46 episodes

The origin story behind the best open source projects and communities.

Contributor Eric Anderson

    • Technology
    • 5.0 • 9 Ratings

The origin story behind the best open source projects and communities.

    Feast with Willem Pienaar

    Feast with Willem Pienaar

    Eric Anderson (@ericmander) and Willem Pienaar (@willpienaar) talk about Feast, the open-source feature store for machine learning. Feature stores act as a bridge between models and data, and allow data scientists to ship features into production without the need for engineers. Willem co-created Feast at Gojek, and later teamed up with the folks at Tecton to back the project.

    In this episode we discuss:


    The value of feature stores in MLOps
    What happens when you open-source too early
    Why most open-source code has nothing to hide
    Bringing an open-source project to an existing company
    Good and bad use cases for a feature store

    Links:


    Feast
    Tecton
    Turing
    Merlin
    Kubeflow
    apply() Conference

    People mentioned:


    Mike Del Balso
    Kevin Stumpf (@kevinmstumpf)
    Ajey Gore (@AjeyGore)
    Demetrios Brinkmann (@Dpbrinkm)
    Wes McKinney (@wesmckinn)

    Other episodes:


    Flyte with Ketan Umare
    Great Expectations with Abe Gong and Kyle Eaton

    • 32 min
    Flyte with Ketan Umare

    Flyte with Ketan Umare

    Eric Anderson (@ericmander) and Ketan Umare (@ketanumare) discuss Flyte, the open-source workflow automation platform for large-scale machine learning and data use cases. Ketan is a former engineer at Lyft, where he created Flyte to help models in Pricing, Locations, ETA, and more. Today, the project allows machine learning developers everywhere to bring their ideas from conception to production.

    In this episode we discuss:


    How Flyte combines compute with parts of a workflow engine in a way that is best for the user
    The importance of reliable fares and ETA predictions at a ride-sharing app
    A progenitor to Flyte called “Better Airflow”
    Ketan’s innovative approach to bringing typing to machine learning workloads
    Why Flyte landed at the Linux Foundation

    Links:


    Flyte
    Union.ai
    Apache Airflow
    Kubeflow
    Luigi
    MLTwist

    Other episodes:


    Great Expectations with Abe Gong and Kyle Eaton
    Envoy Proxy with Matt Klein

    • 36 min
    Activeloop with Davit Buniatyan

    Activeloop with Davit Buniatyan

    Eric Anderson (@ericmander) meets with Davit Buniatyan (@DBuniatyan) of Activeloop, the database for AI. Davit was inspired to found Activeloop while working on large datasets in a neuroscience research lab at Princeton. Powering the technology at Activeloop is Hub, the open-source dataset format for AI applications. Join us to learn how Hub promises to enhance and expand various verticals in deep learning.

    In this episode we discuss:


    Reconfiguring traditional ML tooling for the cloud
    Connectomics - working with thin slices of a mouse brain with neuroscientist Sebastian Seung
    Choosing between university, a start-up, and open-source
    Davit’s original product, that ran computation on crypto mining GPUs on a distributed scale
    Focusing on different data modalities for computer vision

    Links:


    Activeloop
    Activeloop Hub
    Apache Parquet
    Apache Spark
    TensorFlow
    Snowflake
    Databricks
    Timescale

    People mentioned:


    Sebastian Seung (@SebastianSeung)

    Other episodes:


    TensorFlow with Rajat Monga

    • 30 min
    Unikraft with Alexander Jung and Simon Kuenzer

    Unikraft with Alexander Jung and Simon Kuenzer

    Eric Anderson (@ericmander), Alexander Jung (@nderjung) and Simon Kuenzer (Github: @skuenzer) get technical on Unikraft, the open-source unikernel development kit. Unikernels are specialized, high performing OS images that have the potential to revolutionize virtualization. Unikraft makes unikernels easy to use by prioritizing modularity, security, and POSIX-compatibility.

    In this episode we discuss:


    How Unikraft seeks wider adoption of unikernels in real-world applications
    Unikraft’s background in research and academia
    Bottom-up as well as top-down specialization
    Building a community with a large proportion of students

    Links:


    Unikraft
    Unikraft: Fast, Specialized Unikernels the Easy Way
    Xen Project
    MirageOS
    HermitCore
    Firecracker

    • 27 min
    EdgeDB with Yury Selivanov

    EdgeDB with Yury Selivanov

    Eric Anderson (@ericmander) has a conversation with Yury Selivanov (@1st1), the co-founder of EdgeDB. EdgeDB is the world’s first “graph-relational database.” It’s a term coined specifically for this new type of database, designed to ease the pain of dealing with the usual relational and NoSQL models. And no, EdgeDB is NOT a graph database!

    In this episode we discuss:


    A glitch at EdgeDB’s Matrix-inspired launch event
    Origin of the term and design philosophy, “graph-relational”
    What to know about becoming a Python core developer
    How EdgeDB’s next-gen query language compares to GraphQL and SQL

    Links:


    EdgeDB
    magicstack
    uvloop

    People mentioned:


    Elvis Pranskevichus (@elprans)
    Colin McDonnell (@colinhacks)
    Victor Petrovykh (Github: @vpetrovykh)
    Dan Abramov (@dan_abramov)
    Brett Cannon (@brettsky)
    Daniel Levine (@daniel_levine)

    Other episodes:


    Hasura with Tanmai Gopal
    Dgraph with Manish Jain

    • 45 min
    Deephaven with Pete Goddard

    Deephaven with Pete Goddard

    Eric Anderson (@ericmander) sits down with Pete Goddard (@pete_paco) to talk about Deephaven, the open-core query engine built for real-time streams and batch data. Pete is the CEO of Deephaven Data Labs, and comes to the data world from a background in capital markets trading. Deephaven originally addressed a need for real-time data infrastructure in the finance world, but the team realized how useful their technology could be in a wider variety of verticals. Join us for Pete’s unique perspective on reaching out into alternate industries and use cases through community development.

    In this episode we discuss:


    How Pete transitioned from Wall Street to open-source software
    Selling investors on open-source
    Two questions people always ask Pete
    The luxury of Deephaven’s incremental update model
    Barrage, Deephaven’s API for streaming tables that extends Apache Arrow Flight

    Links:


    Deephaven
    Barrage
    Apache Kafka
    Apache Arrow Flight
    Eclipse Jetty

    Other episodes:

    TensorFlow with Rajat Monga

    • 41 min

Customer Reviews

5.0 out of 5
9 Ratings

9 Ratings

Beach View ,

The best

Love this show!

8thofficeontheright ,

Great podcast

Always love a good origin story.

MKateAnd ,

I love this show

Great guests. A good way to stay on top of new projects.

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