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The Value of z-index | CSS-Tricks How we look at the stacking order of our projects, how we choose z-index values, and more importantly, the implications of those choices.

#Development #Guides
The CSS `z-index` value · “Stop racing for the highest number.” ilo.im/16b8yj by Amit Sheen

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#Predictability #Maintainability #Stacking #Layers #Tokens #Tooltips #WebDev #Frontend #CSS #JavaScript

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The disappearing quasi-biennial oscillation under sustained global warming - Nature Communications Under sustained high greenhouse-gas emissions, the stratospheric quasi-biennial oscillation (QBO) may weaken and eventually disappear, potentially reducing short-term climate predictability, highlight...

New study shows that under sustained #GlobalWarming, the stratospheric quasi-biennial oscillation (#QBO) may weaken and eventually disappear, potentially reducing short-term #climate #predictability. www.nature.com/articles/s41...

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Unsung heroes: Flickr’s URLs scheme – Unsung A blog about software craft and quality

#Design #Explorations
Flickr’s URLs scheme · ”It was a beautiful and predictable scheme.” ilo.im/16aq98 by Marcin Wichary

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#Flickr #URLs #Schemes #Keyboard #Readability #Predictability #UrlDesign #ProductDesign #UiDesign #WebDesign

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#bskyart #surrealism #iconoplasm #AIArt #AIArtist #AIArtwork #AIimages #GenArt #DigitalArt #AIArtGallery #AIGeneratedArt #creativeai #AIArtCommunity #synthart #sigil #octagram #determination #predictability #opalescent #hrim

Sigil 4072

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Unpredictable And more life.
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LinkedIn This link will take you to a page that’s not on LinkedIn

Many software delivery teams are measuring the wrong things.

If you only tracked one thing in a Kanban system, this would be it.
lnkd.in/eTa3eK4F

#Kanban #FlowMetrics #DeliveryLeadership #Predictability #AgileDelivery

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This graph will change how you see the world
This graph will change how you see the world YouTube video by Veritasium

Veritasium musing about income distribution, abnormal events, power laws, risk, and predictability.
www.youtube.com/watch?v=HBlu...

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I’m a CEO who’s built, scaled and turned around companies. The next arms race in business isn’t about supply chains or rate cuts — it’s about predictability | Fortune This is the new arms race in business — building certainty in an uncertain world.

I’m a CEO who’s built, scaled and turned around companies. The next arms race in business isn’t about #supply chains or rate cuts — it’s about #predictability

fortune.com/2025/11/24/n...

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Future Of Drone Warfare In South Asia
Future Of Drone Warfare In South Asia YouTube video by The Defence Horizon Journal

"To mitigate the escalatory #risks associated with the use of #UAVs, both #Pakistan and #India need to introduce #transparency and #predictability in their use of UAVs."

tdhj.org/blog/post/dr...

youtube.com/shorts/mIQSw...

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Scientists analyzed 15,000 games of rock, paper, scissors and found the trick to winning _This article originally appeared in_The Conversation _._ There’s an optimal strategy for winning multiple rounds of rock, paper, scissors: be as random and unpredictable as possible. Don’t pay attention to what happened in the last round. However, that’s easier said than done. To find out how brains make decisions in a competitive setting, we asked people to play 15,000 games of rock, paper, scissors while recording their brain activity. Our results, now published in Social Cognitive and Affective Neuroscience, found that those who were influenced by previous rounds really did tend to lose more often. We also showed that people struggle to be truly random, and we can discern various biases and behaviours from their brain activity when they make decisions during a competition. Rock, paper, scissors. via Canva/Photos ## What we can learn from a simple game The field of social neuroscience has mostly focused on studying the brains of individual people. However, to gain insight into how our brains make decisions when we interact with each other, we need to use a method called hyperscanning. With this method, researchers can record the brain activity from two or more people while they are interacting with each other, providing a more real-world measure of social behaviour. So far, most research has used this method to investigate cooperation. When cooperating with someone else, it’s useful to act as predictably as possible to make it easier to anticipate each other’s actions and intentions. However, we were interested in decision-making during competition where unpredictability can give you a competitive advantage – such as when playing rock, paper, scissors. Rock, paper, scissors. via Canva/Photos How do our brains make decisions, and do they keep track of the previous actions of both ourselves and the other person? To investigate this, we simultaneously recorded the brain activity from pairs of players as they played 480 rounds of rock, paper, scissors with each other on a computer. From the resulting 15,000 total rounds across all participating pairs, we discovered that players were not good at being unpredictable when deciding which option to play next. Even though the best strategy is randomness, most people had a clear bias where they overplayed one of the options. More than half of the players favoured “rock”, followed by “paper”, and “scissors” was favoured least. In addition, people tended to avoid repeating choices – they went for a different option on their next round more often than would be expected by chance. ## Real-time decisions We could predict a player’s decision about whether to choose “rock”, “paper”, or “scissors” from their brain data even before they had made their response. This means we could track decision-making in the brain, as it unfolds in real time. Not only did we find information in the brain about the upcoming decision, but also about what happened in the previous game. The brain had information about both the previous response of the player and their opponent during this decision-making phase. Rock, paper, scissors.via Canva/Photos This shows that when we make decisions, we use information about what happened before to inform what to do next: “they played rock last time, so what’s my move?” We can’t help but try to predict what’ll happen next by looking back. Importantly, when trying to be unpredictable, it’s not helpful to rely on past outcomes. Only the brains of those who lost the game had information about the previous game – the brains of the winners did not. This means overreliance on past outcomes really does hinder one’s strategy. ## Why does this matter? Who hasn’t wished they knew what their opponent would play next? From simple games to global politics, a good strategy can lead to a decisive advantage. Our research highlights our brains aren’t computers: we can’t help but try to predict what’ll happen next, and we rely on past outcomes to influence our future decisions, even when that might be counterproductive. Of course, rock, paper, scissors is one of the simplest games we could use – it made for a good starting point for this research. The next steps would be to move our work into competitive settings where it’s more strategic to keep track of past decisions. Our brains are bad at being unpredictable. This is a good thing in most social contexts and could help us during cooperation. However, during competition, this can hinder us. A good takeaway here is that people who stop overanalyzing the past may have a better chance at winning in the future. _This article is republished from The Conversation under a Creative Commons license.Read the original article._
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Can a Website Make You Feel Safe? A website can make you feel safe: not in the technical sense of firewalls and passwords, but in the psychological sense - the feeling of calm, predictability, and trust that allows someone to relax enough...

#Design #Approaches
Can a website make you feel safe? · Good design not only works but also feels right ilo.im/16826v by Sarah Edwards

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#Communication #Trust #Safety #Predictability #Website #EmotionalDesign #ProductDesign #UxDesign #UiDesign #WebDesign

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🗽📊 The New York mayoral race just took a turn. Zohran Mamdani’s once double-digit lead has shrunk to six points as moderates and independents rally behind Andrew Cuomo’s message of steady leadership.

🔗 t.ly/E_rej
#NYCPolitics #NYCElection2025 #AndrewCuomo #Predictability

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CASCO + taxe in rata. Planificati fara batai de cap. #RiskManagement #Predictability https://www.auto-rent.ro

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Construction’s biggest enemy? Uncertainty.

🎧 Listen to the full episode https://youtu.be/ntDvBKpgC64

#constructioninnovation #projectmanagement #contech #dataquality #AIinConstruction #buildsmarter #certainty #predictability

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Predictable Reinforcement Learning Dynamics through Entropy Rate Minimization

Daniel Jarne Ornia, Giannis Delimpaltadakis, Jens Kober, Javier Alonso-Mora

Action editor: Mirco Mutti

https://openreview.net/forum?id=DDUsc1lD27

#predictable #reinforcement #predictability

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Totul pe o singura factura lunara. Buget previzibil, mai putin stres. #Budgeting #SME #Predictability https://www.auto-rent.ro

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#WolfSinger: #Chaos in the #brain#Determinism and #predictability

#Interview with German #neurophysiologist and #brainresearcher Wolf Singer on the topic “Can the brain understand the brain?”

More at: youtu.be/C2FVIbAyaH4

or: philosophies.de/index.php/20...

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The Interface as a Privileged Level of Organization in Life Sciences: Implications for Control and Causation in Complex Systems - Biological Theory Nature is a continuum of living and nonliving systems from the microscale to the macroscale that are interdependent and dynamically interact with each other. Approaching such complexity by identifying...

Interested in tackling the #COMPLEXITY of #BRAIN🧠 and #MIND?

The #INTERFACE is
1️⃣ a privileged level of #CONTROL
2️⃣ characterized by HIGH REGULARITY and #PREDICTABILITY
3️⃣ a boundary between types of #CAUSALITY WITHIN and OUTSIDE a system

Just out #BiologicalTheory
link.springer.com/article/10.1...

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Joel Tosi presents 'The problems that arise when focusing on predictability instead of variability' July 25th at Nebraska.Code().

nebraskacode.amegala.com

#ValueStream #JoelTosi #Predictability #Variability #Dev #Operations #TechConference #PracticalAgile #Nebraska #Agile #agileprojectmanagement

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Mastering Modern Time Series Forecasting : The Complete Guide to Statistical, Machine Learning & Deep Learning Models in Python 📘 Mastering Modern Time Series Forecasting (early access)This book will rise to $80+ as more chapters drop. Preorder now and lock in lifetime access.The Definitive Guide to Statistical, Machine Learning & Deep Learning Models in PythonLet’s be honest — most forecasting books are either outdated, too shallow, or written by folks who’ve never actually built a real forecasting system.If you’ve ever felt frustrated by books that skip the basics, toss in code without explaining it, or barely touch on what forecasting really involves — you’re not alone.This is different.Mastering Modern Time Series Forecasting is your all-in-one, no-shortcuts guide to building reliable, high-impact forecasting systems. Whether you're just getting started or looking to deepen your expertise, this book takes you from rock-solid foundations to the latest advances in forecasting — including deep learning, transformers, and FTSM (Foundational Time Series Models).Written by a practitioner with over a decade of experience, who’s built production-grade forecasting systems for multibillion-dollar companies, this book is grounded in reality — not hype. The systems I’ve helped build have delivered multimillion-dollar business value, but I’ve also seen the other side: data science teams chasing shiny tools, only to ship systems that crash in production, fail silently, or burn through budgets without results.This book is a response to that — combining practical Python examples, real-world case studies, and a clear path to building forecasting solutions that actually work, scale, and deliver value.🔍 What You'll Learn📘 Core Forecasting FoundationsGrasp what forecast accuracy really means, master model validation strategies, and sidestep common pitfalls that trip up even experienced practitioners.📈 Classical Models, Done RightIn-depth, modern takes on ARIMA, Exponential Smoothing, and other classical statistical and econometrics models — with clarity, not complexity.🤖 Machine Learning for Time SeriesBuild feature-rich forecasts using state-of-the-art ML techniques that go far beyond black-box models.🧠 Deep Learning & TransformersExplore powerful deep learning architectures, including Transformer-based models — all with clear, readable PyTorch code.📊 FTSMs – Foundational Time Series ModelsExplore the rise of Foundational Time Series Models (FTSMs) — large, pre-trained models designed to generalize across domains, tasks, and time horizons. Think GPT for time series.🎯 Probabilistic & Interpretable ForecastingMove beyond point forecasts with uncertainty quantification, conformal prediction, SHAP, attention mechanisms, and explainability tools.📊 Real-World Case StudiesApply what you’ve learned on practical datasets across domains like retail, energy, and finance.🚀 MLOps & DeploymentLearn how to deploy, monitor, and scale your forecasting pipelines in the real world — without the headaches.👥 Who It’s For Data Scientists & ML EngineersSolving real-world forecasting challenges and building production-ready systems. Analysts & DevelopersLooking for a practical, hands-on reference that covers both fundamentals and advanced techniques. Students, Educators & ResearchersIn need of a modern, curriculum-friendly resource grounded in both theory and application. Demand Planners & Business StrategistsFocused on delivering real value through accurate, actionable forecasts. 🧠 Why This Book Stands Out 🔍 Starts with what matters — metrics and validationBefore jumping into models, you’ll learn how to evaluate them properly so you’re building on a solid foundation. 🧠 Focuses on understanding, not just codingLearn how methods work, why they work, and when to use them — not just how to run the code. 💻 Fully documented, transparent codeNo black boxes. Every example is clearly explained so you can learn and adapt, not guess. 🔄 Updated continuously with reader feedbackBuy once, benefit forever — you’ll get lifetime updates as the field evolves. 📚 Everything in one placeFrom classical models to deep learning and FTSMs — no need to juggle multiple resources ever again. 📦 What You Get Instant download of the full book All code examples, datasets, and notebooks Free lifetime updates (including new chapters, errata fixes, and bonus content) Exclusive early access to upcoming bonus chapters & Q&A sessions 💸 Pricing 🎉 Introductory Price Suggested: $40 | Minimum: $35 This is the introductory price — it will increase as more chapters, tools, and content are released. If you find value or want to support the project, feel free to pay what it’s worth to you ❤️ Ready to take your forecasting skills from stats to neural nets, and from theory to real-world deployment?👉 Hit “Buy Now” and start mastering forecasting like never before.


Conquer the Chaos: My book "Mastering Modern Time Series Forecasting : The Complete Guide to Statistical, Machine Learning & Deep Learning Models in Python -> valeman.gumroad.com/...

#Forecasting #TimeSeries #Entropy #DataScience #MachineLearning #Predictability #SignalProcessing #Analytics

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Old News And more from the apocalypse.
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Old News And more from the apocalypse.
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I have 4C hair and 3 months ago, I loc’d at 3.5 inches. I didn’t expect my locks to curl into themselves to where I look like I have a curly pixie cut & I ❤️ that for me. I also also like that it’s gonna look like I have a curly pixie for the next year or so. #locshrinkage #microlocs #predictability

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Mastering Modern Time Series Forecasting : The Complete Guide to Statistical, Machine Learning & Deep Learning Models in Python 📘 Mastering Modern Time Series Forecasting (early access - release in 2025)This book will rise to $60+ as more chapters drop. Preorder now for $25 and lock in lifetime access.The Definitive Guide to Statistical, Machine Learning & Deep Learning Models in PythonLet’s be honest — most forecasting books are either outdated, too shallow, or written by folks who’ve never actually built a real forecasting system.If you’ve ever felt frustrated by books that skip the basics, toss in code without explaining it, or barely touch on what forecasting really involves — you’re not alone.This is different.Mastering Modern Time Series Forecasting is your all-in-one, no-shortcuts guide to building reliable, high-impact forecasting systems. Whether you're just getting started or looking to deepen your expertise, this book takes you from rock-solid foundations to the latest advances in forecasting — including deep learning, transformers, and FTSM (Foundational Time Series Models).Written by a practitioner with over a decade of experience, who’s built production-grade forecasting systems for multibillion-dollar companies, this book is grounded in reality — not hype. The systems I’ve helped build have delivered multimillion-dollar business value, but I’ve also seen the other side: data science teams chasing shiny tools, only to ship systems that crash in production, fail silently, or burn through budgets without results.This book is a response to that — combining practical Python examples, real-world case studies, and a clear path to building forecasting solutions that actually work, scale, and deliver value.🔍 What You'll Learn📘 Core Forecasting FoundationsGrasp what forecast accuracy really means, master model validation strategies, and sidestep common pitfalls that trip up even experienced practitioners.📈 Classical Models, Done RightIn-depth, modern takes on ARIMA, Exponential Smoothing, and other classical statistical and econometrics models — with clarity, not complexity.🤖 Machine Learning for Time SeriesBuild feature-rich forecasts using state-of-the-art ML techniques that go far beyond black-box models.🧠 Deep Learning & TransformersExplore powerful deep learning architectures, including Transformer-based models — all with clear, readable PyTorch code.📊 FTSMs – Foundational Time Series ModelsExplore the rise of Foundational Time Series Models (FTSMs) — large, pre-trained models designed to generalize across domains, tasks, and time horizons. Think GPT for time series.🎯 Probabilistic & Interpretable ForecastingMove beyond point forecasts with uncertainty quantification, conformal prediction, SHAP, attention mechanisms, and explainability tools.📊 Real-World Case StudiesApply what you’ve learned on practical datasets across domains like retail, energy, and finance.🚀 MLOps & DeploymentLearn how to deploy, monitor, and scale your forecasting pipelines in the real world — without the headaches.👥 Who It’s For Data Scientists & ML EngineersSolving real-world forecasting challenges and building production-ready systems. Analysts & DevelopersLooking for a practical, hands-on reference that covers both fundamentals and advanced techniques. Students, Educators & ResearchersIn need of a modern, curriculum-friendly resource grounded in both theory and application. Demand Planners & Business StrategistsFocused on delivering real value through accurate, actionable forecasts. 🧠 Why This Book Stands Out 🔍 Starts with what matters — metrics and validationBefore jumping into models, you’ll learn how to evaluate them properly so you’re building on a solid foundation. 🧠 Focuses on understanding, not just codingLearn how methods work, why they work, and when to use them — not just how to run the code. 💻 Fully documented, transparent codeNo black boxes. Every example is clearly explained so you can learn and adapt, not guess. 🔄 Updated continuously with reader feedbackBuy once, benefit forever — you’ll get lifetime updates as the field evolves. 📚 Everything in one placeFrom classical models to deep learning and FTSMs — no need to juggle multiple resources ever again. 📦 What You Get Instant download of the full book All code examples, datasets, and notebooks Free lifetime updates (including new chapters, errata fixes, and bonus content) Exclusive early access to upcoming bonus chapters & Q&A sessions 💸 Pricing 🎉 Introductory Launch Price Suggested: $35 | Minimum: $30 This is the initial price — it will increase as more chapters, tools, and content are released. If you find value or want to support the project, feel free to pay what it’s worth to you ❤️ Ready to take your forecasting skills from stats to neural nets, and from theory to real-world deployment?👉 Hit “Buy Now” and start mastering forecasting like never before.

#TimeSeries #Forecasting #MachineLearning #DataScience #AI #Entropy #Predictability #ChapterDrop

Order book here -> valeman.gumroad.com/...

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Predictability is the backbone of a strong economy. It builds trust, drives investment, and keeps markets stable.
Trump-Uncertainty? It kills confidence, delays decisions, and slows growth. Stability isn’t boring—it’s powerful. #economics #business #predictability
ChatGPT 2025/4/14

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If ever there was a way to widely. circulate a pic of El Furor it was for him to say he dislikes it. Let the gremlins in the Liberal’s heads do the rest. #Predictability

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Portugal rules out buying F-35s because of Trump The country’s air force has recommended buying the jets, but the outgoing defense minister said “the predictability of our allies” must be taken into account when making procureme…

#Portugal #rules out buying #F-35s because of #Trump
The #country’s #airforce has recommended #buying the jets, but the outgoing #defense minister said “the #predictability of our #allies” must be taken into #account when making #procurement decisions.

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• The restoration comes through #actsOfAbsurdity, #unexpectedgenerosity, and #breaking the #predictability of #mechanisedcontrol.

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Towards Measuring Predictability: To which extent data-driven approaches can extract deterministi...

Saleh GHOLAM ZADEH, Vaisakh Shaj, Patrick Jahnke, Gerhard Neumann, Tim Breitenbach

Action editor: Fredrik Johansson

https://openreview.net/forum?id=jZBAVFGUUo

#predictability

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Why the universe remains predictable: Insights from quantum mechanics Recent studies suggest quantum mechanics supports cosmic censorship, reinforcing black holes' role in hiding singularities.

Why the universe remains predictable: Insights from quantum mechanics: Recent studies suggest quantum mechanics supports cosmic censorship, reinforcing black holes' role in hiding singularities.

#QuantumMechanics #Predictability #GeneralRelativity #Singularities #CosmicCensorship #EarthDotCom

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