First ever In-person MLOPs Tel Aviv meetup!
Details
We would like to invite you to the first ever Tel Aviv Mlops.community in-person meetup!
Hosted by Ironscales.
Amot Atrium Tower, Ze'ev Jabotinsky Road, Ramat Gan,
Floor 19
Agenda:
18:00-18:30 Gathering and snacks
18:30-18:40 Welcome to our first event. Mlops Tlv is looking for more speakers :)
18:40-18:50 Welcome words from our host
18:50-19:10 Towards an automated R&D workflow for edge AI systems - Dan Malowany, VP R&D at SightX AI
19:10-19:30 ML Workflow for parallel model improvements. - Mordechai Worch, Data Team Lead at Ironscales
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Dan Malowany
Towards an automated R&D workflow for edge AI systems
The R&D workflow of an AI-based product is inherently characterized by the experimental nature of the deep-tech research process. Adding to the challenges of edge technology - working on various ARM-based SOMs with multiple GPUs and DSP types, the inevitable conclusion is that a bespoke R&D methodology is required.
This talk will discuss our design and successful application of an end-to-end MLOPS methodology. The proposed design enabled us to tackle the management of deep learning research aimed to be deployed on various platforms and to become faster and better with every version release. We recently added a feedback loop to this methodology which gets us a step closer to the holy grail of automated and continuously learning R&D workflow for edge AI.
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Mordechai Worch
ML Workflow for parallel model improvements.
Deploying machine learning models is hard. Deploying multiple machine learning models in parallel is harder. This talk we will discuss our strategy for decomposing a machine learning system and providing components that allow highly parallelized development. We will answer 4 core questions.
Why should we care about boring stuff like workflows?
What are the main bottlenecks in parallelizing machine learning development?
What software engineering design patterns can we introduce to minimize these bottlenecks?
How can we design a development workflow that is best suited for introducing new improvements?