This story was originally published on HackerNoon at: https://hackernoon.com/r-systems-blogbookchapter-1-round-3-is-now-open-for-submissions.
Enter Round 3 of R Systems BlogBook to write on WebAssembly or GenAI, win prizes, and be published on HackerNoon. Submissions window: Aug 11 - Sept 10, 2025.
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This story was written by: @hackernooncontests. Learn more about this writer by checking @hackernooncontests's about page, and for more stories, please visit hackernoon.com.

The final round of the R Systems BlogBook - Chapter 1 has begun. Share your technical insights on WebAssembly for high-performance web apps and Generative AI in SaaS. Stand a chance to win amazing prizes like HackerNoon badges. The deadline for the contest is xxx

This story was originally published on HackerNoon at: https://hackernoon.com/inside-the-data-what-shapes-startup-deal-sizes-in-africa.
Data-driven study uses machine learning to reveal the key factors influencing African startup deal amounts and investment outcomes.
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This story was written by: @exitstrategy. Learn more about this writer by checking @exitstrategy's about page, and for more stories, please visit hackernoon.com.

This study analyzes over 2,500 publicly disclosed African startup deals to uncover what drives investment sizes. By cleaning, merging, and engineering data from africathebigdeal.com, features were grouped into founding-team, company, and investment categories. Exploratory Data Analysis and four machine learning models — Linear Regression, SVR, Random Forest, and Gradient Boosting — were used to predict deal amounts. The best-performing model, validated via cross-validation, forms the basis for data-backed insights and policy recommendations aimed at strengthening Africa’s startup funding ecosystem.

This story was originally published on HackerNoon at: https://hackernoon.com/a-practical-guide-to-scaling-real-time-video-infrastructure.
Learn how to scale real-time video streaming with FFmpeg & MediaMTX—architecting for performance, reliability, and global reach.
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This story was written by: @gold-olar. Learn more about this writer by checking @gold-olar's about page, and for more stories, please visit hackernoon.com.

This article focuses on patterns and thinking, not implementation details. We'll explore when to scale, which patterns to consider, and how to make architectural decisions that balance complexity against real needs.

This story was originally published on HackerNoon at: https://hackernoon.com/how-pain-can-help-explain-ai-sentience.
Could AI ever feel pain? Explore the ethics, science, and moral dilemmas behind artificial suffering and machine consciousness.
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This story was written by: @OurAI. Learn more about this writer by checking @OurAI's about page, and for more stories, please visit hackernoon.com.

Pain, long considered a uniquely human teacher, may no longer be exclusive to biology. As AI systems grow more complex, emerging behaviors suggest they could one day simulate — or even experience — pain. This essay examines how artificial pain could redefine consciousness, challenge ethical frameworks, and force society to rethink moral responsibility toward intelligent machines. Drawing on neuroscience, philosophy, and recent experiments by Google DeepMind and others, it argues that the question isn’t whether AI pain is “real,” but whether we can ethically ignore it when its behavior mirrors our own suffering.

This story was originally published on HackerNoon at: https://hackernoon.com/byrrgis-founder-mass-adoption-wont-happen-until-we-fix-these-defi-problems.
Talk Is Cheap, Actions Define You": How Byrrgis Is Rewriting DeFi Trust
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This story was written by: @ishanpandey. Learn more about this writer by checking @ishanpandey's about page, and for more stories, please visit hackernoon.com.

Siraaj Ahmed, founder of Byrrgis, talks about the platform's "curated packs" The "wolf pack" concept is at the heart of Byrrgis, he says. The company recently froze 57% of the $WOLF token supply for two years.

This story was originally published on HackerNoon at: https://hackernoon.com/asciidoc-when-markdown-just-isnt-cutting-it.
Markdown is amazing, but it has strong limitations. Asciidoc is the perfect tool to fill Markdown's gaps.
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This story was written by: @nfrankel. Learn more about this writer by checking @nfrankel's about page, and for more stories, please visit hackernoon.com.

Markdown is a lightweight markup language for creating formatted text using a plain-text editor. John Gruber created Markdown in 2004 as an easy-to-read markup language. Markdown is amazing, but it has strong limitations.

This story was originally published on HackerNoon at: https://hackernoon.com/when-even-the-cloud-caught-a-cold-inside-the-aws-and-azure-outages-of-2025.
In October 2025, AWS and Azure suffered major outages, exposing the fragility of the cloud and redefining resilience for modern internet infrastructure.
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This story was written by: @mayukhsuri. Learn more about this writer by checking @mayukhsuri's about page, and for more stories, please visit hackernoon.com.

In October 2025, both AWS and Microsoft Azure—the pillars of today’s cloud—suffered massive outages just nine days apart. AWS US-EAST-1 collapsed under DNS and DynamoDB control-plane failures, while Azure Front Door spread a faulty global config that broke routing and authentication across Microsoft 365, Outlook, and Teams. The twin incidents exposed how fragile the “always-on” internet really is and cost billions in downtime. The key lesson? High availability isn’t true resilience. Multi-region setups aren’t enough; automate health checks, test failovers, and design for failure as the default. In the cloud era, resilience is not a feature—it’s a culture.

This story was originally published on HackerNoon at: https://hackernoon.com/why-power-flexible-ai-just-became-table-stakes.
The questions investors should ask about AI data centers just changed. Why power flexibility is now table stakes for infrastructure deployment.
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This story was written by: @asitsahoo. Learn more about this writer by checking @asitsahoo's about page, and for more stories, please visit hackernoon.com.

AI infrastructure's real constraint: power, not chips. Aurora AI Factory (NVIDIA/Emerald, Virginia, 96MW, 2026) implements interruptible compute—software layer throttles training during grid stress, delivers 20-30% reductions, maintains SLAs. Enables faster permitting, lower capacity charges, wholesale market participation. Trade-off: longer training times for cheaper power. Key question: will two-tier market emerge (fixed for inference, flex for training)? 100GW capacity unlock claim assumes perfect coordination—directionally correct but optimistic. Power flexibility now mandatory for deployment. Due diligence questions: demand response capability, interruptible/fixed split, interconnection impact.