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Thursday, October 3, 2019

AI + Intent Data: The Key to Ending Inefficient Marketing Tactics

AI + Intent Data: The Key to Ending Inefficient Marketing Tactics

AI + Intent Data: The Key to Ending Inefficient Marketing Tactics

There’s no greater transformative force in the world’s businesses than technology’s ability to connect people, increase competitiveness, and ultimately help organizations grow. But as the Business Technology market nears $4 trillion in annual spend, two significant challenges have emerged for both the businesses who buy technology and the vendors who sell it.
First, technology buyers are operating in a landscape that’s constantly shifting as new technologies are introduced and new challenges emerge, such as ever-evolving cybersecurity threats, infrastructure upgrades, and data privacy regulations. With limited time and resources, it’s difficult for buyers to sort through an overwhelming amount of information to determine the best technology solutions for their organization’s needs and find trusted resources and experts to help make the right purchase decisions.
And technology buyers aren’t alone. Technology vendors spend more than $300 billion annually on Marketing and Sales to reach their customers and prospects. Yet much of this investment is wasted or spent inefficiently. Why? Because it’s difficult to identify when potential buyers are in-market and ready to purchase.
As a result, B2B marketers often use inefficient tactics with too little targeting, simply hoping to hit some of their targets at the right time with the right message. However, the traditional tactics of capturing demand are yielding fewer opportunities as buyers become more frustrated with irrelevant Sales calls and Marketing emails that aren’t timely or personalized.
Despite this challenging backdrop, there’s no doubt in Marketing’s ability to benefit the bottom line. In fact, 80% of businesses surveyed in Spiceworks’ 2019 State of IT Marketing study reported their B2B marketing budgets would grow or remain steady in 2019. Companies planning to expand their marketing budget anticipated an average increase of 24%, with most stating their organization’s increased prioritization on Marketing is the top driver of budget growth.
But as Marketing budgets continue to grow, businesses are still facing challenges when it comes to generating leads and acquiring new customers. Nearly half of B2B marketers said their biggest challenge in 2019 is driving conversions with Marketing content. After all, it’s hard to pinpoint the right buyer, especially considering up to 10 decision makers can be involved in a business technology purchase.
How the Marriage of AI and Intent Data Can Change the Game
A revolutionary approach is needed to help B2B marketers identify, engage, and nurture the right buyers at the right time. This requires the use of artificial intelligence married with intent data to reshape how buyers and sellers connect in ways that reduce friction and improve the experience for both parties. Intent data – digital signals buyers emit as they’re moving through the purchase journey – pinpoints where buyers are in their path-to-purchase and can be a powerful predictor of who’s in-market (and who’s not). Artificial Intelligence is key to accurately analyzing these signals at scale.
But it’s critical for brands to focus on the right signals that show true purchase intent when buyers are actively evaluating new products and services vs. the time buyers spend casually reading to stay up to date on the latest technology trends. In other words, buyers’ actions need to be deeply understood in a way that goes beyond basic content consumption.
So what does this look like in practice? As a B2B marketer or sales professional, you leverage AI-powered intent data to provide timely, relevant content to people who are in-market for your solutions, resulting in leads with a higher likelihood to convert. As a buyer, you’re presented with the information you need, right when you need it as your journey evolves, saving time and energy during the purchase process. It’s a win-win for both buyers and sellers.
Imagine the possibilities if you knew exactly which businesses to target and what message to use based on where they are in the purchase journey, what solutions they’re actively researching, and which competitors they’re evaluating.
At the end of the day, Artificial Intelligence – used to transform intent data into actionable insights on the most likely-to-buy prospects – can enable all marketers to step up their Account-Based Marketing efforts, connect directly with the people who need their help, and provide the best solution… at the best price.
And better yet, it can help put an end to the hundreds of irrelevant Sales calls and emails B2B buyers receive weekly and the millions of Marketing and Sales dollars spent inefficiently every year.
Copyright read more https://aithority.com/guest-authors/ai-intent-data-the-key-to-ending-inefficient-marketing-tactics/
at October 03, 2019 No comments:
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AI Winter Is Coming? Why Does Huawei Shift to Deep Learning Now?

AI Winter Is Coming? Why Does Huawei Shift to Deep Learning Now?

Since the release of the full-stack, full-scenario  strategy at the end of 2018, Huawei has made a strong breakthrough in  with its powerful computing advantages.

In particular, Huawei released the world’s most powerful  processor Ascend 910 on August 23 this year, which earned a ticket for Huawei to enter the field full of world’s top players. Giants in the industry quickly realize that Huawei has more than 5G and mobile phones. Huawei is investing greatly in basic research, which is helping Huawei seize the high ground in the future.
When we look back, however, the recent years of development has not ushered in an  era with an established ecosystem, which brings more worries about the  road ahead. Such worries were even stoked by the lack of computing power.
In the seem-to-come  winter, Huawei did not slow down its pace. Within one year,  processors and computing frameworks were implemented successively. One could not help but wonder how Huawei gain insights, why they are confident, and how do they develop their technical knockout.
We may find answers in Huawei Connect 2019 where the latest  and cloud products and solutions are released to “make computing power more inclusive and algorithms simpler”.
An  Winter Is Coming?
In 1956, John McCarthy, an assistant professor at Dartmouth College, organized a workshop where the definition of  was formally proposed for the first time. In the next 60 years,  has experienced two periods of slow development, the socalled “winters”, but its development has never stopped.
At a conference in 2018, Kai-Fu Lee, CEO of Innovation Works, said in his  that the biggest breakthrough in  was made nine years ago and no major breakthrough was made afterwards.
Similar voices can be heard more and more often recently. Over the years,  has been at the forefront of the  revolution. Many believe that  will lead us into a new era. However, the tide seems to keep receding. Questions and uncertainty are emerging about the road of  ahead.
New Battlefield for Deep Learning
To put it simply,  is implemented after reams of data are processed with the  to form a model and this model is applied to a specific service scenario. In this regard,  is an important driving force for .
Of course,  is just one of the implementation methods of , and is a subset of . Deep learning itself is not independent from other learning methods as supervised and  are used to train the deep neural networks. But it has been developing rapidly in recent years, and some dedicated learning methods (such as residual neural network) have been proposed one after another, more and more people now regard  as an independent method.[…]
read more – copyright by www.cio.com
at October 03, 2019 No comments:
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Wednesday, October 2, 2019

Big Data, Machine Learning and APSs: Marketers Share the Digital Jargon They Don’t Understand

Big Data, Machine Learning and APSs: Marketers Share the Digital Jargon They Don’t Understand

Big Data, Machine Learning and APSs: Marketers Share the Digital Jargon They Don’t Understand

Despite 60% of Marketers Demanding Control of the ‘Digital Experience’, Many Do Not Understand Common Digital Terms
Despite 60% of marketers wanting to ‘own’ the digital experience, many admit that they don’t fully understand digital terminology such as API, big data and machine learning. That’s according to a new study from leading content management system (CMS), Magnolia.
The research, which surveyed over 200 IT professionals and 200 marketers, explores the growing disconnect between each group as they struggle to decide who should ‘own’ the emerging digital experience sector.
Magnolia found that 24% of marketers don’t understand what ‘machine learning’ is, and 23% say they don’t know what the term ‘big data’ means. A third of marketers also confess to not know what API stands for.
IT teams are also suffering from a similar disconnect, with 77% saying they don’t understand the buzzwords marketers use. Similarly, 84% of marketers admit that they don’t fully understand the work of IT.
According to Magnolia, this disconnect is weakening brands’ overall digital experiences. As such, marketing technology is needed that can help bridge the divide.
As Darren Hitchcock, General Manager at Magnolia, explains, “In order to build a great digital experience you need both creative ideas and an in-depth knowledge of the latest technology. While it’s easy for marketers or IT teams to claim ‘ownership’ of the emerging digital experience space, the reality is that both groups are needed to develop an effective DX approach.
“In order to make the relationship between marketing and IT function, you need an interface that brings both groups together. To me, that should be the role of the modern CMS. Rather than simply allowing teams to edit their websites, today’s CMSs should bridge the divide between the best work of IT and the very best work of marketers. That will be the secret to a truly effective digital experience.”
Copyright read more https://aithority.com/technology/big-data/big-data-machine-learning-and-apss-marketers-share-the-digital-jargon-they-dont-understand/
at October 02, 2019 No comments:
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machineVantage’s Breakthrough AI-Powered Market Research Technology Wins Ogilvy Award

machineVantage's Breakthrough AI-Powered Market Research Technology Wins Ogilvy Award

Artificial Intelligence Company Honored by the Advertising Research Foundation
machineVantage, the company specializing in artificial intelligence and machine learning applications for businesses, was honored with the Silver David Ogilvy Award from the Advertising Research Foundation. The prize was given in the Health & Personal Care category of the ARF’s annual awards competition.
machineVantage applies proprietary artificial intelligence and machine learning algorithms combined with advanced neuroscience knowledge to deliver innovations in marketing and product development.
“This award underscores the value of growing global applications of artificial intelligence-driven systems for companies looking to gain unique competitive advantages in the marketplace, through innovations in marketing and new product development,” said Dr. A. K. Pradeep, founder and CEO of machineVantage. “To receive this industry-wide recognition signals how advanced technologies are transforming and improving the effectiveness of every aspect of business today, in this instance the field of market research.”
Dr. Pradeep himself is a prior winner of the ARF’s top individual honor, the Grand Prize – Great Minds Award, which he received for his pioneering work combining neuroscientific knowledge and methodologies with marketing. He is the co-author of “AI For Marketing And Product Innovation”, and also wrote the best-selling “The Buying Brain”.
machineVantage (www.machinevantage.com) applies proprietary artificial intelligence algorithms and machine learning techniques to extract product innovations, brand semiotics, creative inspirations, and digital and retail point of sale messaging. The company works with major multinational clients in North America and in individual markets in Europe, the Asia Pacific region, Latin America, and the Middle East.
Copyright read more https://aithority.com/machine-learning/machinevantages-breakthrough-ai-powered-market-research-technology-wins-ogilvy-award/
at October 02, 2019 No comments:
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TigerGraph Launches PartnerGraph Program To Meet Growing Demand For Graph Analytics In AI And Machine Learning

TigerGraph Launches PartnerGraph Program To Meet Growing Demand For Graph Analytics In AI And Machine Learning

TigerGraph Launches PartnerGraph Program To Meet Growing Demand For Graph Analytics In AI And Machine Learning


New Program Enables Partners to Leverage Leading Scalable Graph Database and Analytics Platform
TigerGraph, the only scalable graph database for the enterprise, announced the launch of its PartnerGraph Program. The program enables businesses to redefine the graph database market with TigerGraph’s platform that is opening new markets for graph applications in AI and machine learning. It provides partners with the tools, infrastructure and support required to enhance their competitive position. New PartnerGraph members will join a roster of companies such as Accenture, Expero, Intel, NEORIS, UL Systems and 6point6 that have joined forces with TigerGraph to capitalize on accelerating demand for a scalable graph analytics platform.
“With analysts in agreement that graph databases will become a multi-billion-dollar market in the coming years, it’s important that the graph database ecosystem become much bigger and stronger. Our announcement today is a major step forward in meeting that imperative,” said Todd Blaschka, chief operating officer at TigerGraph.
“PartnerGraph members will benefit from a focused program that will advance their goals and allow easy access to our industry-leading real-time graph analytics platform,” Blaschka added. “Partners are vital to creating innovative solutions that help our customers make sense of their No. 1 hidden asset: the connected data powering today’s AI and machine learning applications.”
PartnerGraph Benefits
Offering an array of services, technology, capabilities, resources and industry expert collaboration, TigerGraph’s PartnerGraph Program is the leading ecosystem solely dedicated to delivering graph’s unique value and power to enterprises.
  • Customers benefit: With a broader set of implementation and integration opportunities to deliver on graph use cases, customers see faster time to solution, faster insights and better business outcomes.
  • Partners benefit: Partners now have a platform for building new solutions that enable greater enduring customer success than ever before and can rely on TigerGraph for marketing and sales support, technical services, training and certification opportunities.  Specific programs for training, certification, technical support, and marketing enablement are all part of the PartnerGraph program.
  • Industry benefit: The graph database market finally has a platform that can scale — with an ecosystem that drives greater value than ever before with a new set of best practices.
Partner Quotes
“Accenture is developing Knowledge Graphs to drive actionable data intelligence for our enterprise clients across industries. TigerGraph offers real-time analytics capability, scalability and high-performance to enhance the trust in their data and meet business KPIs.”
– Harsh Sharma, Innovation Lead, Data Business Group, Accenture
“Expero develops custom software exclusively for domain-expert users such as scientists, traders, engineers, healthcare professionals and government officials. We succeed only by quickly learning our clients’ domains and becoming true partners in their problem-solving. For many applications, the power of connected data and graph analytics is a game changer. The TigerGraph platform enables us to build these new ground-breaking solutions and solve key issues that we simply could not otherwise solve for our joint customers.”
Read More: Unified Office Announces Food Safety Service Platform for Restaurants Utilizing IoT Infrastructure Management and Business Analytics
– Sebastian Good, CEO, Expero
“Intel’s newest hardware advancements, including the 2nd Gen Intel Xeon Scalable processors and Intel Optane DC persistent memory provide industry-leading performance to power software platforms such as TigerGraph. Our latest benchmarks show  up to 24.8x performance gains on Data Warehousing queries on the new 2nd Gen Intel® Xeon® Platinum 8280 processor with Windows Server 2016 vs. 4-year old legacy server with old hardware and software platforms and we expect to see even greater advances as we work together to drive the future of connected data together.”
– Arijit Bandyopadhyay, CTO of Data Center Group, Intel
“At NEORIS we are delighted to join this new partnership program in order to continue to expand the capabilities of our Augmented Intelligence Platform, which allows our partners to turn data into actionable insights in the most efficient and flexible way possible. We are also very excited to continue to work and learn from the TigerGraph team and find innovative ways to leverage GSQL and its unique features, such as accumulators, to answer our client’s most complex and mission-critical questions.”
– Demian Bellumio, Global Vice President of Augmented Intelligence, NEORIS
“In the Japanese market, we clearly see a need for graph analytics to help customers understand how connected data can drive deeper insights and better business outcomes. TigerGraph is a powerful platform for great solutions across all geographies.”
– Shigeru Urushibara, President and CEO, UL Systems
“Our data science and engineering teams at 6point6 are hearing from more and more of our clients that they need a new breed of scalable graph processing in order to extract more insight and features from ever increasing sets of both structured and unstructured data. 6point6 looks forward to driving enterprise adoption of this leading scalable graph platform as the first UK certified partner of TigerGraph.”
– Dr. Dan Smith, PhD., Lead Graph Data Architect, 6point6
TigerGraph offers the world’s fastest graph analytics platform that tackles the toughest data challenges in real time, no matter how large or complex the data set. TigerGraph stores all data sources in a single, unified multiple-graph store that can scale out and up easily and efficiently to explore, discover and predict relationships. Unlike traditional graph databases, TigerGraph can scale for real-time multi-hop queries to trillions of relationships.
Copyright read more https://aithority.com/machine-learning/tigergraph-launches-partnergraph-program-to-meet-growing-demand-for-graph-analytics-in-ai-and-machine-learning/

at October 02, 2019 No comments:
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New Survey Reveals That HR Leaders Are Prioritizing AI to Improve the Employee Experience

New Survey Reveals That HR Leaders Are Prioritizing AI to Improve the Employee Experience

Espressive, in Collaboration with AWS, Sponsors Pulse Report on Strategies for HR Service Management
Espressive, the pioneer in artificial intelligence (AI) for enterprise service management and a 2019 Gartner Cool Vendor, released the findings of a new Pulse Report focused on the top HR service management strategies and initiatives for 2019. The report revealed that increasing the efficiency of HR service management and improving the employee self-help experience will be critical for achieving the top three HR initiatives of 2019: increasing employee retention; improving employee satisfaction; and improving the new-hire onboarding experience. The report, sponsored by Espressive in collaboration with Amazon Web Services (AWS), surveyed senior HR decision makers across a wide variety of industries. With 59 percent of respondents already considering or actively adding virtual employee assistants (i.e., chatbots), it is evident that HR leaders are prioritizing AI to improve the employee experience.
“This past January, Espressive sponsored a similar report on IT service management and found that 62 percent of IT leaders were considering or actively adding virtual support agents,” said Pat Calhoun, CEO and founder of Espressive. “The new report, done just six months later, reveals that HR leaders have almost caught up with IT in their desire to leverage AI to improve the employee experience. The new report also revealed that 26 percent would need IT approval even if HR had funding, and another 24 percent said that funding would have to come from IT. With that in mind, organizations would benefit by implementing one solution that can be shared across the enterprise.”
Employees are Challenged with Getting Help in the Workplace
Although many enterprises provide an intranet or self-service HR portal for answering questions, survey respondents indicated that only 45 percent of employees commonly search there. More frequently used methods for getting help include calling the help desk (72 percent) and emailing the help desk (64 percent). This is problematic when 34 percent say they have no formal tracking or assignment process and 27 percent use a shared inbox with multiple people potentially working on the same questions.
When asked for employees’ biggest complaints about getting answers from HR, the top complaint at 57 percent was that it is too hard to find the right answer when searching the HR portal. Another 53 percent of employees report that they can’t keep track of where to go for an answer. 48 percent say that when they reach HR by way of phone or email it takes too long to get a response.
Giving Employees a Personalized Onboarding Experience is a Top Challenge
The report also revealed that new-hire onboarding is top of mind for HR leaders. The top onboarding challenge cited, providing a personalized onboarding experience, ranked 18 percentage points higher than the next challenge. The next three reported onboarding challenges were all related to process: getting hiring managers to kick off the process on time; creating and enforcing a business process framework across departments; and getting new hires to complete onboarding tasks.
“All of the challenges revealed in the new Pulse Report can be solved with automation and AI,” said Calhoun. “When employees have one place to go across the enterprise to not only receive answers from HR, but also from IT, Payroll, Workplace Resources, and more, their productivity goes up. And when the self-help experience is similar to what they have come to expect in their consumer lives, employee satisfaction and retention rise as well.”
Copyright read more https://aithority.com/hrtechnology/new-survey-reveals-that-hr-leaders-are-prioritizing-ai-to-improve-the-employee-experience/
at October 02, 2019 No comments:
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DataRobot Enhances Enterprise AI Platform, Further Automating the Path from Data to Value

DataRobot Enhances Enterprise AI Platform, Further Automating the Path from Data to Value

DataRobot , the leader in enterprise , today unveiled new features to its Enterprise  platform designed to automate the entire end-to-end data science process, introducing an  Catalog and next-generation automated feature engineering

In the race to innovate with , organizations must embrace a solution that can automate the time-intensive process for everything associated with  success, including identifying relevant data sources, preparing data for , building and deploying  models, and monitoring and managing models over time. According to Gartner, Inc., “By 2025, 50% of data scientist activities will be automated by , easing the acute talent shortage.” (Gartner, Inc., How Augmented Machine Learning is Democratizing Data Science, August 29, 2019).
With its newly enhanced platform, DataRobot further empowers citizen data scientists to successfully create advanced  applications while making expert data scientists even more productive. The DataRobot Enterprise  Platform provides automation across the entire  lifecycle — organizing, building, deploying, running, and managing  assets — to accelerate and streamline a user’s journey from data to value.
 CatalogIn its latest release, DataRobot has added an  Catalog to its software. This is based on DataRobot’s February acquisition of Cursor, a data collaboration platform founded to help organizations find, understand, and use data more efficiently. The  Catalog creates a collaborative environment for enterprise  by providing users with the ability to search for any dataset, share new sources, and comment and tag assets to promote understanding and reuse.  Catalog also assists with data science productivity by providing the ability to prepare and manage feature lists to share and use in new projects.
By integrating search and collaboration capabilities into its existing platform, DataRobot users now have secure access to trusted data assets from a governed  environment. DataRobot enforces strict sharing permissions and provides lineage to promote safe and trustworthy  applications. Additional data management benefits include the ability to connect to any location to access data — whether it’s in a data lake, database, in the cloud, or on-premise.
Automated Feature EngineeringDataRobot pioneered automated feature engineering and makes extensive use of it in its Automated Machine Learning and Automated Time Series products. The release of DataRobot’s new  Catalog has enabled the next-generation of automated feature engineering by allowing users to automatically discover new features from multiple related datasets.
Manual feature engineering is often considered the most laborious and time-consuming step in the data science workflow. By automating this process, DataRobot is greatly accelerating how users prepare datasets to improve  model performance. These new capabilities, which are the culmination of research and development DataRobot has conducted over the last three years, enable users to quickly find new data from multiple sources and apply simple business rules to automate the creation of large numbers of useful features and the subsequent transformation of those features for each specific algorithm.[…]
read more – copyright by www.businesswire.com
at October 02, 2019 No comments:
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Finance jobs requiring A.I. skills increased 60% last year—here’s what they look like

Finance jobs requiring A.I. skills increased 60% last year—here’s what they look like

The finance industry is banking on  — and they’re creating new jobs to bridge the gap.

Traditional financial institutions and fintech start-ups alike are looking for more candidates who specialize in ,  and data science. According to reporting by Bloomberg reporting and data from LinkedIn , job listings requiring these skills in the financial industry increased nearly 60% in the past year.
According to Glassdoor data, “some of the most common job openings in  and finance are for  engineers and data engineers, among other highly specialized software engineering roles,” Glassdoor senior economist Daniel Zhao tells CNBC Make It . “We’re also seeing job openings for workers who can help navigate the  landscape, including consultants and researchers. As companies establish the foundations for their  functions, we’re seeing employers hire more senior candidates to lead these new teams.”
Not all new job functions are rooted in computer science or engineering, however. For example, chatbot copywriters (those who write conversational answers to technical questions customers ask on websites’ “chat” functions), product strategists and technical sales representatives are also in demand, Zhao says. Those who have a business or communications background may be better suited to these roles.
And workers who already work in finance but are willing to learn more about  have a leg up, Zhao says. “Their domain expertise in business and finance is a great way to differentiate themselves in a hot technical field.”

Learning  without a computer science degree

Professionals with a background in engineering will have a growing field of opportunities within the finance space. For those without a STEM education, however, the ability to adapt and learn such skills will be crucial across a wide set of job functions. “With numerous online courses and boot camps available, it’s never been easier to learn  and  skills that can enhance your career,” Zhao says.
LinkedIn provides online courses to learn skills like ,  and analytical reasoning. Hundreds of universities around the world offer online courses for free — or partially free — with many falling in the categories of computer science, mathematics, programming and data science. Furthermore, training academies and boot camps have cropped up in order to bridge the gap of working professionals who want to pick up technical skills that can translate to a new role or enhance their current work.
The question of whether workers will have to seek out these opportunities, or if they’ll be encouraged and provided by employers, hangs in the balance.
“It’s important for companies to continue to invest in their people so that they are up-skilling and re-skilling their people to keep up with the roles that are in demand,” said Feon Ang, vice president for talent and learning solutions in Asia Pacific at LinkedIn, to CNBC’s “Capital Connection.” “At the same time, people need to continue to invest in themselves and have a growth mindset.”[…]
read more – copyright by www.cnbc.com
at October 02, 2019 No comments:
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The Next Wave of Digital Paranoia: Full-Body Deepfakes Are Now Here

The Next Wave of Digital Paranoia: Full-Body Deepfakes Are Now Here

In a way, deepfakes are democratizing what Hollywood has done for years with CGI technology by putting the tech in the hands of anyone who downloads the app.

So, we’ve already warned you of the dangers of deepfakes . Security experts have provided a cautionary tale that deepfakes will play a sinister role in the 2020 election. And we’ve already seen the mayhem that erupted when a Nancy Pelosi video was slowed down to make it appear like she was drunk . Though not a deepfake, the footage showcased how fast an altered video can go viral and make people question the validity of what they are seeing.
Now, to bring us up to speed, a deepfake is like a digital puppet that uses  and 3D models of a target’s face, which allows you to manipulate a person in a video, as well as edit and change what he or she say. As the technology advances, these changes appear more-and-more as a seamless audio-visual flow without jump cuts.
What problems could occur with that?
Well, let’s say during election season, someone creates a deepfake of a candidate spewing racial epithets. The video could easily go viral before it could be proven to be a fake, and the damage would already be done.
In the world of deepfakes, so much attention is focused on the havoc that could potentially be wreaked by altering and/or manipulating the faces of political leaders, celebrities and ordinary people.
But that’s just the beginning. Ready for the next level of deepfakery?
There’s actually much more damage these  algorithms can do to destroy people’s lives. Imagine this if you will: synthetic media technology that’s capable of creating… full-body deepfakes.
Holy great balls of deepfake fire! Yes, it was only just a matter of time.
Before I go into the nuts-and-bolts of how this work, let’s take a breath and think of all the possible hell-raising this could cause. So, instead of breaking news reports speculating about President Donald Trump’s fabled “Pee Tape,” deepfakers could potentially create a full-body mimicry of said act and leak it, so to speak, out into the world. (Yuck.)
The seeds of full-body deepfakes were already in place back in those archaic days of August 2018. University of California Berkeley researchers presented a paper called: Everybody Dance Now. The premise of their research is how  algorithms can transfer a professional dancers’ moves onto the bodies of amateurs.  […]
Read more – observer.com
at October 02, 2019 No comments:
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Akin Fakokunde
Engineering leader of high-performance teams empowered to deliver high-quality software on time. Broad experience designing, architecture, and scaling applications for Fintech and enterprises alike. Tech stacks: Full-stack C#. Net, ASP.NET Core, Machine learning,SQL Server, ReactJs, Blazor, Backlog Prioritization, Roadmapping, Agile, Scrum, Git, Azure DevOps, Azure deployments, Product development and marketing
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