Different target audience, but similar lessons in this book by @storywithdata … https://
amzn.to/4bm17D0
INNOVATION
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Data Storytelling Book Insights for Technical Audiences
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Create AI Scripts with Notebook LM Tool
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My AI: https://
alignednews.com/ai At the bottom is a button to create you a Notebook LM script. Paste that into Notebook LLM and click "create." -

4 Data Storytelling Strategies to Explain Data Insights
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Learn about these 4 strategies to explain (with #DataStorytelling) insights extracted from data: – Connections
– Coincidences
– Curiosity
– Contradictions See this FREE 16-page PDF that explains these 4 strategies: https://
linkedin.com/feed/update/ur
n:li:activity:7347972721433006081/
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AI-Powered Algorithm Analysis Tool Built on X API
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Been here 19 years and your advice is right on. I've been studying the algorithm at quite a deep level. I even built an AI that lets you see the entire AI community in a new way: https://
alginednews.com/ai (AI using the X API builds that entire page from X). The algorithm is -

Sakana AI Completes Misinformation Countermeasure Technology for Ministry Project
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Sakana AI has completed technology development for the Ministry of Internal Affairs and Communications' "Development and Demonstration Project for Countermeasure Technologies Against Misinformation and Disinformation on the Internet (Fiscal Year 2025)". The project aimed to solve challenges in today's information environment where vast amounts of misinformation and disinformation circulate. Utilizing proprietary technologies including novelty search, the company developed a system that supports visualization of SNS spaces, comprehensive judgment of misinformation and disinformation, and formulation of countermeasures. Going forward, Sakana AI will continue to contribute to the social implementation of AI in the intelligence domain. sakana.ai/mic-project [Translated from EN to English]
→ View original post on X — @sakanaailabs, 2026-04-07 03:22 UTC
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Data Storytelling with Altair: Turn Raw Data Into Insights
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Data Storytelling: http://
amzn.to/3TYx24Z 𝙎𝙐𝙈𝙈𝘼𝙍𝙔: Data Storytelling with Altair (statistical visualization library for Python) and AI teaches you how to turn raw data into effective, insightful data stories. You’ll learn exactly what goes into an effective data story, -

Data Literacy in Practice: Essential Guide for Analytics Professionals
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"Data Literacy in Practice" at: http://
amzn.to/3W4tDli v/ @PacktDataML —————
#Analytics #DataScience #ML #MachineLearning #DataStorytelling #BI #DataScientist -

Mastering Data-Driven Presentations: Storytelling for Impact
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“Winning The Room: Creating and Delivering an Effective Data-Driven Presentation” by @billfranksga (with Foreword by me) Available at http://
amzn.to/3htD2Qb ——————
#DataStorytelling #CDO #CMO #BI #Startup #DataScientist #DataScience #Analytics -

FlowingData Guide to Data Visualization and Statistics
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Visualize This — The FlowingData Guide to Design, Visualization, and Statistics (2nd Ed.): http://
amzn.to/440tCTm by @FlowingData ——————
#BI #DataViz #DataScience #DataScientist #DataStorytelling -
Silicon Valley’s Perverse Incentive: Token Explosion Over Actual Productivity
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It's not the dumbest trend I've ever seen silicon valley companies fall for. Remember who we're talking about here. And Meta is absolutely not the only company doing this. But it is the dumbest possible thing you can do. If you want to do nothing, and watch your token budgets explode, all you have to do is put 100 agents on a discord server, or slack, or anywhere, where you're running multiple session contexts, and just start talking. That's it. You don't have to work on anything useful. One token turns into 100 tokens, which turns into a million tokens, which turns into billions and trillions of tokens, while literally nothing other than eyeball emojis is created. Meanwhile, it's that very problem of token explosion that's actually worth fixing, and optimizing around. But if you're incentivizing based on nothing other than token budgets…. why would you want to reduce that token count? It's a perverse incentive. I think this is where it really starts to feel like boom times for developers. Across the board, the powers that be are, whether they know it or not, asking us to use AI incorrectly. When the subsidies stop, and people are no longer drunk on money (this is going to happen sooner than we think), efficiency is going to be the order of the day. The people at the top of these leaderboards are going to be fired when the people up top realize that nothing was accomplished, and lean will be the order of the day. I think, given the history of this, that it's only a matter of time before the chopping block comes down. If you're concerned about that, optimize for measures of code quality, and productivity as though loc and token counts did not exist. That's how you survive this. Jyoti Mann (@jyoti_mann1) The highest ranked individual user averaged 281 billion tokens, which could cost millions of dollars, depending on the type of model used. theinformation.com/articles/… — https://nitter.net/jyoti_mann1/status/2041162769643327596#m
→ View original post on X — @scobleizer, 2026-04-07 03:11 UTC