This document discusses the use of artificial intelligence in financial investing and identifies some potential pitfalls. It notes that while AI can help analyze large datasets and identify new opportunities, financial time series data can be non-stationary, and AI models may overfit data and lack proper out-of-sample testing. Subject matter expertise is still key to integrating new data sources like news articles. The document provides examples of AI applications at J.P. Morgan Asset Management in areas like trading, earnings estimates, and thematic portfolios.
Ashok Srivastava at AI Frontiers : Using AI to Solve Complex Economic ProblemsAI Frontiers
Nearly half of all small businesses fail within their first 5 years. However, AI-driven solutions can help solve complex economic problems for consumers and small businesses like missed bill payments, insufficient capital, overinvestment in fixed assets, and more.
Ashok Srivastava discusses technology's role in solving economic problems and details how Intuit is using its unrivaled financial dataset to power prosperity around the world. Leveraging technology enablers like deep learning, natural language processing, and automated reasoning and combining with a delightful end-user experience and sophisticated UX, Intuit is using technology to help its users have more confidence in their financial management.
StartUp Health Insights - Digital Health Funding Rankings Q3 2014StartUp Health
If you thought last year was big for digital health funding, take a look at this year's numbers. According to StartUp Health's Q3 funding report, investors have already poured $5 billion into digital health companies. That means funding in the sector isn't just higher than last year's total, it's on track to double it. Our new report includes the top 10 largest deals, as well as the top 10 (or so) most active investors, subsectors and metro areas. And it’s free - so dive in!
The number of startups entering the healthcare AI space has increased in recent years, with over 50 companies raising their first equity rounds since January 2015. Deals to healthcare-focused AI startups went up from less than 20 in 2012 to nearly 70 in 2016.
According to our recently published Game Changers 2020 report, we look at unique tech categories like speed-of-light chips, mind-altering medicines, and quantum cryptography.
You can read the full report, which highlights the following:
• 200 unique investors backed this year's game changers
• 20 investors backed multiple game changers
• 23 game changer companies are based in the U.S
Artificial intelligence (AI) truly is a disruptive force across all industries. One such industry that has been transformed by AI technologies is healthcare. So, in this post, we discuss the many roles of AI in today’s healthcare industry.
Visit: https://www.ezdi.com/blog/the-role-of-ai-in-healthcare/
Outlook on Artificial Intelligence in the Enterprise 2016Narrative Science
Based on a survey of 235 senior business executives, Narrative Science analyzed respondents' data to identify top 4 trends of artificial intelligence in the enterprise.
Ashok Srivastava at AI Frontiers : Using AI to Solve Complex Economic ProblemsAI Frontiers
Nearly half of all small businesses fail within their first 5 years. However, AI-driven solutions can help solve complex economic problems for consumers and small businesses like missed bill payments, insufficient capital, overinvestment in fixed assets, and more.
Ashok Srivastava discusses technology's role in solving economic problems and details how Intuit is using its unrivaled financial dataset to power prosperity around the world. Leveraging technology enablers like deep learning, natural language processing, and automated reasoning and combining with a delightful end-user experience and sophisticated UX, Intuit is using technology to help its users have more confidence in their financial management.
StartUp Health Insights - Digital Health Funding Rankings Q3 2014StartUp Health
If you thought last year was big for digital health funding, take a look at this year's numbers. According to StartUp Health's Q3 funding report, investors have already poured $5 billion into digital health companies. That means funding in the sector isn't just higher than last year's total, it's on track to double it. Our new report includes the top 10 largest deals, as well as the top 10 (or so) most active investors, subsectors and metro areas. And it’s free - so dive in!
The number of startups entering the healthcare AI space has increased in recent years, with over 50 companies raising their first equity rounds since January 2015. Deals to healthcare-focused AI startups went up from less than 20 in 2012 to nearly 70 in 2016.
According to our recently published Game Changers 2020 report, we look at unique tech categories like speed-of-light chips, mind-altering medicines, and quantum cryptography.
You can read the full report, which highlights the following:
• 200 unique investors backed this year's game changers
• 20 investors backed multiple game changers
• 23 game changer companies are based in the U.S
Artificial intelligence (AI) truly is a disruptive force across all industries. One such industry that has been transformed by AI technologies is healthcare. So, in this post, we discuss the many roles of AI in today’s healthcare industry.
Visit: https://www.ezdi.com/blog/the-role-of-ai-in-healthcare/
Outlook on Artificial Intelligence in the Enterprise 2016Narrative Science
Based on a survey of 235 senior business executives, Narrative Science analyzed respondents' data to identify top 4 trends of artificial intelligence in the enterprise.
What do Californians think about Artificial Intelligence?accenture
We polled Californians about attitudes and use of AI technologies such as chatbots, robots, virtual assistants, intelligent machines, etc., such as Alexa or Google Home. Here's what they said. Learn more: https://accntu.re/2JjXUq5
Losing the Cyber Culture War in Healthcare: Accenture 2018 Healthcare Workfor...accenture
Accenture surveyed employees of provider and payer organizations in the United States and Canada to understand health employee attitudes and behaviors related to cybersecurity practices.
Infographic: Symantec Healthcare IT Security Risk Management StudyCheapSSLsecurity
Cybersecurity in Healthcare: While Cyberattacks and data breaches are rising across industries, healthcare is lagging behind in cybersecurity investment.
In early 2015, in a forward-thinking article on Healthcare IT News, HIMSS Analytics identified 18 technologies with positive growth potential that were set to take hold in the industry. This predictive analysis utilized data on technology adoption from 2010 to 2014. HIMSS Analytics has analyzed the changes in buying intent from 2014 through 2015 and is making the analysis available. HIMSS Analytics correctly predicted 4 of the top 5 technologies planned for deployment in 2016. With 2015 behind us and another year’s worth of data at our fingertips, we’ll highlight changes in technology purchase plans by healthcare delivery organizations for 2016.
In response to the onslaught of new AI solutions and products on the healthcare market intended to support physicians, how can organizations ensure the algorithms are clinically relevant? The process of operationalizing an algorithm in live clinical workflows requires an enterprise-wide roadmap and cross-departmental buy-in. Learn how you can assess an AI-related product for clinical relevance with a checklist developed in collaboration with a physician/solutions advisor, Dr. Alan Pitt of the Barrow Neurological Institute.
Healthcare organizations are awash with data. However, electronic health records (EHRs) and digital clinical systems in many healthcare organizations have been deployed without strategic data and IT infrastructure security planning. As a result, chief information security officers (CISOs) frequently have limited authority, sparse staffing and tight budgets. Data security spending in healthcare lags behind other top cybercrime targets such as financial services, according to new research by HIMSS Analytics on behalf of Symantec Corporation.
Asia Pacific Corporate Health Landscape | Galen Growth AsiaGalen Growth
Corporate Health is a key driver in the transformation of healthcare in Asia. HealthTech innovation offers employers and employees with a wealth of resources to enable this transformation. Galen Growth Asia showcases the corporate health solutions landscape.
Galen Growth Asia RESI 2017 PresentationGalen Growth
- Asia health systems are diverse in their needs and pain points
- Asia represents a significant opportunity for healthcare innovators
- HealthTech is an unprecedented opportunity for Asia to transform patient outcomes
- Asia’s HealthTech ecosystem is nascent but thriving
- Galen Growth Asia is the healthtech catalyst in Asia
2017 Consumer Survey: Healthcare Cybersecurity and Digital Trustaccenture
Accenture’s 2017 Consumer Survey on Healthcare Cybersecurity and Digital Trust identifies consumers’ experiences with healthcare data breaches and their attitudes toward healthcare data, digital trust, roles and responsibilities, data sharing and breaches.
Accenture's Applied Customer Engagement (ACE) is a proven approach to re-thinking and revitalizing contact center operations for the digital era. Read more.
Galen Growth Asia HealthTech Summit 2018 | Asia HealthTech Key TrendsGalen Growth
Opening keynote from the Galen Growth Asia HealthTech Summit
Overview of the key trends in the Asia Pac HealthTech ecosystem which has exceeded $5B of funding deployed in first 9 months of the year.
Asia HealthTech Investment Landscape 2017 Full Year reportGalen Growth
We are pleased to share the 2017 Full Year Asia HealthTech Investment Landscape report, a full update of our most popular report in 2017.
As we predicted last July, 2017 was a record-breaking year for HealthTech in Asia Pacific with funding exceeding the US$2.6B mark! Asia also saw a landmark of 230 deals executed in 2017, thus doubling 2016’s total.
Converting Cost to Growth -- Strategic Cost Reduction in Bankingaccenture
Banks want to reclaim profitability. Digital disruption, changing consumer behaviors, and new digital entrants are introducing diverse competition. Banks are faced with three
cost-related challenges. http://bit.ly/1sPHfm2
The Pulse of Pensions: What Members Really Think of Their Pension Plans and R...accenture
Accenture surveyed public and private employees to find out what they really think of their pension plans and retirement readiness. Four critical takeaways? Members value their pensions benefits as much as their healthcare benefits. People may not be as prepared for retirement as they think they are. The hunger for digital retirement services like coaching is intensifying. And opportunities abound for pensions agencies to engage members at all phases of the pensions lifecycle, balancing member needs with fiduciary responsibilities.
This week’s Top #AI, #Data & #Analytics posts include a #puppy!
1) Harvard Business Review's Andrew Likierman explains "what constitutes good #judgment". We're talking about #learning, #trust, #experience, #detachment, #options, and #delivery @ https://bit.ly/2PM0HOD
2) Dave Kellogg's got your back: read his #entrepreneurship #checklist and see if you pass his #leadership test @ https://bit.ly/2Oh3U7C
3) #ODTUG #rockstar Gary M. Adashek shares a very #personal story with #data, #ai, and #analytics. More @ https://bit.ly/2Sf5JTG
4) #Good #Product #Manager, #Bad #Product #Manager? Read Ben Horowitz's #Seminal #blog post and apply it! A great #companion to Dave's blog above. More @ https://bit.ly/2Oh3U7C
5) See you in London at the #Analytics #Summit in #London next week. Register @ https://bit.ly/2RXmh3U
Biopharma is facing compressive disruption that could impact traditional approaches. Find out how New Science can reshape the biopharma landscape and patient care. Visit http://www.accenture.com/newscience to learn more.
Data Is the New Strategic Asset in M&As: Is Ripping and Replacing EHRs Really...Health Catalyst
In this webinar, Tim and Dale, who worked together at Northwestern Medicine to establish an early-on and leading enterprise data warehouse solution for the hospital, physicians and medical school, will present their unique perspectives creating a thoughtful environment of comparison and contrast. This won’t be a typical corporate dozer—rather it will provide an opportunity for you to think deeply about the novel nature of your organization’s data. Historically, hospital expansion by building a larger footprint was the way to scale and capture market share. While those things still matter, attention has shifted to the expansion of the distribution of care through virtual and physical access points that embody a far more consumer friendly means to deliver care. It is in those entities that enriched data can be used to deliver care outreach that actually makes a difference for patients. That is where the new margins exist.
With 25 years of investment management experience I am excited to begin my own firm in order to grow and preserve the hard earned assets of my clients.
What do Californians think about Artificial Intelligence?accenture
We polled Californians about attitudes and use of AI technologies such as chatbots, robots, virtual assistants, intelligent machines, etc., such as Alexa or Google Home. Here's what they said. Learn more: https://accntu.re/2JjXUq5
Losing the Cyber Culture War in Healthcare: Accenture 2018 Healthcare Workfor...accenture
Accenture surveyed employees of provider and payer organizations in the United States and Canada to understand health employee attitudes and behaviors related to cybersecurity practices.
Infographic: Symantec Healthcare IT Security Risk Management StudyCheapSSLsecurity
Cybersecurity in Healthcare: While Cyberattacks and data breaches are rising across industries, healthcare is lagging behind in cybersecurity investment.
In early 2015, in a forward-thinking article on Healthcare IT News, HIMSS Analytics identified 18 technologies with positive growth potential that were set to take hold in the industry. This predictive analysis utilized data on technology adoption from 2010 to 2014. HIMSS Analytics has analyzed the changes in buying intent from 2014 through 2015 and is making the analysis available. HIMSS Analytics correctly predicted 4 of the top 5 technologies planned for deployment in 2016. With 2015 behind us and another year’s worth of data at our fingertips, we’ll highlight changes in technology purchase plans by healthcare delivery organizations for 2016.
In response to the onslaught of new AI solutions and products on the healthcare market intended to support physicians, how can organizations ensure the algorithms are clinically relevant? The process of operationalizing an algorithm in live clinical workflows requires an enterprise-wide roadmap and cross-departmental buy-in. Learn how you can assess an AI-related product for clinical relevance with a checklist developed in collaboration with a physician/solutions advisor, Dr. Alan Pitt of the Barrow Neurological Institute.
Healthcare organizations are awash with data. However, electronic health records (EHRs) and digital clinical systems in many healthcare organizations have been deployed without strategic data and IT infrastructure security planning. As a result, chief information security officers (CISOs) frequently have limited authority, sparse staffing and tight budgets. Data security spending in healthcare lags behind other top cybercrime targets such as financial services, according to new research by HIMSS Analytics on behalf of Symantec Corporation.
Asia Pacific Corporate Health Landscape | Galen Growth AsiaGalen Growth
Corporate Health is a key driver in the transformation of healthcare in Asia. HealthTech innovation offers employers and employees with a wealth of resources to enable this transformation. Galen Growth Asia showcases the corporate health solutions landscape.
Galen Growth Asia RESI 2017 PresentationGalen Growth
- Asia health systems are diverse in their needs and pain points
- Asia represents a significant opportunity for healthcare innovators
- HealthTech is an unprecedented opportunity for Asia to transform patient outcomes
- Asia’s HealthTech ecosystem is nascent but thriving
- Galen Growth Asia is the healthtech catalyst in Asia
2017 Consumer Survey: Healthcare Cybersecurity and Digital Trustaccenture
Accenture’s 2017 Consumer Survey on Healthcare Cybersecurity and Digital Trust identifies consumers’ experiences with healthcare data breaches and their attitudes toward healthcare data, digital trust, roles and responsibilities, data sharing and breaches.
Accenture's Applied Customer Engagement (ACE) is a proven approach to re-thinking and revitalizing contact center operations for the digital era. Read more.
Galen Growth Asia HealthTech Summit 2018 | Asia HealthTech Key TrendsGalen Growth
Opening keynote from the Galen Growth Asia HealthTech Summit
Overview of the key trends in the Asia Pac HealthTech ecosystem which has exceeded $5B of funding deployed in first 9 months of the year.
Asia HealthTech Investment Landscape 2017 Full Year reportGalen Growth
We are pleased to share the 2017 Full Year Asia HealthTech Investment Landscape report, a full update of our most popular report in 2017.
As we predicted last July, 2017 was a record-breaking year for HealthTech in Asia Pacific with funding exceeding the US$2.6B mark! Asia also saw a landmark of 230 deals executed in 2017, thus doubling 2016’s total.
Converting Cost to Growth -- Strategic Cost Reduction in Bankingaccenture
Banks want to reclaim profitability. Digital disruption, changing consumer behaviors, and new digital entrants are introducing diverse competition. Banks are faced with three
cost-related challenges. http://bit.ly/1sPHfm2
The Pulse of Pensions: What Members Really Think of Their Pension Plans and R...accenture
Accenture surveyed public and private employees to find out what they really think of their pension plans and retirement readiness. Four critical takeaways? Members value their pensions benefits as much as their healthcare benefits. People may not be as prepared for retirement as they think they are. The hunger for digital retirement services like coaching is intensifying. And opportunities abound for pensions agencies to engage members at all phases of the pensions lifecycle, balancing member needs with fiduciary responsibilities.
This week’s Top #AI, #Data & #Analytics posts include a #puppy!
1) Harvard Business Review's Andrew Likierman explains "what constitutes good #judgment". We're talking about #learning, #trust, #experience, #detachment, #options, and #delivery @ https://bit.ly/2PM0HOD
2) Dave Kellogg's got your back: read his #entrepreneurship #checklist and see if you pass his #leadership test @ https://bit.ly/2Oh3U7C
3) #ODTUG #rockstar Gary M. Adashek shares a very #personal story with #data, #ai, and #analytics. More @ https://bit.ly/2Sf5JTG
4) #Good #Product #Manager, #Bad #Product #Manager? Read Ben Horowitz's #Seminal #blog post and apply it! A great #companion to Dave's blog above. More @ https://bit.ly/2Oh3U7C
5) See you in London at the #Analytics #Summit in #London next week. Register @ https://bit.ly/2RXmh3U
Biopharma is facing compressive disruption that could impact traditional approaches. Find out how New Science can reshape the biopharma landscape and patient care. Visit http://www.accenture.com/newscience to learn more.
Data Is the New Strategic Asset in M&As: Is Ripping and Replacing EHRs Really...Health Catalyst
In this webinar, Tim and Dale, who worked together at Northwestern Medicine to establish an early-on and leading enterprise data warehouse solution for the hospital, physicians and medical school, will present their unique perspectives creating a thoughtful environment of comparison and contrast. This won’t be a typical corporate dozer—rather it will provide an opportunity for you to think deeply about the novel nature of your organization’s data. Historically, hospital expansion by building a larger footprint was the way to scale and capture market share. While those things still matter, attention has shifted to the expansion of the distribution of care through virtual and physical access points that embody a far more consumer friendly means to deliver care. It is in those entities that enriched data can be used to deliver care outreach that actually makes a difference for patients. That is where the new margins exist.
With 25 years of investment management experience I am excited to begin my own firm in order to grow and preserve the hard earned assets of my clients.
AI in Financial Asset Management Market – Notable Developments, Upcoming Tren...ShivamGaur62
Machine learning, computer vision, and speech recognition technologies are in demand and major number of acquisitions in the recent years were associated with these technologies, and the same technologies will dominate the investment patterns in the coming years
More insightful information | Request a sample copy @ https://www.trendsmarketresearch.com/report/sample/9723
The global management consulting services market was valued at around $751 billion in 2017. North America was the largest region in the management consulting services market
Ted Alexander of Magellan Asset Management discusses the investment implications of 8 predictions in artificial intelligence, with a focus on healthcare.
Ted delivered his presentation at 'The Future of Financial Advice', the Booster Financial Adviser Conference 2016 in Wellington, New Zealand on 4 November 2016.
Sample_Global Cashew Kernel Market research report.pptxkvsreerag096
Introduction to the Cashew Kernel Market
The cashew kernel market is an integral segment of the global nut industry, characterized by its robust growth and immense economic potential. Cashew kernels, derived from the cashew nut, not only serve as a popular snack but are also pivotal in culinary applications worldwide due to their rich nutritional profile, which includes healthy fats, proteins, and essential minerals. The market is driven by rising consumer awareness towards healthy snacking, dynamic food processing innovations, and increasing demand for plant-based proteins. Key factors propelling market expansion include advancements in agricultural practices, efficient supply chain mechanisms, and expanding production capabilities in major cashew-producing regions like Vietnam, India, and Ivory Coast. As the market continues to evolve, stakeholders are focusing on sustainability and quality enhancement to cater to the growing global demand.
CapitalX is a corporate strategy and advisory firm, with a specialized focus on innovation and technology.
We use market research and data science to gain perspective on market opportunities and business challenges. These insights allow our clients to de-risk key decisions and execute strategic initiatives with confidence.
Divya Jain at AI Frontiers : Video SummarizationAI Frontiers
As video content is becoming mainstream, video summarization is becoming a hot research topic in academia and industry. Video thumbnail generation and summarization has been worked on for years, but deep learning and reinforcement learning is changing the landscape and emerging as the winner for optimal frame selection. Recent advances in GANs are improving the quality, aesthetics and relevancy of the frames to represent the original videos. Come join this session to get an understanding of various challenges and emerging solutions around video summarization.
Training at AI Frontiers 2018 - LaiOffer Data Session: How Spark Speedup AI AI Frontiers
Topic: How to use big data to enhance AI
Outline:
1. Spark ETL
Spark SQL
Spark Streaming
2. Spark ML
Spark ML pipeline
Distributed model tuning
Spark ML model and data lineage management
3. Spark XGboost
XGboost introduction
XGboost with Spark
XGboost with GPU
4. Spark Deep Learning pipeline
Transfer learning
Build Spark ML pipeline with TensorFlow
Model selection on distributed TF model
Training at AI Frontiers 2018 - Ni Lao: Weakly Supervised Natural Language Un...AI Frontiers
In this tutorial I will introduce recent work in applying weak supervision and reinforcement learning to Questions Answering (QA) systems. Specifically we discuss the semantic parsing task for which natural language queries are converted to computation steps on knowledge graphs or data tables and produce the expected answers. State-of-the-art results can be achieved by novel memory structure for sequence models and improvements in reinforcement learning algorithms. Related code and experiment setup can be found at https://github.com/crazydonkey200/neural-symbolic-machines. Related paper: https://openreview.net/pdf?id=SyK00v5xx.
Training at AI Frontiers 2018 - Udacity: Enhancing NLP with Deep Neural NetworksAI Frontiers
Instructor: Mat Leonard
Outline
1. Text Processing
Using Python + NLTK
Cleaning
Normalization
Tokenization
Part-of-speech Tagging
Stemming and Lemmatization
2. Feature Extraction
Bag of Words
TF-IDF
Word Embeddings
Word2Vec
GloVe
3. Topic Modeling
Latent Variables
Beta and Dirichlet Distributions
Laten Dirichlet Allocation
4. NLP with Deep Learning
Neural Networks
Recurrent Neural Networks (RNNs)
Word Embeddings
Sentiment Analysis with RNNs
Training at AI Frontiers 2018 - Lukasz Kaiser: Sequence to Sequence Learning ...AI Frontiers
Sequence to sequence learning is a powerful way to train deep networks for machine translation, various NLP tasks, but also image generation and recently video and music generation. We will give a hands-on tutorial showing how to use the open-source Tensor2Tensor library to train state-of-the-art models for translation, image generation, and a task of your choice!
Percy Liang at AI Frontiers : Pushing the Limits of Machine LearningAI Frontiers
In recent years, machine learning has undoubtedly been hugely successful in driving progress in AI applications. However, as we will explore in this talk, even state-of-the-art systems have "blind spots" which make them generalize poorly out of domain and render them vulnerable to adversarial examples. We then suggest that more unsupervised learning settings can encourage the development of more robust systems. We show positive results on two tasks: (i) text style and attribute transfer, the task of converting a sentence with one attribute (e.g., sentiment) to one with another; and (ii) solving SAT instances (classical problems requiring logical reasoning) using end-to-end neural networks.
Ilya Sutskever at AI Frontiers : Progress towards the OpenAI missionAI Frontiers
I will present several advances in deep learning from OpenAI. First, I will present OpenAI Five, a neural network that learned to play on par with some of the strongest professional Dota 2 teams in the world in an 18-hero version of the game. Next, I will present Dactyl, a human-like robot hand trained entirely in simulation with reinforcement learning that has achieved unprecedented dexterity on a physical robot. I will also present our results on unsupervised learning in language, that show that pre-training and finetuning can achieve a significant improvement over state of the art. Finally, I will present an overview of the historical progress in the field.
Mario Munich at AI Frontiers : Consumer robotics: embedding affordable AI in ...AI Frontiers
The availability of affordable electronics components, powerful embedded microprocessors, and ubiquitous internet access and WiFi in the household has enabled a new generation of connected consumer robots. In 2015, iRobot launched the Roomba 980, introducing intelligent visual navigation to its successful line of vacuum cleaning robots. In 2018, iRobot launched the Roomba i7, equipped with the latest mapping and navigation technology that provides spatial information to the broader ecosystem of connected devices in the home. In this talk, I will describe the challenges and the potential of introducing consumer robots capable of developing spatial context by exploring the physical space of the home, and I will elaborate on the impact of AI in the future of robotics applications. Moreover, I will describe our vision of the Smart Home, an AI-powered home that maintains itself and magically just does the right thing in anticipation of occupant needs. This home will be built on an ecosystem of connected and coordinated robots, sensors, and devices that provides the occupants with a high quality of life by seamlessly responding to the needs of daily living – from comfort to convenience to security to efficiency.
Anima Anandkumar at AI Frontiers : Modern ML : Deep, distributed, Multi-dimen...AI Frontiers
As the data and models scale, it becomes necessary to have multiple processing units for both training and inference. SignSGD is a gradient compression algorithm that only transmits the sign of the stochastic gradients during distributed training. This algorithm uses 32 times less communication per iteration than distributed SGD. We show that signSGD obtains free lunch both in theory and practice: no loss in accuracy while yielding speedups. Pushing the current boundaries of deep learning also requires using multiple dimensions and modalities. These can be encoded into tensors, which are natural extensions of matrices. These functionalities are available in the Tensorly package with multiple backend interfaces for large-scale deep learning.
Sumit Gupta at AI Frontiers : AI for EnterpriseAI Frontiers
The use of AI for voice search and image recognition is talked about often. Enterprises, however, have different challenges and requirements. In this talk, we will focus on talking about use cases in the enterprise and challenges in building out AI solutions. We will talk about how an Auto-machine learning software for videos and images called PowerAI Vision enables quick AI model training & deployment for various enterprise use cases.
Yuandong Tian at AI Frontiers : Planning in Reinforcement LearningAI Frontiers
Deep Reinforcement Learning (DRL) has made strong progress in many tasks, such as board games, robotics, navigation, neural architecture search, etc. I will present our recent open-sourced DRL frameworks to facilitate game research and development. Our framework is scalable so we can can reproduce AlphaGoZero and AlphaZero using 2000 GPUs, achieving super-human performance of Go AI that beats 4 top-30 professional players. We also show usability of our platform by training agents in real-time strategy games, and show interesting behaviors with a small amount of resource.
Alex Ermolaev at AI Frontiers : Major Applications of AI in HealthcareAI Frontiers
The latest AI advances have the potential to massively improve our health and well being. However, most of the work is yet to be done. In this talk, we will explore the most important opportunities for AI in healthcare. For example, we will explore how AI can diagnose major life-threatening conditions even before those conditions emerge. We will talk about AI ability to recommend dramatically more effective and less harmful treatment plans based on AI understanding of patient's medical history and current conditions. Finally, we will talk about AI role in making our healthcare system effective and affordable for everyone.
Long Lin at AI Frontiers : AI in GamingAI Frontiers
Games have been leveraging AI since the 1950s, when people built a rules-based AI engine that played tic-tac-toe. With technological advances over the years, AI has become increasingly popular and widely used in the gaming industry. The typical characteristics of games and game development makes them an ideal playground for practicing and implementing AI techniques, especially deep learning and reinforcement learning. Most games are well scoped; it is relatively easy to generate and use the data; and states/actions/rewards are relatively clear. In this talk, I will show a couple of use cases where ML/AI helps in-game development and enhances player experience. Examples include AI agents playing game and services that provide personalized experience to players.
Melissa Goldman at AI Frontiers : AI & FinanceAI Frontiers
AI in finance is having wide-ranging impact and solving some of the most critical societal problems. The talk gives overview of the opportunities of applying AI in finance with specific examples and highlights some of the unique challenges financial services firms face in deploying AI at scale.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
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.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
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/
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
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.
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.
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.
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.
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
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.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
Yazann Romahi at AI Frontiers : The Pitfalls of Using AI in Financial Investing
1. FOR EDUCATIONAL PURPOSES ONLY | NOT INTENDED TO BE USED AS ADVERTISING OR SALES LITERATURE
The Pitfalls of Using AI in Financial Investing
November 2018
Yazann Romahi, PhD
2. 1 | FOR EDUCATIONAL PURPOSES ONLY | NOT INTENDED TO BE USED AS ADVERTISING OR SALES LITERATURE
Areas of AI Applications in Finance
Trading
Fraud Detection
Credit LendingImage Recognition
Robo-Advisors
For illustrative purposes only
$
Asset Management
3. 2 | FOR EDUCATIONAL PURPOSES ONLY | NOT INTENDED TO BE USED AS ADVERTISING OR SALES LITERATURE
The March of Quantitative Methods in Financial Investing
Markowitz
Modern
Portfolio
Theory
Louis
Bachelier’s
Thesis
published
Rapid
Advances
in Portfolio
Theory
1980s
First CTA
funds
1990s
Growth of
Quant Equity
Long Short
Hedge Funds
2000s
Increasing Use
of AI in Trading
Strategies
2009-
Growth of
Alternative
Beta
Growth of Quantitative Investing Strategies
New sources
Of Data
Rapidly Being
Created
1900 1952 1960s 1980 2010 2014
𝒌=𝟎
𝒏
𝒏
𝒌
𝒙 𝒌
For illustrative purposes only
4. 3 | FOR EDUCATIONAL PURPOSES ONLY | NOT INTENDED TO BE USED AS ADVERTISING OR SALES LITERATURE
Understanding Approaches to Building Investment Strategies
$370 Bn
$973 Bn
Hedge Fund and CTA AUM
Trend Following
Trend-following hedge funds (also known as
CTAs) are exclusively quantitatively based
Typically employ momentum and reversion
signals at different time frequencies
AI is used, but traditional methods are more
prevalent
Fundamental
Equity
Quantitative, equity long/short approaches
began to gain prominence in the early 90s.
Fundamental signals (e.g. valuation, quality) are
an important component of these processes
New sources of data are creating new
opportunities for alpha generation
Source: BarclayHedge as of 2Q 2018. For illustrative purposes only
5. 4 | FOR EDUCATIONAL PURPOSES ONLY | NOT INTENDED TO BE USED AS ADVERTISING OR SALES LITERATURE
An Expansion of the Quant’s Toolkit
NEW TECHNIQUES
TRADITIONAL
DATA
NEWDATA
TRADITIONAL TECHNIQUES
Building a neural
network (machine
learning) on textual data
Building random
forests for fraud
detection
Time series extracted
from satellite data of
industrial sites in China
Regression on
Earnings Yield;
Time series analysis
using econometrics
For illustrative purposes only
6. 5 | FOR EDUCATIONAL PURPOSES ONLY | NOT INTENDED TO BE USED AS ADVERTISING OR SALES LITERATURE
New Data Sources Abound
of the data available today has been
collected in the last two years90%
Alternative Data
Individuals Business Processes Sensors
Social Media Transaction Data Satellites
News and Reviews Corporate Data Geo-location
Web Searches,
Personal Data
Government Agencies Data Other Sensors
For illustrative purposes only
7. 6 | FOR EDUCATIONAL PURPOSES ONLY | NOT INTENDED TO BE USED AS ADVERTISING OR SALES LITERATURE
Pitfalls of Time Series Analysis in Trading Strategies
New sources of data have cross-sectional depth, but lack time-series depth1
Probability of random noise ~30% Not statistically significant (p=0.12)
For illustrative purposes only
Monthly Trading Model (55% Success Rate) Weekly Trading Model (55% Success Rate)
8. 7 | FOR EDUCATIONAL PURPOSES ONLY | NOT INTENDED TO BE USED AS ADVERTISING OR SALES LITERATURE
Pitfalls of Time Series Analysis in Trading Strategies
Financial time-series are non-stationary2
Stationary Data
-15%
-10%
-5%
0%
5%
10%
15%
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
S&P 500
(Daily Returns, 2008)
-1,000
-800
-600
-400
-200
0
200
400
600
1995
1997
1999
2001
2003
2005
2007
2009
2011
2013
2015
Total Nonfarm Payrolls
(Change, Thousands of Persons)
Source: Bloomberg, as of November 2018. For illustrative purposes only
9. 8 | FOR EDUCATIONAL PURPOSES ONLY | NOT INTENDED TO BE USED AS ADVERTISING OR SALES LITERATURE
Jan-05 Jan-06 Jan-07 Jan-08 Jan-09
S&P500Level
Example Financial Time Series
Pitfalls of Time Series Analysis in Trading Strategies
Everything should be made as simple as possible, but not simpler3
Traditional Methods
• Require modeler to determine functional form
• Econometrics methods are often perfectly adequate
Artificial Intelligence
• Significantly higher degrees of freedom allows
for flexibility, but is often less statistically robust
due to inability to properly test out of sample
Source: Bloomberg, as of November 2018. For illustrative purposes only
0
20
40
60
80
100
120
ModelError
Model Complexity
Model Complexity vs. Error
Total Model Error
In-sample Error
Best Model
10. 9 | FOR EDUCATIONAL PURPOSES ONLY | NOT INTENDED TO BE USED AS ADVERTISING OR SALES LITERATURE
100
120
140
160
180
200
220
240
Jan-17 Feb-17 Mar-17 Apr-17 May-17 Jun-17 Jul-17 Aug-17 Sep-17 Oct-17
Subject Matter Expertise is Key: An Example
Corporate activity is a source of binary idiosyncratic risk
Stock price movements following confirmation
or denial of a merger agreement
News articles
are a source of
useful
information, if
appropriately
handled
For illustrative purposes only
11. 10 | FOR EDUCATIONAL PURPOSES ONLY | NOT INTENDED TO BE USED AS ADVERTISING OR SALES LITERATURE
2% RELEVANT
NEWSMILLIONS OF
ARTICLES
PER YEAR1
Investment Process Application of AI: NewsFilter
1 For illustrative purposes only
2 Awarded based on use of machine-learning based News-Filter
Most Cutting-Edge IT Initiative
Best use of Emerging or Innovative Technology
AWARDS2
AI can provide a solution to managing large data sets more effectively allowing it to be systematically incorporated
in factor portfolios
12. 11 | FOR EDUCATIONAL PURPOSES ONLY | NOT INTENDED TO BE USED AS ADVERTISING OR SALES LITERATURE
Investment Process Application of AI: NewsFilter
Machine learning algorithm can improve performance by reducing idiosyncratic risk
Source: J.P. Morgan Asset Management, Bloomberg
15
20
25
30
35
1-Sep 15-Sep 29-Sep 13-Oct 27-Oct 10-Nov 24-Nov 8-Dec 22-Dec
General Cable Corporation
~75% increase in
price post rumor
Identification of M&A rumor led to short constraint on General Cable in
equity factor models, preventing loss of 25bps at portfolio level
13. 12 | FOR EDUCATIONAL PURPOSES ONLY | NOT INTENDED TO BE USED AS ADVERTISING OR SALES LITERATURE
Areas of AI Applications at J.P. Morgan Asset Management
Trading
Using reinforcement learning in
enhanced trading
Earnings Revisions
Analysis of company earnings reports
and Q&A yielding better estimates of
earnings
Image Recognition
Analysis of industrial site satellite
imagery in China as a leading
indicator of industrial production
Thematic Portfolios
Using NLP of news, social media and
financial reports, to create on demand
thematic portfolio ideas
$
14. 13 | FOR EDUCATIONAL PURPOSES ONLY | NOT INTENDED TO BE USED AS ADVERTISING OR SALES LITERATURE
Disclosures
The views contained herein are not to be taken as advice or a recommendation to buy or sell any investment in any jurisdiction, nor is it a commitment from J.P. Morgan Asset Management or any of
its subsidiaries to participate in any of the transactions mentioned herein. Any forecasts, figures, opinions or investment techniques and strategies set out are for information purposes only, based on
certain assumptions and current market conditions and are subject to change without prior notice. All information presented herein is considered to be accurate at the time of production. This material
does not contain sufficient information to support an investment decision and it should not be relied upon by you in evaluating the merits of investing in any securities or products. In addition, users
should make an independent assessment of the legal, regulatory, tax, credit and accounting implications and determine, together with their own professional advisers, if any investment mentioned
herein is believed to be suitable to their personal goals. Investors should ensure that they obtain all available relevant information before making any investment. It should be noted that investment
involves risks, the value of investments and the income from them may fluctuate in accordance with market conditions and taxation agreements and investors may not get back the full amount
invested. Both past performance and yields are not reliable indicators of current and future results.
J.P. Morgan Asset Management is the brand for the asset management business of JPMorgan Chase & Co. and its affiliates worldwide.
To the extent permitted by applicable law, we may record telephone calls and monitor electronic communications to comply with our legal and regulatory obligations and internal policies. Personal
data will be collected, stored and processed by J.P. Morgan Asset Management in accordance with our Company’s Privacy Policy. For further information regarding our regional privacy policies
please refer to the EMEA Privacy Policy; for locational Asia Pacific privacy policies, please click on the respective links: Hong Kong Privacy Policy, Australia Privacy Policy, Taiwan Privacy Policy,
Japan Privacy Policy and Singapore Privacy Policy.
This communication is issued by the following entities: in the United Kingdom by JPMorgan Asset Management (UK) Limited, which is authorized and regulated by the Financial Conduct Authority; in
other European jurisdictions by JPMorgan Asset Management (Europe) S.à r.l.; in Hong Kong by JF Asset Management Limited, or JPMorgan Funds (Asia) Limited, or JPMorgan Asset Management
Real Assets (Asia) Limited; in Singapore by JPMorgan Asset Management (Singapore) Limited (Co. Reg. No. 197601586K), or JPMorgan Asset Management Real Assets (Singapore) Pte Ltd (Co.
Reg. No. 201120355E); in Taiwan by JPMorgan Asset Management (Taiwan) Limited; in Japan by JPMorgan Asset Management (Japan) Limited which is a member of the Investment Trusts
Association, Japan, the Japan Investment Advisers Association, Type II Financial Instruments Firms Association and the Japan Securities Dealers Association and is regulated by the Financial
Services Agency (registration number “Kanto Local Finance Bureau (Financial Instruments Firm) No. 330”); in Australia to wholesale clients only as defined in section 761A and 761G of the
Corporations Act 2001 (Cth) by JPMorgan Asset Management (Australia) Limited (ABN 55143832080) (AFSL 376919); in Brazil by Banco J.P. Morgan S.A.; in Canada for institutional clients’ use
only by JPMorgan Asset Management (Canada) Inc., and in the United States by JPMorgan Distribution Services Inc. and J.P. Morgan Institutional Investments, Inc., both members of FINRA; and
J.P. Morgan Investment Management Inc. In APAC, distribution is for Hong Kong, Taiwan, Japan and Singapore. For all other countries in APAC, to intended recipients only.
Copyright 2018 JPMorgan Chase & Co. All rights reserved.
Editor's Notes
Maybe put right after timeline?
Going to walk through main areas of quant use in HF land
Two main areas – find better icons? Ai – Smarter trend following, but traditional is adequate and upside for algos is limited
Fundamental – more domain knowledge necessary – equity long short 1/3 of AUM, fundamental signals at the core of the model – value – some version of cheapness. Analyst estimate earnings or trailing. But with new data, there are ways to look at earnings with new data sources – credit card data – Netflix, etc
Interesting applications
When AI researchers come to finance, need to rethink
AI are black box models
When you have functional forms, assumptions are cleaner and relationships are clear
Not enough data to adapt to non-stationary
Need to remove clicks
Use the above template as a starting point for your disclosure page(s). Product-specific risk disclosure may be obtained on fact sheets, or product web pages.
Regarding footnotes: It is NOT permissible to run footnotes together in large blocks of print. If disclosure is in a footnote, separate or number the footnotes so they can be read. Therefore, footnotes must be at least 8-pt font, and in the same font-type used in the majority of the presentation. Using smaller-type fonts, such as Calibri or Arial Narrow, is not permitted.