Category Archives: Machine Learning

AI and machine-learning advances have made it possible to produce fake videos and photos that seem real, commonly known as deepfakes. Deepfake content is exploding in popularity.[i] In Star Wars: The Rise of Skywalker, for instance, a visage of Carrie Fischer graced the screen, generated through artificial intelligence models trained on historic footage. Using thousands of hours of interviews with Salvador Dali, the Dali Museum of Florida created an interactive exhibit featuring the artist.[ii] For Game of Thrones fans miffed over plot holes in the season finale, Jon Snow can be seen profusely apologizing in a deepfake video that looks all too real.[iii]

Deepfake technologyhow does it work? From a technical perspective, deepfakes (also referred to as synthetic media) are made from artificial intelligence and machine-learning models trained on data sets of real photos or videos. These trained algorithms then produce altered media that looks and sounds just like the real deal. Behind the scenes, generative adversarial networks (GANs) power deepfake creation.[iv] With GANs, two AI algorithms are pitted against one another: one creates the forgery while the other tries to detect it, teaching itself along the way. The more data is fed into GANs, the more believable the deepfake will be. Researchers at academic institutions such as MIT, Carnegie Mellon, and Stanford University, as well as large Fortune 500 corporations, are experimenting with deepfake technology.[v] Yet deepfakes are not solely the province of technical universities or AI product development groups. Anybody with an internet connection can download publicly available deepfake software and crank out content.[vi]

Deepfake risks and abuse. Deepfakes are not always fun and games. Deepfake videos can phish employees to reveal credentials or confidential information, e-commerce platforms may face deepfake circumvention of authentication technologies for purposes of fraud, and intellectual property owners may find their properties featured in videos without authorization. For consumer-facing online platforms, certain actors may attempt to leverage deepfakes to spread misinformation. Another well-documented and unfortunate abuse of deepfake technology is for purposes of revenge pornography.[vii]

In response, online platforms and consumer-facing companies have begun enforcing limitations on the use of deepfake media. Twitter, for example, announced a new policy within the last year to prohibit users from sharing synthetic or manipulated media that are likely to cause harm. Per its policy, Twitter reserves the right to apply a label or warning to Tweets containing such media.[viii] Reddit also updated its policies to ban content that impersonates individuals or entities in a misleading or deceptive manner (while still permitting satire and parody).[ix] Others have followed. Yet social media and online platforms are not the only industries concerned with deepfakes. Companies across industry sectors, including financial and healthcare, face growing rates of identity theft and imposter scams in government services, online shopping, and credit bureaus as deepfake media proliferates.[x]

Deepfake legal claims and litigation risks. We are seeing legal claims and litigation relating to deepfakes across multiple vectors:

1. Claims brought by those who object to their appearance in deepfakes. Victims of deepfake media sometimes pursue tort law claims for false light, invasion of privacy, defamation, and intentional infliction of emotional distress. At a high level, these overlapping tort claims typically require the person harmed by the deepfake to prove that the deepfake creator published something that gives a false or misleading impression of the subject person in a manner that (a) damages the subjects reputation, (b) would be highly offensive to a reasonable person, or (c) causes mental anguish or suffering. As more companies begin to implement countermeasures, the lack of sufficient safeguards against misleading deepfakes may give rise to a negligence claim. Companies could face negligence claims for failure to detect deepfakes, either alongside the deepfake creator or alone if the creator is unknown or unreachable.

2. Product liability issues related to deepfakes on platforms. Section 230 of the Communications Decency Act shields online companies from claims arising from user content published on the companys platform or website. The law typically bars defamation and similar tort claims. But e-commerce companies can also use Section 230 to dismiss product liability and breach of warranty claims where the underlying allegations focus on a third-party sellers representation (such as a product description or express warranty). Businesses sued for product liability or other tort claims should look to assert Section 230 immunity as a defense where the alleged harm stems from a deepfake video posted by a user. Note, however, the immunity may be lost where the host platform performs editorial functions with respect to the published content at issue. As a result, it is important for businesses to implement clear policies addressing harmful deepfake videos that broadly apply to all users and avoid wading into influencing a specific users content.

3. Claims from consumers who suffer account compromise due to deepfakes. Multiple claims may arise where cyber criminals leverage deepfakes to compromise consumer credentials for various financial, online service, or other accounts. The California Consumer Privacy Act (CCPA), for instance, provides consumers with a private right of action to bring claims against businesses that violate the duty to implement and maintain reasonable security procedures and practices.[xi] Plaintiffs may also bring claims for negligence, invasion of privacy claims under common law or certain state constitutions, and state unfair competition or false advertising statutes (e.g., Californias Unfair Competition Law and Consumers Legal Remedies Act).

4. Claims available to platforms enforcing Terms of Use prohibitions of certain kinds of deepfakes. Online content platforms may be able to enforce prohibitions on abusive or malicious deepfakes through claims involving breach of contract and potential violations of the Computer Fraud and Abuse Act (CFAA), among others. These claims may turn on nuanced issues around what conduct constitutes exceeding authorized access under the CFAA, or Terms of Use assent and enforceability of particular provisions.

5. Claims related to state statutes limiting deepfakes. As malicious deepfakes proliferate, several states such as California, Texas, and Virginia have enacted statutes prohibiting their use to interfere with elections or criminalizing pornographic deepfake revenge video distribution.[xii] More such statutes are pending.

Practical tips for companies managing deepfake risks. While every company and situation is unique, companies dealing with deepfakes on their platforms, or as a potential threat vector for information security attacks, can consider several practical avenues to manage risks:

While the future of deepfakes is uncertain, it is apparent that the underlying AI and machine-learning technology is very real and here to staypresenting both risks and opportunity for organizations across industries.

Read more here:
The Collision of AI's Machine Learning and Manipulation: Deepfake Litigation Risks to Companies from a Product Liability, Privacy, and Cyber...

Department of Computer Science

Grade 7:-33,797 - 40,322 per annumFixed Term-Full TimeContract Duration:7 monthsContracted Hours per Week:35Closing Date:13-Mar-2021, 7:59:00 AM

Durham University

Durham University is one of the world's top universities with strengths across the Arts and Humanities, Sciences and Social Sciences. We are home to some of the most talented scholars and researchers from around the world who are tackling global issues and making a difference to people's lives.

The University sits in a beautiful historic city where it shares ownership of a UNESCO World Heritage Site with Durham Cathedral, the greatest Romanesque building in Western Europe. A collegiate University, Durham recruits outstanding students from across the world and offers an unmatched wider student experience.

Less than 3 hours north of London, and an hour and a half south of Edinburgh, County Durham is a region steeped in history and natural beauty. The Durham Dales, including the North Pennines Area of Outstanding Natural Beauty, are home to breathtaking scenery and attractions. Durham offers an excellent choice of city, suburban and rural residential locations. The University provides a range of benefits including pension and childcare benefits and the Universitys Relocation Manager can assist with potential schooling requirements.

Durham University seeks to promote and maintain an inclusive and supportive environment for work and study that assists all members of our University community to reach their full potential. Diversity brings strength and we welcome applications from across the international, national and regional communities that we work with and serve.

The Department

The Department of Computer Science is rapidly expanding. A new building for the department (joint with Mathematical Sciences) has recently opened to house the expanded Department. The current Department has research strengths in (1) algorithms and complexity, (2) computer vision, imaging, and visualisation and (3) high-performance computing, cloud computing, and simulation. We work closely with industry and government departments. Research-led teaching is a key strength of the Department, which came 5th in the Complete University Guide. The department offers BSc and MEng undergraduate degrees and is currently redeveloping its interdisciplinary taught postgraduate degrees. The size of its student cohort has more than trebled in the past five years. The Department has an exceptionally strong External Advisory Board that provides strategic support for developing research and education, consisting of high-profile industrialists and academics.Computer Science is one of the very best UK Computer Science Departments with an outstanding reputation for excellence in teaching, research and employability of our students.

The Role

Postdoctoral Research Associate to work on the AHRC-funded project Visitor Interaction and Machine Curation in the Virtual Liverpool Biennial.

The project looks at virtual art exhibitions that are curated by machines, or even co-curated by humans and machines; and how audiences interact with these exhibitions in the era of online art shows. The project is in close collaboration with the 2020 (now 2021) Liverpool Biennial (http://biennial.com/). The role of the post holder is, along with the PI Leonardo Impett, to implement different strategies of user-machine interaction for virtual art exhibits; and to investigate the interaction behaviour of different types of users with such systems.

Responsibilities:

This post is fixed term until31 August 2021 as the research project is time limited and will end on 31 August 2021.

The post-holder is employed to work on research/a research project which will be led by another colleague. Whilst this means that the post-holder will not be carrying out independent research in his/her own right, the expectation is that they will contribute to the advancement of the project, through the development of their own research ideas/adaptation and development of research protocols.

Successful applicants will, ideally, be in post byFebruary 2021.

How to Apply

For informal enquiries please contactDr Leonardo Impett (leonardo.l.impett@durham.ac.uk).All enquiries will be treated in the strictest confidence.

We prefer to receive applications online via the Durham University Vacancies Site.https://www.dur.ac.uk/jobs/. As part of the application process, you should provide details of 3 (preferably academic/research) referees and the details of your current line manager so that we may seek an employment reference.

Applications are particularly welcome from women and black and minority ethnic candidates, who are under-represented in academic posts in the University.We are committed to equality: if for any reason you have taken a career break or periods of leave that may have impacted on your career path, such as maternity, adoption or parental leave, you may wish to disclose this in your application.The selection committee will recognise that this may have reduced the quantity of your research accordingly.

What to Submit

All applicants are asked to submit:

The Requirements

Essential:

Qualifications

Experience

Skills

Desirable:

Experience

Skills

DBS Requirement:Not Applicable.

Read more:
Postdoctoral Research Associate in Digital Humanities and Machine Learning job with DURHAM UNIVERSITY | 246392 - Times Higher Education (THE)

To improve speed and intelligence of threat detection and response, Guruculs cloud-native XDR platform is adding machine learning, integration risk scoring and more.

by Anne Lessman

Tags: cloud-native, Gurucul, integration, machine learning, real-time, threat detection,

The latest upgrade to the Gurucul XDR platform adds extended detection and response alongside improved risk scoring to strengthen security operations effectiveness and productivity.

Improvements to Guruculs cloud-native solution also sport features to enable intelligent investigations and risk-based response automation. New features include extended data linking, additions to its out-of-the-box integrations, contextual machine learning (ML) analytics and risk-prioritized alerting.

The driving force behind these updates is to provide users a single pane of risk, according to Gurucul CEO Saryu Nayyar.

Most XDR products are based on legacy platforms limited to siloed telemetry and threat detection, which makes it difficult to provide unified security operations capabilities, Nayyar said.

Gurucul Cloud-native XDR is vendor-agnostic and natively built on a Big Data architecture designed to process, contextually link, analyze, detect, and risk score using data at massive scale. It also uses contextual Machine Learning models alongside a risk scoring engine to provide real-time threat detection, prioritize risk-based alerts and support automated response, Nayyar.added.

Gurucul XDR provides the following capabilities that are proven to improve incident response times:

AI/ML Suggestive Investigation and Automated Intelligent Responses: Traditional threat hunting tools and SIEMs focus on a limited number of use cases since they rely on data and alerts from a narrow set of resources. With cloud adoption increasing at a record pace, threat hunting must span hybrid on-premises and cloud environments and ingest data from vulnerability management, IoT, medical, firewall, network devices and more.

Guruculs approach provides agentless, out-of-the-box integrations that support a comprehensive set of threat hunting applications. These include: Insider threat detection, Data exfiltration, Phishing, Endpoint forensics, Malicious processes and Network threat analytics.

Incident Timeline, Visualizations, and Reporting: Automated Incident Timelines create a smart link of the entire attack lifecycle for pre-and post-incident analysis. Timelines can span days and even years of data in easy-to-understand visualizations.

Guruculs visualization and dashboarding enables analysts to view threats from different perspectives using several widgets, including TreeMap, Bubble Chart, etc., that provide full drill-down capabilities into events without leaving the interface. The unique scorecard widget generates a spider chart representation of cyber threat hunting outcomes such as impact, sustaining mitigation measures, process improvements scores, etc.

Risk Prioritized Automated Response: Integration with Gurucul SOAR enables analysts to invoke more than 50 actions and 100 playbooks upon detection of a threat to minimize damages.

Entity Based Threat Hunting: Perform contextual threat hunting or forensics on entities. Automate and contain any malicious or potential threat from a single interface.

Red Team Data Tagging: Teams can leverage red team exercise data and include supervised learning techniques as part of a continuous AI-based threat hunting process.

According to Gartner, XDR products aim to solve the primary challenges with SIEM products, such as effective detection of and response to targeted attacks, including native support for behavior analysis, threat intelligence, behavior profiling and analytics.

Further, the primary value propositions of an XDR product are to improve security operations productivity and enhance detection and response capabilities by including more security components into a unified whole that offers multiple streams of telemetry, Gartner added.

The result, the firm said, is to present options for multiple forms of detection and . . multiple methods of response.

Gurucul XDR provides the following capabilities that are proven to improve incident response times by nearly 70%:

Surgical Response

Intelligent Centralized Investigation

Rapid Incident Correlation and Causation

Gurucul XDR is available immediately from Gurucul and its business partners worldwide.

back

Visit link:
Gurucul XDR Uses Machine Learning & Integration for Real-Time Threat Detection, Incident Response - Integration Developers

05 February 2021

Researchers in EPFLs Digital and Cognitive Musicology Lab in the College of Humanities used an unsupervised machine learning model to reveal how modes such as major and minor have changed throughout history.

Many people may not be able to define what a minor mode is in music, but most would almost certainly recognise a piece played in a minor key. Thats because we intuitively differentiate the set of notes belonging to the minor scale which tend to sound dark, tense, or sad from those in the major scale, which more often connote happiness, strength, or lightness.

But throughout history, there have been periods when multiple other modes were used in addition to major and minor or when no clear separation between modes could be found at all.

Understanding and visualising these differences over time is what Digital and Cognitive Musicology Lab (DCML) researchers Daniel Harasim, Fabian Moss, Matthias Ramirez, and Martin Rohrmeier set out to do in a recent study, which has been published in the open-access journal Humanities and Social Sciences Communications. For their research, they developed a machine learning model to analyze more than 13,000 pieces of music from the 15th to the 19th centuries, spanning the Renaissance, Baroque, Classical, early Romantic, and late-Romantic musical periods.

We already knew that in the Renaissance [1400-1600], for example, there were more than two modes. But for periods following the Classical era [1750-1820], the distinction between the modes blurs together. We wanted to see if we could nail down these differences more concretely, Harasim explains.

Machine listening (and learning)

The researchers used mathematical modelling to infer both the number and characteristics of modes in these five historical periods in Western classical music. Their work yielded novel data visualizations showing how musicians during the Renaissance period, like Giovanni Pierluigi da Palestrina, tended to use four modes, while the music of Baroque composers, like Johann Sebastian Bach, revolved around the major and minor modes. Interestingly, the researchers could identify no clear separation into modes of the complex music written by Late Romantic composers, like Franz Liszt.

Harasim explains that the DCMLs approach is unique because it is the first time that unlabelled data have been used to analyse modes. This means that the pieces of music in their dataset had not been previously categorized into modes by a human.

We wanted to know what it would look like if we gave the computer the chance to analyse the data without introducing human bias. So, we applied unsupervised machine learning methods, in which the computer 'listens' to the music and figures out these modes on its own, without metadata labels.

Although much more complex to execute, this unsupervised approach yielded especially interesting results which are, according to Harasim, more cognitively plausible with respect to how humans hear and interpret music.

We know that musical structure can be very complex and that musicians need years of training. But at the same time, humans learn about these structures unconsciously, just as a child learns a native language. Thats why we developed a simple model that reverse engineers this learning process, using a class of so-called Bayesian models that are used by cognitive scientists, so that we can also draw on their research.

From class project to publicationand beyond

Harasim notes with satisfaction that this study has its roots in a class project that he and his co-authors Moss and Ramirez did together as students in EPFL professor Robert Wests course, Applied Data Analysis. He hopes to take the project even further by applying their approach to other musical questions and genres.

For pieces within which modes change, it would be interesting to identify exactly at what point such changes occur. I would also like to apply the same methodology to jazz, which was the focus of my PhD dissertation because the tonality in jazz is much richer than just two modes.

See original here:
- Retracing the evolution of classical music with machine learning - Design Products & Applications

Travel Guard has specific cruise insurance policies, which makes it simpler than trying to find an add-on. If youre getting a quote online, theyll ask you to specify if youre taking a plane, a cruise, or both. They cover any emergency travel assistance, trip interruption, delay, or cancellation.

Cruise travel insurance secures non-refundable investments related to your trip. It reimburses you if you have to cancel your international cruise unexpectedly prior to your departure. It also provides medical coverage for unexpected injuries and illnesses. Cruise travel insurance policies provide medical coverage while you are on a holiday. A cancellation after this can mean a huge financial loss, but a cruise travel insurance policyholder shall be covered for cancellation or postponement of trips.

The aim of the report is to equip relevant players in deciphering essential cues about the various real-time market based developments, also drawing significant references from historical data, to eventually present a highly effective market forecast and prediction, favoring sustainable stance and impeccable revenue flow despite challenges such as sudden pandemic, interrupted production and disrupted sales channel in the Cruise Travel Insurance market.

Request a sample copy of report @ https://www.reportconsultant.com/request_sample.php?id=77601

Key players profiled in the report includes:

Allianz, AIG, Munich RE, Generali, Tokio Marine, Sompo Japan, CSA Travel Protection, AXA, Pingan Baoxian, Mapfre Asistencia, USI Affinity, Seven Corners, Hanse Merkur, MH Ross, STARR

Market Segmentation by type:

Market Segmentation by application:

This report is well documented to present crucial analytical review affecting the Cruise Travel Insurance market amidst COVID-19 outrage. The report is so designed to lend versatile understanding about various market influencers encompassing a thorough barrier analysis as well as an opportunity mapping that together decide the upcoming growth trajectory of the market. In the light of the lingering COVID-19 pandemic, this mindfully drafted research offering is in complete sync with the current ongoing market developments as well as challenges that together render tangible influence upon the holistic growth trajectory of the Cruise Travel Insurance market.

Besides presenting a discerning overview of the historical and current market specific developments, inclined to aid a future-ready business decision, this well-compiled research report on the Cruise Travel Insurance market also presents vital details on various industry best practices comprising SWOT and PESTEL analysis to adequately locate and maneuver profit scope. Therefore, to enable and influence a flawless market-specific business decision, aligning with the best industry practices, this specific research report on the market also lends a systematic rundown on vital growth triggering elements comprising market opportunities, persistent market obstacles and challenges, also featuring a comprehensive outlook of various drivers and threats that eventually influence the growth trajectory in the Cruise Travel Insurance market.

Get reports for upto 40% discount @ https://www.reportconsultant.com/ask_for_discount.php?id=77601

Global Cruise Travel Insurance Geographical Segmentation Includes:

North America (U.S., Canada, Mexico)

Europe (U.K., France, Germany, Spain, Italy, Central & Eastern Europe, CIS)

Asia Pacific (China, Japan, South Korea, ASEAN, India, Rest of Asia Pacific)

Latin America (Brazil, Rest of L.A.)

Middle East and Africa (Turkey, GCC, Rest of Middle East)

Some Major TOC Points:

Chapter 1. Report Overview

Chapter 2. Global Growth Trends

Chapter 3. Market Share by Key Players

Chapter 4. Breakdown Data by Type and Application

Chapter 5. Market by End Users/Application

Chapter 6. COVID-19 Outbreak: Cruise Travel Insurance Industry Impact

Chapter 7. Opportunity Analysis in Covid-19 Crisis

Chapter 9. Market Driving Force

And More

In this latest research publication a thorough overview of the current market scenario has been portrayed, in a bid to aid market participants, stakeholders, research analysts, industry veterans and the like to borrow insightful cues from this ready-to-use market research report, thus influencing a definitive business discretion. The report in its subsequent sections also portrays a detailed overview of competition spectrum, profiling leading players and their mindful business decisions, influencing growth in the Cruise Travel Insurance market.

About Us:

Report Consultant A worldwide pacesetter in analytics, research and advisory that can assist you to renovate your business and modify your approach. With us, you will learn to take decisions intrepidly by taking calculative risks leading to lucrative business in the ever-changing market. We make sense of drawbacks, opportunities, circumstances, estimations and information using our experienced skills and verified methodologies.

Our research reports will give you the most realistic and incomparable experience of revolutionary market solutions. We have effectively steered business all over the world through our market research reports with our predictive nature and are exceptionally positioned to lead digital transformations. Thus, we craft greater value for clients by presenting progressive opportunities in the global futuristic market.

Contact us:

Rebecca Parker

(Report Consultant)

sales@reportconsultant.com

http://www.reportconsultant.com

Read this article:
Machine Learning and Artificial Intelligence in Healthcare Market 2021 inclining trends with NVIDIA Corporation, Intel Corporation, GENERAL ELECTRIC...

SINGAPORE -Media OutReach-5 February2021 -Despite majority of Singapore employers(89%) reporting that the COVID-19 pandemic has accelerated the adoption of cloudcomputing and Machine Learning (ML) in their companies, obstacles abound. Singaporebusiness leaders say that the largest hindrance to adopting cloud computing andML technologies is the shortage of relevant in-house IT support (64%), amongstother reasons such as 'employees do not have the relevant skill sets' (58%) and'the lack of financial resources' (46%).

alt="NTUC LearningHub Survey Reveals Accelerated Business Needs In Cloud Computing And Machine Learning Outpacing Singapore Talent Supply; Skills Gap A Hindrance To Implementing These Technologies"

These are some ofthe key findings from the recently launched NTUC LearningHub (NTUC LHUB)Industry Insights report on cloud computing and ML in Singapore. The report is basedon in-depth interviews with industry experts, such as Amazon Web Services (AWS)and NTUC LHUB, and a survey with 300 hiring managers across industries inSingapore.

While organisationsare keen to adopt cloud computing and ML to improve the company's businessperformance (64%), obtain business insights from Big Data (59%) and performmundane or tedious tasks (53%), a third of Singapore employers (32%) say theircompanies have insufficient talent to implement cloud computing and MLtechnologies.

To overcome thisshortage, companies say they have been upskilling employees that have relevantskill sets/ roles (55%), and reskilling employees that have completelydifferent skill sets/ roles (44%). In a further show of how organisations werewilling to take steps to overcome this skills gap, three in five (61%) stronglyagree or agree that they will be open to hiring individuals with relevantmicro-credentials, even if these candidates has no relevant experience oreducation degrees.

Looking to thefuture, four in five employers (81%) agree or strongly agree that ML will bethe most in-demand Artificial Intelligence (AI) skill in 2021. Meanwhile, sevenout of 10 surveyed (70%) indicated they will be willing to offer a premium fortalent with AI and ML skills.

"The report reinforces the growing demand for a cloud-skilled workforce inSingapore, and the critical need to upskill and reskill local talent", said TanLee Chew, Managing Director, ASEAN, Worldwide Public Sector, AWS. "Thecollaboration across government, businesses, education and traininginstitutions will be instrumental in helping Singapore employers address theseskills gaps. AWS will continue to collaborate with training providers like NTUCLearningHub to make skills training accessible to help Singaporeans, fromstudents to adult learners, to remain relevant today and prepare for the future."

NTUC LHUB's Head ofICT, Isa Nasser also adds, "While much of the talent demand encompasses technicalpositions such as data scientists and data engineers, businesses are alsolooking for staff to pick up practical ML and data science skills sets that canbe applied to their existing work. Thatis why in today's digital age, most professionals would benefit greatly frompicking up some data science skills to enable them to deploy ML applicationsand use cases in their organization. We highly urge workers to get started on equipping themselveswith ML skills, including understanding the core concepts of data science, aswell as familiarising themselves on the use of cloud or ML platforms such as AmazonSageMaker."

To download theIndustry Insights: Cloud Computing and ML report, visit

https://www.ntuclearninghub.com/machine-learning-cloud.

NTUCLearningHub is the leading Continuing Education and Training provider in Singapore,which aims to transform the lifelong employability of working people. Since ourcorporatisation in 2004, we have been working employers and individual learnersto provide learning solutions in areas such as Cloud, Infocomm Technology,Healthcare, Employability & Literacy, Business Excellence, Workplace Safety& Health, Security, Human Resources and Foreign Worker Training.

Todate, NTUC LearningHub has helped over 25,000 organisations and achieved over2.5 million training places across more than 500 courses with a pool of over460 certified trainers. As a Total Learning Solutions provider toorganisations, we also forge partnerships and offer a wide range of relevantend-to-end training solutions and work constantly to improve our trainingquality and delivery. In 2020, we have accelerated our foray into onlinelearning with our Virtual Live Classes and, through working with best-in-classpartners such as IBM, DuPont Sustainable Solutions and GO1, asynchronous onlinecourses.

For moreinformation, visitwww.ntuclearninghub.com.

Read the original:
NTUC LearningHub Survey Reveals Accelerated Business Needs In Cloud Computing And Machine Learning Outpacing Singapore Talent Supply; Skills Gap A...