| With the close of 2017 fast approaching, we've been reflecting on the software trends our editors and speakers have focused on this year and how those trends will affect the year to come. Serverless, microservices, and languages like Rust, Go-lang, Swift, Kotlin are still garnering a lot of attention, but demand for AI / machine learning has exploded. The commoditization of tooling has enabled more and more SWEs to adopt AI / ML techniques in their day-to-day roles. Engineers are looking to understand (demanding to understand) more about the tools, frameworks, and application of AI and machine learning. It's one of the reasons we've created a QCon dedicated just to AI and machine learning: QCon.ai. We're taking a different approach to AI / ML than that of other software conferences. Rather than focusing on data scientists, QCon.ai will focus on how full-stack software engineers can apply machine learning and AI techniques in their everyday roles. We're bringing the same quality focus, applied learning experiences, and real-world speakers to QCon.ai that you have come to expect from QCon.
Designed specifically by, and for, software engineers, architects, and technical managers, the conference tracks are developed by our program committee which includes: | AI & ML: “I'm seeing it as the next great wave in Computer Science.” - Martijn Verburg, Co-founder of the London Java Community and CEO of jClarity |
Speakers secured so far include: - Danny Yuan - Real-time Streaming Lead @Uber
- Tyler Akidau - Engineer @Google & Founder/Committer on Apache Beam
- Jeff Magnusson - Director of Data Platform @StitchFix
- Eugene Kirpichov - Cloud Dataflow Sr SE @Google
- Holden Karau - Open Source Distributed Systems @Google, Spark Committer, Formerly Principal Engineer @IBM
- Eric Horesnyi - CEO @streamdata.io
QCon.ai 2018 tracks will focus on: - Deep Learning Applications & Practices: Deep learning lessons using Tensorflow, Keras, PyTorch, Caffe across machine translation, and computer vision
- Predictive Data Pipelines & Architectures: Best practices for building real-world data pipelines doing interesting things like predictions, recommender systems, fraud prevention, ranking systems, and more
- Real-World Data Engineering: Showcasing DataEng tech and highlighting the strengths of each in real-world applications
- ML Applied to Operations (Half-Day Track): Machine learning in the data center. Exploring topics like dynamic rebalancing in dataflow, predictive auto-scaling, and fault prediction
- AI Meets the Physical World: AI use cases from drones to self-driving cars; the track where AI touches the physical world
- Handling Sequential Data Like an Expert (Half-Day Track): Discussing the complexities of time, including HyperLogLog, count-min sketch, and more
- ML in Action: Applied track demonstrating how to train, score, and handle common machine learning use cases, including heavy concentration in the space of security and fraud
Each of these tracks will combine multiple long and short form talks to give depth and breadth to the tools and practices of AI / ML. There will also be the opportunity to get hands-on with codelabs. More to follow soon! QCon.ai takes place in San Francisco from April 9-11, 2018. You can find out more about the conference and register at QCon.ai. Should any of your colleagues express interest in attending as well, we offer discounts for groups as small as three people. Drop us a note at info@qcon.ai if you wish to receive more information.
Sincerely,
The QCon team    | Get a Glimpse of What to Expect: Watch QConSF 2017's The Practice & Frontiers of AI Panel Shubha Nabar (Sr Director @Salesforce Einstin) put together a special treat for attendees of QConSF 2017. In a panel called The Practice & Frontiers of AI Panel, Nabar was joined by Chris Moody (Manager of the Applied AI team at StitchFix), Reena Phillip ( Engineering Manager at Facebook), Melanie Warrick (Senior Developer Advocate for ML and Google Cloud), Kevin Moore (Senior Data Scientist at Salesforce Einstein) & Miju Han (Director of Product at GitHub). On the panel they discussed where each felt AI/ML was going and what it's impact would have on software. We thought we'd share the panel discussion with you as a special bonus to this email. |
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