The hottest Automation Substack posts right now

And their main takeaways
Category
Top Technology Topics

How AI generates text, visually explained 📝

Year 2049 • 6 implied HN points • 18 Jan 25
🕹 Technology AI Machine Learning Automation Data science Software Development
  1. AI generates text by analyzing patterns in data, similar to how a DJ mixes music. This means it learns from examples to create new content.
  2. Understanding how AI learns helps us see its strengths and weaknesses, like how it can sometimes be biased.
  3. The next episode will focus on how AI creates images, which is another interesting aspect of how AI works.

Making Sense of Agentic AI | ThoughtWorks’ Birgitta Boeckeler

Dev Interrupted • 28 implied HN points • 12 Nov 24
🕹 Technology AI Software Programming Development Automation
  1. AI tools can help software teams improve their work, but it's important to pick the right ones that actually make a difference. Sometimes the hype around AI doesn't match up with real-world results.
  2. Governance matters when it comes to programming languages. A strict control model can limit a language's potential for growth, so a more open approach might be better.
  3. Reddit is gaining popularity as users appreciate its less polished, more authentic content. It shows that not all platforms need to rely heavily on AI to attract people.

Agentic AI: Creating An AI Agent Which Can Navigate The Internet

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 17 Jul 24
🕹 Technology AI Web Development Machine Learning Multimodal models Automation
  1. WebVoyager is an AI agent that can browse the web by analyzing screenshots and deciding what to do next. It works like a human browsing the internet, using both visual and text information.
  2. The agent interacts with webpages by performing actions like clicking, scrolling, and typing. This allows it to complete tasks on websites without needing help from humans.
  3. WebVoyager's ability to handle complex web navigation shows the potential of AI agents to perform useful tasks autonomously. It learns to navigate better by using real-world websites rather than just simplified models.

Spacetech Failures: Analyzing Major Industry Missteps and Lessons for Investors

Space Ambition • 259 implied HN points • 29 Sep 23
🕹 Technology Space Tech Investing Engineering Automation Entrepreneurship Market Dynamics
  1. The spacetech industry has seen many failures, like Iridium's bankruptcy and Falcon 1's launch issues, but these stories show how important it is to adapt and learn from mistakes.
  2. Space exploration is getting increasingly crowded and risky with satellite constellations like Starlink, which raises concerns about space debris and potential collisions in orbit.
  3. The integration of AI in space missions is still developing, and while AI can help reduce human errors, we need to carefully test and approve these systems for safe use in space.
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What Is a Software Simulator?

CodeYam’s Substack • 39 implied HN points • 04 Jun 24
🕹 Technology Software Simulations AI Testing Automation
  1. Simulators are valuable tools leveraged by inventors and engineers throughout history to test ideas quickly and gain insights into complex problems.
  2. A robust software simulator has qualities like a simulated environment, scenarios, isolation, and automation, which can significantly speed up the software development process.
  3. Software simulators allow testing how software performs in various scenarios, enabling faster delivery of high-quality products without the need for extensive manual testing.

The Sequence Opinion #470: Open Endedness AI Could be All We Need

TheSequence • 49 implied HN points • 16 Jan 25
🕹 Technology AI Research Machine Learning Innovation Automation
  1. Open-Endedness AI focuses on creating systems that can learn and adapt over time, rather than just completing specific tasks. This allows AI to innovate and find new solutions continuously.
  2. This new approach to AI research aims for something called artificial general intelligence (AGI), which means AI that can perform a wide range of tasks like a human can. It's a big step towards smarter technology.
  3. However, developing Open-Endedness AI comes with challenges. Researchers must find ways to ensure these systems can learn effectively without becoming unreliable or out of control.

Prompting GPT-4 From CSV to PDF: Automated On-the-Fly Data Viz Reports

Data at Depth • 79 implied HN points • 29 Mar 24
🕹 Technology Automation Data Visualization AI
  1. GPT-4 can now create PDF files from data on-the-fly, right in its main prompt window.
  2. The GPT-4 interface has recently undergone significant changes, integrating separate tools and plug-ins like the Advanced Data Analysis tool.
  3. You can subscribe to Data at Depth for a 7-day free trial to access full post archives, including detailed information on automating PDF reports from raw CSV data.

The midwit home

DYNOMIGHT INTERNET NEWSLETTER • 416 HN points • 12 Oct 23
🕹 Technology Sensors Automation
  1. Smart homes can be complicated and require a lot of technical knowledge to set up and maintain.
  2. Simple, midwit solutions like remote-controlled outlets, motion-sensing bulbs, and mechanical outlet timers can make daily tasks easier and more convenient.
  3. Using basic power control for devices can offer a surprisingly effective and user-friendly home automation experience.

E10 - Future Trends: Gen AI and the Next Generation of Products

The Product Channel By Sid Saladi • 6 implied HN points • 16 Jan 25
🕹 Technology AI Product Management Innovation Automation Data Analysis
  1. Generative AI is reshaping industries by creating new opportunities and enhancing product development. It's not just a technology; it can change the way we work and create.
  2. Real-world examples, like DeepMind's AlphaFold, show how generative AI can lead to breakthroughs in fields like healthcare, making processes faster and more efficient.
  3. Product managers should harness generative AI to create better user experiences. By integrating this technology, they can offer more personalized and engaging products.

Evaluating The Quality Of RAG & Long-Context LLM Output

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 08 Jul 24
🕹 Technology AI NLP Machine Learning Data science Automation
  1. Evaluating the performance of RAG and long-context LLMs is tough because there isn't a common task to compare them on. This makes it hard to know which system works better.
  2. Salesforce created a new way to test these models called SummHay, where they summarize information from large text collections. The results show that even the best models struggle to match human performance.
  3. RAG systems generally do better at citing sources, while long-context LLMs might capture insights more thoroughly but have citation issues. Choosing between them involves trade-offs.

Robot Nags

David Friedman’s Substack • 242 implied HN points • 10 Feb 24
🕹 Technology Smartwatches Artificial Intelligence User Experience Automation Privacy
  1. Technology like smart watches and apps can provide constant reminders or notifications, sometimes without the option to stop them.
  2. Encouraging reading habits through rewards or forced reading can have unintended consequences, such as making reading seem like a chore to children.
  3. Various instances of 'robot nags' exist in everyday technology, aimed at influencing behavior or decision-making, sometimes intrusively.

5 SIEM Capabilities for Detection Engineering

Detection at Scale • 59 implied HN points • 15 Apr 24
🕹 Technology Security Data Management Automation Cloud Computing Programming
  1. Detection Engineering involves moving from simply responding to alerts to enhancing the capabilities behind those alerts, leading to reduced fatigue for security teams.
  2. Key capabilities for supporting detection engineering include a robust data pipeline, scalable analytics with a security data lake, and embracing Detection as Code framework for sustainable security insights.
  3. Modern SIEM platforms should offer an API for automated workflows, BYOC deployment options for cost-effectiveness, and Infrastructure as Code capabilities for stable long-term management.

These 7 Software Engineering Skills Give You an Unfair Advantage

Brain Bytes • 119 implied HN points • 17 Jan 24
🕹 Technology Software Engineering Cybersecurity Automation Version Control Cloud Computing
  1. Thinking like a hacker helps in identifying and fixing security flaws before they are exploited, crucial in today's cybersecurity landscape.
  2. Understanding different devices through cross-platform critical thinking gives a competitive edge and promotes reusability of business logic.
  3. Scripting and automation for repetitive tasks enhances productivity by ensuring consistency, accuracy, and freeing up time for more complex work.

AI With “Computer Use”: Agents, Accessibility Fix, Facilitating Usability Tests

Jakob Nielsen on UX • 27 implied HN points • 07 Nov 24
🕹 Technology AI User Experience Accessibility Automation Research Methods
  1. AI can now operate computers just like humans, which means it can click, type, and understand what’s on the screen. This makes using computers easier for everyone, especially for those who struggle with traditional interfaces.
  2. AI agents are expected to take over simple tasks for users, like booking hotels or managing reservations, making life more convenient. However, understanding personal preferences may take some time for AI to improve.
  3. AI's capability to watch and analyze user interactions can help conduct usability studies more effectively. This could lead to better products, as AI can help gather insights about how real users behave.

Unleashing LLMs in Cybersecurity: A Playbook for All Industries

Gradient Flow • 259 implied HN points • 20 Apr 23
🕹 Technology Cybersecurity AI Automation Data Analysis Software Development
  1. Large Language Models (LLMs) are gaining interest in various industries, especially in cybersecurity, and can be used as a playbook for implementation in other domains.
  2. Custom LLMs can be created for cybersecurity applications, leading to potential advancements like specialized chatbots and content generation for enhanced security measures.
  3. LLMs are transforming automation processes in cybersecurity, offering improved accuracy and convenience, and displaying potential for impact across multiple industries through domain-specific adaptations.

AI for Small Business Owners

The Small Business Corner • 39 implied HN points • 16 May 24
🕹 Technology AI Automation Marketing Workflow Content creation
  1. People tend to react to new technology in one of three ways: celebrate it, bash it, or adopt it pragmatically.
  2. AI tools can significantly benefit small business owners by saving time, cutting costs, and enhancing productivity.
  3. Adopting AI tools strategically into business processes can lead to efficiency, cost reduction, and innovation, helping small businesses stay competitive.

How to Learn Like Humans Do

Cybernetic Forests • 199 implied HN points • 06 Aug 23
🎨 Art & Illustration Artificial Intelligence Creative Process Automation
  1. AI is designed to learn and make art the way humans do, as AI models are replicas of the human brain.
  2. The process of creating art historically involved specific, defined steps that have been automated by AI, making art production more efficient and accessible.
  3. AI has streamlined the traditional artistic process, removing inefficiencies and making art creation more uniform and universally accessible.

Job Cuts Due to AI: What to Make of Them?

Last Week in AI • 298 implied HN points • 28 Jul 23
🕹 Technology AI Automation Jobs Economy Innovation
  1. Some workers are losing jobs due to advancements in AI technology like ChatGPT.
  2. Predictions vary on the impact of AI on future jobs, with some foreseeing significant automation that could affect millions of jobs globally.
  3. We are still in a transitional phase with AI technology, and the impact on the workforce is heterogeneous, with job cuts stemming from various economic factors.

Hybrid Evaluation: Scaling human feedback with custom evaluation models

LLMs for Engineers • 159 implied HN points • 15 Nov 23
🕹 Technology AI Machine Learning Human feedback Automation
  1. Human feedback is still very important for evaluating models, especially in areas like customer support, but it can slow things down and increase costs.
  2. Combining human input with automated, model-based evaluation can help improve efficiency and accuracy, reducing errors significantly.
  3. Using fewer human-labeled examples with smart bootstrapping techniques can still yield good results, making it cheaper and faster to train evaluation models.

Intents: the end-game for computing interfaces?

Router by Dmitry Pimenov • 2 HN points • 11 Sep 24
🕹 Technology Interfaces Programming AI Computing Automation
  1. Computing interfaces are evolving from specific command-based systems to more user-friendly methods that focus on overall goals. This makes it easier for developers to work on what really matters instead of getting bogged down in details.
  2. Intent-driven interfaces allow us to express our thoughts directly to machines, removing the need for complicated steps. This means we can communicate what we want in a more natural way.
  3. The rise of AI and new technologies is shifting how we interact with computers. Soon, we may even communicate our intentions directly from our minds, making technology feel more personal and easier to use.

How to metacognate

Sunday Letters • 99 implied HN points • 29 Jan 24
🕹 Technology AI Programming Machine Learning Cognition Data Automation
  1. Working with complex models can be hard when they get confused by incorrect or incomplete information. This can lead to mistakes and conflicts in what they remember.
  2. Creating a stable pattern for how tasks are done can help models work better by giving them a solid structure to follow. This is like giving the model a framework to lean on for more complicated tasks.
  3. As models improve, the need for extra coding to guide their thinking may lessen. Better memory strategies will likely help them function more effectively over time.

The rise of AI work

The AI Frontier • 5 HN points • 22 Aug 24
🕹 Technology AI Data Productivity Workforce Automation
  1. AI products should focus on automating work that humans often find tedious. This helps measure their true value to consumers and businesses.
  2. Companies can choose to specialize deeply in one area or offer a broad service across multiple tasks. Each approach has its own strengths and weaknesses.
  3. Finding a middle ground might be beneficial, as it allows companies to manage a workflow that spans several tasks, though they should focus on making sure their quality remains high.

📽 Fully Virtual: Agents in Production

TheSequence • 77 implied HN points • 01 Nov 24
🕹 Technology AI Machine Learning Software Development Virtual Events Automation
  1. There's a virtual event coming up on November 13, 2024, about using AI agents in different industries. It's a great chance to learn from experts about real-world uses and strategies.
  2. The event features speakers from well-known companies like Hugging Face and OpenAI. You can connect with leaders in AI and machine learning.
  3. If you're interested, you can register for free to join and explore how AI can help in areas like e-commerce and customer service.

AGI Emergence: Tracing the Path from Artificial Narrow Intelligence to the Birth of Superintelligence

The Future of Life • 39 implied HN points • 08 May 24
🕹 Technology Artificial Intelligence Machine Learning Automation Innovation Digital Trends
  1. AI is evolving through different levels, starting from basic text generation to more advanced reasoning and problem-solving abilities.
  2. As AI develops, it will be able to perform tasks across various domains, becoming competitive with humans in many jobs.
  3. Eventually, AI may reach a point of superintelligence, where it surpasses human understanding and decision-making abilities, posing potential risks if not aligned with human values.

FlowMind Is An Automatic Workflow Generator

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 25 Jun 24
🕹 Technology AI Automation Workflow Data science Programming
  1. FlowMind is a new tool that helps create automatic workflows using advanced AI. It takes user requests and generates code to complete tasks quickly.
  2. The system uses APIs to gather information and provides real-time feedback, allowing users to adjust the workflows as needed. This makes the process more interactive.
  3. FlowMind aims to improve the reliability of AI by reducing errors and making sure there is no direct connection to sensitive data. It focuses on keeping user data safe while handling requests.

AI Agents & Marketing: It's Weird.

The Digital Anthropologist • 19 implied HN points • 24 Jun 24
🕹 Technology AI Marketing Ethics Data science Automation
  1. In the future, marketers might need to create separate campaigns for humans and AI agents, requiring unique approaches for each audience.
  2. Marketing teams are facing the challenge of designing campaigns that cater to both human and AI customers, necessitating the development of dual marketing strategies and content.
  3. The integration of AI agents in marketing campaigns has led to increased costs and complexities, requiring specialized roles, technologies, and strategies to navigate successfully.

They're Lying To You About AI Agents

Theology • 29 implied HN points • 30 Jan 25
🕹 Technology AI Digital Transformation Organizational Change Automation
  1. Businesses need to understand their own processes before using AI. If they don't know how things work, they can't expect AI to help them effectively.
  2. Using many different AI agents can make things more complicated, not easier. It could create a messy system that is hard to manage.
  3. AI agents can't replace human intuition or creativity. They follow strict rules and won't come up with new ideas or solutions.

Round-Up of the Yocto Project Summit 2023.11

burkhardstubert • 59 implied HN points • 18 Mar 24
🕹 Technology Embedded Systems Software Development Open Source Continuous Integration Automation
  1. Implementing a fallback mechanism during system updates is crucial. If an update fails, it can prevent endless reboots by reverting to a stable version.
  2. Keeping your Yocto project layers simple can reduce maintenance and complexity. Using minimal layers can help avoid outdated code and improve build efficiency.
  3. Setting up a CI pipeline for Yocto builds can simplify the development process. It provides ready-to-use images for developers without requiring deep knowledge of Yocto.

How many robotaxis are there in the world today?

Alex's Personal Blog • 32 implied HN points • 09 Oct 24
🕹 Technology Transportation Automation Artificial Intelligence Mobility Innovation
  1. There are currently hundreds of robotaxis operating in the United States, with Waymo and Cruise leading the way. However, Tesla is also working on their own robotaxi plans.
  2. In China, thousands of robotaxis are already in use, with companies like Baidu expanding their fleets rapidly. This shows that the technology is advancing quickly in some parts of the world.
  3. The number of self-driving cars is expected to grow significantly in the coming years, potentially reaching tens of thousands in the U.S. and hundreds of thousands globally by 2026 or 2027.

Collaborative Markdown with Lix Change Control

Opral (lix & inlang) • 7 HN points • 07 Aug 24
🕹 Technology Software Development Version Control Automation
  1. Using Lix Change Control for Markdown makes collaborative writing better. It helps everyone work together smoothly and keeps track of changes easily.
  2. With Lix, you can make changes, submit them for review, and see who changed what. This makes it easy to approve or reject edits.
  3. Automation features let you set rules for content quality and manage updates or translations. This saves time and ensures the final product is accurate.

This is Why We Can't Have Nice Things

The Weasel Speaks • 157 implied HN points • 27 May 23
🕹 Technology AI Automation Software Development Generative models
  1. Agile has three main views in the industry: it doesn't work, it's taking away jobs, it accelerates value to customers.
  2. Technological disruptions often make people feel like their jobs are in jeopardy.
  3. AI stirs opinions: it's criticized for not working, it's accused of taking jobs, yet it can accelerate learning and revolutionize work.

Work & Leisure, The Debrief

The Novelleist • 564 implied HN points • 29 May 23
🎭️ Culture AI Automation Future Education
  1. Elle Griffin finished a series on work and leisure discussing important topics like AI, automation, and 20-hour workweeks.
  2. Paid subscribers can engage in discussions and be part of debriefs exploring capitalism, sparking insightful conversations.
  3. Community members also shared thought-provoking essays on work and leisure, adding more perspectives to the discourse.