The Future is Notebooks

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The Future is Notebooks Carol Willing Elijah Meeks noteable.io

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| 2 About the Speakers Elijah Meeks Chief Innovation Officer Carol Willing VP Engineering ● Jupyter Software Steering Council ● JupyterHub and Binder Core Developer ● 2017 ACM Software System Award ● Python Core Developer ● Python Steering Council ● PSF Fellow ● Co-Founder at Noteable & Data Visualization Society ● Author & Speaker on Data Visualization ● Netﬂix, Apple ● Great shirts ● Unconventional path to tech ● Late to Notebooks

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| A Brief History of Notebooks ● First Generation IPython Notebooks to Jupyter ● Second Generation: 2018 - 2023 Collaboration & Modern Data Stack ● Third Generation: Now - 2028 AI, Time, and Scale 3 Agenda: The Future is Notebooks

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| 4 What Are Notebooks Notebooks rock You might not realize that, yet But we’re here to help

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| 5 First Generation: IPython Notebooks to Jupyter

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| 6 First Generation: IPython Notebooks to Jupyter

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| 7 First Generation: 2017 ACM Software System Award

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| 8 The Classic Notebook

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| 9 Second Generation: 2018 - 2023

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| 10 Second Generation: 2018 - 2023

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| 11 Modern Data Notebooks

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| 12 Paradigm Shift: AI, Value of Time, Scale We’re in the middle of a paradigm shift at scale AI is rapidly changing computing and humanity

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| 13 The Third Generation of Notebooks is Here Aspirational and Inspirational ● Productivity of experts ● Unlocking context and capabilities for all ● Available everywhere (mobile, office, global) ● Visualize when a picture can convey a thousand words

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| 14 Where will Notebooks Evolve? Notebook++ Isn’t the Answer ● “Notebook for the Modern Data Stack” ● Modern Data Stack Fatigue ● Integrate new technologies more often than synthesizing new workﬂows ● Creators and Consumers as distinct categories

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| 15 The Third Generation of Notebooks: Onboarding Imagine a Radically Inclusive Data Tool ● Natural language for greater access by all ● Cognitive science and learning: success by a user motivates more usage and more possibility for complex analysis and tasks ● Consolidation of help and docs in one natural language interface

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| 16 The Third Generation of Notebooks: Onboarding What excites people about ChatGPT? ● It does text well ● It does code well ● Code + Text is a notebook

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| 17 The Third Generation of Notebooks: Onboarding Everyone can level up their impact

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| 18 The Third Generation of Notebooks: Superpowers All Users get Superpowers ● Create me a chart that shows… ● Summarize the code cell in prose for my peer ● Create a prose cell that draws conclusions from this dataframe

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| 19 What if I don’t know how to code but I know how to bake?

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| 20 Not a baker? Or a 5th grader interested in baseball Maybe you’re a Hollywood exec… Or a VA psychiatrist… Or you like dogs… or run a small business… or own a Rubik’s Cube…

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| 21 The Third Generation of Notebooks: Superpowers All notebooks will be collaborative ● Never work with data alone again ○ Error response ○ Code copilot ○ ChatGPT in the comments ● AI assistants for creation of prose and viz ● AI guides to assist new users

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| 22 The Third Generation of Notebooks: Superpowers Everyone can create / use notebooks ● Guided visualization (DataPrism) ● AI assistants (Noteable ChatGPT Plugin) ● Fully web based for users ● Guided pipelines for creators

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| 23 The Third Generation of Notebooks: Superpowers It’s not just AI

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| 24 The Third Generation of Notebooks: 2023 to 2028 Context is Key ● Scenarios for business options ● Improved decision making with conﬁdence ● Risk analysis

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| 25 The Third Generation of Notebooks: Context Everyone can share context ● Scenarios ● Domain knowledge sharing ● Risk assessments ● From data to pipelines to business impact

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| 26 The Third Generation of Notebooks: Context Where Will Notebooks Be in 5 Years Anyone can create a notebook anywhere, everyone in a notebook will be simultaneously creator, collaborator and consumer ● What is a data engineer when notebooks have integrated ETLs? ● What is a data analyst when they’re using the same tools with the same feature breadth as data scientists? ● What is a data scientist when anyone can deploy any ML with just a prompt?

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| 27 Takeaways Takeaways ● Notebook++ Isn’t Enough ● Include Everyone in Data Work ● All Users Get Superpowers ● Context is Key