so.

    Businesses rely on data to gain market insights, boost conversion rates, manage risk, design new products, drive innovations, and manage their supply chains. 

    In a Forbes interview with CEOs on in-demand freelance skills during COVID-19, the majority listed mining and analyzing a variety of data.

    You won’t become a high-profile data scientist during coronavirus lockdown. But a certain degree of data literacy and an understanding of how to harness big data for business purposes will raise you a mile above most of the competition.

    3 – Cybersecurity

    During the corona crisis, a multitude of businesses has undergone a digital transformation. They have – often abruptly – shifted a large part of their operations online and suddenly work in remote teams. 

    Security considerations have often been neglected in the rush. 

    Unsurprisingly, hackers are seizing the opportunities right now. Since the beginning of the pandemic, there has been a sharp uptick in the number of cyberattacks. 

    Consequently, freelancers who are knowledgeable about cybersecurity are in high demand. 

    4 – Web Development and Web Design

    With a huge part of business shifting online, web development and design are seeing significant demand. 

    Now more than ever, company websites need to be flawless and unique to stand out from the competition. 

    That means now is the time to step up your WordPress game, get to know the newest trends and plugins, and learn how to build a truly stunning website. Going further, learning the foundations of writing markup and coding, or extending your knowledge on the subject, will go a long way towards raising your profile.

    5 – Content Creation

    Vast numbers of people are stuck at home right now, and they’re hungry for content.

    Learning how to write impactful texts for a variety of purposes – blog posts, video scripts, press releases, newsletter campaigns, website copy – is a valuable and marketable addition to your skillset. 

    The same holds for design and video editing. Visuals are a huge part of marketing, and video is a key trend in marketing in 2020, with platforms like TikTok on the rise. 

    Whether you hone these skills to expand your own online presence or reach the level at which you can provide services to others, content creation is an essential skill. 

    6 – SEO

    Search engines are the largest source of traffic to business websites. 

    As a consequence, Search Engine Optimization is crucial to drive organic traffic to your website, increase your visibility, and ensure business success. 

    Providing high-value content is a major factor in SEO, but building your SEO skills can go much further. Optimizing content, local SEO, and technical SEO all play critical roles in improving your website’s search engine rankings and gaining visibility.

    Ultimately, brushing up on your SEO skills won’t just leave you with a much stronger online presence, but also with abilities that are coveted in the job market. 

    7- Digital and Social Media Marketing

    With the corona-induced shift to life online, digital and social media marketing have become critical. Digital marketing experts are highly sought after. 

    Doing research on crucial digital marketing trends in 2020, and developing your skills accordingly, will put you ahead of the curve. Which are the most prominent (social) media channels in your industry? What are the best strategies to gain an audience there? What sort of content is needed? 

    Answering these questions can give you the focus and knowledge you need to promote your own business and develop highly marketable skills. 

    8 – Critical Thinking and Problem Solving

    It’s not all about marketing and technology. 2019’s State of the Workplace Report by the Society of Human Resource Management found that almost 40% of employers found the problem solving and critical thinking abilities of candidates to be sub-par. 

    Creative problem solving is an essential skill for succeeding in the workplace – whether you’re a full-time freelancer running your own business, or working remotely. 

    Luckily, these skills don’t depend on innate abilities but can be trained and honed through exercises and courses, together with other valuable soft skills. 

    9 – Emotional Intelligence

    Another critical soft skill in high demand on the job market is emotional intelligence. Emotional intelligence (EQ) is the ability to be aware of your own emotions, express them appropriately, and control them when necessary. It includes awareness of the emotions of others. 

    Connecting to people on an emotional level, and establishing rapport is essential in any business relationship. Whether you’re leading a team, interacting with customers, or expanding your network. 

    Investing time in developing your EQ will show returns in your own business life, and represents a valuable addition to your CV. 

    Final Thoughts

    Your time is valuable. And using it well, especially during the corona crisis, is essential.

    Acquiring skills that are valuable to your business, and that complement your freelance profile, will help you adapt to the post-corona market. 

    Whatever you choose to learn, online resources like  Skillshare, edX, Coursera, Codecademy, or Udemy provide the learning materials you need to succeed. 

    At the end of the day, though, committing to continually expanding your skillset, and adapting to new situations, is the most valuable skill you could possess. 

  • How Amperity Uses Machine Learning To Unlock Data and Supercharge Marketing

    How Amperity Uses Machine Learning To Unlock Data and Supercharge Marketing

    “Nobody was using machine learning to point at the underlying consumer data to help make sense of it and bring it together,” says Matthew Biboud-Lubeck of Amperity. “We put together cloud computing that was scalable with better economics alongside a machine learning algorithm that we were pointing at the data to help make sense of it. We realized that what we had was a pretty scalable solution to help brands get to that nirvana of a single view of the customer.”

    Matthew Biboud-Lubeck, VP of Strategic Services at Amperity, discusses how their platform helps brands create a complete view of their customers in an interview on the B2B Growth podcast:

    Helping Brands Create a Single View of Their Customers

    We are a CDP (customer data platform) based in Seattle that is helping brands create a single view of their customers and to unlock personalized experiences from that data. If you look back to the founding of Amperity about three years ago our founders were canvassing the marketplace. What you saw was a marketplace using a lot of buzzwords but having a lot of trouble executing them. You heard about personalization, customer 360, and a 360 view of the customer. Marketers across major consumer brands were super frustrated.

    They spent a fortune trying to cobble some view of their customer. They invested in technology to help them send better emails, to make their media more targeted, and to unveil better analytics. All of those tools that they have invested in talked about the notion of a single view of the customer because they fundamentally needed that to operate. The reality was that nobody was getting to the solution. We came in to say maybe there is a better way.

    Machine Learning Helps Brands Get To Nirvana

    There were two things that changed in the marketplace that we capitalized on. First of all, it was that cloud computing got a lot cheaper. It used to be that if you were a big brand and got hundreds of millions of customer interactions, it’s just a lot of data. Part of the reason that no one was able to create an easy solution to putting that all together was because it was cost prohibitive.

    The second really interesting evolution in the market is that machine learning has become much more mature. What we found was that everyone in the marketplace was using machine learning to make that last mile to the marketer a little bit better. It was used to decide which products to show a customer or to decide which offer to show a customer or to create a customer care solution that’s automated. You go online and type toward a solution and some bot talks back to you. Nobody was using machine learning to point at the underlying consumer data to help make sense of it and bring it together.

    We put together cloud computing that was scalable with better economics alongside a machine learning algorithm that we were pointing at the data to help make sense of it. We realized that what we had was a pretty scalable solution to help brands get to that nirvana of a single view of the customer. That’s how we were born. What’s interesting is that the customer data platform space is a little bit confusing. You have a lot of companies that started as something else that rebranded as a CDP. We were purpose-built from the ground up as a customer data platform designed to bring all of a brands data, reconcile that data to create a notion of identity on it and then to unleash that data back to the brand anywhere that they want to use that data.

    >>> Listen to the full B2B Growth podcast here.

  • Google Cloud Makes Healthcare API Publicly Available

    Google Cloud Makes Healthcare API Publicly Available

    Google Cloud has announced the general availability of its Healthcare API in an effort to help fight COVID-19.

    As the pandemic continues to take a toll, cloud computing and big data are emerging as important factors in the fight to control it. Now, more than ever, the ability to share data is vital. The CMS and ONC released rules a few months ago to aid in that goal, based on the 21st Century Cures Act. As Google points out, however, the necessary tools still need to be created to capitalize on those rules and provide healthcare professionals what they need.

    “To address this gap, we’ve made our Cloud Healthcare API generally available today to the industry at-large,” writes Joe Corkery, MD, Director of Product, Healthcare and Life Sciences, and Aashima Gupta, Director of Industry Solutions, Healthcare and Life Sciences. “The API allows healthcare organizations to ingest and manage key data from a range of inputs and systems—and then better understand that data through the application of analytics and machine learning in real time, at scale. It also enables providers to easily interact with that data using Web-friendly, REST-based endpoints and health plans to rapidly get up and running with a cloud based FHIR server providing the capabilities needed to implement, scale and support interoperability and patient access.”

    Google’s announcement is good news for the medical community, and will hopefully aid in the creation of the tools professionals need to continue combatting COVID-19.

  • Without AI, Real-Time Personalization Would Not Be Possible

    Without AI, Real-Time Personalization Would Not Be Possible

    “How do we shorten the space between a signal that we get, say in behavioral data that we see show up either in an app or on a website, and then churn through all of the possibilities of what we could present, apply algorithms to determine what is the next best offer and next best experience?” asks Adam Justis, Director of Marketing at Adobe Experience Cloud. “Then how do we present that in a way that actually feels if not real-time pretty close to it? That would not be possible without artificial intelligence.”

    Adam Justis, Director of Marketing at Adobe Experience Cloud, discusses how AI and machine learning are enabling near real-time shopping personalization in an interview with theCUBE at Adobe Imagine 2019 in Las Vegas:

    Role of AI in Offering a Personalized Shopping Experience is Core

    You definitely have the data piece and then the content piece. I would also add how the complexity of all that has certainly exceeded the capacity to manage this in a singular sort of engagement with a customer, let alone at scale millions of times a day. So the role of artificial intelligence and machine learning now is so core. It’s sort of the gearbox that’s turning at the center of the data on one hand and the content and elements, the assets, the offers, on the other that allows for ultimately the coalescing of those things and then the delivery of an experience worth having.

    That’s the component pieces that we’re seeing at play and Adobe’s motivation in going into that space. At Adobe when we announced our intent to acquire Magento, we were talking about how does Adobe facilitate or help every experience become shoppable and every moment personal? Really that was a claim we couldn’t make without the Magento piece. It is absolutely a hand in glove relationship especially as we’ve all evolved as consumers.

    Advancements in AI Are Going From the Absurd to the Very Real

    To imagine that we would be subscribing to socks or that we could one-click purchase just about anything, you need the technology that can keep pace with the expectations. That’s what it’s all about. So many of those experiences that Adobe is intent on enabling our customers to present culminate in a transaction of some sort. Magento is absolutely not only the icing on the cake but it’s also so integral. It’s becoming a fundamental or elemental part of what we’re trying to accomplish.

    That (personalized experience) is one of the things that I absolutely love about customer experience management or CXM. In a way I kind of love the absurdity of it. When you think of the scale, to say something like we’re going to make every experience shoppable and every moment personal, to imagine that that’s possible is almost absurd. But when you introduce the advancements that we’re seeing in artificial intelligence and machine learning now it’s literally going from the absurd or the realm of science fiction into very real. That’s what Adobe is looking at.

    Without AI Real-Time Personalization Would Not Be Possible

    How can we literally take some sort of statement like we’re going to personalize experiences across the customer journey and we’re going to do it at scale and in real-time? Really, unless you’re considering how we’re going to meet the needs of the customer in the moment that they’re expressing that need then it’s really moot. It is absolutely artificial intelligence and machine learning that we’re seeing expressed now across the Adobe Experience Cloud that is making that happen in multiple ways. One of the ways would be simply by shortening that span between the latent genius that marketers are walking around in their heads and actual execution. How can we take some of the friction out of the workflows that allow them to translate their ideas into offers?

    How do we shorten the space between a signal that we get, say in behavioral data that we see show up either in an app or on a website, and then churn through all of the possibilities of what we could present, apply algorithms to determine what is the next best offer and next best experience? Then how do we present that in a way that actually feels if not real-time pretty close to it? That would not be possible without artificial intelligence. At Adobe we do that through a product called Adobe Sensei.

    Adobe: Without AI Real-Time Personalization Would Not Be Possible
  • Microsoft Scores With NBA Partnership

    Microsoft Scores With NBA Partnership

    Microsoft has announced a multi-year partnership with the NBA, beginning with the 2020-21 season.

    Microsoft’s technology has been a staple on NFL sidelines for years, but the new NBA deal represents a significant expansion into the sports world. With the new deal, the NBA will use Microsoft’s Azure cloud platform to broadcast on-demand and live broadcasts.

    The partnership will also heavily utilize artificial intelligence (AI) and machine learning (ML) to improve the customer experience. The technology will be used to help generate a “more personalized fan experience,” based on the NBA’s video archives. AI and ML will also help provide coaches and broadcasters with unique insights.

    “We are thrilled to serve as the official AI partner of the NBA,” said Satya Nadella, CEO, Microsoft. “Together, we’ll bring fans closer to the game and players they love with new personalized experiences powered by Microsoft Azure.”

    “This partnership with Microsoft will help us redefine the way our fans experience NBA basketball,” said Adam Silver, NBA commissioner. “Our goal, working with Microsoft, is to create customized content that allows fans — whether they are in an NBA arena or watching from anywhere around the world — to immerse themselves in all aspects of the game and engage directly with our teams and players.”

    The partnership is a big win for Microsoft and the company’s technology will help revolutionize the experience for NBA officials and fans alike.

    Image Credit: Microsoft

  • Microsoft Using AI For Noise Suppression in Teams

    Microsoft Using AI For Noise Suppression in Teams

    Microsoft is working on using artificial intelligence (AI) to improve the sound quality of meetings in Teams.

    Microsoft Teams has been experiencing significant growth, both before and during the pandemic, as it takes on its chief rival Slack. As millions of people shelter in place and work from home, chat and videoconferencing software has become their lifeline to the outside world for work, association, family time and more.

    Unfortunately, one of the biggest irritations with videoconferencing is often the background noise—the cat meowing, dog barking, child playing or significant other watching TV. Now Microsoft is planning on using AI and machine learning to tackle the problem.

    As Robert Aichner, Microsoft Teams group program manager, told VentureBeat, the issue lies in cancelling non-stationary vs stationary noise. Stationary noise is constant, such as a computer’s fan. As such, stationary noise is relatively easy to suppress and Microsoft’s products, such as Teams and Skype, already do that. The challenge is suppressing non-stationary noise, such as a dog barking, a car horn blowing, or someone else in the room suddenly making noise.

    “That is not stationary,” Aichner explained. “You cannot estimate that in speech pauses. What machine learning now allows you to do is to create this big training set, with a lot of representative noises.”

    This is where machine learning comes, training the system using good and bad data examples, to help it better understand what needs to be filtered.

    “We train a model to understand the difference between noise and speech, and then the model is trying to just keep the speech,” Aichner continues. “We have training data sets. We took thousands of diverse speakers and more than 100 noise types. And then what we do is we mix the clean speech without noise with the noise. So we simulate a microphone signal. And then you also give the model the clean speech as the ground truth. So you’re asking the model, ‘From this noisy data, please extract this clean signal, and this is how it should look like.’ That’s how you train neural networks [in] supervised learning, where you basically have some ground truth.”

    The in-depth report at VentureBeat is a fascinating read, and shows what is possible as companies continue to use AI and machine learning across applications.

  • Microsoft and BlackRock Partner to Host Aladdin on Azure

    Microsoft and BlackRock Partner to Host Aladdin on Azure

    Microsoft has announced a big win for its Azure cloud platform: a deal to host BlackRock’s Aladdin infrastructure on Azure.

    Aladdin is an “end-to-end investment management and operations platform used by institutional investors including asset managers, pension funds, insurers and corporate treasurers.” By moving the infrastructure to Azure, BlackRock hopes to bring enhanced capabilities and an improved experience to its clients.

    “As both a user and a provider of Aladdin, this decision reflects BlackRock’s ongoing commitment to continuous innovation and scalable operating solutions,” said Rob Goldstein, Chief Operating Officer of BlackRock. “Aladdin infrastructure deployed on Microsoft Azure’s cloud platform will provide BlackRock with enhanced capabilities to deliver the best outcomes for our Aladdin clients.”

    “By bringing Aladdin to the cloud, Microsoft will support BlackRock in further enhancing its client experience while also enabling continuous innovation in the financial services industry,” said Judson Althoff, executive vice president of Microsoft’s Worldwide Commercial Business. “Together, we will empower an ecosystem of financial services customers running their most critical workloads in the cloud.”

    The two companies are committed to working together to further sustainability through the use of big data, machine learning and artificial intelligence. The deal is a big win for Microsoft, and will likely help it move further into the financial services industry.

  • There’s Been a Lot of Advances In Machine Learning, Says Etsy CEO

    There’s Been a Lot of Advances In Machine Learning, Says Etsy CEO

    “There’s been a lot of advances in machine learning that take things that would have been literally impossible ten years ago and made those things much more possible today,” says Etsy CEO Josh Silverman. “With 62 million products for sale, picking for any given buyer the 20 or 30 that should be on page one of search results is a pretty interesting and pretty challenging task. The key is understanding what an item is with relatively little data and then being able to determine for each individual person how to personalize search results.”

    Josh Silverman, CEO of Etsy, discusses how Etsy has increased growth by standing out in a world of sameness and by employing machine learning technology to personalize the Etsy experience for their customers. Silverman talks about his strategy for success in an interview with Fortune:

    We Started Doing Much Fewer Things Much Better

    Etsy has never been more relevant. In a world where so many of our products are being commoditized and we’re surrounded by a sea of sameness, Etsy stands for something really different. I think it’s really important that we stand out in the world and I’m proud of what the team has done to achieve that. The definition of success was really clear. I think from day one it’s about growing the size of the pie for everyone. The actual tactics that it was going to take to do that we’ve learned together as a team over time. 

    When I arrived, there were maybe eight or ten different metrics of success that we all held relatively equally. I said there’s one metric that matters much more than every other, which is what we call gross merchandise sales. In other words, the total sales of our sellers. When we stopped saying what’s a good idea, what moves any one of these 10 metrics and started saying, what are the fewest things we need to do to really accelerate gross merchandise sales, we came to a very different answer. We started doing much fewer things much better. That’s really been the key to our success.

    There’s Been a Lot of Advances In Machine Learning

    Change is hard. When running a marketplace we have access to a lot of data and insights that each individual seller won’t necessarily have. Our job is to really look after the good of the whole and be willing to make some decisions that sometimes, in the moment, may not feel obvious to every seller but really do lift all boats and make our sellers as a whole much better off. We’ve really focused at a high level on doing two things really well. One, make it much easier for people to find great products on Etsy. And two, once they’ve found those products to actually buy them. 

    With 62 million products for sale, picking for any given buyer the 20 or 30 that should be on page one of search results is a pretty interesting and pretty challenging task. There’s been a lot of advances in machine learning that take things that would have been literally impossible ten years ago and made those things much more possible today. The key is understanding what an item is with relatively little data and then being able to determine for each individual person how to personalize search results. We’ve made leaps and bounds in the science of search and machine learning. That’s more relevant at Etsy than almost anywhere else.

    The mission of Etsy is incredible. As the nature of work changes creativity can’t be automated. The role we play for creators and makers being able to harness their creative passions and power and turn that into a way to earn a living for their families is a mission that I think is ever more important in this fast-changing economy.

    There’s Been a Lot of Advances In Machine Learning, Says Etsy CEO Josh Silverman
  • Coronavirus: YouTube Turns to AI to Address Shortage of Human Moderators

    Coronavirus: YouTube Turns to AI to Address Shortage of Human Moderators

    YouTube is warning that some users’ videos may be improperly flagged due to the company relying on artificial intelligence (AI) to moderate videos.

    With more and more employees working from home during the coronavirus pandemic, YouTube is turning to AI and machine learning (ML) to make up for the shortage of human moderators. Unfortunately, AI and ML doesn’t always get it right and YouTube is warning that—in an attempt to keep violative content in check—some videos may be removed without actually violating policies.

    “Our Community Guidelines enforcement today is based on a combination of people and technology: Machine learning helps detect potentially harmful content and then sends it to human reviewers for assessment,” the blog post reads. “As a result of the new measures we’re taking, we will temporarily start relying more on technology to help with some of the work normally done by reviewers. This means automated systems will start removing some content without human review, so we can continue to act quickly to remove violative content and protect our ecosystem, while we have workplace protections in place.”

    Recognizing the potential inconvenience the situation will cause, YouTube will not be quick to issue “strikes” for removed content, and recommends users appeal any decision they believe was made in error.

    “As we do this, users and creators may see increased video removals, including some videos that may not violate policies. We won’t issue strikes on this content except in cases where we have high confidence that it’s violative. If creators think that their content was removed in error, they can appeal the decision and our teams will take a look. However, note that our workforce precautions will also result in delayed appeal reviews. We’ll also be more cautious about what content gets promoted, including livestreams. In some cases, unreviewed content may not be available via search, on the homepage, or in recommendations.”

    This is just another example of the pandemic’s far-reaching effects, as well as the increasing role AI and ML can play in a variety of situations.

  • Google Cloud Launches Cloud AI Platform Pipelines

    Google Cloud Launches Cloud AI Platform Pipelines

    Google Cloud has announced the launch of Cloud AI Platform Pipelines, to help deploy machine learning (ML) pipelines.

    “A machine learning workflow can involve many steps with dependencies on each other, from data preparation and analysis, to training, to evaluation, to deployment, and more,” writes Anusha Ramesh, Product Manager, TFX. “It’s hard to compose and track these processes in an ad-hoc manner—for example, in a set of notebooks or scripts—and things like auditing and reproducibility become increasingly problematic.”

    Cloud AI Platform Pipelines is designed to help alleviate the challenges of creating an ML pipeline with all the necessary dependencies. The new platform provides a way to “deploy robust, repeatable machine learning pipelines along with monitoring, auditing, version tracking, and reproducibility, and delivers an enterprise-ready, easy to install, secure execution environment for your ML workflows.”

    The new tool has two parts. The first is the enterprise-ready infrastructure the ML workflows will run on, and the second is the tools for creating the ML pipelines and components. Cloud AI Platform Pipelines has push-button installation in the Google Cloud Console and supports both the Kubeflow Pipelines SDK and the TFX SDK.

    Google Cloud’s new tool is available as a beta and should be a welcome addition for customers eager to add artificial intelligence and ML workflows to their cloud environments.

  • Verizon Partners With Pacific Northwest National Laboratory On 5G

    Verizon Partners With Pacific Northwest National Laboratory On 5G

    Verizon Business and the Pacific Northwest National Laboratory (PNNL) are teaming up to deliver 5G applications.

    The PNNL tackles some of the world’s biggest challenges, including energy efficiency, scientific discovery and national security. To aid in that goal, Verizon will be deploying its 5G Ultra Wideband at the PNNL’s Richmond, Washington facility. Together, the organizations will develop 5G applications for use in everything, ranging from first responders to chemistry to earth sciences research.

    Verizon’s 5G Ultra Wideband promises speeds measured in gigabits rather than megabits, along with sub-millisecond lag. That performance will open a world of new possibilities for PNNL, as it researches artificial intelligence, machine learning, AR/VR and more.

    “With Verizon, we plan to explore how cybersecurity will underpin 5G for critical infrastructure and how 5G will drive transformation in the protection of endpoint devices, advancement of artificial intelligence, the science behind autonomous systems and related internet of things applications,” said Scott Godwin, general manager of Corporate Partnerships & Alliances at PNNL. “This partnership fits squarely with PNNL’s commitment to explore the capability of new science and technology to further safety and security worldwide.”

    “Our 5G Ultra Wideband network is built to support transformational innovations and solutions across all industries,” said Tami Erwin, CEO of Verizon Business. “There’s no doubt 5G’s increased data bandwidth and super-low lag will help play a critical role in evolving response connectivity and mission operations for first responders. We’ve seen exciting use cases come out of our 5G First Responder Lab and are thrilled to see the new applications that will arise from our work with PNNL.”

  • Google Cloud and AT&T Partner For Network Edge 5G Computing

    Google Cloud and AT&T Partner For Network Edge 5G Computing

    Google Cloud and AT&T have announced a partnership between the two companies to help enterprises take advantage of 5G and edge computing.

    Edge computing moves processes closer to where data is being collected and used, rather than sending it to a data center for processing. Thanks to 5G, edge computing stands to usher in a whole new era of on or near-premise computing, significantly speeding up the speed and latency of critical and intensive operations.

    The partnership will allow Google Cloud to deliver technologies and capabilities to companies using AT&T’s 5G network. These technologies include artificial intelligence, machine learning, data and analytics, Kubernetes and more.

    “We are delighted to work with AT&T, a 5G leader, to help enterprises and the industry harness the potential of 5G,” said Thomas Kurian, CEO, Google Cloud. “Our co-innovation with AT&T aims to bring a multitude of 5G and Edge Computing solutions to address a diversity of use cases, driving real business value in industries like retail, manufacturing, gaming and more. We are deeply committed to helping drive positive business outcomes for enterprises by working with AT&T on 5G.”

    “We’re working with Google Cloud to deliver the next generation of cloud services,” said Mo Katibeh, EVP and CMO, AT&T Business. “Combining AT&T’s network edge, including 5G, with Google Cloud’s edge compute technologies can unlock the cloud’s true potential. This work is bringing us closer to a reality where cloud and edge technologies give businesses the tools to create a whole new world of experiences for their customers.”

    The announcement is another in a string of wins for Google Cloud as it works to take on AWS and Microsoft.

  • Google Cloud Replaces AWS As MLB’s Cloud Provider

    Google Cloud Replaces AWS As MLB’s Cloud Provider

    In its efforts to gain ground against AWS and Microsoft, Google has signed a multi-year deal to become Major League Baseball’s cloud provider.

    Google Cloud continues to be a distant third-place in the U.S. cloud market, behind leader AWS and second-place Microsoft. Despite its current standing, Google Cloud’s CEO Thomas Kurian has committed to becoming at least the second-place provider within five years. In its efforts to reach its goal, the company has recently completed an internal shakeup, cutting a number of jobs to better streamline its focus.

    Now the company has secured a multi-year deal to become MLB’s Official Cloud and Cloud Data and Analytics partner, replacing AWS as MLB’s provider. The deal also includes running Statcast on Google Cloud. Statcast is an automated tool to help the MLB analyze player abilities and movement. MLB will also use Google Ad Manager and Dynamic Ad Insertion in its ads business.

    “Every season we work to apply emerging technology to engage and support our fans, clubs and broadcasters in new and exciting ways,” said Jason Gaedtke, MLB’s Chief Technology Officer. “MLB has enjoyed a strong partnership with Google based on Google Ad Manager’s live ad delivery with MLB.tv as well as YouTube’s strong fan engagement during exclusive live games. We are excited to strengthen this partnership by consolidating MLB infrastructure on Google Cloud and incorporating Google’s world-class machine learning technology to provide personalized and immersive fan experiences. We couldn’t have picked a better technology partner across ad delivery, streaming, cloud computing and machine learning.”

    “MLB, which has led the sporting world in the use of data since the early 1990s, has shown the sports industry and sporting fans globally what’s possible when you combine data with human performance,” said Thomas Kurian, CEO of Google Cloud. “We’re looking forward to working with MLB to usher in a new era of innovation in sport, and together we can have a substantial impact on the game, giving the next generation of fans a different way to experience America’s favorite pastime.”

    This contract is a big win for Google as it touts its cloud abilities. According, to Google’s statement, “MLB’s migration to Google Cloud has already resulted in an exponential improvement in analytics and decision making, enabling MLB to provide teams with a unified data plane to enable accelerated decision making.”

    The company will likely be able to leverage that positive feedback to capture even more market share.

  • Oracle Launches Machine Learning Platform

    Oracle Launches Machine Learning Platform

    Oracle has announced the launch of its Oracle Cloud Data Science Platform, aiming to help enterprises take advantage of AI and machine learning.

    The new platform is an acknowledgement of the fact that few organizations today benefit from data science and machine learning to the extent possible. In many cases, this is because they lack the tools to take advantage of the data at their disposal. The new platform will enable enterprise customers to “collaboratively build, train, manage and deploy machine learning models to increase the success of data science projects.”

    The Cloud Data Science Platform is designed specifically with data science teams and scientists in mind, and includes the tools they need to streamline their processes.

    “Effective machine learning models are the foundation of successful data science projects, but the volume and variety of data facing enterprises can stall these initiatives before they ever get off the ground,” said Greg Pavlik, senior vice president product development, Oracle Data and AI Services. “With Oracle Cloud Infrastructure Data Science, we’re improving the productivity of individual data scientists by automating their entire workflow and adding strong team support for collaboration to help ensure that data science projects deliver real value to businesses.”

    With computer and information research scientists being in high demand, with tremendous future growth opportunities, tools like Oracle’s latest will become ever more important.

  • ARM Working On New Edge AI Chips

    ARM Working On New Edge AI Chips

    Artificial intelligence (AI) on the edge is a critical factor to widespread AI adoption and ARM is tackling the problem head-on with a pair of new chips, according to The Verge.

    Edge AI is the ability to run AI locally, on-device, rather than offloading to a remote server. The obvious benefits are increased speed, since there’s no latency back and forth between the remote server, as well as increased privacy.

    According to The Verge, ARM is working on “the Arm Cortex-M55 and the Ethos-U55, a neural processing unit meant to pair with the Cortex-M55 for more demanding use cases.” The Cortex-M55 provides up to 15 times better machine learning performance and up to 5 times better digital signal processing performance than previous Cortex-M processors.

    Unlike Intel or AMD, ARM doesn’t manufacture its own processors. Instead, it designs them and then licenses those designs to other companies, such as Apple, who go on to manufacture and use them. With these new chips, however, ARM isn’t targeting phones and tablets. The goal is to use the chips to “develop new Internet of Things devices, bringing AI processing to more devices that otherwise wouldn’t have those capabilities.”

    If the Cortex-M55 lives up to the hype, it should help usher in a whole new generation of AI-enabled devices and services.