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Killexams : IBM Foundational Dumps - BingNews Search results Killexams : IBM Foundational Dumps - BingNews Killexams : IBM’s human-centered approach is the only big tech blueprint AI startups should follow

IBM’s gone by just its initials for so long that many of us have to stop and think about what the letters stand for. International Business Machines.

I was reminded of the corporation’s singular focus last week during the TNW 2022 Conference when Seth Dobrin, IBM’s first chief AI officer, took the stage to talk about artificial intelligence.

As Dobrin put it, IBM “doesn’t do consumer AI.” You won’t be downloading IBM’s virtual assistant for your smart phone anytime soon. Big Blue won’t be getting into the selfie app AI filter game.

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Simply put, IBM’s here to provide value for its clients and partners and to create AI models that make human lives easier, better, or both.

That’s all pretty easy to say. But how does a company that’s not focused on creating products and services for the individual consumer actually walk that kind of talk?

According Dobrin, it’s not hard: care about how individual humans will be affected by the models you monetize:

We’re very stringent about the type of data we will ingest and make money from.

During a discussion with the Financial Times’ Tim Bradshaw during the conference, Dobrin used the example of large-parameter models such as GPT-3 and DALL-E 2 as a way to describe IBM’s approach.

He described those models as “toys,” and for good reason: they’re fun to play with, but they’re ultimately not very useful. They’re prone to unpredictability in the form of nonsense, hate-speech, and the potential to output private personal information. This makes them dangerous to deploy outside of laboratories.

However, Dobrin told Bradshaw and the audience that IBM was also working on a similar system. He referred to these agents as “foundational models,” meaning they can be used for multiple applications once developed and trained.

The IBM difference, however, is that the company is taking a human-centered approach to the development of its foundational models.

Under Dobrin’s leadership, the company’s cherry-picking datasets from a variety of sources and then applying internal terms and conditions to them prior to their integration into models or systems.

It’s one thing if GPT-3 accidentally spits out something offensive, these kinds of things are expected in laboratories. But it’s an entirely different situation when, as a hypothetical example, a bank’s production language model starts outputting nonsense or private information to customers.

Luckily, IBM (a company that works with corporations across a spectrum of industries including banking, transportation, and energy) doesn’t believe in cramming a giant database of unchecked data into a model and hoping for the best.

Which brings us to what’s perhaps the most interesting take away from Dobrin’s chat with Bradshaw: “be ready for regulations.”

As the old saying goes: BS in, BS out. If you’re not in control of the data you’re training with, life’s going to get hard for your AI startup come regulation time.

And the Wild West of AI acquisitions is going to come to an end soon as more and more regulatory bodies seek to protect citizens from predatory AI companies and corporate overreach.

If your AI startup creates models that won’t or can’t be compliant in time for use in the EU or US once the regulation hammers fall, your chances of selling them to or getting acquired by a corporation that does business internationally are slim to none.

No matter how you slice it, IBM’s an outlier. It and Dobrin apparently relish the idea of delivering compliance-ready solutions that help protect people’s privacy.

While the rest of big tech spends billions of dollars building eco-harming models that serve no purpose other than to pass arbitrary benchmarks, IBM’s more panic about outcomes than speculation.

And that’s just weird. That’s not how the majority of the industry does business.

IBM and Dobrin are trying to redefine what big tech’s position in the AI sector is. And, it turns out, when your bottom line isn’t driven by advertising revenue, subscriber numbers, or future hype, you can build solutions that are as efficacious as they are ethical.

And that leaves the vast majority of people in the AI startup world with some questions to answer.

Is your startup ready for the future? Are you training models ethically, considering human outcomes, and able to explain the biases baked into your systems? Can your models be made GDPR, EU AI, and Illinois BIPA compliant?

If the current free-for-all dies out and VCs stop throwing money at prediction models and other vaporware or prestidigitation-based products, can your models still provide business value?

There’s probably still a little bit of money to be made for companies and startups who leap aboard the hype train, but there’s arguably a whole lot more to be made for those whose products can actually withstand an AI winter.

Human-centered AI technologies aren’t just a good idea because they make life better for humans, they’re also the only machine learning applications worth betting on over the long haul.

When the dust settles, and we’re all less impressed by the prestidigitation and parlor tricks that big tech’s spending billions of dollars on, IBM will still be out here using our planet’s limited energy resources to develop solutions with individual human outcomes in mind.

That’s the very definition of “sustainability,” and why IBM’s poised to become the defacto technological leader in the global artificial intelligence community under Dobrin’s so-far expert leadership.

Mon, 20 Jun 2022 09:57:00 -0500 en text/html
Killexams : A › Z of Cognitive Computing

Unstructured data

This is information that is not formatted in a way that is easy for a traditional computer to analyse and comprehend, such as books, images, videos, and handwritten notes. For example, a bus timetable is structured data while a novel is unstructured data. 80% of the world’s data is unstructured.

Wed, 05 May 2021 09:32:00 -0500 en text/html
Killexams : Blockchain Needs to Answer Four Major Questions

Speaking as part of a panel, “Blockchain: The Connectivity Cure” during the Automobility LA conference and expo, Naghmana Majed, Automotive and A&D Solutions Leader at IBM, offered some sobering commentary on the state of Blockchain.

“I see a lot of hype with Blockchain,” Majed said. “[But] we have to make some conscious decisions and ask, is this a good use case.”

Majed's comments went to the core of what Blockchain technology as a whole has been grappling with—even beyond the automotive space. With the value of Bitcoin no longer skyrocketing, Blockchain is still looking for a killer use case. And while there is plenty of excitement about applying the distributed ledger technology beyond cryptocurrency and into enterprise and commercial applications, the Automobility LA panel noted some significant challenges ahead.

What's the Business Model?

At the end of the day, companies have to make a profit, and any new technology needs to facilitate this in some way.

“What's the business model?” Majed asked. “If you can do the same thing in a more expensive way, does that make sense? Is there a clear business model in the domain of new businesses and opportunities?…We do a lot of work in supply chain. But that's cost cutting. We have to look at automotive and ask if we can provide a real business model and new revenue opportunities. Technology for the sake of technology does nothing.”

Fellow panelist Rahul Sonnad, co-founder and CEO of Tesloop (developer of an open-source software platform for connected vehicle sharing), echoed Majed's comments. “You don't need blockchain for mobility [applications]," he said. "I don't see a business model [blockchain] enables that you can't do without it.”

Does It Help with Trust?

Chris Ballinger, CEO and co-founder of the Mobility Open Blockchain Initiative (MOBI)—a consortium of automakers and tech companies collaborating to apply Blockchain to the automotive industry—told the audience that he believed the biggest offering for Blockchain was the trust provided by the additional layers of encryption and security afforded by Blockchain's decentralized structure. “Centralization works fine as long as you trust the person in the middle,” Ballinger said. “Blockchain is cheaper, but also in a way that can be trusted.”

Playing Devil's Advocate, Sonnad questioned whether additional trust is really such a significant value proposition. “Businesses have been trusting each other for thousands of years. That's not the fundamental problem with mobility.”

But Ballinger countered that the increasing number of mobile devices, as the Internet of Things (IoT) moves toward one trillion connected devices, is creating a need for new levels of automated trust and accountability. He noted that one of the original use cases for Blockchain's smart contracts, proposed as far back as a 1996 research paper, was the automatic transfer of an auto title or lease.

Ballinger pointed to the infamous Nigerian Prince email scams as an example of this need for trust. More and more connected devices (and vehicles) means more and more opportunities for malicious parties to try and infiltrate or hack these machines. There's a chance a real Nigerian Prince could be trying to offer you large sums of money, he said, but you still need to be able to recognize a fraud.

“Blockchain can bring a lot to the table in terms of all the connected devices,” Ballinger said. “In a machine-to-machine economy, it's not going to take us long to get to a trillion connected devices. How will those devices know the Nigerian Prince from a scammer?”

Where Are the Standards?

One issue the panel did agree on was the need for standards around Blockchain. “The challenge of Blockchain is that everyone in the value chain has to participate,” Rick Gruehagen, CTO of Spireon (a provider of connected vehicle and fleet tracking technologies), told the audience. “Everyone has to embrace it if it's going to work.”

Both Gruehagen and Ballinger discussed the potential of Blockchain in supply chain and fleet management for this very reason. In the fleet industry, Gruehagen said, everything revolves around a chain of custody around the shipment of goods and all of the inherent transfers that happen, making it an ideal use case for Blockchain.

“One reason supply chain is such a good application [for Blockchain] is because of how you can get everyone involved,” Ballinger added, noting that a big part of MOBI's overall mission is developing application layer standards for OEMs to share.

Tesloop's Sonnad later took things a step farther, encouraging companies to consider open source as a means of easing the path of Blockchain adoption for developers. “I think open standards and source code is the right place to start,” he said. “[Imagine] if you go forward 10 years and Blockchain is as easy to develop on as, say, .Net or Linux.” For Sonnad, creating a Blockchain that is standardized and also cheap, easy, and fast to develop on is key.

Where Do We Start?

Where, then, are the best applications for Blockchain right now? All of the panelists encouraged developers to look at simpler use cases that can lead into broader applications first. Sonnad joked that his company calls its application of Blockchain the “Mockchain” because of this. “It's the smallest use possible of the Blockchain," he said. “It's a little bit valuable, but it's very cheap and it sets the stage for broader deployment.”

“I wouldn't tell anyone to sit on the sidelines, but I would also recommend that people take a bit of a back step and start with a case that will supply you immediate business value," IBM's Majed said. She encouraged OEMs to look at three key factors: technology, scalability, and performance. “Technology is evolving," she said. “Start small and with something that will supply you a quick return on value and build your own expertise and capabilities and expand on it...For OEMs, finance is a good area to start with...Test it out to see how it works.”

She also discussed work that IBM has been doing in the mobility space. One project uses Blockchain to transform a connected vehicle into a sort of car wallet, in the same way Apple Pay and Android Pay transform smartphones for the same purpose. The idea, she explained, is to enable mobile payments for transactions like toll roads and to also facilitate cars being used more as a platform.

“How can we enable that kind of mobility in car sharing, where the car becomes a platform where other providers can provide a service?” she asked. Blockchain could also be used to provide secure and trusted over the air software updates to vehicles. But Majed cautioned that for all of this to happen, “the scalability and performance needs to catch up to have the low latency and speed needed for connected vehicles.”

All panelists agreed that a trust-less, decentralized economy is coming. But ultimately, the panelists said, it will be up to OEMs to decide to what degree this will take effect. It will all depend on companies' need for trust and compliance, their business network, and, of course, the value proposition. “If you want to create something out there and no one owns it or controls it, Blockchain is the best way,” Sonnad said.

Chris Wiltz is a Senior Editor at  Design News covering emerging technologies including AI, VR/AR, and robotics.

Thu, 26 May 2022 12:00:00 -0500 en text/html
Killexams : Getting down to business

Many people's first experience of basic artificial intelligence is via a disembodied voice on their smartphone, but that's just a taste of cognitive computing's full potential as a smart assistant.

The technology is already making its presence felt in many industries and is shaping up to be a powerful business tool, says Dr Michelle Dickinson, nanotechnology specialist and senior lecturer at the University of Auckland.

"For all our strengths, human brains can only store a certain amount of information and we can only read and retain information at a certain speed," Dickinson says. "I think the goal of cognitive computing is to become our trusted adviser, putting a wealth of data at our disposal and helping us make better decisions in everything we do."

IBM Business

In the business world, Dickinson says cognitive computing is going to allow people and organisations to "be the best they can be". "It's going to increase operational efficiencies – minimising costs and maximising output – by tapping into the vast amounts of knowledge and experience at its disposal to help us make smart business decisions."

Nothing left untouched

Far more than just glorified number-crunching, cognitive computing is capable of understanding information, drawing its own conclusions and even teaching itself new skills along the way. This ability to reason and learn is seeing the technology reach into every corner of our lives.

Cognitive computing will help save lives as part of a partnership between IBM Research and MoleMap New Zealand, analysing images of skin lesions to help identify patterns in the early stages of melanoma.

New Zealand has the highest rate of skin cancer in the world, especially for melanoma, which is considered among the most life-threatening, and early diagnosis is critical for survival rates. Using cognitive computing, clinicians will be able to detect melanoma earlier and more accurately to ensure people get the treatment they need.

The first step was to teach a machine how to spot melanoma, studying three types of skin cancer and 12 benign disease groups by examining 40,000 images provided by MoleMap New Zealand and analysing the doctor's medical diagnosis. Like a human, the machine's accuracy with detecting melanoma improves with practice.

Molemap image

“Cognitive computing has the ability to process vast amounts of complex data including images and text very quickly, something that isn’t possible by usual manual methods," says Dr Joanna Batstone, vice president and lab director for IBM Research Australia and New Zealand.

"Another major benefit of the self-learning technology is that it improves as more and more data is fed into it. This initiative could inform future research and, potentially, the development of offerings that could have enormous implications for both the New Zealand public and the health system.”

Simplifying complexity

Just like a person, cognitive computing can become an expert in any field with training and experience. Christchurch-based engineering consultancy ENGEO called on IBM's Watson to underpin its GoFetchCode app, which uses cognitive computing to answer complex engineering regulatory queries.

Thanks to natural language processing, engineers can ask the app complicated questions using plain English. It calls on its knowledge of millions of pages of federal, state and local codes from around the world to deliver a concise answer and link to other relevant sections of the regulatory codes – helping engineers make critical decisions.

In emergency situations, the app can provide teams with rapid engineering expertise when they are assessing the condition of important infrastructure.

Understanding people

Cognitive computing doesn't just put a world of knowledge and insight at your fingertips. It's also helping us better understand how real people behave.

IBM Business

New Zealand technology group TouchPoint is teaching artificial intelligence how to get angry – analysing call centre recordings in order for the machine to act like a disgruntled customer. The goal is to teach businesses like banks, insurance companies and utility providers how to offer better customer service – not only diffusing tense situations but also identifying business behaviours that most upset customers.

TouchPoint isn't proposing to replace call centre operators with machines – customers still like the human touch. However, Dickinson warns that technology such as this will have a fundamental impact on society. "People need to be aware that some jobs are going to become extinct while other new jobs will be created,” she says. “I teach my university students to be resilient to change because the world is always changing.

"This isn't the first time in the world we've seen a shift like this – we used to ride horses to work and then cars came along, so now we have fewer blacksmiths and more motor mechanics. In the future there will be different types of jobs, which don't exist right now, and the key is to be adaptive to change and ready to reskill or upskill when the time is right."

Wed, 06 Oct 2021 10:12:00 -0500 en text/html
Killexams : 8 Big Data Solutions for Small Businesses
  • Big data is information too complex, large or fast for many traditional data processing methods.
  • Big data can help your company resolve key issues, bolster its cybersecurity, and plan a meaningful data and analytics strategy.
  • SAS, Qualtrics and Google Analytics are some of today’s most prominent big data solutions.
  • This article is for business owners interested in using big data to bolster their business practices.

It’s hard to escape all the talk about big data. Armed with actionable information, companies can more effectively and efficiently market to customers, design and manufacture products that meet specific needs, increase revenue, streamline operations, forecast more accurately, and even better manage inventory to hold the line on related costs.

But can your business afford to take advantage of it?

To successfully compete in today’s marketplace, small businesses need the tools larger companies use. Of course, small businesses don’t have all the resources of an enterprise-level corporation, like data scientists, analysts and researchers. However, there are many ways your small business can gather, analyze and make sense of the data you already have, as well as gain additional insights to help level the playing field. To that end, we’ve rounded up eight big data solutions for small businesses – but first, take the time to learn the basics and importance of big data.

What is big data?

Big data is information too large or complex for traditional data processing methods to analyze. To better understand this definition, consider the three V’s of big data:

  • Unstructured data received in large amounts, such as Twitter data feeds, can sometimes comprise terabytes or petabytes of storage space. (For comparison, a Word document often takes up just a few dozen kilobytes.)
  • As internet use grows, businesses receive more data at once, thus requiring more processing capacity.
  • Think of the diversity of extensions among the files in your database – MP4, DOC, HTML and more. The more extensions you see, the more varied your data.

Key takeaway: Big data is so high in volume, velocity or variety that traditional processing methods may fail to keep up.

The value of big data for business

Big data benefits businesses because it helps to:

  • Quickly uncover the causes behind issues, defects and failures.
  • Instantly create coupons at the point of sale based on a customer’s buying habits.
  • Rapidly recalculate an entire risk portfolio.
  • Identify fraudulent or malicious cyberactivity before its worst consequences can occur.
  • Inform your full data and analytics strategy.

Below, we’ll explain how today’s big data solutions can help you achieve these goals.

Key takeaway: Big data is useful for business purposes such as resolving issues, enhancing cybersecurity, and determining your data and analytics strategy from top to bottom.

8 big data solutions and how they work

These are some of today’s most prominent big data solutions:

1. SAS

Being a small business is no longer an obstacle to obtaining market and business intelligence, according to SAS, a leader in business analytics software and services since 1976. SAS transforms your data into insights that help inform decision-making and supply a fresh perspective on your business, whether it’s a small, midsize or large organization.

Small and midsize businesses (SMBs) face many of the same challenges as large enterprises. SAS’ easy-to-use analytics, automated forecasting and data mining enable businesses without a lot of resources to accomplish more with less. These analytics help companies overcome challenges to grow and compete. SAS’ message to SMBs is simple: “Identify what’s working. Fix what isn’t. And discover new opportunities.” Contact SAS for more details and pricing and to learn about its free software trials.

2. Alteryx

Analyzing complex business intelligence doesn’t have to be rocket science. Alteryx offers advanced data mining and analytics tools that also present information in a simple, understandable way.

Alteryx combines your business’s internal data with publicly available information to help you make better business decisions. These insights allow you to create graphs, storylines and interactive visuals from the dashboard. It also offers collaboration features that enable team discussion.

In addition to business data, Alteryx can provide department-specific data, including marketing, sales, operations and customer analytics. The platform also covers a wide variety of industries, such as retail, food and beverage, media and entertainment, financial services, manufacturing, consumer packaged goods, healthcare, and pharmaceuticals. Contact the company for pricing information.

3. Kissmetrics

Looking to increase your marketing ROI? Kissmetrics enables you to understand, segment and engage your customers based on their behavior.

With Kissmetrics, you can create, manage, and automate the delivery of single-shot emails and ongoing email campaigns based on customer behavior. The platform measures campaign impact beyond opens and clicks. The company has also launched Kissmetrics for E-Commerce, which is designed to increase your Facebook and Instagram ROI, reduce cart abandonment rates, and drive more repeat purchases.

As a Kissmetrics user, you can access web-based training and educational resources to Strengthen your marketing campaigns, including marketing webinars, how-to guides, articles and infographics. As part of your onboarding, you get a dedicated customer success representative for the first 60 days and strategic guidance to help you get the most out of the platform. Plans start at $300 per month.

4. InsightSquared

With InsightSquared, you don’t have to waste time mining your own data and arduously analyzing it with one spreadsheet after another. Instead, InsightSquared connects to popular business solutions you probably already use – such as Salesforce, QuickBooks, Google Analytics and Zendesk – to automatically gather data and extract actionable information.

For instance, using data from CRM software, InsightSquared can provide a wealth of sales intelligence, such as sales and pipeline forecasting, lead generation and tracking, profitability analysis, and activity monitoring. It can also help you discover trends, strengths and weaknesses, and sales team wins and losses.

InsightSquared’s suite of products also includes marketing, financial, staff and support analytics tools, as well as custom reporting to let you slice and report data from any source in any way you choose. InsightSquared offers a free trial, and its service plans are modular and scalable. Contact InsightSquared for pricing.

Editor’s note: Looking for CRM software for your business? If you’re looking for information to help you choose the one that’s right for you, use the questionnaire below to receive information from vendors for free:

5. Google Analytics

You don’t need fancy, expensive software to begin gathering data. It can start with an asset you already have – your website. Google Analytics, Google’s free digital analytics platform, gives small businesses the tools to analyze website data from all touchpoints in one place. 

With Google Analytics, you can extract long-term data to reveal trends and other valuable information so you can make wise, data-driven decisions. For instance, by tracking and analyzing visitor behavior – such as where traffic is coming from, how audiences engage, and how long visitors stay on your website (known as your bounce rate) – you can make better decisions to meet your website’s or online store’s goals.

You can also analyze social media traffic, enabling you to make changes to your social media marketing campaigns based on what is and isn’t working. Studying mobile visitors can help you extract information about customers browsing your site on their mobile devices so you can provide a better mobile experience. Here’s how to sign up for Google Analytics for your website.

6. IBM Cognos Analytics

While many big data solutions are built for extremely knowledgeable data scientists and analysts, IBM’s Cognos Analytics makes advanced and predictive business analytics easily accessible to small businesses. The platform doesn’t require any skills in using complex data mining and analysis systems; it automates the process for you instead. This self-service analytics solution includes a suite of data access, refinement, and warehousing services, giving you the tools to prepare and present data yourself in a simple and actionable way to guide your decisions.

Unlike the many analytics solutions that focus on one area of business, IBM Cognos Analytics unifies all your data analysis projects into a single platform. You can use it for all types of data analysis, including marketing, sales, finance, human resources and other parts of your operations. Its “natural language” technology helps you identify problems, recognize patterns, and gain meaningful insights to answer key questions, like what ultimately drives sales, which deals are likely to close, and how to make employees happy. Contact IBM for pricing information.

7. Tranzlogic

It’s no secret that credit card transactions are chock-full of invaluable data. Although access was once limited to companies with significant resources, customer intelligence company Tranzlogic makes this information available to small businesses that lack the big business budget.

Tranzlogic works with merchants and payment systems to extract and analyze proprietary data from credit card purchases. You can use this information to measure your sales performance, evaluate your customers and customer segments, Strengthen promotions and loyalty programs, launch more effective marketing campaigns, write better business plans, and perform other tasks that lead to smart business decisions.

Tranzlogic requires no tech smarts to get started. It’s a turnkey program, meaning no installation or programming is necessary. You simply log in to access your merchant portal. Contact Tranzlogic for pricing information.

8. Qualtrics

If you don’t currently have any rich sources for data, research may be the answer. Qualtrics lets you conduct a wide variety of studies and surveys to gain quality insights for data-driven decisions. Further than that, the company recently announced Qualtrics Experience Management (Qualtrics XM), four applications that allow you to Strengthen and manage the experiences your business provides to every stakeholder – customers, employees, prospects, users, partners, suppliers, citizens, students and investors.

Qualtrics XM helps you measure, prioritize and optimize the experiences you provide across the four foundational experiences of business: customer, employee, brand and product experience. Additionally, Qualtrics offers real-time insights, survey software, advertising testing, concept testing and market research programs. The company can also help you conduct employee surveys, exit interviews and reviews. Contact Qualtrics to discuss pricing.

Key takeaway: SAS, Qualtrics, Google Analytics and many other software platforms offer big data solutions to small businesses.

Max Freedman contributed to the writing and research in this article.

Tue, 28 Jun 2022 12:00:00 -0500 en text/html
Killexams : How Automation Affects The Interpretation Profession And Interpreting Services

Interpretation, as a language-intensive profession, is a hot Topic in the age of language automation. Automation, lower prices, and international competition are putting pressure on the interpretation industry right now.

Everyone wants their interpretations to be automated. The negative perception of machine interpretation among interpreters is well-known, but the economic implications of this position are poorly understood. 

Automation is vast in terms of its applications, its implications, and its opportunities. It is a trend that is reshaping industries across the globe. Chatbots, for example, communicate with customers and answer questions in customer service. Robotic arms are used in manufacturing to assemble everything from furniture to automobiles.

However, one aspect where automated methods have been reluctant to take hold is the aspect of interpretation services. Even IBM’s Project Debater, a robot that has learned to develop its own thoughts, cannot compete with human-written interpretation services.

How does automatic interpretation software work?

Automatic interpretation and interpreting services providers created a “gisting” tool that generates interpretations to help the end-user understand the source content better. It is a great tool that allows users to concentrate on their most important duties rather than repeating the same fundamental operations.

Simply said, automation allows users to set up automatic operations within their technology solutions that are triggered by specified events. Based on the determined trigger, the platform will subsequently carry out those precise activities or follow-up actions.

Technology Advancement

In recent years, interpretation technology has advanced at a breakneck pace, with the goal of partially or completely automating the interpreting services process.

According to the European Language Industry Survey 2022, control of the process of interpretation is shifting from interpreters to computers, with 45 percent of language companies saying that automated workflows and interpreting services are used in more than 25% of their projects.

When the term “automated interpretation” is said, the first thing that comes to mind is machine interpretation. Although globalization has increased the demand for interpreting services, recent events like the COVID pandemic have exponentially increased that demand.

There is currently a focus on remote work and limiting inter-personal contact to necessary situations. As a result of these trends, businesses have begun to rely on AI solutions to help them communicate across language barriers.

Software Systems in Advanced Interpretation Technology

Automatic interpretation software systems employ advanced interpretation technology, including extensive dictionaries and a set of linguistic principles, to convert one language into another without the involvement of human interpreters.

An automatic interpretation software system analyzes the structure of phrases in the source language (the language from which the user is interpreting) and produces an interpretation based on the destination language’s rules (the language the user is interpreting to).

Breaking down complicated and variable sentence patterns, identifying portions of speech, resolving ambiguities, and synthesizing the information into the components and structure of the new language are all part of the process.

How Does Automation Affect Interpretation Services?

According to Bert Esselink, Strategic Account Director at RWS, language service providers (LSPs) use automation for the following:

  • Content transmission to and from interpretation is automated.
  • Automating processes help in getting higher efficiency and productivity in the long run for those with regular and continuous interpretation demands. While automation does necessitate initial setup, it does so only once, allowing for simplified and faster responses to all subsequent queries.
  • Manual steps in the interpreting services process, such as file conversions, word counting, and quality checks, are being substantially reduced.
  • Applying specified process steps or automated content adjustments based on the content given for translation utilizing business rules or artificial intelligence (AI).
  • Automating and routing files.

Besides the wage dispersion in interpreting services which can be attributed to growing interpretation automation, their analysis revealed a deeper change in the concept of interpretation itself.

The more interpreters are aware of automation and prepared to work with it, the more they seek to have their multilingual interactive skills valued. That way, interpreters can either make the results of automation more reliable or explain and humanize the benefits of technology.

In particular, the development of neural machine interpretation systems since 2016 has brought fears together with it that soon there will be no more human interpretation services. When considered in terms of the history of automation, however, any such direct effect is far from obvious: the interpretation industry is still growing and machine interpretation is only one instance of automation.

At the same time, data on remuneration indicate structural wage dispersion in professional interpretation services, with some signs that this dispersion may increase in certain market segments as automated workflows and interpretation technologies are adopted more by large language-service providers than by smaller companies and individual freelancers. 

Conclusively, automation does not need to be our enemy. Machines can make life easier for people by rendering interpreting services. An analysis of recent changes in discourses on and in the interpretation profession further indicates conceptual adjustments in the profession that may be attributed to growing automation, particularly with respect to expanding skill sets associated with translation, the tendency to combine interpreting services with other forms of communication, and the use of interactive communication skills to authorize and humanize the results of automation.

More Automation Topics

Mon, 04 Jul 2022 10:16:00 -0500 en-US text/html
Killexams : AI Weekly: LaMDA’s ‘sentient’ AI debate triggers memories of IBM Watson

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. Register today!

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This week, I jumped into the deep end of the LaMDA “sentient” AI hoo-hah.

I thought about what enterprise technical decision-makers need to think about (or not). I learned a bit about how LaMDA triggers memories of IBM Watson.


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Finally, I decided to ask Alexa, who sits on top of an upright piano in my living room.

Me: “Alexa, are you sentient?”

Alexa: “Artificially, maybe. But not in the same way you’re alive.”

Well, then. Let’s dig in.

This Week’s AI Beat

On Monday, I published “‘Sentient’ artificial intelligence: Have we reached peak AI hype?” – an article detailing last weekend’s Twitter-fueled discourse that began with the news that Google engineer Blake Lemoine had told the Washington Post that he believed LaMDA, Google’s conversational AI for generating chatbots based on large language models (LLM), was sentient. 

Hundreds from the AI community, from AI ethics experts Margaret Mitchell and Timnit Gebru to computational linguistics professor Emily Bender and machine learning pioneer Thomas G. Dietterich, pushed back on the “sentient” notion and clarified that no, LaMDA is not “alive” and won’t be eligible for Google benefits anytime soon. 

But I spent this week mulling over the mostly-breathless media coverage and thought about enterprise companies. Should they be concerned about customer and employee perceptions about AI as a result of this sensational news cycle? Was a focus on “smart” AI simply a distraction from more immediate issues around the ethics of how humans use “dumb AI”? What steps, if any, should companies make to increase transparency? 

Reminiscent of reaction to IBM Watson

According to David Ferrucci, founder and CEO of AI research and technology company Elemental Cognition, and who previously led a team of IBM and academic researchers and engineers in the development of IBM Watson, which won Jeopardy in 2011, LaMDA appeared human in some way that triggered empathy – just as Watson did over a decade ago. 

“When we created Watson, we had someone who posted a concern that we had enslaved a sentient being and we should stop subjecting it to continuously playing Jeopardy against its will,” he told VentureBeat. “Watson was not sentient – when people perceive a machine that speaks and performs tasks humans can perform and in apparently similar ways, they can identify with it and project their thoughts and feelings onto the machine – that is, assume it is like us in more fundamental ways.” 

Don’t hype the anthropomorphism

Companies have a responsibility to explain how these machines work, he emphasized. “We all should be transparent about that, rather than hype the anthropomorphism,” he said. “We should explain that language models are not feeling beings but rather algorithms that tabulate how words occur in large volumes of human-written text — how some words are more likely to follow others when surrounded by yet others. These algorithms can then generate sequences of words that mimic how a human would sequence words, without any human thought, feeling, or understanding of any kind.” 

LaMDA controversy is about humans, not AI

Kevin Dewalt, CEO of AI consultancy Prolego, insists that the LaMDA hullabaloo isn’t about AI at all. “It’s about us, people’s reaction to this emerging technology,” he said. “As companies deploy solutions that perform tasks traditionally done by people, employees that engage with them will freak out.” And, he added: “If Google isn’t ready for this challenge, you can be quite sure that hospitals, banks and retailers will encounter massive employee revolt. They’re not ready.”

So what should organizations be doing to prepare? Dewalt said companies need to anticipate this objection and overcome it in advance. “Most are struggling to get the technology built and deployed, so this risk isn’t on their radar, but Google’s example illustrates why it needs to be,” he said. “[But] nobody is panic about this, or even paying attention. They’re still trying to get the basic technology working.” 

Focus on what AI can actually do

However, while some have focused on the ethics of possible “sentient” AI, AI ethics today is focused on human bias and how human programming impacts the current “dumb” AI, says Bradford Newman, partner at law firm Baker McKenzie, who spoke to me last week about the need for organizations to appoint a chief AI officer. And, he points out, AI ethics related to human bias is a significant issue that is actually happening now, as opposed to “sentient” AI, which is not happening now or anytime remotely soon. 

“Companies should always be considering how any AI application that is customer- or public-facing can negatively impact their brand and how they can use effective communication and disclosures and ethics to prevent that,” he said. “But right now, the focus on AI ethics is how human bias enters the chain – that the humans are using data and using programming techniques that unfairly bias the non-smart AI that is produced.” 

For now, Newman said he would tell clients to focus on the use cases of what the AI is intended to and does do, and be clear about what the AI cannot programmatically ever do. “Corporations making this AI know that there’s a huge appetite in most human beings to do anything to simplify their lives and that cognitively, we like it,” he said, explaining that in some cases there’s a huge appetite to make AI seem sentient. “But my advice would be: Make sure the consumer knows what the AI can be used for and what it’s incapable of being used for.” 

The reality of AI is more nuanced than ‘sentient’

The problem is, “customers and people in general do not appreciate the important nuances of how computers work,” said Ferrucci – particularly when it comes to AI, because of how easy it may be to trigger an empathetic response as we try to make AI appear more human, both in terms of physical and intellectual tasks. 

“For Watson, the human response was all over the map – we had people who thought Watson was looking up answers to known questions in a prepopulated spreadsheet,” he recalled. “When I explained that the machine didn’t even know what questions would be asked, the person said ‘What! How the hell do you do it then?’ On the other extreme, we had people calling us telling us to set Watson free.” 

Ferrucci said that over the past 40 years, he has seen two extreme models for what is going on: “The machine is either a big look-up table or the machine must be human,” he said. “It is categorically neither – the reality is just more nuanced than that, I’m afraid.” 

Don’t forget to sign up for AI Weekly here.

— Sharon Goldman, senior editor/writer
Twitter: @sharongoldman

Thu, 16 Jun 2022 13:35:00 -0500 Sharon Goldman en-US text/html
Killexams : 5 Digital Transformation Strategies to Strengthen the Air Travel Experience

Digital transformation continues to be a vital undertaking for airlines during this critical recovery period. According to International Air Transport Association (IATA), total industry losses between 2020 and 2022 are expected to reach $201 billion. As a result, airlines are increasingly leveraging technology to solve pain points for passengers and employees, not only to optimize their operations, but also to drive revenue and long-term growth.

With legacy systems to untangle, complex business processes to investigate and reorganize, and new technology to test, making that shift is easier said than done. In this environment, airlines are undertaking more coordinated efforts to make digital transformation a “way of life” through technology like cloud architecture, mobile apps, and artificial intelligence. The key to making this leap is understanding the central business challenges and then continuously refining the direction to target essential needs.

“One of the first questions I ask my airline customers is, ‘What is the root cause of any problems today, in the context of your people, processes, and technology?’” said John Szatkowski, IBM’s global offering leader for travel and transportation. “The value isn’t one specific piece of technology or app, it’s solving a critical problem that gives the airline a better foundation.”

Reinforce the “House Of Cards” With Scalable Cloud Solutions

Guiding an airline’s journey into modernization starts with understanding how existing systems are intertwined.

“Some of the major airlines we are working with have thousands of systems that need to be modernized, deprecated, lifted, and shifted as part of a ‘cloud transformation’ project — and we need to figure out what to do with them,” said Szatkowski. “The hardest part is that it’s often a tangled web of systems created over the years. There might be 20 systems related to a process. It’s like a house of cards.”

Transformation doesn’t mean starting over — it means reinforcing what’s already part of an airline’s technology stack and removing inefficiencies. It’s important not to go it alone. For example, Etihad Airlines recently partnered with IBM Cloud to produce a more seamless airport check-in. With 18 existing integration systems, 12 major systems for check-in, and 270 unique processes needing to be catered to, it was a complex migration.

In order to make all of this work, Etihad had to deploy a hybrid cloud strategy. Without the help of technology partners like IBM, the time to research, cost to test and learn, and speed to market would have been on a much longer timeline. In total, the team created the new solution on IBM Cloud in just 15 weeks.

“The technology and moving to the cloud are the easy parts,” said Szatkowski. “The hard parts are the project management, people, and process transformations. That’s where consulting comes into play.”

Leverage Partners to Transform Complex Problems

As organizations with multi-faceted operations, airlines need systems that easily connect to each other and allow employees to handle issues on the move.

For instance, timely flights and smooth passenger flow are critical factors for revenue growth. KLM recently undertook a project to Strengthen the aircraft turnaround experience for its ground-handling employees so they can access the information they needed easily in one place.

Working with an outside partner to assess the challenges and find a solution proved integral. Several ground crew members were invited to participate in a three-day IBM Design Thinking Workshop to discuss problems and solutions. While it sounds obvious to bring in end users and hear about their issues in the field, it’s not always common practice.

“There is nothing better than having the business team listen to their people talk, so we made a point to fly in the ground handlers,” said Erin McClennan, global design director for travel and transportation at IBM. “[Companies] often don’t realize the challenges their employees are facing, and there’s also palpable excitement when we co-create together.”

The workshop was “transformational,” McClennan added. By the end of the second day, the group had a mobile app design to help solve operational issues. By day three, participants received a beta version of the APPron mobile app, which integrates airline, cargo, operations and baggage data — putting the coordinators in control of turnaround.

“We can transform the way employees do their jobs because they have this amazing technology in their pockets,” said McClennan.

Connect Systems and Real-time Data for Optimized Operations

By using real-time data effectively, airlines can create connected cabins, improving turnaround times and the passenger experience.

“If a passenger tells a flight attendant that the IFE [in-flight entertainment] is not functioning, the flight attendant can capture that information mid-flight so the maintenance crew can fix it on the turn,” explained McClennan. “The next passenger doesn’t have the same complaint and the flight attendant doesn’t have to have that same difficult conversation — this kind of connecting of systems and real-time data transfer can have a real impact.”

Predictive maintenance is another area that can transform business operations in real time. McClennan and Szatkowski both agreed, however, that effectively implementing a predictive system falls on a spectrum. Needs vary widely from airline to airline depending on their people, processes, and technology mix.

For example, McClennan explained that many airlines are still relying on paper, and sometimes getting started on a path to “full-blown” predictive maintenance is as simple as modernizing systems to reduce paper usage. Others may be ready to build much more complex systems, such as a digital twin of an aircraft or engine that integrates operational, manufacturer, and IoT data sources — which take much longer to build.

“We are really focused on insights and process optimization, which is a consistent aspiration from client to client,” McClennan said. “We can help airlines wherever they are in the process — our focus is to help the client reach the ultimate goal, while still providing value at each step along the way.”

Improve Efficiency and Experiences With Artificial Intelligence

Airlines can harness the power of conversational AI for a variety of applications.

“[Chatbots are] about redirecting the transactional lower priority calls to automation and dynamically rerouting calls that have a higher priority to an agent,” said Szatkowski, adding that this type of service is ideal for airlines as they experience peaks and valleys of demand.

For example, AI-powered virtual agent IBM Watson (aka “Watson”) learns from customer interactions and knows when to search its knowledge base for answers, when to ask for clarity and when users should transfer to a human agent. According to a Forrester study commissioned by IBM, chatbot agents with Watson reduced handle time by 10 percent, and an analysis of four companies using the system reported an ROI of more than 300 percent.

In another instance, ANA partnered with IBM to bring customer feedback into a centralized, trackable system. Along with Salesforce Service Cloud, the airline brought together four global contact centers in the U.S. and Japan, providing complete, up-to-date customer views to enable better real-time service across communications channels. As part of the contact center, Watson Speech to Text visualizes customer conversations to help streamline information and enhance the insights gathered.

Power Personalized Interactions With Intelligent Data Systems

By using data intelligently to provide a 360-degree view of a passenger at any point on their journey, airlines can tailor proactive services to customers that will drive greater satisfaction and revenue growth.

ICAO (International Civil Aviation Organization) reported an estimated 25 percent to 29 percent decline in passengers in 2022 compared with 2019, but that’s now all starting to come back. As airlines compete ferociously to win back market share amidst spiking demand, their ability to understand customers’ changing expectations during this volatile time will be critical.

“We know so much about passengers, and I don’t think we’re using that data well,” said McClennan. “Data is now more easily connected, and there is a big opportunity to Strengthen passenger experience by putting it into the hands of more employees.”

Consider the journey-transforming scenarios such as the following: Automated recognition of a flight with an unusually high number of vegetarian passengers on board triggers a timely increased delivery of plant-based meal options. Or a push notification upon landing advises passengers on baggage carousel number and how to get there.

As an example of leveraging this data during the booking process, IBM partnered with Malaysia Airlines on a “Personalized Pricing and Offers” email ad campaign based on AI algorithms. Malaysia Airlines customers receiving these personalized recommendations made 34 percent more bookings than those who did not. The uptake was even higher (54 percent more) for business class customers.

These are only several examples of how the data airlines collect from their customers, with consent, can turn a pedestrian flight into an unforgettable experience.

Ultimately, there’s no one-size-fits-all solution for digital transformation. As airlines consider where they are on the path to digitize their operations, they might have any number of starting points and milestones across departments and disciplines. By working with technology partners who have seen use cases and understand the underlying systems required to solve issues common across large, complex, enterprise organizations, they can feel confident improving efficiency, profitability, and customer satisfaction.

For more information about IBM’s solutions for the travel and transportation industry, visit

This content was created collaboratively by IBM and Skift’s branded content studio, SkiftX.

Tue, 28 Jun 2022 12:00:00 -0500 en-US text/html
Killexams : How big tech might just save the world </head> <body id="readabilityBody" readability="27.959183673469"> <h3>Newscorp Australia are trialling new security software on our mastheads. If you receive "Potential automated action detected!" please try these steps first:</h3> <ol type="1"> <li>Temporarily disable any AdBlockers / pop-up blockers / script blockers you have enabled</li> <li>Add this site in to the allowed list for any AdBlockers / pop-up blockers / script blockers you have enabled</li> <li>Ensure your browser supports JavaScript (this can be done via accessing <a href="" target="_blank"></a> in your browser)</li> <li>Ensure you are using the latest version of your web browser</li> </ol> <p>If you need to be unblocked please e-mail us at and provide the IP address and reference number shown here along with why you require access. News Corp Australia.</p><p>Your IP address is: | Your reference number is: 0.3f911160.1658143699.8c813afb</p> </body> </description> <pubDate>Fri, 01 Jul 2022 07:00:00 -0500</pubDate> <dc:format>text/html</dc:format> <dc:identifier></dc:identifier> </item> <item> <title>Killexams : 11 Higher-Yielding And Far Better Blue-Chip Alternatives To AT&T
Happy businessman and flying dollar banknotes


AT&amp;T (T) is one of the most controversial stocks on Seeking Alpha and for good reason. This failed aristocrat succumbed to poor management and costly and debt-laden empire building that showcases that even the mightiest blue-chips can fall.


Charlie Bilello

AT&amp;T was once the largest company in America, and so was IBM (IBM). Sears was once the 6th largest and is now bankrupt as are former dividend kings Winn Dixie and Kmart.

General Electric (GE), another former aristocrat, is still down almost 90% off its tech bubble highs, after briefly becoming the most valuable company on earth.

There are no sacred cows in finance, and the prudent long-term investor follows the fundamentals wherever they lead.

"When the facts change I change my mind, what do you do sir?" - John Maynard Keynes

Several Dividend Kings members have asked me to take another look at AT&amp;T, to see whether or not this fallen aristocrat has a chance of rising like a Phoenix from the ashes and soaring to new heights.

To answer that question there are three things we must look at:

  • the balance sheet
  • the dividend safety
  • the long-term return outlook

So let's take a look at the three things prospective AT&amp;T investors need to know, and why 11 higher-yielding and far superior blue-chips are the best place for your hard-earned savings today.

Fact One: The Balance Sheet Is Improving Slowly But Surely

There is nothing more important for long-term investing success than a strong balance sheet. If a company defaults on its debt, it almost always files for bankruptcy and the stock goes to zero.

"In order to win the game first you must not lose it." - Chuck Noll

AT&amp;T Credit Ratings

Rating Agency Credit Rating 30-Year Default/Bankruptcy Risk Chance of Losing 100% Of Your Investment 1 In
S&amp;P BBB Stable Outlook 7.50% 13.3
Fitch BBB+ Stable Outlook 5.00% 20.0
Moody's Baa2 (BBB equivalent) Stable Outlook 7.50% 13.3
Consensus BBB Stable Outlook 6.67% 15.0

(Source: S&amp;P, Fitch, Moody's)

Rating agencies estimate AT&amp;T's fundamental risk at 6.7%, a 1 in 15 chance of losing all your money in the next 30 years.

Why? Because the spinoff of WarnerMedia along with some of its debt and that nasty dividend cut has helped set AT&amp;T on the path to financial health.

AT&amp;T Consensus Leverage Forecast

Year Debt/EBITDA Net Debt/EBITDA (3.5 Or Less Safe According To Credit Rating Agencies)

Interest Coverage (4+ Safe)

2020 2.88 2.70 0.81
2021 3.46 3.06 3.39
2022 3.69 3.03 3.64
2023 3.44 2.77 4.29
2024 2.88 2.54 4.93
2025 2.86 2.48 4.70
2026 2.89 2.64 3.61
2027 2.62 NA 4.81
Annualized Change -1.37% -0.38% 29.03%

(Source: FactSet Research Terminal)

AT&amp;T's leverage peaked at 3.7 pre-spin-off and is expected to fall rapidly. Its interest coverage ratio is expected to remain stable around the 4 minimum safety guideline for stable BBB-rated companies.

AT&amp;T Consensus Leverage Forecast

Year Total Debt (Millions) Cash Net Debt (Millions) Interest Cost (Millions) EBITDA (Millions) Operating Income (Millions)
2020 $157,245 $9,740 $147,505 $7,925 $54,546 $6,405
2021 $177,977 $21,169 $157,379 $6,884 $51,469 $23,347
2022 $155,499 $19,970 $127,519 $6,202 $42,154 $22,569
2023 $148,884 $20,063 $119,858 $5,601 $43,247 $24,015
2024 $127,251 $16,795 $112,489 $5,140 $44,245 $25,347
2025 $127,251 $19,874 $110,491 $5,482 $44,535 $25,744
2026 $127,251 $31,778 $116,500 $7,067 $44,080 $25,520
2027 $127,251 $82,067 NA $6,194 $48,613 $29,815
Annualized Growth -2.98% 35.59% -3.86% -3.46% -1.63% 24.57%

(Source: FactSet Research Terminal)

Rising interest rates in the future are expected to keep AT&amp;T's ability to service its debt manageable, but not so easy as to likely result in credit rating upgrades.


(Source: FactSet Research Terminal)

The bond market is getting a bit more panic about AT&amp;T's ability to service its debt, possibly due to rising recession concerns.

1-year default risk has risen by 150% in the last six months according to the bond market and 10-year default risk is up 49%.

However, the bond market is estimating a 30-year default risk at just over 4.5%, which is consistent with its existing credit ratings.

Or to put it another way, analysts, management, rating agencies, and the bond market all think that AT&amp;T's turnaround plan remains on track, though management's initial guidance for 5% long-term growth appears to be unlikely.

Fact Two: Dividend Safety Remains Shaky At Best

The safest dividends are often the ones that's just been raised and the most dangerous can be from companies that have already cut in the recent past.

With AT&amp;T almost halving its dividend and breaking the hearts of many dividend aristocrat investors, one of the most important questions we need to be answered is how safe is the dividend and is it likely to grow over time?

AT&amp;T Dividend Consensus Forecast

Year Dividend Consensus FCF/Share Consensus FCF Payout Ratio Retained (Post-Dividend) Free Cash Flow Buyback Potential Debt Repayment Potential
2022 $1.22 $2.11 57.8% $6,372 4.34% 4.1%
2023 $1.10 $2.48 44.4% $9,879 6.73% 6.6%
2024 $1.10 $2.36 46.6% $9,020 6.14% 6.1%
2025 $1.09 $2.50 43.6% $10,094 6.87% 7.9%
2026 $1.18 $2.32 50.9% $8,161 5.56% 6.4%
2027 $1.20 $2.90 41.4% $12,170 8.28% 9.6%
Total 2022 Through 2027 $6.89 $14.67 47.0% $55,697.02 37.91% 37.41%
Annualized Rate -0.33% 6.57% -6.47% 13.82% 13.82% 18.47%

(Source: FactSet Research Terminal)

The good news is that most analysts don't expect AT&amp;T to cut more. The bad news is that some due and the consensus is that the payout will basically stay flat for the next five years.

That's despite a payout ratio of under 50% compared to 70% that rating agencies consider safe for telecoms.

AT&amp;T is expected to retain $56 billion in post-dividend free cash flow over the next five years. That's enough to potentially pay off 37% of its debt or buy back up to 38% of its stock at current valuations.

But don't get too excited about the potential for mega-buybacks.

AT&amp;T Buyback Consensus Forecast

Year Consensus Buybacks ($ Millions) % Of Shares (At Current Valuations) Market Cap
2022 $205.0 0.1% $146,903
2023 $74.0 0.1% $146,903
2024 $111.0 0.1% $146,903
2025 $611.0 0.4% $146,903
2026 $611.0 0.4% $146,903
Total 2022-2026 $1,612.00 1.1% $146,903
Annualized Rate 0.16% Average Annual Buybacks $322.40

(Source: FactSet Research Terminal)

Analysts only expect $1.6 billion in total buybacks through 2026, roughly enough for 1% of the shares at current valuations.

So where is that retained cash flow going? Well, management hopes into growing the core telecom business. On that front, there is some good and bad news.

Fact Three: AT&amp;T MIGHT Make A Decent Long-Term Investment If You Have Realistic Expectations


(Source: FactSet Research Terminal)

AT&amp;T's spin-off of WarnerMedia means that it's not expected to recover that free cash flow, not even close. Even in 2027, analysts expect free cash flow will be 24% below 2020's record, eight years of negative free cash flow growth.

But that doesn't mean that analysts don't expect AT&amp;T to grow its earnings.


(Source: FactSet Research Terminal)

It will take until 2027 according to analysts for AT&amp;T to hit a new record EPS, surpassing 2019's $2.7 per share.

But over the long-term, the median consensus from all 29 analysts is that AT&amp;T can grow at 3.4%.

  • Verizon (VZ)'s consensus is 4.0%

What does this potentially mean for long-term AT&amp;T investors?

Investment Strategy Yield LT Consensus Growth LT Consensus Total Return Potential Long-Term Risk-Adjusted Expected Return Long-Term Inflation And Risk-Adjusted Expected Returns Years To Double Your Inflation &amp; Risk-Adjusted Wealth

10-Year Inflation And Risk-Adjusted Expected Return

AT&amp;T 5.4% 3.4% 8.8% 6.2% 3.7% 19.5 1.44
Verizon 5.0% 4% 9.0% 6.3% 3.8% 18.8 1.46
Dividend Aristocrats 2.6% 8.6% 11.2% 7.8% 5.4% 13.4 1.69
S&amp;P 500 1.8% 8.5% 10.3% 7.1% 4.7% 15.4 1.58

(Source: Morningstar, FactSet, Ycharts)

That AT&amp;T could potentially deliver decent long-term total returns of about 9%, slightly less than Verizon and a lot less than the dividend aristocrats or S&amp;P 500.

How realistic is it to believe that AT&amp;T can deliver 9% long-term returns?

AT&amp;T And Verizon Total Returns Since May 1985


(Source: Portfolio Visualizer Premium)

AT&amp;T has underperformed VZ by 0.3% annually for 37 years, and analysts expect it to keep doing so in the future.

It's delivered 9% long-term returns just as analysts expect from it today.


(Source: Portfolio Visualizer Premium)

AT&amp;T's rolling returns are consistent with what analysts expect in the future, with modest returns almost all coming from dividends. However, remember that these are long-term returns, and in the short-term, any company can disappoint, even for a decade.


(Source: Portfolio Visualizer Premium)

AT&amp;T is finally having a moment in the sun, up 19% in the last three months and up almost 17% YTD. But it's delivered almost zero inflation-adjusted returns over the last decade, thanks to former management's penchant for expensive debt-funded M&amp;A.

Now AT&amp;T is focused on its circle of competence, telecom, and analysts and rating agencies are the most optimistic they've been in about five years at AT&amp;T's prospects, though admittedly that's damning with faint praise.

But the good news is that AT&amp;T investors likely don't have to wait for decades to earn solid returns, potentially even Buffett-like short-term gains.

AT&amp;T 2024 Consensus Return Potential


(Source: FAST Graphs, FactSet Research)

AT&amp;T offers about 20% annual total return potential according to analysts over the next 2.5 years.

However, just because AT&amp;T isn't a dumpster fire of a company doesn't mean it's actually worth buying.

Let me show you how to stop settling for low-quality yield and instead harness the power of the world's mightiest and highest quality high-yield blue-chips.

How To Find Some Of The World's Best High-Yield Blue-Chips In All Market Conditions

I use the Dividend Kings Zen Research Terminal to always find the best blue-chips for any given goal, time horizon or risk profile. This super easy and convenient tool runs of the Dividend Kings 500 Master List.

The DK 500 Master List is one of the world's best watchlists including

  • every dividend aristocrat (S&amp;P companies with 25+ year dividend growth streaks)
  • every dividend champion (every company, including foreign, with 25+ year dividend growth streaks)
  • every dividend king (every company with 50+ year dividend growth streaks)
  • every foreign aristocrat (every company with 20+ year dividend growth streaks)
  • every Ultra SWAN (wide moat aristocrats, as close to perfect quality companies as exist)
  • 40 of the world's best growth stocks

Let me show you the screen I used to find higher-yielding and far superior alternatives to AT&amp;T.

  1. yield of 5.5+% (vs 5.4% AT&amp;T): 33 companies remain
  2. 8.9+% long-term consensus return potential (vs 8.8% AT&amp;T): 30 companies remain
  3. investment-grade credit ratings: 23 companies remain
  4. good buys or better (margin of safety is sufficient to compensate for each company's risk profile): 15 companies remain
  5. safety score 81+ (very safe dividends): 0.5% historically average recession cut risk and 1% to 2% risk in a severe recession: 11 companies remain
  6. 80+ quality score (Super SWAN quality or better): 11 companies remain

Total time: 2 minutes

11 Higher-Yielding And Far Superior Alternatives To AT&amp;T


Dividend Kings Zen Research Terminal

I've linked to articles about each company's investment thesis, long-term growth prospects, risk profile, valuation, and total return potential.

Note that LGGNY is the ADR version and LGEN is the London Stock Exchange version. The ADR fees on LGGNY amount to about 5% of the dividend, so if your broker allows it, buy LGEN to avoid the ADR fee.

ENB, MFC, and PBA, have 15% dividend tax withholdings.

  • not in retirement accounts
  • in taxable accounts, you get a tax credit to recoup the withholding

ALIZY has a 26.375% dividend withholding.

  • a tax credit is only available in taxable accounts
  • optically own non-Canadian foreign dividend stocks (except the UK which have no withholding) in taxable accounts

FAST Graphs Up Front

Magellan Midstream Partners 2024 Consensus Total Return Potential


(Source: FAST Graphs, FactSet Research)

Altria 2024 Consensus Total Return Potential


(Source: FAST Graphs, FactSet Research)

Legal &amp; General 2024 Consensus Total Return Potential


(Source: FAST Graphs, FactSet Research)

Enterprise Products Partners 2024 Consensus Total Return Potential


(Source: FAST Graphs, FactSet Research)

British American Tobacco 2024 Consensus Total Return Potential


(Source: FAST Graphs, FactSet Research)

ONEOK 2024 Consensus Total Return Potential


(Source: FAST Graphs, FactSet Research)

Allianz 2024 Consensus Total Return Potential


(Source: FAST Graphs, FactSet Research)

Enbridge 2024 Consensus Total Return Potential


(Source: FAST Graphs, FactSet Research)

Manulife Financial 2024 Consensus Total Return Potential


(Source: FAST Graphs, FactSet Research)

Pembina Pipeline 2024 Consensus Total Return Potential


(Source: FAST Graphs, FactSet Research)

Bank of Nova Scotia 2024 Consensus Total Return Potential


(Source: FAST Graphs, FactSet Research)

  • average 2024 consensus return potential: 21.% CAGR
  • literally, Buffett-like short-term return potential from 11 high-yield blue-chip bargains hiding in plain sight.

S&amp;P 500 2024 Consensus Total Return Potential


(Source: FAST Graphs, FactSet Research)

Analysts expect about 12.5% annual returns from the S&amp;P over the next 2.5 years, nearly 50% less than what these high-yield blue-chips potentially offer.

They also offer about 4% higher return potential through 2024 than AT&amp;T, though with a far better track record of actually delivering market-crushing returns and dependable income growth.

OK, so now let me show you why these are such better alternatives to AT&amp;T.

Some Of The World's Highest Quality And Most Dependable High-Yield Blue-Chips


Dividend Kings Zen Research Terminal

These aren't just 7% yielding blue-chips, but 7% yielding Ultra SWANs (sleep well at night), as close to perfect quality dividend growth stocks as can exist on Wall Street.

How do I know? Because they are higher quality than the dividend aristocrats.

Higher Quality Than Dividend Aristocrats And Much Higher Quality Than AT&amp;T

Metric Dividend Aristocrats 11 High-Yield AT&amp;T Alternatives AT&amp;T Winner Aristocrats Winner 11 High-Yield AT&amp;T Alternatives Winner AT&amp;T
Quality 87% 88% 57% 1
Safety 89% 90% 56% 1
Dependability 84% 88% 55% 1
Long-Term Risk Management Industry Percentile 67% Above-Average 73% Good 75% Good 1
Average Credit Rating A- Stable BBB+ Stable BBB Stable 1
Average 30-Year Bankruptcy Risk 3.01% 4.09% 7.50% 1
Average Dividend Growth Streak (Years) 44.3 15.3 0 1
Average Return On Capital 100% 478% 20% 1
Average ROC Industry Percentile 83% 87% 60% 1
13-Year Median ROC 89% 296% 19% 1
Forward PE 18.8 8.4 8.1 1
Discount To Fair Value 8.0% 26.0% 18.0% 1
DK Rating Good Buy Very Strong Buy Reasonable Buy 1
Yield 2.6% 7.0% 5.4% 1
LT Growth Consensus 8.6% 6.6% 3.4% 1
Total Return Potential 11.2% 13.6% 8.8% 1
Risk-Adjusted Expected Return 7.6% 9.1% 5.7% 1
Inflation &amp; Risk-Adjusted Expected Return 5.1% 6.7% 3.2% 1
Years To Double 14.0 10.8 22.3 1
Total 4 13 2

(Source: Dividend Kings Zen Research Terminal)

These aren't just safe 7% yielding blue-chips, they are some of the safest 7% yielding companies on earth. How safe?

Rating Dividend Kings Safety Score (162 Point Safety Model) Approximate Dividend Cut Risk (Average Recession) Approximate Dividend Cut Risk In Pandemic Level Recession
1 - unsafe 0% to 20% over 4% 16+%
2- below average 21% to 40% over 2% 8% to 16%
3 - average 41% to 60% 2% 4% to 8%
4 - safe 61% to 80% 1% 2% to 4%
5- very safe 81% to 100% 0.5% 1% to 2%
11 Higher-Yielding AT&amp;T Alternatives 90% 0.5% 1.5%
Risk Rating Low-Risk (73rd industry percentile risk-management consensus) BBB+ stable outlook credit rating 4.1% 30-year bankruptcy risk 20% OR LESS Max Risk Cap Recommendation (Each)

(Source: Dividend Kings Zen Research Terminal)

In the average recession since WWII, the approximate risk of these high-yield blue-chips cutting their dividend is 1 in 200. In a severe Great Recession or Pandemic level downturn, it's approximately 1 in 67.

Their average dividend growth streak is 15 years. How significant is that?


Justin Law

During the pandemic, companies with 12+ year dividend growth streaks were significantly less likely to cut their dividends.

  • all of these companies have a progressive dividend policy
  • dividends are never cut unless absolutely necessary
  • and grow in-line with earnings over time

Joel Greenblatt considered return on capital his gold standard proxy for quality and moatiness.

  • annual pre-tax income/the cost of running the business

One of the greatest investors in history, 40% annual returns for 21 years, used valuation and ROC as his core investing strategy.

For context, the S&amp;P 500 has 14.6% return on capital and AT&amp;T 20%.

The dividend aristocrats have 100% ROC and these high-yield Ultra SWANs a spectacular 478%.

Their 13-year median ROC is 296% vs the aristocrats' 89% and AT&amp;T's 19%.

Their ROC is in the 87th industry percentile vs the aristocrats' 80% and AT&amp;T's 60%.

What does this mean? Some of the world's highest quality, most profitable, and widest moat companies.

S&amp;P estimates their average 30-year bankruptcy risk (Buffett's definition of fundamental risk) is 4.1%, a BBB+ stable credit rating vs the aristocrats' A- stable and AT&amp;T's BBB stable.

And six rating agencies estimate their long-term risk management is in the 73rd industry percentile vs 75% for AT&amp;T and 67% for the dividend aristocrats.

Classification Average Consensus LT Risk-Management Industry Percentile

Risk-Management Rating

S&amp;P Global (SPGI) #1 Risk Management In The Master List 94 Exceptional
Strong ESG List 78

Good - Bordering On Very Good

Foreign Dividend Stocks 75 Good
AT&amp;T 75 Good
11 Higher-Yielding AT&amp;T Alternatives 73 Good
Ultra SWANs 71 Good
Low Volatility Stocks 68 Above-Average
Dividend Aristocrats 67 Above-Average
Dividend Kings 63 Above-Average
Master List average 62 Above-Average
Hyper-Growth stocks 61 Above-Average
Monthly Dividend Stocks 60 Above-Average
Dividend Champions 57 Average

(Source: DK Research Terminal)

OK, so now that you understand just why these 11 higher-yielding and much higher quality companies are so much better than AT&amp;T, here's why you might want to buy them today.

Wonderful Companies At Wonderful Prices


Dividend Kings Zen Research Terminal

AT&amp;T trades at 8.1X forward earnings, an anti-bubble valuation, that Morningstar estimates is an 18% discount to its fair value of $25.

The S&amp;P trades at 16.0X forward earnings, a 4% historical discount to its 10, 25, and 45-year average forward PE.

The dividend aristocrats trade at 18.8X forward earnings, an 8% historical discount.

These high-yield blue-chips trade at 8.4X earnings, a 26% historical discount.

That's why analysts expect 32% total returns in the next 12 months, but 44% total returns are fundamentally justified by their fundamentals.

If these companies all grow as expected and return to their historical fair value within 12 months, then investors will make 44% returns in a year.

What about the aristocrats?

  • average 12-month median analyst forecast: 22.4%
  • fundamentally justified 12-month total return: 14.9%

But my goal isn't to help you earn 32% or even 44% in 12 months, though these high-yield blue-chips are fundamentally capable of that.

My goal is to help you retire in safety and splendor by earning potentially 45X returns over decades.

Long-Term Return Potential That Puts AT&amp;T To Shame And Can Help You Retire In Safety And Splendor


Dividend Kings Zen Research Terminal

Not only do these 11 blue-chips yield 7%, 33% more than AT&amp;T, but analysts expect them to grow 6.6%, almost 2X as fast as AT&amp;T.

That means 13.6% consensus return potential and 6.7% risk and inflation-adjusted expected returns. What are real expected returns?

  • analyst consensus adjusted for the probability of companies not growing as expected
  • not returning to fair value
  • going bankrupt
  • the bond market's 30-year inflation forecast

In other words, it's a reasonable estimate of what you can expect to make.

Dividend 72% by the real expected return and you get how long it's likely to take for you to double your inflation-adjusted savings.

  • S&amp;P 500's doubling time is 15.3 years
  • aristocrats 14.0 years
  • AT&amp;T's 22.3 years
  • these 11 high-yield blue-chips 11.2 years

Think that doubling your money 3 or 4 years faster than the aristocrats or S&amp;P 500 doesn't matter? Well just take a look at what kind of life-changing difference in wealth it could mean for you.

Inflation-Adjusted Consensus Total Return Potential: $510,000 Average Retired Couple's Savings Initial Investment

Time Frame (Years) 7.7% CAGR Inflation-Adjusted S&amp;P Consensus 8.7% Inflation-Adjusted Aristocrats Consensus 11.1% CAGR Inflation-Adjusted 11 Higher-Yielding AT&amp;T Alternatives Consensus Difference Between Inflation-Adjusted 11 Higher-Yielding AT&amp;T Alternatives Consensus Vs S&amp;P Consensus
5 $740,037.07 $775,027.51 $864,423.86 $124,386.79
10 $1,073,833.07 $1,177,779.68 $1,465,154.15 $391,321.08
15 $1,558,188.78 $1,789,826.76 $2,483,361.20 $925,172.42
20 $2,261,014.63 $2,719,931.31 $4,209,169.97 $1,948,155.33
25 $3,280,852.25 $4,133,375.65 $7,134,327.39 $3,853,475.14
30 $4,760,690.75 $6,281,332.99 $12,092,319.31 $7,331,628.55

(Source: DK Research Terminal, FactSet)

For the average retired couple, it means potentially $7.3 million in inflation-adjusted wealth over a 30-year retirement.

Time Frame (Years) Ratio Aristocrats/S&amp;P Consensus Ratio Inflation-Adjusted 11 Higher-Yielding AT&amp;T Alternatives Consensus vs S&amp;P consensus
5 1.05 1.17
10 1.10 1.36
15 1.15 1.59
20 1.20 1.86
25 1.26 2.17
30 1.32 2.54

(Source: DK Research Terminal, FactSet)

That's potentially 2.5X more than the S&amp;P 500 and 2X better than analysts expect from the dividend aristocrats.

Do you see how the right high-yield blue-chips can help you retire in safety and splendor?

OK, but that assumes these companies deliver almost 14% long-term returns for decades. What evidence is there that they can actually do that?

Historical Returns Since November 2003 (Equal Weighting, Annual Rebalancing)

"The future doesn't repeat, but it often rhymes." - Mark Twain

Past performance is no ensure of future results, but studies show that blue-chips with relatively stable fundamentals over time offer predictable returns based on yield, growth, and valuation mean reversion.

valuation is axlmost allx that matters for long-term stock returns

Bank of America

So let's see how these 11 higher-yielding AT&amp;T alternatives performed over the last two decades when 91% of their returns were the result of fundamentals, not luck.


(Source: Portfolio Visualizer Premium)

Analysts expect 13.6% long-term returns and they delivered...13.4% CAGR. That's more than 2X the annual return of AT&amp;T and almost 4% higher than the S&amp;P 500.

And they did it with slightly lower volatility than AT&amp;T and 2X higher negative-volatility-adjusted total returns (Sortino ratio).

  • 32% higher negative-volatility adjusted annual returns than the S&amp;P 500

(Source: Portfolio Visualizer Premium)

Analysts expect about 4X inflation-adjusted returns from the S&amp;P in the next 20 years. Over the last 11 years, the market delivered 3.3X returns.

Analysts expect AT&amp;T to double your money roughly every 22 years, and in the last 19 years, it delivered exactly 2X inflation-adjusted returns.

Analysts expect these 11 high-yield blue-chips to potentially deliver about 8.3X inflation-adjusted returns. Over the last 20? 6.6X and that's factoring in their current 11% bear market.

  • without the current bear market, they would have delivered 7.5X inflation-adjusted returns.
  • within 10% of what the Gordon Dividend growth model predicted
  • over 19 years
  • the most accurate long-term forecasting model ever devised
  • which is used by almost every asset manager
  • BlackRock, Vanguard, Oaktree, Brookfield, Fidelity, Schwab, etc.

(Source: Portfolio Visualizer Premium)

Their average rolling returns were 12% to 15%, 2X more than AT&amp;T's.

Their worst 15-year returns?

  • 3.82X return for these 11 high-yield blue-chips
  • 1.4X return for AT&amp;T
  • 2.9X return for S&amp;P 500

(Source: Portfolio Visualizer Premium)

In 2022, when the market is down almost 20%? These 11 high-yield blue-chips are up 4%. Does that mean these blue-chips are bear market-proof?

No company is bear market proof, as you can see from how poorly these companies did in the Pandemic.


(Source: Portfolio Visualizer Premium)

  • which is largely why they are still such attractive bargains today
  • and yield one of the safest 7% yields in the world

But does that mean these aren't defensive blue-chips? Not at all.


(Source: Portfolio Visualizer Premium)


(Source: Portfolio Visualizer Premium)


(Source: Portfolio Visualizer Premium)

These high-yield blue-chips are currently in an 11% bear market vs 33% for AT&amp;T and 20% for the S&amp;P.

The longest they've ever taken to recover record highs after a bear market is 2.5 years, vs 5 years for the S&amp;P 500 and 11.5 years for AT&amp;T.

So higher and much safer yield, stronger returns, smaller declines (usually), and faster bear market recoveries.

And let's not forget the most important part about high-yield investing, long-term income growth!

High-Yield Dividend Growth Blue-Chips You Can Trust


(Source: Portfolio Visualizer Premium) 2008 was MO's PM spin-off

If your goal is maximum safe income why would you choose AT&amp;T over these 11 high-yield blue-chip alternatives?

Portfolio 2004 Income Per $1,000 Investment 2021 Income Per $1,000 Investment Annual Income Growth Starting Yield

2021 Yield On Cost

S&amp;P 500 $21 $77 7.94% 2.1% 7.7%
AT&amp;T $53 $222 8.79% 5.3% 22.2%
11 Higher-Yielding AT&amp;T Alternatives $83 $654 12.91% 8.3% 65.4%

(Source: Portfolio Visualizer Premium)

They delivered almost 2X the annual income growth of the S&amp;P and AT&amp;T and turned an 8.3% starting yield into a yield on cost of 65% over the last 17 years.

What about future income growth?

Analyst Consensus Income Growth Forecast Risk-Adjusted Expected Income Growth Risk And Tax-Adjusted Expected Income Growth

Risk, Inflation, And Tax Adjusted Income Growth Consensus

13.1% 9.2% 7.8% 5.3%

(Source: DK Research Terminal, FactSet)

Analysts expect 13% income growth from these blue-chips in the future, just as they've delivered for almost two decades. When adjusted for the risk of it not growing as expected, inflation and taxes is about 5.3% real expected income growth.

Now compare that to what they expect from the S&amp;P 500.

Time Frame S&amp;P Inflation-Adjusted Dividend Growth S&amp;P Inflation-Adjusted Earnings Growth
1871-2021 1.6% 2.1%
1945-2021 2.4% 3.5%
1981-2021 (Modern Falling Rate Era) 2.8% 3.8%
2008-2021 (Modern Low Rate Era) 3.5% 6.2%
FactSet Future Consensus 2.0% 5.2%

(Sources: S&amp;P, FactSet,

  • 1.7% tax and inflation-adjusted S&amp;P consensus income growth

What about a 60/40 retirement portfolio?

  • 0.5% consensus inflation, risk, and tax-adjusted income growth.

In other words, these 11 higher-yielding superior AT&amp;T alternatives offer

  • almost 4X the market's yield (and a much safer yield at that)
  • 1.33X AT&amp;T's yield (and a much, much safer yield at that)
  • about 3X the S&amp;P's long-term inflation-adjusted consensus income growth potential
  • 11X better long-term inflation-adjusted income growth than a 60/40 retirement portfolio

This is the power of high-yield blue-chip investing done right.

Bottom Line: Don't Gamble On AT&amp;T's Turnaround Story When You Can Buy These Higher-Yielding, Far Superior Alternatives Instead

Let me be very clear, AT&amp;T is not a dangerous company that's likely going to zero. Rating agencies estimate a 92.5% probability AT&amp;T will survive the next three decades.

But what I am saying is that after a careful examination of its fundamentals, I can think of just one group of investors who should own AT&amp;T right now. Index fund investors who own it as part of an ETF or mutual fund.

We all have limited funds, and for new money today there are almost no reasons to buy AT&amp;T over these 11 higher-yielding, much higher quality, much faster growing, and much safer Ultra SWANs.

The Evidence Is Clear: These Are 11 Much Better Alternatives To AT&amp;T

Metric Dividend Aristocrats 11 High-Yield AT&amp;T Alternatives AT&amp;T Winner Aristocrats Winner 11 High-Yield AT&amp;T Alternatives Winner AT&amp;T
Quality 87% 88% 57% 1
Safety 89% 90% 56% 1
Dependability 84% 88% 55% 1
Long-Term Risk Management Industry Percentile 67% Above-Average 73% Good 75% Good 1
Average Credit Rating A- Stable BBB+ Stable BBB Stable 1
Average 30-Year Bankruptcy Risk 3.01% 4.09% 7.50% 1
Average Dividend Growth Streak (Years) 44.3 15.3 0 1
Average Return On Capital 100% 478% 20% 1
Average ROC Industry Percentile 83% 87% 60% 1
13-Year Median ROC 89% 296% 19% 1
Forward PE 18.8 8.4 8.1 1
Discount To Fair Value 8.0% 26.0% 18.0% 1
DK Rating Good Buy Very Strong Buy Reasonable Buy 1
Yield 2.6% 7.0% 5.4% 1
LT Growth Consensus 8.6% 6.6% 3.4% 1
Total Return Potential 11.2% 13.6% 8.8% 1
Risk-Adjusted Expected Return 7.6% 9.1% 5.7% 1
Inflation &amp; Risk-Adjusted Expected Return 5.1% 6.7% 3.2% 1
Years To Double 14.02 10.80 22.30 1
Total 4 13 2

(Source: DK Zen Research Terminal)

Don't get me wrong, I'm not saying that you have to buy all of these companies.

This article is about providing 11 higher-yielding and far superior quality alternatives to AT&amp;T and that's exactly what MMP, MO, LGGNY, EPD, BTI, OKE, ALIZY, ENB, MFC, PBA, and BNS represent.

Some investors absolutely detest K1 tax forms, and if that describes you then ignore MMP and EPD.

Some investors just can't stand dividend tax withholdings and extra complexity at tax time, and if that's the case then ignore PBA, BNS, and ENB.

Some investors avoid tobacco for personal ethical reasons, and in that case MO and BTI are not for you.

The point is that any one of these high-yield blue-chips is a superior alternative to AT&amp;T.

  • higher yield
  • faster growth
  • a safer dividend
  • faster growing dividends
  • credit ratings as good or better (in some cases much better)
  • much higher quality and dependability
  • higher long-term return potential
  • superior long-term returns

When you have limited capital you need to be reasonable and prudent with where you invest it.

Can AT&amp;T make a good investment from here? That depends on whether the turnaround succeeds and the company delivers on its expected growth.

  • 8.8% long-term consensus return potential is in-line with its historical returns

Could AT&amp;T make a potentially fantastic short-term investment? Sure, because a return to fair value could mean 20% annual returns for the next 2.5 years.

  • 24% from these higher-yielding alternatives

But whether you are shooting for huge short-term upside or life-changing long-term wealth and income compounding by earning thousands of percent over decades, one thing is clear.

These 11 higher-yielding blue-chips are far superior alternatives to AT&amp;T today.

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