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Facebook: Announcing New Products to Make Business Messaging Easier

The way people and businesses communicate is changing. One billion people message with a business each week on WhatsApp, Messenger and Instagram Direct — whether it’s DMing brands, browsing product catalogs, asking for support, or interacting with stories. This consumer behavior is accelerating and it’s changing how business gets done. Today at Conversations, our inaugural…

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The way people and businesses communicate is changing. One billion people message with a business each week on WhatsApp, Messenger and Instagram Direct — whether it’s DMing brands, browsing product catalogs, asking for support, or interacting with stories. This consumer behavior is accelerating and it’s changing how business gets done. Today at Conversations, our inaugural business messaging event, we discussed how messaging is transforming interactions between people and businesses, and announced new products to make conversations easier.

Introducing Cloud-based API on the WhatsApp Business Platform

Today, Mark Zuckerberg announced we’re opening up the new, cloud-based version of the WhatsApp Business Platform, hosted by Meta, to any business across the world. With this new API, we’re offering free, secure cloud hosting services so businesses and developers can easily access our service within minutes, build directly on top of WhatsApp to customize their experience and increase their response time for their customers. So now, whether a business wants to work with one of our 100+ partners or access our service directly, it will be much faster to get up and running on WhatsApp.

When growing a business, you need smart, robust and easy-to-use conversation tools. For smaller businesses using the WhatsApp Business app, we’re building tools so it’s easier to handle an influx of chats as they grow their customer base. 

Launching Recurring Notifications on Messenger

Today we’re announcing a new way for businesses to keep the conversation going with Recurring Notifications. As businesses acquire new customers and begin to scale operations, there’s incredible opportunity to build loyalty and trust — and we believe this is where the value of messaging really shines. This new capability makes it easy to re-engage people right in the messaging thread and deliver tailored messaging at the best time for customers, whether to hear about special promotions, new product drops or tips and tricks.

You can choose the topics you’d like to let people opt-in to, how often customers can hear from you and shape your content, so your messages are always on-brand and relevant. Recurring notifications will also be available for businesses on Instagram this fall.

We also highlighted our click-to-message ads to help customers immediately start conversations with businesses, our CRM platform Kustomer and Meta Business Suite for higher volumes of messages across Facebook, Messenger and Instagram. Read more about our product investments in business messaging on our Meta for Developers blog.

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Facebook: New AI Model Translates 200 Languages, Making Technology Accessible to More People

Language is our lifeline to the world. But because high-quality translation tools don’t exist for hundreds of languages, billions of people today can’t access digital content or participate fully in conversations and communities online in their preferred or native languages. This is particularly an issue for hundreds of millions of people who speak the many…

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Language is our lifeline to the world. But because high-quality translation tools don’t exist for hundreds of languages, billions of people today can’t access digital content or participate fully in conversations and communities online in their preferred or native languages. This is particularly an issue for hundreds of millions of people who speak the many languages of Africa and Asia.

To help people connect better today and be part of the metaverse of tomorrow, our AI researchers created No Language Left Behind (NLLB), an effort to develop high-quality machine translation capabilities for most of the world’s languages. Today, we’re announcing an important breakthrough in NLLB: We’ve built a single AI model called NLLB-200, which translates 200 different languages with results far more accurate than what previous technology could accomplish.

When comparing the quality of translations to previous AI research, NLLB-200 scored an average of 44% higher. For some African and Indian-based languages, NLLB-200’s translations were more than 70% more accurate. 

To best evaluate and improve NLLB-200, we built FLORES-200, a dataset that enables researchers to assess this AI model’s performance in 40,000 different language directions. FLORES-200 allows us to measure NLLB-200’s performance in each language to confirm that the translations are high quality. 

And to help other researchers improve their translation tools and build on our work, we’re opening NLLB-200 models and the FLORES-200 dataset to developers, in addition to our model training code and code for re-creating the training dataset. 

We’re also awarding up to $200,000 of grants for impactful uses of NLLB-200 to researchers and nonprofit organizations with initiatives focused on sustainability, food security, gender-based violence, education or other areas in support of the UN Sustainable Development Goals. Nonprofits interested in using NLLB-200 to translate two or more African languages, as well as researchers working in linguistics, machine translation and language technology, are invited to apply.

These research advancements will support more than 25 billion translations served every day in Feed on Facebook, Instagram and our other technologies. You can explore a demo of NLLB-200 and take a deeper dive into how we developed this model.

Expanded Translation and Greater Inclusion

An illustrative graphic showing how Meta's new AI translation model can be used in many ways.

A handful of languages — including English, Mandarin, Spanish and Arabic — dominate the web. Native speakers of these very widely spoken languages may take for granted how meaningful it is to read something in your own mother tongue. NLLB will help more people read things in their preferred language, rather than always requiring an intermediary language that often gets the sentiment or content wrong.

This work can also help advance other technologies, like building assistants that work well in languages such as Javanese and Uzbek, or creating systems to take Bollywood movies and add accurate subtitles in Swahili or Oromo. 

As the metaverse begins to take shape, the ability to build technologies that work well in a wider range of languages will help to democratize access to immersive experiences in virtual worlds.

Learn more about our work to build NLLB-200, which will help make the metaverse accessible to more people around the world.

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How to build a modern field service organization

Field service organizations have traditionally operated under the break-fix model—that is, responding to a device failure after the customer reports an issue. This operating model has grown antiquated due to rising costs and inefficiencies in labor and operations. It is also proving less than effective in satisfying the customer’s growing expectations. The field service industry…

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Field service organizations have traditionally operated under the break-fix model—that is, responding to a device failure after the customer reports an issue. This operating model has grown antiquated due to rising costs and inefficiencies in labor and operations. It is also proving less than effective in satisfying the customer’s growing expectations.

The field service industry is evolving quickly in new and exciting directions with cutting-edge technology continuing to enter the arena. These innovations in technology and workflows are helping to transform field service by providing customers optimal device uptime, along with greater visibility, efficiency, and profitability. The evolution of field service includes automation, AI, new learning tools, and mixed reality to help technicians achieve success.  

The ability to capture, digest, and derive actionable insights from data is critical in modernizing a field service organization. Intelligent, predictive systems driven by AI can automate time-consuming manual tasks like collecting data, diagnosing problems, and identifying the best solution to resolve an issue. AI can optimize resource management, empower field teams through mixed reality and mobilization, and can improve customer service with proactive and predictive service. In short, AI is providing organizations the ability to optimize the delivery of field service.

While service organizations lay frameworks of sensors and solutions to capture data across every facet of their organization, AI and machine learning represent the next steps that organizations are taking to leverage the value of the captured information. The ultimate goal is to transition from a reactive, break-fix service model to one that is proactive and predictive, achieving a near constant uptime. 

One organization leveraging mixed reality and field service is Burckhardt Compression. The leading global compressor company adopted Microsoft Dynamics 365 Remote Assist and Dynamics 365 Field Service so that engineers can quickly collaborate with ship technicians in remote locations and provide specialized mechanical expertise. They successfully reduced costs, decreased its carbon footprint, and can now respond to customer needs in mere minutes instead of days.

Improve the customer experience

Field service customers need stability and reliability in their businesses. They want visibility into their assets and need to minimize downtime when breakdowns occur.

Prior to AI-empowered systems, the customer would have to actively reach out to report that the device had failed. Depending on the type of failure, work using the device could be slowed or blocked for days or weeks until a technician could complete the repairs. Without intelligent support, the technician may need to return for follow-up visits, unnecessarily wasting both time and money.

AI allows for automated, remote self-healing and predictive forecasting, monitoring, and analyzing connected devices for potential issues. If one is identified, the system can remotely attempt to resolve problems through self-healing processes, like having the device restart itself during an off-time to mitigate an overheating failure. Using historical device data and predictive analytics, the system might make a recommendation to schedule a technician site visit to head off future problems, notifying the customer of the work order. The customer could then plan around the scheduled downtime and even track the technician’s arrival to the appointment in real-time.

During the visit, using recommendations from the system, the technician would be able to discuss additional products and services with the customer that meet their specific usage and operating needs. Ultimately, the customer gains more control over their assets, and the field service organization is empowered to provide improved service delivery capabilities.

Increase technician productivity

To be the most effective and prevent costly return visits, technicians must have complete access to the information and real-time guidance they need. The technician could utilize a digital twin of the device to learn about its status and operating condition, and to train on the particular problem that requires repair. AI’s cognitive capabilities can even help optimize repairs before a technician arrives, taking care of routine diagnostics and testing for common or similar issues. These capabilities ensure the technician is better prepared for the work and that their time—and the customer’s—is used efficiently.

The technician’s mobile service app empowers the technician to better manage appointment schedules and access turn-by-turn driving directions to the customer site. Onsite, this app can highlight the top two to three possibilities that might be wrong with the device. Chatbots can assist in locating customer, product, and work order information. Mixed reality tools, like Dynamics 365 Remote Assist, can create 3D renderings overlaid directly onto the device, highlighting missing or broken parts and allowing the technician to view performance data. AI can use data from predictive analytics to make just-in-time recommendations. A headset can be worn to identify irregularities and help maintain focus on the right issues without having to stop and troubleshoot, ensuring work is completed correctly the first time. And the technician can obtain assistance from a more experienced technician through Microsoft Teams if the issue is beyond their current skill set.

Optimize resource management

And finally, effectively managing resources, such as inventory and technician time, is at the heart of the challenge for any field service organization, creating a powerful competitive advantage when performed well. 

In a traditional field service organization, technicians are often dispatched based on availability, not proximity to the customer or experience with a specified device. A technician may arrive on-site with limited access to customer information and device history, impacting the ability to complete the repair on a first visit and driving up overall costs for the customer and the field service organization.

As an example, let’s look at a manufacturing customer experiencing a device failure. When a work order is scheduled in an intelligent system, assignments are optimized using multiple factors, such as a technician’s experience in handling the specific failure, the customer’s preferred technician, or the proximity to the site. Leveraging machine learning, this intelligent system can automatically assign the work order to the closest, best available technician matching specific criteria.

If the device were outfitted with an Internet of Things (IoT)-connected sensor, a real-time alert would be sent, triggering an automatic service request. The system would attempt to self-heal the issue first, and if unsuccessful, a technician would then analyze the data and commit a repair remotely, often without the customer ever knowing there was a problem. Sending the technician for an onsite visit would be the last option if the device could not be repaired remotely.

As more requests come in, the system would then optimize the technician’s schedule to create the most efficient path to navigate, allowing the technician more time to perform additional calls per day and driving greater revenue.

Real-time inventory management ensures that the replacement part is available on the scheduled date and that the technician has access to the tools needed to complete the repair. The system can identify the best parts to replace, where they should be purchased, and provide more accurate lead time predictions for the organization. Field service managers and technicians alike can synchronize and track inventory down to the truck level with real-time visibility to increase first time fix rates.

Get started today

AI enables field service organizations to evolve from the break-fix model by empowering technicians, optimizing resources, and improving customer experiences.

Microsoft offers a unique combination of world-class IoT, intelligence, scalability, and end-to-end field service capabilities. 

Learn more about Dynamics 365 Field Service and how it can transform your service organization.

Get started today with a live demo or a free trial today.

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Facebook: Taking Action Against Scraping for Hire

Today, we’ve filed separate actions in federal court against a company and an individual for scraping data from Facebook and Instagram. Octopus: Scraping For Hire The first action is against a company called Octopus, a US subsidiary of a Chinese national high-tech enterprise that claims to have over one million customers. Octopus offers scraping services…

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Today, we’ve filed separate actions in federal court against a company and an individual for scraping data from Facebook and Instagram.

Octopus: Scraping For Hire

The first action is against a company called Octopus, a US subsidiary of a Chinese national high-tech enterprise that claims to have over one million customers. Octopus offers scraping services and access to software that customers can use to scrape any website. For a fee, Octopus customers can launch scraping attacks from its cloud-based platform or hire Octopus to scrape websites directly. Octopus offers to scrape data from Amazon, eBay, Twitter, Yelp, Google, Target, Walmart, Indeed, LinkedIn, Facebook and Instagram.

After paying for access to the scraping software, customers self-compromised their Facebook and Instagram accounts by providing their authentication information to Octopus. Octopus designed the software to scrape data accessible to the user when logged into their accounts, including data about their Facebook Friends such as email address, phone number, gender and date of birth, as well as Instagram followers and engagement information such as name, user profile URL, location and number of likes and comments per post.

Meta is an industry leader in taking legal action to protect people from scraping and exposing these types of services, which provide scraping as a service across multiple websites. Companies like Octopus are part of an emerging scraping industry that provides automation services to any customer — regardless of who they target and for what purpose they scrape. This industry makes scraping available to individuals and companies that otherwise would not have the capabilities.

Our lawsuit alleges that Octopus has violated our Terms of Service and the Digital Millennium Copyright Act, by engaging in unauthorized and automated scraping and attempting to conceal their scraping and avoid being detected and blocked from Facebook and Instagram. We are seeking a permanent injunction against Octopus. Protecting people against scraping for hire services, operating across many platforms and national boundaries, also requires a collective effort from platforms, policymakers and civil society and is needed to deter the abuse of these capabilities both among those who sell them and those who buy them.

Mystalk: Targeting Clone Sites

We have also filed an action against a Turkish-based individual, Defendant Ekrem Ateş, for using automated Instagram accounts to scrape data from the profiles of over 350,000 Instagram users. These profiles were viewable to logged-in Instagram users. The Defendant published the scraped data on his own websites or “clone sites.” A clone site is a website that copies and displays Instagram profiles, posts and other information without authorization. Our External Data Misuse team has provided an overview of how we work to safeguard people against clone sites.

Since February 2021, we have taken a number of enforcement actions against this Defendant, including disabling accounts, sending a cease and desist letter, and revoking his access to Meta’s services.

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