Machine learning is a field of science that offers machines an ability to understand data and carry out processes just as a human would do. Sometimes, even more efficiently.
The ML technology uses complex algorithms to analyze large data sets and find data patterns that help in business decisions. This is why machine learning can detect fraud in the system easily. It is, in fact, used for various other purposes such as spam detection, product recommendation, image recognition, predictive analysis, etc.
Artificial Intelligence and Machine Learning in the Insurance IndustryMaruti Techlabs
The insurance industry is facing tumultuous times with #technology shaping the way it operates.
Chatbots are employed in various industries today & pose massive opportunities for the insurance industry.
According to a report by @Business Insider, four top messenger apps have a combined user base of more than 3.5 billion, exceeding the combined user base of four largest social networks.
Machine learning capabilities are already being used in the insurance space in the form of automated policy writing.
Today, insurers are customizing rates for individuals based on their specific #data & historical records. AI is helping them achieve this scale of personalization.
AI is a critical factor of success for companies in the insurance industry & companies can leverage technology for fraud detection, claims #management, #analytics, & customer experience.
Insurance companies are also able to bundle services & products for each user separately, given the demand & use of services for them.
Since sales & marketing departments get better visibility of customer interests & insights on buying behaviour, they can sell according to buyer intention.
Link to the complete article in the comments below ⬇️
#ML #AI #artificialintelligence #machinelearning #insurance
Streamlining aml processes through automation with aiVarun Mittal
This solution harnesses artificial intelligence and scalable algorithmic-based analytics to transform anti-money laundering (AML) processes, leading to improved risk coverage, reduced operational expenses and increased operational efficiencies.
How are Machine Learning & mHealth transforming the healthcare industry?Maruti Techlabs
The primary goal of the healthcare industry is to cure health-related issues through proper care, medication and monitoring.
And in the current scenario, the market for global healthcare is on a rise, owing to multiple factors like rise in chronic health conditions, technological advancements, growing labour costs due to staff shortage, and expensive infrastructure.
The report by ResearchandMarkets on the global healthcare opportunities and strategies mentioned that the industry showed an annual growth rate of 7.3% since 2014. In 2018 alone, the industry valued at $11.9Tn.
The growth is also attributed to growing health related awareness and increasing technology support people are receiving in this segment.
With time, the use of #technology has brought structural changes to the healthcare industry, for the better.
Whether it’s managing endless administrative processes in #hospitals, providing personalized care & treatment or facilitating better access.
Technological advancements like mobile healthcare, also known as mhealth, & machine learning in healthcare have streamlined the healthcare sector to a great extent.
As per @Statista, there were close to 2.4Bn #medical mobile apps in 2017 in the U.S. alone. It is estimated to reach 11.2Bn by 2025.
Machine learning in #healthcare can be trained to look at images, identify abnormalities, & point to areas that need attention, thus improving the accuracy of all these processes.
Let us dive deeper into how machine learning in healthcare combined with the easier accessibility of mobile devices is transforming the healthcare space.
Link to the complete article in the comments below ⬇️
#ML #Machinelearning #deeplearning #digitalhealth
Operationalize deep learning models for fraud detection with Azure Machine Le...Francesca Lazzeri, PhD
Recent advancements in computing technologies along with the increasing popularity of ecommerce platforms have radically amplified the risk of online fraud for financial services companies and their customers. Failing to properly recognize and prevent fraud results in billions of dollars of loss per year for the financial industry. This trend has urged companies to look into many popular artificial intelligence (AI) techniques, including deep learning for fraud detection. Deep learning can uncover patterns in tremendously large datasets and independently learn new concepts from raw data without extensive manual feature engineering. For this reason, deep learning has shown superior performance in domains such as object recognition and image classification.
Although, neural networks have been used for fraud detection for decades, recent advancements in computing technologies along with large volumes of data available today have dramatically improved the effectiveness of these techniques. Using a sample dataset that contains transactions made by credit cards in September 2013 by European cardholders, Francesca Lazzeri and Jaya Mathew explain how to build, deploy, and operationalize a deep learning model to identify and prevent fraud, using Azure Machine Learning Workbench to show the main steps in the operationalization process (from data ingestion to consumption) and the Keras deep learning library with Microsoft Cognitive Toolkit CNTK as the backend.
Artificial Intelligence and Machine Learning in the Insurance IndustryMaruti Techlabs
The insurance industry is facing tumultuous times with #technology shaping the way it operates.
Chatbots are employed in various industries today & pose massive opportunities for the insurance industry.
According to a report by @Business Insider, four top messenger apps have a combined user base of more than 3.5 billion, exceeding the combined user base of four largest social networks.
Machine learning capabilities are already being used in the insurance space in the form of automated policy writing.
Today, insurers are customizing rates for individuals based on their specific #data & historical records. AI is helping them achieve this scale of personalization.
AI is a critical factor of success for companies in the insurance industry & companies can leverage technology for fraud detection, claims #management, #analytics, & customer experience.
Insurance companies are also able to bundle services & products for each user separately, given the demand & use of services for them.
Since sales & marketing departments get better visibility of customer interests & insights on buying behaviour, they can sell according to buyer intention.
Link to the complete article in the comments below ⬇️
#ML #AI #artificialintelligence #machinelearning #insurance
Streamlining aml processes through automation with aiVarun Mittal
This solution harnesses artificial intelligence and scalable algorithmic-based analytics to transform anti-money laundering (AML) processes, leading to improved risk coverage, reduced operational expenses and increased operational efficiencies.
How are Machine Learning & mHealth transforming the healthcare industry?Maruti Techlabs
The primary goal of the healthcare industry is to cure health-related issues through proper care, medication and monitoring.
And in the current scenario, the market for global healthcare is on a rise, owing to multiple factors like rise in chronic health conditions, technological advancements, growing labour costs due to staff shortage, and expensive infrastructure.
The report by ResearchandMarkets on the global healthcare opportunities and strategies mentioned that the industry showed an annual growth rate of 7.3% since 2014. In 2018 alone, the industry valued at $11.9Tn.
The growth is also attributed to growing health related awareness and increasing technology support people are receiving in this segment.
With time, the use of #technology has brought structural changes to the healthcare industry, for the better.
Whether it’s managing endless administrative processes in #hospitals, providing personalized care & treatment or facilitating better access.
Technological advancements like mobile healthcare, also known as mhealth, & machine learning in healthcare have streamlined the healthcare sector to a great extent.
As per @Statista, there were close to 2.4Bn #medical mobile apps in 2017 in the U.S. alone. It is estimated to reach 11.2Bn by 2025.
Machine learning in #healthcare can be trained to look at images, identify abnormalities, & point to areas that need attention, thus improving the accuracy of all these processes.
Let us dive deeper into how machine learning in healthcare combined with the easier accessibility of mobile devices is transforming the healthcare space.
Link to the complete article in the comments below ⬇️
#ML #Machinelearning #deeplearning #digitalhealth
Operationalize deep learning models for fraud detection with Azure Machine Le...Francesca Lazzeri, PhD
Recent advancements in computing technologies along with the increasing popularity of ecommerce platforms have radically amplified the risk of online fraud for financial services companies and their customers. Failing to properly recognize and prevent fraud results in billions of dollars of loss per year for the financial industry. This trend has urged companies to look into many popular artificial intelligence (AI) techniques, including deep learning for fraud detection. Deep learning can uncover patterns in tremendously large datasets and independently learn new concepts from raw data without extensive manual feature engineering. For this reason, deep learning has shown superior performance in domains such as object recognition and image classification.
Although, neural networks have been used for fraud detection for decades, recent advancements in computing technologies along with large volumes of data available today have dramatically improved the effectiveness of these techniques. Using a sample dataset that contains transactions made by credit cards in September 2013 by European cardholders, Francesca Lazzeri and Jaya Mathew explain how to build, deploy, and operationalize a deep learning model to identify and prevent fraud, using Azure Machine Learning Workbench to show the main steps in the operationalization process (from data ingestion to consumption) and the Keras deep learning library with Microsoft Cognitive Toolkit CNTK as the backend.
Learn how IBM Smarter Analytics Solution for insurance helps Detect and prevent insurance claims fraud, waste and abuse. For more information on IBM Systems, visit http://ibm.co/RKEeMO.
Visit the official Scribd Channel of IBM India Smarter Computing at http://bit.ly/VwO86R to get access to more documents.
Google’s smart reply mechanism uses ML extensively to create a next-generation email interface. It can automatically suggest three customized responses to each email that hits the inbox. It resulted in 10% of email replies sent via smart reply.
Artificial Intelligence in Life Sciences: Friend or Foe? by Luke StewartSaama
Luke Stewart was keynote at the AI and Big Data conference hosted by Innovation Enterprises in December 2018 in New York City. Luke talked about Artificial Intelligence in Life Sciences.
Artificial intelligence in Pharma by Malai SankarasubbuSaama
Malai Sankarasubbu, VP of AI Research at Saama Technologies, speaks about Artificial Intelligence in Pharma at the ExL AI Innovation Summit in Philadelphia in 2019.
Saama Presents Is your Big Data Solution Ready for StreamingSaama
Amit Gulwadi and Karim Damji presented at Panagora's IoT in Clinical Trials Summit in Boston in November 2018. Using the right analytic solution that can incorporate your unstructured IoT data provides tremendous benefits including faster time to commercialization and better business and patient outcomes.
Role of artificial intelligence in cyber security | The Cyber Security ReviewFreelancing
Emerging technologies put cybersecurity at risk. Even the new advancements in defensive strategies of security professionals fail at some point. Let's see what the latest AI technology in cybersecurity is.
Discover 5 ways you can apply Data Science for Finance.
Follow @theclickreader and head over to www.theclickreader.com for the world's best collection of data science resources.
#data #datascience #datascientist
#machinelearning #artificialintelligence #datavisualization #dataanalysis
Technological advancements in the field of Machine Learning has led ML to find use in various crucial applications. Machine learning has been instrumental in resolving some of the critical business problems and optimizing various business processes. Machine Learning has been used for a variety of applications such as detecting email spam, customer retention, focused product recommendation, accurate medical diagnosis, etc.
Governance includes managing and handling of functions of a state, involving interference and keen monitoring by the government. Artificial intelligence and machine learning now play an important role in identifying challenges and addressing concerns.
Transforming Insurance Analytics with Big Data and Automated Machine Learning Cloudera, Inc.
3 Things to Learn About:
*How to create a next generation data platform and why it is important
*How to monetize this data using predictive modeling and machine learning
*Automated machine learning as a sustainable, cost-effective and efficient solution
Learn how IBM Smarter Analytics Solution for insurance helps Detect and prevent insurance claims fraud, waste and abuse. For more information on IBM Systems, visit http://ibm.co/RKEeMO.
Visit the official Scribd Channel of IBM India Smarter Computing at http://bit.ly/VwO86R to get access to more documents.
Google’s smart reply mechanism uses ML extensively to create a next-generation email interface. It can automatically suggest three customized responses to each email that hits the inbox. It resulted in 10% of email replies sent via smart reply.
Artificial Intelligence in Life Sciences: Friend or Foe? by Luke StewartSaama
Luke Stewart was keynote at the AI and Big Data conference hosted by Innovation Enterprises in December 2018 in New York City. Luke talked about Artificial Intelligence in Life Sciences.
Artificial intelligence in Pharma by Malai SankarasubbuSaama
Malai Sankarasubbu, VP of AI Research at Saama Technologies, speaks about Artificial Intelligence in Pharma at the ExL AI Innovation Summit in Philadelphia in 2019.
Saama Presents Is your Big Data Solution Ready for StreamingSaama
Amit Gulwadi and Karim Damji presented at Panagora's IoT in Clinical Trials Summit in Boston in November 2018. Using the right analytic solution that can incorporate your unstructured IoT data provides tremendous benefits including faster time to commercialization and better business and patient outcomes.
Role of artificial intelligence in cyber security | The Cyber Security ReviewFreelancing
Emerging technologies put cybersecurity at risk. Even the new advancements in defensive strategies of security professionals fail at some point. Let's see what the latest AI technology in cybersecurity is.
Discover 5 ways you can apply Data Science for Finance.
Follow @theclickreader and head over to www.theclickreader.com for the world's best collection of data science resources.
#data #datascience #datascientist
#machinelearning #artificialintelligence #datavisualization #dataanalysis
Technological advancements in the field of Machine Learning has led ML to find use in various crucial applications. Machine learning has been instrumental in resolving some of the critical business problems and optimizing various business processes. Machine Learning has been used for a variety of applications such as detecting email spam, customer retention, focused product recommendation, accurate medical diagnosis, etc.
Governance includes managing and handling of functions of a state, involving interference and keen monitoring by the government. Artificial intelligence and machine learning now play an important role in identifying challenges and addressing concerns.
Transforming Insurance Analytics with Big Data and Automated Machine Learning Cloudera, Inc.
3 Things to Learn About:
*How to create a next generation data platform and why it is important
*How to monetize this data using predictive modeling and machine learning
*Automated machine learning as a sustainable, cost-effective and efficient solution
Reconciliation is an essential control function in financial services, aimed at eliminating operational risk that can lead to fraud, fines or in the worst case, the failure of a whole firm. And yet, since an early push in the early 2000s that automated parts of the very back-end of the system (cash and custody), innovation in this area has stalled and operations reliant on people power and spreadsheets are prevalent.
https://runfrictionless.com/b2b-white-paper-service/
Machine learning and artificial intelligence are two of the most rapidly growing and transformative technologies of our time. These technologies are revolutionizing the way businesses operate, improving healthcare outcomes, and transforming the way we live our daily lives. Learn more about it in the PPT below!
Utilizing Machine Learning In Banking To Prevent Fraud.pdfMindfire LLC
Machine Learning (ML) is a vital tool for fraud detection in banks. It can spot potential fraud by examining patterns in transactions and comparing them with known fraudulent activity. It uses algorithms to identify these patterns, which are then used to predict whether or not a transaction is fraudulent. These algorithms are trained using historical data, so they can only identify patterns in existing data and cannot learn new ways as they occur.
This means that companies must constantly update their machine learning models with further information for continuing to use machine learning in Banking to prevent fraud.
AI and Machine Learning In Cybersecurity | A Saviour or Enemy?SahilRao25
Let's take a look at implementations of AI or machine learning in the cybersecurity world. To know more: https://www.softwarefirms.co/blog/ai-and-machine-learning-in-cybersecurity-a-saviour-or-enemy?utm_source=Social+media&utm_medium=Traffic&utm_campaign=SR
with great enthusiasm Insights Success has
shortlisted The 10 Most Trusted Fraud Detection
Solution Providers, 2019, who are working round the
clock to help is clients detect fraud, faster!
The Key Differences Between Rule-Based AI And Machine LearningRobert Smith
While a rules-based system could be considered as having “fixed” intelligence, in contrast, a machine learning system is adaptive and attempts to simulate human intelligence. Eventually, the machine will be able to interpret, categorize, and perform other tasks with unlabeled data or unknown information on its own.
Internet 2.0 Conference Reviews The Use Of Machine Learning In Fraud & Scam P...Internet 2Conf
This presentation by the Internet 2.0 Conference reviews the importance of embracing new technologies like machine learning to detect and deal with fraudulent scenarios. This presentation also highlights a few potential advantages of using ML in the scam and spam detection.
ghtyfvgyhuohikbjgcfgvhkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkAir pollution is the act of mixing pollutants into air which is not ideal because it decreases the quality of life of human-beings and affects the overall planet’s habitat. Air pollution occurs when dangerous particles, gases, and chemicals are released into the air. The pollutants of air can be found in vehicle exhausts, fumes from factories and power plants, and construction sites. Respiratory problems, skin diseases, irritation of the eyes are some of the major health issues caused by air pollution. To combat this, many governments have created and enforced policies to reduce air pollution, such as shutting down coal power plants or requiring car owners to switch over to electric cars. Air purifiers are being installed at points of high vehicular movement. Rain seeding is another step to clean up the air. We should also plant more trees and care for them as trees filter pollutants and absorb carbon dioxide. Air Pollution is a challenge that humankind needs to overcome to see a better tomorrow.
(166 words)
Example 2: Importance of Trees
Trees are very important, valuable and necessary to our existence as they have furnished us with two important life essentials; food and oxygen. Trees intake Carbon dioxide from air and breathe out fresh oxygen. Carbon dioxide breathed in by the trees is one of the greenhouse gases. So planting more trees will clean the air and reduce the ill – effects of global warming.
Trees provide food to man and all herbivorous animals. Animals, insects, birds, and fungi make their home in the trees and make a diverse ecosystem. Trees also help in binding the soil. When trees are cut off, the most fertile top soil layer gets washed away easily in rains or floods. Trees provide us with medicinal herbs, timber, shelter too.
Hence, We should encourage planting more and more trees. It is for our own betterment and the sooner we understand this, the better it is for us.
(150 words)
Example 3: India of my Dreams
India is a country where people of all cultures and religions coexist. As Indian citizens, we are continuously looking for ways to improve our country and see a better India.
In the India of my dreams, women would be safe and be able to travel freely. Additionally, it will be a place where everyone may experience freedom and equality in its truest form. It would also be a place without caste, colour, gender, creed, social or economic standing, or race prejudice. India of my dreams should be a place where poor people get empowerment, face no poverty, do not starve, and get the proper roof to live. Additionally, I think of it as a place that experiences a lot of technological growth and development. I wish our wonderful nation nothing ggggggggg
AI for optimizing customer journeys in online bettingFrosmo
The machines we use on a daily basis are getting smarter, and with AI shaping our world far more than many of us realize, how does it affect the online betting industry? How do you predict churn? Fraud? How do you identify problem gamblers? Find out how AI is shaping the online betting industry.
These are some general ideas to get one started with "Machine Learning".Machine learning is a vast subject in the field of computer science & needs intense research to master.
Similar to Why machine learning is the best way to reduce fraud (20)
How artificial intelligence can transform the music industry GlobalTechCouncil
Artificial intelligence implementation comes with a promise of augmentation and enhancement in the business processes. With AI by our side, we are empowered to make better decisions and choices related to the future of the business. No doubt, AI drives both innovation and growth, which is why it is about to become one of the most utilized technologies in the music industry for creative processes.
We are sure, many of us are already tired of hearing this. The actual question that we want to answer today is where. How do we use machine learning in our daily lives? What devices or applications are included in this everywhere? Let’s find out.
How entrepreneurs can benefit from machine learning GlobalTechCouncil
A study released by Harvard Business Review revealed that AI allows humans to improve social skills, creativity, leadership, and teamwork.
Let’s see how machine learning can empower entrepreneurs to improve their productivity.
Just a few years back, artificial intelligence meant adaptions like Jarvis. Who would have thought that AI would soon become an application of our daily lives?
Artificial intelligence has the potential to streamline several business processes, analyze data for insights, and help in building fruitful business strategies. Hence, globally, it is being used to remediate old processes, invent new methods, and improve productivity.
The analytics market is abuzz where professionals from various disciplines and background are leveraging data in their daily activities to get maximum insights and help a business to grow.
To evaluate an intelligent answer, we need to assess the broader or narrower meaning of smart, which is rightly defined by J. P. Guilford. The psychologist has divided thinking into two aspects: divergent thinking and convergent thinking. The convergent thinking means answering given questions correctly, which displays logic and memory. However, the divergent memory is forming various answers for one problem statement, displaying the presence of curiosity – the ability of extraordinary thinking.
How can artificial intelligence be used in e learning GlobalTechCouncil
Artificial Intelligence allows for machines to learn from past experience, adjust to present inputs and perform human-like tasks, with utmost perfection. Research estimates that the artificial intelligence market will grow to a $190 billion industry by 2025. And by 2021, uses of artificial intelligence in education industry will grow by 47.5%.
Is artificial intelligence the future tool for anti corruption GlobalTechCouncil
The World Bank report suggests that the amount of goods and services that governments purchase to discharge their official business is a staggering $10 trillion per year – and is estimated at 10 to 25 percent of global GDP. Unless an effective public scrutiny mechanism is not in place, there are high chances of the money being lost to corruption.
How cosmetic brands use augmented reality to boost sales GlobalTechCouncil
Sephora is a leading beauty brand that truly transformed the application of augmented reality in beauty and cosmetics. They collaborated with ModiFace to help their users see how cosmetics will look their face. The app can simulate a given cosmetic product on the photo containing the face of the user.
Washington introduces new bill to recognize and encourage blockchainGlobalTechCouncil
The development around Blockchain technology seems to be buzzing the world every day. There isn’t a day when you would not hear people talking about this technology.
How data science can be used to break down the interoperability problem GlobalTechCouncil
Have you ever experienced any of the following scenarios?
• The alarm of the infusion-pump keeps beeping, but the nurse station can’t recognize it. When you finally call the nurse, she says that there is an issue.
• The oximeter alarm goes off, and the nurse comes just to say that you don’t have to worry because this happens a lot.
this happens a lot.
Artificial intelligence advancements for the betterment of our planetGlobalTechCouncil
The world is focussing on the technological advancements in the hope of a better future. But we often forget more than anything else; our future depends upon the health of our planet. Humans have taken the planet earth for granted, and its health is deteriorating. Without a healthy planet, all the efforts and hopes of a better future are worthless.
Should india invest more in developing artificial intelligence GlobalTechCouncil
To be true, we are living in an era of artificial intelligence. From smart homes and personal assistants to surgical robots and self-driving cars, everything proves us how powerful technology has become. All these inventions radiate advancement of machine learning, artificial intelligence, robotics, internet of things, and predictive analysis.
Augmented reality vs. virtual reality differences and similaritiesGlobalTechCouncil
Augmented Reality and Virtual Reality are two buzzwords we hear in the technology sector. Though People are aware of the two technologies in a broad manner but very few understand their true meaning, potential and how they are similar in certain ways yet different altogether.
Let’s have an insight into the two futuristic technologies that are slowly transforming the world around us.
How big data analytics can optimize the telecom sector GlobalTechCouncil
We are in the era of Big data. Big data is presenting excellent optimizing opportunities to the companies in various sectors. Big data when analyzed well, can provide actionable insights that aids in devising strategies to optimize multiple business processes.
Big data has become an essential part of the telecom industry due to the enormous amount of data being generated by the telecom world. Telecom operators are sitting on gold mines as the smart devices have enabled the telecom operators to gain access to specific information about their customers’ behavior, preferences, movement, etc.
How artificial intelligence is changing content marketing GlobalTechCouncil
It was a long time ago that Alan Turing questioned the intelligence of machines in the 1950s. We’ve come a long way since then with the IBM supercomputer Deep Blue winning against reigning world champion Garry Kasparov in 1996
Do you use the internet? Do you use websites with customer support live chat? If you answered yes to any of the questions I asked above, then chances are you have the first-hand experience of interacting with a chatbot. With digital interaction reaching new heights, chatbots have become quite the new buzz. And over the time chatbots have evolved too. When chatbots were conceived, they sounded entirely robotic, but today with the advancements in machine learning, these chatbots have improved in analysing the legions of data provided to them. They almost feel human when talking to.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.