This presentation was given at an INTERPOL / United Nations events about law enforcement and AI, at INTERPOL's innovation lab in Singapore, July 11th, 2018.
The presentation itself covers nearly a dozen AI-related use cases, along with their possible uses in law enforcement, surveillance, or falsifying evidence.
This deck is from Interpol Conference 2017, these slides shows the holistic view of machine learning in cyber security for better organization readiness
In this talk we provide an overview of how Artificial Intelligence and technology development can contribute to existing policing practices. In particular, we discuss three different projects conducted in the context of the Centre of Policing Research and Learning of the Open University (http://centre-for-policing.open.ac.uk/) and the Trivalent project (http://trivalent-project.eu/). The first project, policing engagement via social media, provides an overview of how police forces in the UK make use of social media to communicate with the public, and what attracts citizens to engage with social media policing content. The second project, detecting grooming behaviour on social media, describes the problem of child grooming online, and our proposed approach to automatically identify the different stages of grooming behaviour from online content. The third project, radicalisation detection on social media targets the problem of online radicalisation, where individuals are introduced to extreme views, primarily through the use of social media. Within this context our work focuses on the detection of pro-ISIS stances and on the understanding of the processes that influence the adoption of radicalised behaviour.
This deck is from Interpol Conference 2017, these slides shows the holistic view of machine learning in cyber security for better organization readiness
In this talk we provide an overview of how Artificial Intelligence and technology development can contribute to existing policing practices. In particular, we discuss three different projects conducted in the context of the Centre of Policing Research and Learning of the Open University (http://centre-for-policing.open.ac.uk/) and the Trivalent project (http://trivalent-project.eu/). The first project, policing engagement via social media, provides an overview of how police forces in the UK make use of social media to communicate with the public, and what attracts citizens to engage with social media policing content. The second project, detecting grooming behaviour on social media, describes the problem of child grooming online, and our proposed approach to automatically identify the different stages of grooming behaviour from online content. The third project, radicalisation detection on social media targets the problem of online radicalisation, where individuals are introduced to extreme views, primarily through the use of social media. Within this context our work focuses on the detection of pro-ISIS stances and on the understanding of the processes that influence the adoption of radicalised behaviour.
“AI is the new electricity” proclaims Andrew Ng, co-founder of Google Brain. Just as we need to know how to safely harness electricity, we also need to know how to securely employ AI to power our businesses. In some scenarios, the security of AI systems can impact human safety. On the flip side, AI can also be misused by cyber-adversaries and so we need to understand how to counter them.
This talk will provide food for thought in 3 areas:
Security of AI systems
Use of AI in cybersecurity
Malicious use of AI
Digital Forensics is the use of scientifically derived and proven methods toward the preservation, collection, validation, identification, analysis, interpretation, documentation, and presentation of digital evidence derived from digital devices.
AI for security or security for AI - Sergey GordeychikSergey Gordeychik
Machine learning technologies are turning from rocket science into daily engineering life. You no longer have to know the difference between Faster R-CNN and HMM to develop a machine vision system, and even OpenCV has bindings for JavaScript allowing to resolve quite serious tasks all the while remaining in front end. On other hand massive implementation of AI in various areas brings about problems, and security is one of the greatest concerns. In the broader context security is really all about trust.
Do we trust AI? I don’t, personally.
What is “state of the art” in AI security? Yesterday it was a PoC, not a product, today becoming a We will fix it later, tomorrow it will be a if it works, don’t touch it. And tomorrow is too late.
But what we can do for Trustworthy AI? There are just no simple answers.
You can’t install antivirus or calculate hashes to control integrity of annotated dataset. Traditional firewalls and IDS are almost useless in ML cloud internal SDN Infiniband network. Event C-level Compliance such as PCI DSS and GDPR doesn’t work for massive country-level AI deployments. What about vulnerability management for TensorFlow ML model? How it will impact ROC and AUC?..
To make it better we should rethink Cyber Resilience for AI process, systems and applications to make sure that they continuously deliver the intended outcome despite adverse cyber events. Make sure that security is genuinely integrated into innovation that AI brings into our lives. To trust AI and earn his trust, perhaps?
Forensic science is a scientific method of gathering and examining information about the past which is then used in the court of law. Digital Forensics is the use of scientifically derived and proven methods toward the preservation, collection, validation, identification, analysis, interpretation, documentation, and presentation of digital evidence derived from digital devices for the purpose of facilitation or furthering the reconstruction of events found to be criminal, or helping to anticipate unauthorized actions shown to be disruptive to planned operations.
The release of TensorFlow 2.0 comes with a significant number of improvements over its 1.x version, all with a focus on ease of usability and a better user experience. We will give an overview of what TensorFlow 2.0 is and discuss how to get started building models from scratch using TensorFlow 2.0’s high-level api, Keras. We will walk through an example step-by-step in Python of how to build an image classifier. We will then showcase how to leverage a transfer learning to make building a model even easier! With transfer learning, we can leverage other pretrained models such as ImageNet to drastically speed up the training time of our model. TensorFlow 2.0 makes this incredibly simple to do.
A Theory of Knowledge Lecture given by Mark Steed, Director of JESS Dubai on Monday 4th March 2019
The lecture explains how AI works and then looks at some of the ethical implications
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.
The Artificial Intelligence World: Responding to Legal and Ethical IssuesRichard Austin
The presentation examines the legal and ethical issues that Facial Recognition Systems and Autonomous and Self-driving Vehicles present then looks at organizational, regulatory and individual tools available to respond to these issues.
“AI is the new electricity” proclaims Andrew Ng, co-founder of Google Brain. Just as we need to know how to safely harness electricity, we also need to know how to securely employ AI to power our businesses. In some scenarios, the security of AI systems can impact human safety. On the flip side, AI can also be misused by cyber-adversaries and so we need to understand how to counter them.
This talk will provide food for thought in 3 areas:
Security of AI systems
Use of AI in cybersecurity
Malicious use of AI
Digital Forensics is the use of scientifically derived and proven methods toward the preservation, collection, validation, identification, analysis, interpretation, documentation, and presentation of digital evidence derived from digital devices.
AI for security or security for AI - Sergey GordeychikSergey Gordeychik
Machine learning technologies are turning from rocket science into daily engineering life. You no longer have to know the difference between Faster R-CNN and HMM to develop a machine vision system, and even OpenCV has bindings for JavaScript allowing to resolve quite serious tasks all the while remaining in front end. On other hand massive implementation of AI in various areas brings about problems, and security is one of the greatest concerns. In the broader context security is really all about trust.
Do we trust AI? I don’t, personally.
What is “state of the art” in AI security? Yesterday it was a PoC, not a product, today becoming a We will fix it later, tomorrow it will be a if it works, don’t touch it. And tomorrow is too late.
But what we can do for Trustworthy AI? There are just no simple answers.
You can’t install antivirus or calculate hashes to control integrity of annotated dataset. Traditional firewalls and IDS are almost useless in ML cloud internal SDN Infiniband network. Event C-level Compliance such as PCI DSS and GDPR doesn’t work for massive country-level AI deployments. What about vulnerability management for TensorFlow ML model? How it will impact ROC and AUC?..
To make it better we should rethink Cyber Resilience for AI process, systems and applications to make sure that they continuously deliver the intended outcome despite adverse cyber events. Make sure that security is genuinely integrated into innovation that AI brings into our lives. To trust AI and earn his trust, perhaps?
Forensic science is a scientific method of gathering and examining information about the past which is then used in the court of law. Digital Forensics is the use of scientifically derived and proven methods toward the preservation, collection, validation, identification, analysis, interpretation, documentation, and presentation of digital evidence derived from digital devices for the purpose of facilitation or furthering the reconstruction of events found to be criminal, or helping to anticipate unauthorized actions shown to be disruptive to planned operations.
The release of TensorFlow 2.0 comes with a significant number of improvements over its 1.x version, all with a focus on ease of usability and a better user experience. We will give an overview of what TensorFlow 2.0 is and discuss how to get started building models from scratch using TensorFlow 2.0’s high-level api, Keras. We will walk through an example step-by-step in Python of how to build an image classifier. We will then showcase how to leverage a transfer learning to make building a model even easier! With transfer learning, we can leverage other pretrained models such as ImageNet to drastically speed up the training time of our model. TensorFlow 2.0 makes this incredibly simple to do.
A Theory of Knowledge Lecture given by Mark Steed, Director of JESS Dubai on Monday 4th March 2019
The lecture explains how AI works and then looks at some of the ethical implications
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.
The Artificial Intelligence World: Responding to Legal and Ethical IssuesRichard Austin
The presentation examines the legal and ethical issues that Facial Recognition Systems and Autonomous and Self-driving Vehicles present then looks at organizational, regulatory and individual tools available to respond to these issues.
3 Steps To Tackle The Problem Of Bias In Artificial IntelligenceBernard Marr
Artificial intelligence (AI) is facing a problem: Bias. As more and more decisions are being made by AIs, this is an issue that is important to us all. In this article we look at some key steps you can take to ensure AIs of the future are not biased against, e.g., race, gender, sexuality, etc.
SHOULD ALGORITHMS DECIDE YOUR FUTUREThis publication was .docxmaoanderton
SHOULD ALGORITHMS DECIDE YOUR FUTURE?
This publication was prepared by Kilian Vieth and
Joanna Bronowicka from Centre for Internet and
Human Rights at European University Viadrina. It was
prepared based on a publication “The Ethics of
Algorithms: from radical content to self-driving cars”
with contributions from Zeynep Tufekci, Jillian C. York,
Ben Wagner and Frederike Kaltheuner and an event
on the Ethics of Algorithms, which took place on
March 9-10, 2015 in Berlin. The research was support-
ed by the Dutch Ministry of Foreign Affairs.
Find out more: cihr.eu/ethics-of-algorithms/
Follow the discussion on Twitter: #EoA2015
Graphic design by Thiago Parizi
cihr.eu @cihr_eu
1 | ETHICS OF ALGORITHMS ETHICS OF ALGORITHMS | 2
WHAT IS AN ALGORITHM?
ALGORITHMS SHAPE OUR WORLD(S)!
Our everyday life is shaped by computers and our computers are shaped
by algorithms. Digital computation is constantly changing how we commu-
nicate, work, move, and learn. In short, digitally connected computers are
changing how we live our lives. This revolution is unlikely to stop any time
soon.
Digitalization produces increasing amounts of datasets known as ‘big
data’. So far, research focused on how ‘big data is produced and stored.
Now, we begin to scrutinize how algorithms make sense of this growing
amount of data
Algorithms are the brains of our computers, mobiles, Internet of Things.
Algorithms are increasingly used to make decisions for us, about us, or
with us – oftentimes without us realizing it. This raises many questions
about the ethical dimension of algorithms.
WHY DO ALGORITHMS RAISE ETHICAL
CONCERNS?
First, let's have a closer look at some of the critical features of algorithms.
What are typical functions they perform? What are negative impacts for
human rights? Here are some examples that probably affect you too.
THEY KEEP INFORMATION AWAY FROM US
Increasingly, algorithms decide what gets attention, and what is ignored;
and even what gets published at all, and what is censored. This is true for
all kinds of search rankings, for example the way your social media news-
feed looks. In other words, algorithms perform a gate-keeping function.
EXAMPLE
Hiring algorithms decide if you are invited for an interview.
• Algorithms, rather than managers, are more and more taking part in
hiring (and firing) of employees. Deciding who gets a job and who does
not, is among the most powerful gate-keeping function in society.
• Research shows that human managers display many different biases in
hiring decisions, for example based on social class, race and gender.
Clearly, human hiring systems are far from perfect.
• Nevertheless, we may not simply assume that algorithmic hiring can
easily overcome human biases. Algorithms might work more accurate
in some areas, but can also create new, sometimes unintended, prob-
lems depending on how they are programmed and what input data is
used.
Ethical.
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
Ethical Dimensions of Artificial Intelligence (AI) by Rinshad ChoorapparaRinshad Choorappara
Explore the ethical landscape of Artificial Intelligence (AI) through our insightful PowerPoint presentation. Delve into crucial considerations that shape the responsible development and deployment of AI technologies. From privacy concerns and bias mitigation to transparency and accountability, this presentation covers the key ethical dimensions of AI. Gain a comprehensive understanding of the ethical challenges and solutions in the rapidly evolving world of artificial intelligence. Stay informed and empower your audience with the knowledge needed to navigate the ethical intricacies of AI responsibly.
Let us see the good and bad effects of the impact of Artificial Intelligence and the emerging technologies!
A Glimpse Into the Future of Data Science - What's Next for AI, Big Data & Ma...Pangea.ai
We are living in the era of "the fourth industrial revolution". How did we get here? Read this presentation to explore current application trends in Artificial Intelligence (AI,) The Internet of Things (IoT), Big Data, and Machine Learning (ML) technology. Also, to discover the future implications of big data in our lives.
Read the original article here: https://www.pangea.ai/data-science-resources/future-of-data-science/
Work with a data science expert at Pangea: https://www.pangea.ai/
Digital Forensics for Artificial Intelligence (AI ) Systems.pdfMahdi_Fahmideh
Digital Forensics for Artificial
Intelligence (AI ) Systems:
AI systems make decisions impacting our daily life Their actions might cause accidents, harm or, more generally, violate
regulations either intentionally or not and consequently might be considered suspects for various events. In this lecture we explore how digital forensics can be performed for AI based systems.
Richard van der Velde, Technical Support Lead for Cookiebot @CMP – “Artificia...Associazione Digital Days
The training of artificial intelligence systems is just the latest use of users’ personal data that companies collect online. But the information on how the data is used, what consent is needed or how it will be regulated is not always clear. Strong concerns have already been raised about data privacy and consent.
[DSC Adria 23] MARIJANA ŠAROLIĆ ROBIĆ Everyone is invited to AI enhanced pres...DataScienceConferenc1
Recent development in technology led to AI being in the spotlight of general public and media. Some of us are terrified, some of us surprised, some excited by such technology shifts. However, what is the actual status of AI regulatory framework in EU and what are the key concerns for AI startups and SMEs implementing AI in their products and services. Let us find out together.
What do you need to think about before bringing advanced technology into your community, library or organization? How do you introduce it to staff? Will they worry about being replaced or losing their jobs? And how do you get machines to operate at optimal efficiency? Machines need to learn to be effective, whether it’s Siri, Alexa, or Watson. And people have to adapt to the machines. Join us and learn more!
The “algorithm” is now an entity. It is a subject that society is talking a lot lately. In 2015, a photo app automatically tagged two Afro-American friends as gorillas. In 2016, a bot called Tay learned to be racist, Holocaust denier and that feminists “should all die and burn in hell”, in 12 hours. In less than 24 hours, it was shut down. There is unpredictability of machine learning algorithms when confronted with real people. How much bias machine learning algorithms can introduce? How much came from the data used to train the algorithms and how much came from the algorithm itself? How to create products based on machine learning avoiding gender, race, age or culture bias and others and avoiding doing harm to those groups?
Yates (Communication of ACM, June 2018) said that “any remedy for bias must start with awareness that bias exists.” Page (The Difference, 2007) proposed that identity diversity (our gender, race, religion, etc.) leads to cognitive diversity (the way we think and solve problems), mainly in tasks as prediction and problem-solving. A study made by McKinsey & Company in 2014 says that diversity fosters innovation and increase financial results. So, workplace diversity can help in different ways, including to detect and reduce bias in algorithms design and execution.
How much agile teams, from the beginning of software development chain, can help to minimize bias and reduce backslash to the end user? What is the role of agile when teams are built to work in a machine learning world? Agile Manifesto values individuals and interactions over processes and tools. Agile teams are built on that. Recently, Modern Agile also set two of four values based on people: make people awesome and make safety a prerequisite. Not as a causality, but, maybe, as a correlation, agile values are good evidence that we can have development environments that better support diversity. Once we have more diverse teams, we can expect better outputs (less biased) from machine learning algorithms.
[DSC Europe 23] Shahab Anbarjafari - Generative AI: Impact of Responsible AIDataScienceConferenc1
Today, we embark on a journey into the realm of Generative AI (Gen AI), a force of innovation and possibility. We'll not only unveil the vast opportunities it offers but also confront the ethical challenges it poses. In the spirit of responsible innovation, we'll then dive deep into Responsible AI, illuminating the path to its implementation in this era of Gen AI. Join us for a profound exploration of this technological frontier, where our commitment to responsibility and foresight shapes the future.
Spring Splash 3.4.2019: When AI Meets Ethics by Meeri Haataja Saidot
Meeri Haataja's keyote 'When AI Meets Ethics' at Keväthumaus 2019 / Spring Splash 2019 (organised by Väestörekisterikeskus / Population Register Centre).
Similar to AI in Law Enforcement - Applications and Implications of Machine Vision and Machine Learning (20)
Artificial Intelligence in Lumber Retail (Home Depot, Lowe’s, etc)Daniel Faggella
These slides were used for my presentation at the Northeastern Retail Lumber Association's annual Expo, 2020.
Building materials and home improvement is a market ripe for disruption. This presentation draws on much of our retail AI landscape research at Emerj:
https://emerj.com/?s=retail
The Challenges and Opportunities of AI for the Indian EconomyDaniel Faggella
A presentation I gave to the KV Management Institute in India, based on our research on the Indian AI ecosystem (https://emerj.com/ai-market-research/artificial-intelligence-in-india/).
AI in Mental Health and Wellbeing - Current Applications and TrendsDaniel Faggella
This is a presentation I gave at TransTech 2018 in the Bay Area - drawing from our research on mental health AI startups (https://emerj.com/ai-sector-overviews/diagnosing-and-treating-depression-with-ai-ml/).
The full video of this presentation is available online:
https://www.youtube.com/watch?v=CvrqoPpYF94
Video of the live presentation: https://www.youtube.com/watch?v=lUczD5jW96s
Event Title: 2019 New Shape Forum: Weapons Governance
Date: September 30, 2019 – October 1, 2019
Presentation Title: Weaponised Artifical Intelligence – Critical Dual-Use Applications and Trends
Team Member: Daniel Faggella, Emerj Founder and CEO
Host Organizations: Global Challenges Foundation, Geneva Disarmament Platform
AI, Automation, and Economic Impact - National Security ImplicationsDaniel Faggella
The slides from my presentation at the United Nations (UNICRI)/ Shanghai Institutes for International Studies event in Shanghai.
Event Title: Artificial Intelligence – Reshaping National Security
Event Host: United Nations (UNICRI), Shanghai Institutes for International Studies
Date: December 17 – 18, 2018
Team Member: Daniel Faggella, Emerj Founder and CEO
Presentation Title: AI, Automation, and Economic Impact – National Security Implications
Article on Emerj.com: https://emerj.com/emerj-team-updates/dan-presented-at-a-joint-unicri-shanghai-institutes-for-international-studies-event/
AI Innovation in the Pharmaceutical Sector - Accelerating ResearchDaniel Faggella
This is a deck I presented at the OECD's International Symposium on Machine Learning and Artificial Intelligence in Mexico City, October 2019.
The presentation draws from a number of AI executive interviews and in-depth research on AI innovation in pharma R&D, much of which is available on Emerj: https://emerj.com/?s=pharma
The Digital Workplace Powered by Intelligent SearchDaniel Faggella
This presentation covers the landscape of AI-enabled enterprise search.
The presentation was given at Sinequa's INFORM2019 events in both NYC and Paris.
Learn more about AI-enabled enterprise search on Emerj: https://emerj.com/?s=enterprise+search
Managing the Risks of AI - A Planning Guide for ExecutivesDaniel Faggella
I gave this presentation to the Mendoza School of Business at Notre Dame University on September 20th, 2018.
The presentation covers 5 major ethical themes of AI's application in business, and simple frameworks for helping executives assess those risks, and the potential costs that they might imply.
Artificial Intelligence in Pharma - Where it MattersDaniel Faggella
This slide deck is for a presentation for a room of French pharmaceutical executives at the Paris Region Enterprises offices in San Francisco. The presentation draws on some of our pharma coverage from TechEmergence over the last year, including:
1) https://www.techemergence.com/ai-in-pharma-and-biomedicine/
2) https://www.techemergence.com/machine-learning-in-pharma-medicine/
Artificial Intelligence in Real Estate - 3 Ways AI can Drive SavingsDaniel Faggella
This presentation covers:
1 - The state of AI in business and real estate
2 - Current machine learning applications in real estate
3 - Tips for real estate executives to avoid AI hype and pay attention to the use-cases that may actually have value for their firms
This presentation was originally given to a group of real estate executives at a Grupo4s "Future of Real Estate" event in San Francisco, in March of 2018.
How AI is (and isn't) Making it's Way into EnterpriseDaniel Faggella
This presentation with given to the Business Executives for National Security group in Atlanta, GA. The presentation is an overview of the state of AI in enterprise, and what business leaders should do when considering artificial intelligence solutions and evaluating vendors.
Artificial Intelligence in the Hospital SettingDaniel Faggella
This presentation was given at the AI Applications Summit (an event for healthcare and pharma professionals) in December 2017. The presentation itself covers to current traction of artificial intelligence in the hospital setting, as well as the unique challenges of applying AI in healthcare (including compliance, resistance from some doctors, the "black box" problem of machine learning, and more). Includes references to Machine Learning in Healthcare Executive Consensus: https://www.techemergence.com/machine-learning-in-healthcare-executive-consensus/
Artificial Intelligence in Restaurants and Food ServicesDaniel Faggella
This presentation was given at the Mid-America Restaurant Expo in 2018 (a fun event with over 4,000 execs and businesspeople in the food services sector). The presentation itself covers near-term and long-term applications, from smart kiosks to chatbot ordering services to robotics and more.
Artificial Intelligence Impact - What AI is (and isn't) Helping Startups Scal...Daniel Faggella
(This presentation was created as a short talk for a French Tech Hub event in San Francisco)
Contents:
- What investors see as "drivers of value" in terms of the use of AI in specific industries and business applications
- Examples of AI in industry (exploring business models and use cases)
- Where AI fits into (or doesn't) the business model of your startup, and how to determine whether or not AI has any short-term value in a specific business model
Dan Faggella - TEDx Slides 2015 - Artificial intelligence and ConsciousnessDaniel Faggella
URL of the original TEDx Talk: https://www.youtube.com/watch?v=PjiZbMhqqTM
Notes from my 2015 TEDx presentation, titled: "We Should Wake Up Before The Machines Do," on the topic of artificial intelligence and consciousness.
Speaker: Daniel Faggella
Location: Southern New Hampshire University
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/
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
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.
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
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.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
PHP Frameworks: I want to break free (IPC Berlin 2024)
AI in Law Enforcement - Applications and Implications of Machine Vision and Machine Learning
1. Machine Learning and
Machine Vision -
Cutting-Edge Trends and
Implications in Law
Enforcement
with Dan Faggella, CEO, Emerj.com
AI in Law Enforcement | Emerj.com | @danfaggella | 1
2. Presentation Outline
1. An introduction - our background and research at Emerj
2. Example applications of machine vision-related technologies with law
enforcement implications
i. Visual detection technologies
ii. Visual media creation technologies
3. Implications for law enforcement, security, and policy
AI in Law Enforcement | Emerj.com | @danfaggella | 2
3. Critical Applications of AI in Marketing - with Dan Faggella, CEO, Emerj.com
Daniel Faggella, CEO at Emerj (formerly TechEmergence)
Twitter, Facebook, LinkedIn:
@danfaggella
Emerj helps business and government leaders survive and
thrive in artificial intelligence disruption - with jargon free
research and industry-specific insights and case studies.
www.Emerj.com (TechEmergence.com)
AI in Law Enforcement | Emerj.com | @danfaggella | 3
4. Presentation Outline
● We’ve conducted over a thousand one-to-one interviews, in
addition to thousands of survey responses from AI
researchers and executives
● Most of our work revolves around helping business and
government leaders make sense of artificial intelligence, to
aide in their efforts for technology procurement and
strategic planning
● This presentation won’t simply be about surveillance, it’ll be
about upcoming trends with AI for video and visual media,
and what those technologies might mean for law
enforcement (a Silicon Valley perspective)
AI in Law Enforcement | Emerj.com | @danfaggella | 4
5. Detection Technologies - Facial Recognition
Possibilities:
● Recognize faces
● Determine emotions and
reactions (advertising,
security, etc)
● Recognize faces with hats,
sunglasses, beards, or in
different light or angles
Company: Kairos
AI in Law Enforcement | Emerj.com | @danfaggella | 5
6. Detection Technologies - Facial Validation
Possibilities:
● Detecting images, vs. real
people in video
● Detecting iPad or digital
screens, so that people who
are not present cannot get
clearance for friends via
Skype call
● (This kind of security measure
will at some point be
completely normal for all
facial recognition companies)
Company: TrueFace.ai
AI in Law Enforcement | Emerj.com | @danfaggella | 6
7. Detection Technologies - Movement and Occupancy
Possibilities:
● Determine the percent
occupancy in any given room
or floor, and changes over
time
● Determine movement
between rooms - and patterns
of movement throughout a
day or week
● Determine anomalies in
movement and occupancy
and receive notifications
Company: PointGrab
AI in Law Enforcement | Emerj.com | @danfaggella | 7
8. Detection Technologies - Behavior Detection
Possibilities:
● Detect shoplifting at the
checkout counter
● Detect someone taking their
medicine
● Detect suspicious walking or
loitering
● (These systems are very
narrow, and it should be noted
that they require massive
training to detect very basic,
discrete behaviors)
Company: StopLift
Company: AICure
AI in Law Enforcement | Emerj.com | @danfaggella | 8
9. Detection Technologies - Non-Visual Proxies for Behavior
Possibilities:
● Determining the movement or
behavior of individuals and
groups based on heat
detection
● This tech could be enhanced
to consider noise, vibration,
and other non-visual data -
adding better predictive ability
(using sensors outside a room
to determine how many
people are in it and what
they’re doing)
Company: MIT CSAIL
AI in Law Enforcement | Emerj.com | @danfaggella | 9
10. Detection Technologies - Skeletal Construction / Behavior
Detect
Possibilities:
● Determine the postures of
anyone in video footage
● Eventually predict behaviors
based on postures and
movement, such as
determining if two people are
likely to begin fighting, or if
someone is about to cross the
street
● This kind of data can be used
to create more realistic
simulationsCompany: Wrnch
AI in Law Enforcement | Emerj.com | @danfaggella | 10
11. Creation Technologies - Augmenting Human Movement
Possibilities:
● (See image to the left) A “skin”
can be put on the face of body
of a user (special effects,
gaming, etc)
● This might be used to video
games, and might also be
used to create more realistic
programmatically generated
human movement, making
indistinguishably “human”-like
movement and poses
Company: Wrnch
AI in Law Enforcement | Emerj.com | @danfaggella | 11
12. Creation Technologies - Future-Casting Videos
Possibilities:
● Determine which driving
behaviors are more likely to
lead to accidents
● Determine which loitering
activities are most likely to be
criminal, or which behaviors
of crowds are more likely to
lead to riots
● Hypothetically this tech could
fool viewers, showing them a
generated view of events, not
a real oneCompany: MIT CSAIL
AI in Law Enforcement | Emerj.com | @danfaggella | 12
13. Creation Technologies - Manipulate Body Movement in Video
Possibilities:
● Take images of a specific
person, and programmatically
generate images of that
person in other poses or doing
other activities
● Could be used to falsely
accuse people of actions, or
as immoral entertainment
Company: MIT CSAIL
AI in Law Enforcement | Emerj.com | @danfaggella | 13
14. Creation Technologies - Manipulate Face Movement in Video
Possibilities:
● Using images of a target
person’s face, that face can
be “mapped” onto a new face,
giving the creator control over
a face that looks just like the
target
● This technology is already
being used to put existing
people’s faces into sexual
content. Voice can also be
replicated, making the
technology more immersive.
Company: MIT CSAIL
AI in Law Enforcement | Emerj.com | @danfaggella | 14
15. Detection - Where We’re Headed
● Privacy is dying, and it doesn’t seem to be able to be revived. It is likely that people will accept knowing
that their movements and whereabouts will be tracked.
● Rather than pre-crime taking off any time soon, it’s likely that suspicious behavior will be flagged for
human analysts, or possibly appended to a person’s contact record within a security system.
● While societies and governments should determine laws and rules (where cameras can and cannot be
used, how long data can be stored, what kind of data can be stored), there are inherent challenges:
○ Rules about storing / using data are borderline impossible to uphold
○ Anything regulating governments isn’t going to be easy (who judges the judge)?
○ Major world governments will adopt this technology en masse and further set the stage for it to be
the norm
AI in Law Enforcement | Emerj.com | @danfaggella | 15
16. Detection - Where We’re Headed
“The virtue of a noble ruler is like
the wind; the virtue of his subjects
is like grass. If the wind sweeps
across the grass, the grass will
bend.”
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17. Creation - Where We’re Headed
● In the next 2-4 years any high school kid with free time will be able to create fake videos and voices of
any person living or dead.
● The paradigm we have to grapple with is this: What was once a representative artifact of a past reality
(videos, images, voice recordings), will not be so any longer. Fortunately this change will be gradual, but
we should already be imagining what the far end of it implies.
● If we’re smart, we’ll see this as no different than other cybersecurity: There are mutually adversarial
efforts, constantly aiming to get ahead of one another. “Creation” tech will be the same dynamic.
AI in Law Enforcement | Emerj.com | @danfaggella | 17
18. Creation - Where We’re Headed
“In the coming 20 years, essentially all
entertainment, learning, and
communication will be programmatically
generated, tailored to each individual.
There will be little reason to ‘go analog’
and practically living in our digital
systems will become more and more the
norm. This is a critical and unavoidable
step towards transhumanism - and we
should consider its consequences.”
AI in Law Enforcement | Emerj.com | @danfaggella | 18
19. Creation - Where We’re Headed
“In the coming 20 years, essentially all
entertainment, learning, and
communication will be programmatically
generated, tailored to each individual.
There will be little reason to ‘go analog’
and practically living in our digital
systems will become more and more the
norm. This is a critical and unavoidable
step towards transhumanism - and we
should consider its consequences.”
AI in Law Enforcement | Emerj.com | @danfaggella | 19
21. That’s All, Folks
Feel free to be in touch.
For questions about this presentation:
dan@emerj.com
Research or consulting inquiries:
sales@emerj.com
- Connections to relevant startups for partnerships
- Guidance on AI adoption strategy
- Go-to-market strategy for AI-related B2B products
- Market research reporting with in-depth quotes and
perspectives from industry-leading execs and
researchers
- Competitive intelligence on industries, sectors, or
large companies
AI in Law Enforcement | Emerj.com | @danfaggella | 21
22. Creation Technologies - Manipulate Face Movement in Video
● https://www.techemergence.com/facial-recognition-applications/
● https://www.techemergence.com/machine-vision-for-advertising-possibilities-social-online-media/
● https://www.techemergence.com/can-businesses-use-emotional-intelligence/
● https://www.techemergence.com/computer-vision-for-body-language/
● https://www.techemergence.com/ai-crime-prevention-5-current-applications/
● https://www.techemergence.com/ai-in-biometrics-current-business-applications/
● https://www.techemergence.com/category/expert-interviews/
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