Big Data & AI Toronto 2021
| title | author | length |
|---|---|---|
| Leveraging AI to enhance human creativity | Domhnaill Hernon | 21m |
Argues machines lack bodies, lived experience and therefore cannot match human intelligence, while machine learning can excel at speed and scale but only in… | ||
| How Air Miles drives end-to-end marketing solutions | Maxime Guy | 28m |
AIR MILES builds PRECISION™ as an ensemble AI recommender (logistic regression, market-basket, collaborative filtering and deep learning) that scales to… | ||
| Want to adopt AI in your business: Good luck! | Olivier Blais | 31m |
Claim: 15% of AI projects are used and most failure comes from scope and ops not algorithms. Big examples: UPS saves $200M/year with delivery bundling… | ||
| Enabling your business for AI | Steve Astorino | 25m |
IBM pitches Cloud Pak for Data as a hybrid multicloud platform built on Red Hat OpenShift that virtualizes data so it stays in place while presenting a unified… | ||
| Fireside chat: Digital IQ and marketing big data | Adam Rodricks, Carolina Bessega | 35m |
Social listening surfaces that 2 million posts around Hurricane Sandy reveal not what is said but where silence signals outages and need, and volume often… | ||
| ML feature store a cornerstone in modern data architecture for AI/ML | Taimur Rashid | 19m |
Argues that Redis and Redis Enterprise serve as the low‑latency backbone for feature stores, describing four concrete manifestations: online feature store for… | ||
| Getting business value from AI: Everyday AI, extraordinary people | Claire Gubian | 20m |
Argues that systematizing AI and upskilling business people creates measurable value: GE Aviation trains non‑data staff through an academics program producing… | ||
| ISO's aim for standardization in machine learning | Maria Dimitrova | 29m |
Claims that internationally recognized ISO management system standards can make machine learning adoption trustworthy and auditable, offering concrete guidance… | ||
| Scaling analytics and AI: It's mostly about culture | Jaime Tatis | 22m |
TELUS is consolidating legacy warehouses and modern lakes into a single enterprise data hub on cloud infrastructure that delivers 10x scale and operationalizes… | ||
| Save your ML model from degradation with data logging | Danny Leybzon | 27m |
WhyLogs is an open-source data-logging library that profiles 100% of inputs to catch drift and prevent model degradation, trading samples for statistical… | ||
| Storytelling with data | Craig Bloor | 24m |
Argues that storytelling turns analysis into action and gives three concrete tools: the pyramid principle (top takeaway supported by arguments)… | ||
| Do's and don'ts of big data analytics | Richard Boire | 38m |
Ten practical rules and concrete checks: prioritize whether analytics can help (a business with 50% defection probably needs pricing or competitive fixes, not… | ||
| Panel: Inspiring women in tech and championing data leadership | Erin McGowan, Sonia Carreno, Kishawna Peck, Sasha Fay, Irina Delidjakova | 38m |
Panelists outline concrete programs and measurable goals: a Toronto Womxn in Data Science campaign to empower a million women and an inclusive data fellowship… | ||
| When AI goes wrong and how to fix it fast | Dan Jeffries | 29m |
Algorithms fail in visible and subtle ways — Tay went toxic, an autonomous Uber misclassified a pedestrian, Google Photos labeled people as gorillas — so build… | ||
| AIaaS with Dell AI ready infrastructure | Yochay Ettun | 21m |
cnvrg.io presents a Kubernetes-native machine learning platform that unifies on-prem Dell APEX gear, DGX-1 nodes and AWS/GCP under a single control plane and a… | ||
| Hacking the human mind: The rise of social engineering security threat | Hisham Qaddoumi, Jim Pagiamtzis | 25m |
Claims that 95% breaches from human error and that a third of phishing targets financial services drive the narrative; examples include phishing… | ||
| Delta sharing: An open protocol for secure data sharing | Lee Blackwell | 15m |
A protocol and server that lets a provider share live Delta Lake tables (Parquet with Delta transaction logs) to any client — pandas, Spark, Tableau — by… | ||
| ML meets NoSQL: Integrating Python user-defined functions (UDFs) with N1QL for analytics | Luke DeBruin | 30m |
Couchbase Server 7.0 (Developer Preview) adds python UDFs to Analytics and external data access from AWS S3/Azure Blob so queries can join local JSON buckets… | ||
| AI-powered digital transformation in healthcare and life sciences | Bill Wong | 22m |
Claims concrete results: UBC uses deep docking on ZINC15 (1.36 billion compounds) to prioritize candidates, first to publish a billion-plus virtual docking… | ||
| Leveraging software optimization to reduce cloud footprint | Tejas Chopra | 14m |
Cloud object storage sits in exabytes and companies spend billions a year to store and retrieve it; applying classic file-system tricks — compression… | ||
| Fireside chat: Breaking the wall of unethical AI | Ari Kamlani, Keith Plummer | 30m |
Advocates an evidence-based workflow: require bias assessment before launch, involve diverse beta testers, and use curated training datasets that include edge… | ||
| Panel: Building responsible, human-centric AI models | Domhnaill Hernon, Banu Raghuraman, Conor Jensen | 44m |
Panelists argue that responsible, human‑centric AI requires concrete practices not buzzwords: apply an engineering safety factor to models, treat datasets as… | ||
| Completing the machine learning loop | Jimmy Whitaker | 26m |
Argues that reliable ML requires treating data like code and shows a concrete stack: git-like data repositories plus data-driven pipelines on Kubernetes that… | ||
| The indigenous languages technology (ILT) project at NRC in 2021 | Roland Kuhn | 21m |
Project starts with $6M (2017) to build community-driven tools; code is open-source and governed by an all-Indigenous advisory committee. Deliverables include… | ||
| Human-machine intelligence in cybersecurity | Tahseen Shabab | 25m |
Argues that existing SIEM, EDR and SOAR stacks miss human context and are being repackaged into XDR without solving gaps, cites adversarial ML failures (image… | ||
| Big data changes customer engagement: Is your MarTech ready? | Lisa Loftis | 24m |
Claims that real-time, in-stream analytics become mandatory: 76% of marketers expect a hybrid digital/physical model, 66% expect smart machines to make most… | ||
| Data health for customer 360 | Jamie Fiorda | 24m |
Companies report 78% of executives struggle to make data driven decisions and Talend frames the gap as data health, a productized approach combining… | ||
| Cyberterrorism during and post COVID-19: How the pandemic boosted cyber crime | Hisham Qaddoumi, Raja Mishal | 19m |
Claims that COVID-19 sharpens online recruitment into violence by boosting isolation, economic stress and conspiracy uptake, citing Christchurch, Quebec mosque… | ||
| Fireside chat: How AI is moving fashion forward | Marc Cortes, Stephane Courtioux | 30m |
Claims that feeding a machine learning model a critical amount of quality body photos plus labeled measurements predicts garment measurements in seconds and… | ||
| Why Samsung top AI executive thinks incrementalism is hobbling AI | Sajid Sadi | 15m |
Argues that incrementalism is hobbling AI and shows why fixing isolated ML components (ASR, TTS, intent handlers) misses the hard problem: the interconnections… | ||
| What machines can teach us about ourselves? | Banu Raghuraman | 30m |
Claim: machines expose human bias, surface hidden correlations, and reveal actionable gaps. Examples include facial recognition has lower accuracy for darker… | ||
| Masterclass: The right path to ML | Olivier Blais | 42m |
Claims a concrete playbook: start with data capture and dashboards, prove prediction before automating, and move iteratively from MVM (minimum viable model) to… | ||
| Sharing is caring: Building a modern microservice architecture helps everyone get ahead | David Wilmer, Swathi Paladugu | 31m |
Lowe's migrates legacy ESB to a cloud-native, hybrid microservice platform using Talend (Apache Camel), Kafka, Apigee Hybrid, GKE/other Kubernetes and Istio… | ||
| Data and analytics talent: Managing the workforce of the future | Sidita Zhabjaku, Charline Simon, Anoop Gulati, Adrian Lok, Jeanne Foucault | 47m |
TD describes concrete moves: a cloud migration to lift the data analytics platform, an acquisition of Layer 6 to inject advanced ML expertise, and formal… | ||
| Orchestrating multi-cloud data pipelines with | Joe Goldberg, Basil Faruqui | 21m |
Control‑M claims to abstract multi‑cloud pipeline complexity and shows concrete integrations: Kafka → Lambda/micro‑batch → S3 → Athena → SageMaker with… | ||
| Non fungible tokens and IP issues | Richard Thurston | 21m |
Claim: NFTs can function as licensable business assets and even qualify as trade secrets when paired with point‑in‑time registries, enable royalty tracking and… | ||
| AI and analytics for better marketing performance | Ceren Kolsarici | 27m |
Claims that advertising budgets are reverse-engineered into four methods—baseline spending, adaptive experimentation, advertising-to-sales ratio and… | ||
| Panel: Building and scaling a metadata management program | Manan Joshi, Carine Botturi, Tanja Glisin, Yolande Dykstra | 29m |
TELUS builds a searchable metadata repository on Collibra that automatically harvests technical metadata from Oracle, Hive, BigQuery and SQL Server, enriches… | ||
| Spotlight on AI use cases and innovators around the world | Richard Boire | 41m |
Surveys and case studies show concrete outcomes: computer vision and GANs enable using images for auto and property claim pricing, while NLP/LSTM powers text… | ||
| Fireside chat: Innovation in a new era of advertising | Leanne Gibson, Sonia Carreno | 27m |
Conference claims that pandemic-accelerated e‑commerce shifts are permanent: 81% of consumers changed shopping habits and 92% plan to keep them. Advertising… | ||
| The future of databases: Combining operational and analytical data at massive scale | Rob Hedgpeth | 25m |
Explains how MariaDB Xpand uses a shared‑nothing cluster with a single proxy entry point (MaxScale) to load‑balance reads/writes, auto‑rebalance data, and… | ||
| Patterns of an AI lineup card | Ari Kamlani | 28m |
Argues that an AI portfolio needs a measurable playbook: use lineup cards to rank and sequence ranked opportunities, keep hot spares for pivots, and use… | ||
| AI workflows and teaming - how do teams deliver AI products? | Ashley Beattie, Yerzat Marat, Amir Feizpour | 44m |
Panel argues a three‑stage checklist: discovery → prototype → production with concrete short tests (quick prototypes) then full MLOps (deploy, SLIs/SLOs… | ||
| AI for human and the planet: AI in nutrition | William Brendel | 36m |
Nutrition AI shows concrete results and clear limits. Heali AI assembles a food graph of 30,000 raw food items and 500,000 products and recipes and finds 75%… | ||
| Small teams, big dreams: How you can get started with AI today | Carolina Bessega | 26m |
A mid-market product uses Kepler automated ML platform to let non-experts build end-to-end models: a session-intent classifier reaches 86% accuracy in 2–3… | ||
| What's changing and what hasn't in AI | Richard Zuroff | 20m |
Company history anchors the claims: automation started in 2012 and the platform now reports DataRobot (founded 2012) and $1B+ funding, 700+ data scientists… | ||
| How external data and intelligence gathering is transforming the public sector | Ahmed Badruddin | 12m |
Claims a searchable infrastructure intelligence platform built from 1.4 billion public documents across 31,000 cities, towns and planning organizations that it… | ||
| The future of AI in powering clinical trial innovation | Oksana Andreiuk | 19m |
Pharma shows almost $4 billion raised in early-stage AI drug discovery, 64 FDA‑cleared AI devices catalogued by 2020, and a projection that 70% of trials use… | ||
| AI-powered digital transformation | Bill Wong | 25m |
Forrester-backed research shows 88% face data challenges and organizations spend months on discovery and platform work instead of production. The ecosystem… | ||
| Fireside chat: Solving media and advertising challenges | Sonia Carreno, Noel Geer | 44m |
Predicts three audience paths: 30% identified IDs and the rest via contextual plus cohorts (roughly 70%), urges immediate work on first‑party collection… | ||
| Logical data fabric for building a unified data warehouse and data lake | Sapta Sengupta | 26m |
TDWI finds 64% of orgs name unified warehouse and lake as a business objective and 84% call a unified approach important based on a 150‑respondent survey… | ||
| How Air Miles leverages their data asset to drive value for their customers and partners | Paul Raso | 27m |
AIR MILES runs a 11 million member coalition across 300 partners, ingesting first‑party retail feeds into an in‑house data lake and Data Hub, exposing datasets… | ||
| Panel: The shape of AI governance | May Masoud, Piotr Mierzejewski, Prashant Sharma | 45m |
Panel argues governance rests on concrete practices not slogans and recommends starting at data: track origin of data, version models, add explainability and… | ||
| Masterclass: Building a data stack in 2021 | Ryan Janssen, Paul Blankley | 50m |
After 30 years of tooling the modern data stack crystallizes into specific choices: use ELT connectors like Fivetran (or open source Airbyte/Meltano) to load… | ||
| Raising capital for your startup | Tahseen Shabab, Ryan Janssen | 29m |
Two founders describe how their companies actually raised money and built products: one models analyst skillsets in real time by instrumenting behavior to… | ||
| Machine learning: Necessity vs obligation | Azin Asgarian, Rohit Saha, Brian Ritz | 15m |
Retail data cleaning compares a simple rule table and rule-based tree against a language transformer model: pack-count prediction moves from 79% to 85%… | ||
| Data Ecosystem to power AI | Nishan Subedi | 22m |
Retail site with 59 million monthly visits and 8 million SKUs uses an event-first design that publishes backwards-compatible domain events from each… | ||
| Panel: Managing data in a distributed world | Trevor Trodd, Tanja Glisin, Steve Hoskin, Ben Salvador-Watts | 45m |
Collibra is implemented as a universal catalog after a multi‑year proof of work that starts with a small proof of concept and grows teams from two to about a… | ||
| Data & AI platform components in Azure | Rahat Yasir | 30m |
A practical walkthrough of the enterprise pieces needed for an end-to-end data and AI platform and how Azure supplies them: ingestion with Event Hubs/IoT Hub… | ||
| Democratizing analytics to scale innovation | Alan Jacobson, Gus Leite | 27m |
Most companies land around 2.2/5 analytic maturity, keeping a tiny core of data scientists on Hadoop/Databricks and a large population of spreadsheet-reliant… | ||
| nothing matches | ||