Antitrust Policy
All project meetings are subject to the Linux Foundation Antitrust Policy.
The following topics must not be discussed:
▪Price-sensitive information
▪Actual or projected changes in production, output, capacity or inventories
▪Matters relating to bids, prospective bids, or bid policies
▪Matters relating to actual or potential individual suppliers that might influence the business
conduct of firms toward such suppliers
▪Matters relating to actual or potential customers that might have the effect of influencing the
business conduct of firms toward such customers
▪Current or projected costs of procurement, development or manufacture of any product
▪Market shares for any product or for all products
▪Confidential or otherwise sensitive business plans or strategy
If you have questions, please contact legal@finos.org
Meeting Notice
▪FINOS Project leads are responsible for observing the FINOS guidelines for running project
meetings. Project maintainers can find additional resources in the FINOS Maintainers
Cheatsheet.
▪All participants in FINOS project meetings are subject to the LF Antitrust Policy, the FINOS
Community Code of Conduct and all other FINOS policies.
▪FINOS meetings involve participation by industry competitors, and it is the intention of
FINOS and the Linux Foundation to conduct all of its activities in accordance with applicable
antitrust and competition laws. It is therefore extremely important that attendees adhere to
meeting agendas, and be aware of, and not participate in, any activities that are prohibited
under applicable US state, federal or foreign antitrust and competition laws. Please contact
legal@finos.org with any questions.
▪FINOS project meetings may be recorded for use solely by the FINOS team for
administration purposes. In very limited instances, and with explicit approval, recordings
may be made more widely available.
Emerging Technology
Special Interest Group
July 13th, 2023
Please add your attendance to:
https://github.com/finos/zenith/issues/41
Agenda
▪Announcements
▪POC Program
▪Deep Dives
▪Any Other Admin
▪Calls to Arms
▪Any Other Business
▪Thanks & Close-Out
Announcements
Announcements
Blogs & Znglists
New Blogs
▪Meta releasing ‘Game
Super Resolution’
technology for Quest
▪Zoom joins the tools in
Meta Horizon Workrooms
Znglist Updates
▪Zenith Showcase is now
live with 2 new videos
▪Zenith Program Overview
▪Brain Trust Overview
Announcements
Upcoming Events
Thursday, July 13 (Today!)
▪11am EST / 4pm BST
FDC3: Web Browsers - Calendar Invite
▪11pm EST / 4pm BST
Morphir - Calendar Invite
https://www.finos.org/news-and-events
▪August 2 –
Open Source London
Our August meetup in partnership with Scott Logic will be
hosted at NatWest's Bishopsgate offices in London and will
focus AI and open source, and the opportunities and challenges
of harnessing AI's business potential. Register here.
▪November 1 –
Open Source in Finance Forum - NYC
Registration is open for our annual Open Source in Finance
Forum in the Marriott Marquis Hotel in Times Square NYC. Find
information on how to sponsor or register here.
Announcements
New Teammates
Announcements
New Teammates
Carly
Richmond
Developer
Engagement
Move List
Super Art
Developer
Advocacy
Front End Engineer
Blogger
Public Speaker
Announcements
New Teammates
Leo
Mordasini
POC Program
Co-ordinator
Move List
Super Art
Tinkering
Innovation Program
Expert
Cloud & Data Focus
Latin America
Engagement
Polina
Levyant
Developer
Announcements
New Teammates
Move List
Super Art
Economics
Software Engineer
Decentralised
Finance Industry
Emerging Tech
Enthusiasm
Deep Dive
Primers
Initial Technologies
Artificial Intelligence 4D Printing
Blockchain & DLT Biotechnology
IOT, 5G & 6G Regulatory Technology
Robotics & RPA Next-Gen Materials
Spatial Computing Natural Language
Processing
Quantum Technology Advanced Data
Processing
Neural Interfacing Cloud Computing
Space Technology Crypto Agility
First Primer Launch
▪Artificial Intelligence
Next Primers
▪Quantum Tech
▪Spatial Computing
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
▪Learning
▪Perception
▪Reasoning
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Weak AI
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Weak AI
▪Collects Information
▪Analyses preferences
▪Improves over time
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Strong AI
▪Contextualise
▪Learn new skills
▪Apply knowledge
to plan ahead
▪Adapt as changes
occur
Artificial
General
Intelligence
(AGI)
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Strong AI
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Strong AI
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Superintelligence in AI
▪Completely Self Aware
▪Surpasses human
intelligence in every way
▪Still complete science
fiction
▪Data is from the
24th Century
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Imitation Game/Turing Test
proposed by Alan Turing (1950)
1. Take a neutral evaluator
2. Observe a conversation
between two parties
3. Decide which one is the
machine
4. Test to see if machines can
“think”
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Arthur Samuel develops a
Checkers playing algorithm (1952)
Alpha-Beta Pruning: Search algorithm that seeks to decrease
the number of nodes evaluated by the minimax algorithm in
its search tree. Can be used well in adversarial games!
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
First use of the term
“Artificial Intelligence” and the
Logic Theorist program (1955)
“The science and engineering of making
intelligent machines”
John McCarthy
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
First use of the term
“Artificial Intelligence” and the
Logic Theorist program (1955)
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Frank Rosenblatt creates Perceptron
Neural Networks Innovation (1957)
X
Y
Z
Net
input
function
Weighted Inputs Output
Binary classifier algorithm which can tell if
an input belongs to a specific class
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Developments through
the 20th Century
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Developments of the 60s
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Developments of the 60s
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Developments of the 70s
Funding cuts caused by lack of progress
and over-ambitious statements
Raj Reddy publishes “Speech Recognition
by Machine: A Review” creating a brilliant
primer on early Natural Language
Processing (NLP)
The Stanford Cart crosses a chair-filled
room becoming an Autonomous Vehicle
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Developments of the 80s
WABOT-2 Mercedes-Benz
self-driving car
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Developments of the 90s
Long short-term memory (LSTM)
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Developments of the 90s
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Developments through
the 21st Century
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Image courtesy of CB Insights
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
AI Development Tools
AI Chipsets Data
Annotation
Synthetic
Data
Data
De-Identification
Data Quality
& Observability
Version Control
& Experiment
Tracking
Model Validation
& Monitoring
Machine Learning
Platforms
Machine Learning
Deployment
Resource
Optimisation
Computer
Vision
Natural Language
Processing
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
For the Final Primer
▪Showcasing of where the commercialisation
of adoption lies for each technology
▪Considerations for ethics and fair use by
members of the open source community
▪Where we perceive security vulnerabilities
▪What comes next once blockers are resolved?
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Technology Readiness
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
AI Chipsets
▪Enable high performance computer for AI Applications
▪Used in deep learning & neural networks
▪Extremely specialised & expensive to make
Data Annotation
▪Labelling & tagging datasets to train AI models
▪Used in supervised machine learning
▪Scaling automation is complex and costly
TRL 8
TRL 7
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Synthetic Data
▪Creating artificial data that mimics real world data
▪Mirrors existing patterns and distributions
▪Helps to address privacy concerns
Data De-Identification
▪Anonymises and pseudonymisation protect sensitive
information
▪Crucial for addressing data privacy regulations
TRL 6
TRL 7
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Data Quality & Observability
▪Ensures that AI data is accurate, consistent and
trustworthy
▪Relies on Anomaly detection, governance frameworks &
data profiles
Version Control & Experiment Tracking
▪Ensures AI reproducibility and managing projects
▪Involves tracking code versions, parameters and results
TRL 6
TRL 7
TRL 8
TRL 8
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Model Validation & Monitoring
▪Monitoring & assessing the performance and behaviour of
AI Models in real-world scenarios
▪Detects model drift, bias and ensures ongoing accuracy
Machine Learning Platforms
▪Infrastructure & tools to develop, train and deploy
AI models
▪Focus on integrated environments for data preparation,
model building and deployment pipelines
TRL 6
TRL 7
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Machine Learning Deployment
▪Deploying trained models into production systems to
make predictions / generate insights
▪Requires managed model versions, scalability and real-time
interference
Resource Optimisation
▪Focuses on the efficient utilisation of CPU, GPU or cloud
infrastructure
▪Seeks to improve performance while reducing operational
costs
TRL 9
TRL 9
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Computer Vision
▪Enable AI systems to analyse and understand visual data
(e.g., images and videos)
▪Can cover tasks like object recognition, image
classification & scene understanding
Natural Language Processing
▪Involves interaction between computers and human
language
▪Covers tasks like language understanding, sentiment
analysis and language generation
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
AI Chipsets
Blockers:
❑Complexity and cost of development
❑Optimisation for specific algorithms
▪Convolutional Neural Networks (CNNs)
▪Recurrent Neural Networks (RNNs)
▪Transformer Networks
▪Deep Reinforcement Learning
▪Generative Adversarial Networks (GANs)
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Data Annotation
Blockers:
❑Availability of high-quality annotated datasets
❑Standards of consistency for automation
❑Blueprints for automated annotation
Synthetic Data
Blockers:
❑Identification of Financial Services use cases
❑Generating accurate & diverse synthetic data
❑Validation of effectiveness
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Data De-Identification
Blockers:
❑Standards for obfuscation to satisfy evolving privacy
regulations
Data Quality & Observability
Blockers:
❑Identification of common data inconsistencies
❑Establishing comprehensive data quality processes for
automation or process improvement
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Version Control & Experiment Tracking
Blockers:
❑Integration with common platforms
▪Identification of expected platforms for
interoperability
❑Understanding versioning control governance at
different levels of enterprise
Model Validation & Monitoring
Blockers:
❑Automation of validation & monitoring
❑Mathematical models for model drift & bias
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Machine Learning Platforms
Blockers:
❑Creating common use frameworks for rapid
testing/training deployment
❑Addressing scalability for adaptations of micro-
systems
Machine Learning Deployment
Blockers:
❑Defining common deployment pipelines
❑Creating plug-ins for specific purposes from common
framework such as Miniature model training
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Resource Optimisation
Blockers:
❑Creation of common libraries for industry standard
hardware
❑Creation of guiding principles for ASICs and their
designers
Computer Vision
Blockers:
❑Defining core libraries for accuracy and robustness
❑Addressing example real-world scenarios to further
develop core libraries
Artificial Intelligence
Introduction to AI
History of AI
Current AI ETAC
Technology Readiness
Current Blockers
Natural Language Processing
Blockers:
❑Create standard language models for common global
languages
❑Develop interoperability into special purpose use-
cases and domains
❑Scale for running on diverse systems
▪Local device configurations
▪Windows
▪MacOS
▪Linux
▪Entry tier common cloud provider offerings
Any Other Admin
Please add your
attendance to this call!
https://github.com/finos/zenith/issues/41
Join our mailing list
for future updates
(You don’t need to put anything in the message)
Next Deep Dive:
Tech Passporting
for enterprise
and innovation
Call to Arms
Potential POCs Get in touch with us
through the mail group
Any Other Business?
Thank you
Join the discussion at
zenith.finos.org
zenith+subscribe@lists.finos.org
