Open||Source||Data The AI-Native Stack in Practice with Charna Parkey and Sam Bean
This episode features a panel discussion with Charna Parkey, a Real-Time AI Product and Strategy leader at DataStax; and Sam Bean, Staff Engineer at You.com. Charna is a co-author and inventor on several patents, including patent-pending work on ML/coordinated feature engine at the edge. Sam helped create the Spark connector to Weaviate, and is passionate about Big Data, Spark, NLP, Hugging Face, and large language models.
In this episode, Charna and Sam discuss adapting to user expectations, what’s missing in the AI stack, and how to become an advanced citizen in open source.
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"We've seen these companies start to better understand that these streaming technologies have a place, whether it's Kafka or Flink or Pulsar, but it's still incredibly difficult to use and we need a different level of abstraction. [...] We're starting to see the stack change so that it becomes more interchangeable of the components and try to sort of raise that layer of abstraction so that we can get these types of models and these types of capabilities to more people." – Charna Parkey
"I think that a lot of what you need to adjust to are these, what you were discussing as I call interaction data, you were calling it event data. But these interactions that people have with the internet and trying to find ways to model that in a way that even if your models aren't real-time, having ways to featurize real-time data in a way that's interpretable by a model. [...] I think Spark and Kafka and Delta and all of those things, give you a lot more flexibility now to move in different directions and readjust and I think, pivot what you want to do with the system." – Sam Bean
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Episode Timestamps:
(01:29): Sam explains his background
(03:36): Charna explains her background
(18:13): Sam explains the problems You.com is solving for
(28:21): Changes in user expectations in the AI-native stack
(39:09): Advice for becoming an advanced citizen in open source
(47:25): What’s missing in the AI stack
(54:51): What open source data means to the panelists
(58:22): How technologists should prepare for the future
(01:03:10): Executive producer, Audra Montenegro's backstage takeaways
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