LIVE
[Private video]
48:57
Why Most ML Projects Fail (and How to Fix It)
InfoQ
50:14
Mind Your Language Models: an Approach to Architecting Intelligent Systems
59:17
AI Integration for Java: To the Future, From the Past
50:03
Applying AI to the SDLC: New Ideas and Gotchas! - Leveraging AI to Improve Software Engineering
51:15
Why a Hedge Fund Built Its Own Database
41:37
Generative AI and Organizational Resilience
49:38
Generative Search: Practical Advice for Retrieval Augmented Generation (RAG)
49:40
LIquid: a Large-Scale Relational Graph Database
46:04
Being a Responsible Developer in the Age of AI Hype
45:15
Retrieval-Augmented Generation (RAG) Patterns and Best Practices
49:56
Large Language Models for Code: Exploring the Landscape, Opportunities, and Challenges
50:12
Redesigning OLTP for a New Order of Magnitude
46:58
The Rise of the Serverless Data Architectures
49:08
Amazon DynamoDB Distributed Transactions at Scale
50:58
Needle in a 930M Member Haystack: People Search AI @LinkedIn
48:54
PostgresML: Leveraging Postgres as a Vector Database for AI
45:35
Performance and Scale - Domain-Oriented Objects vs Tabular Data Structures
40:59
Back to Basics: Scalable, Portable ML in Pure SQL
41:31
Strategy & Principles to Scale and Evolve MLOps @DoorDash
41:27
AI Bias and Sustainability
46:53
A Bicycle for the (AI) Mind: GPT-4 + Tools
50:04
A New Era for Database Design with TigerBeetle
46:36
Operationalizing Responsible AI in Practice
48:30
Orchestrating Hybrid Workflows with Apache Airflow
46:19
Open Machine Learning: ML Trends in Open Science and Open Source
46:03
Taming the Data Mess, How Not to Be Overwhelmed by the Data Landscape
48:01
Data Versioning at Scale: Chaos and Chaos Management
Resilient Real-Time Data Streaming across the Edge and Hybrid Cloud
38:25
GraphQL Caching on the Edge
36:23
The Unreasonable Effectiveness of Zero Shot Learning
38:32
Machine Learning at the Edge
39:12
Building & Operating High-Fidelity Data Streams
38:10
Federated GraphQL to Solve Service Sprawl at Major League Baseball
40:26
Data Pipelines & Data Mesh: Where We Are and What the Future Looks Like
39:39
Panel: Future of Language Support for ML
39:15
How Do You Distribute Your Database over Hundreds of Edge Locations?
38:18
Robust Foundation for Data Pipelines at Scale - Lessons from Netflix
38:03
Data Mesh: an Architectural Deep Dive
From Batch to Streams: Building Value from Data In-Motion
38:13
Evolving Analytics in the Data Platform
19:44
Designing Better ML Systems: Learnings from Netflix
29:12
Data-Driven Development in the Automotive Field
31:17
Designing IoT Data Pipelines for Deep Observability
21:40
Scaling & Optimizing the Training of Predictive Models
52:37
Anti-Entropy Using CRDTs on HA Datastores @Netflix
0:39
QCon Plus (Virtual Conference on Nov 4-20)
49:24
Applying Machine Learning to Financial Payments
0:30
InfoQ Live - Delivering Technology Through Software Engineering Leadership - September 23rd 2020
34:43
BERT for Sentiment Analysis on Sustainability Reporting
40:55
The Fast Track to AI with JavaScript and Serverless
54:31
Visual Intro to Machine Learning and Deep Learning
0:26
InfoQ Live (Microservices Virtual Event on Aug 25th)
54:12
Accuracy as a Failure
46:56
Databases and Stream Processing: a Future of Consolidation
41:02
Machine Learning through Streaming at Lyft
44:41
Machine Learning on Mobile and Edge Devices with TensorFlow Lite
42:06
Monitoring and Tracing @Netflix Streaming Data Infrastructure
40:22
Swift for Tensorflow
43:53
Kafka Needs No Keeper
50:36
ML in the Browser: Interactive Experiences with Tensorflow.js
48:08
Data Mesh Paradigm Shift in Data Platform Architecture
46:05
ML's Hidden Tasks: A Checklist for Developers When Building ML Systems
47:44
Machine Learning 101
47:23
Practical Change Data Streaming Use Cases with Apache Kafka & Debezium
51:39
Future of Data Engineering
45:19
MLflow: An Open Platform to Simplify the Machine Learning Lifecycle
From Research to Production with PyTorch
48:00
EBtree - Design for a Scheduler and Use (Almost) Everywhere
49:28
Not Sold Yet, GraphQL: A Humble Tale from Skeptic to Enthusiast
51:01
Intuition & Use-Cases of Embeddings in NLP & beyond
43:58
The Future of Transportation
49:45
Test-Driven Machine Learning
37:15
Open Source Robotics: Hands on with Gazebo and ROS 2
46:12
Michelangelo - Machine Learning @Uber
51:28
The Whys and Hows of Database Streaming
49:12
Human-Centric Machine Learning Infrastructure @Netflix
49:03
Algorithms behind Modern Storage Systems
34:59
Building the Enchanted Land
33:21
Engineering Systems for Real-Time Predictions @DoorDash
55:08
ML Data Pipelines for Real-Time Fraud Prevention @PayPal
39:01
ETL Is Dead, Long Live Streams: real-time streams w/ Apache Kafka
39:22
Fundamentals of Stream Processing with Apache Beam
51:33
Semi-Supervised Deep Learning on Large Scale Climate Models
54:21
Panel: SQL over Streams, Ask the Experts
25:31
Bias in BigData/AI and ML
1:33
Artificial Intelligence and Machine Learning for the SWE
41:04
Artificial Intelligence and Machine Learning for the SWE - QCon London 2018
46:08
Serverless & GraphQL
