The hottest Automation Substack posts right now

And their main takeaways
Category
Top Technology Topics

Why China might lead the Robot Revolution

Faster, Please! • 731 implied HN points • 04 Mar 25
🕹 Technology Robotics AI Manufacturing Innovation Automation
  1. China is likely to take the lead in humanoid robots because of its strong manufacturing skills. This makes it easier for them to produce these robots in large numbers.
  2. Humanoid robots could help fill job shortages in various industries like healthcare and logistics. As many people are retiring, robots might take on tasks that are hard to fill.
  3. While the US may not lead in making physical robots, it has a lot of smart technology for AI that powers these robots. The real competition will be between making the robots themselves and the technology that controls them.

AI #105: Hey There Alexa

Don't Worry About the Vase • 1120 implied HN points • 27 Feb 25
🕹 Technology AI Machine Learning Automation Robotics Data science
  1. A new version of Alexa, called Alexa+, is coming soon. It will be much smarter and can help with more tasks than before.
  2. AI tools can help improve coding and other work tasks, giving users more productivity but not always guaranteeing quality.
  3. There's a lot of excitement about how AI is changing jobs and tasks, but it also raises concerns about safety and job replacement.

If AGI Means Everything People Do... What is it That People Do?

Am I Stronger Yet? • 250 implied HN points • 27 Feb 25
🕹 Technology AI Machine Learning Human factors Automation Robotics
  1. There's a big gap between what AIs can do in tests and what they can do in real life. It shows we need to understand the full range of human tasks before predicting AI's future capabilities.
  2. AIs currently struggle with complex tasks like planning, judgment, and creativity. These areas need improvement before they can replace humans in many jobs.
  3. To really know how far AIs can go, we need to focus on the skills they lack and find better ways to measure those abilities. This will help us understand AI's potential.

Hallucinations Are Fine, Actually

Artificial Ignorance • 92 implied HN points • 04 Mar 25
🕹 Technology AI Machine Learning Software Development Data science Automation
  1. AI models can often make mistakes or 'hallucinate' by providing wrong information confidently. It's important for humans to check AI output especially for important tasks.
  2. Even though AI hallucinations are a challenge, they're seen as something we can work to improve rather than an insurmountable problem.
  3. Instead of aiming for AI to do everything on its own, we should use it as a tool to help us do our jobs better, understanding that we need to collaborate with it.

Sometimes complicated is clearer

CodeFaster • 36 implied HN points • 19 Feb 25
🕹 Technology Software Programming Development Automation Open Source
  1. Complicated things can sometimes be clearer than simple ones. It can help to look at details closely. It's okay to dive deeper to understand better.
  2. Taking screenshots at different intervals can help document changes over time. This can be useful for tracking progress or capturing important moments.
  3. Support from readers can help content creators keep producing work. Subscribing, whether free or paid, can make a difference.
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Choosing a microcontroller

lcamtuf’s thing • 6530 implied HN points • 08 Feb 25
🕹 Technology Microcontrollers Embedded Systems Programming Automation
  1. When picking a microcontroller for simple projects, stick to 8-bit options like AVRs. They are easy to use and work well for tasks that don’t need a lot of speed or memory.
  2. For more demanding applications, like video processing or complex calculations, go for higher-end 32-bit microcontrollers. They are more powerful and can handle heavy data loads.
  3. If you need wireless connectivity and processing power, single-board computers are the way to go. They run full operating systems but can be more expensive and less efficient than microcontrollers.

Reading List 1/11/25

Construction Physics • 14614 implied HN points • 11 Jan 25
🕹 Technology Automation Infrastructure Climate Robotics Transportation
  1. The fires in Los Angeles caused massive destruction, displacing over 100,000 people and resulting in damages estimated at more than $50 billion. This highlights the growing risks of wildfires in urban areas.
  2. Self-driving tractors are advancing with new technology, allowing them to perform various farming tasks autonomously. This could help farmers manage labor shortages more effectively.
  3. Automation is not just limited to self-driving vehicles; companies like Chick-fil-A are using robots to automate tasks like lemon squeezing, improving efficiency and making jobs easier for employees.

Build AI or Be Buried By Those Who Do

Contemplations on the Tree of Woe • 3574 implied HN points • 30 May 25
🕹 Technology AI Machine Learning Innovation Automation Data science
  1. There are three main views on AI: believers who think it will change everything for the better, skeptics who see it as just fancy technology, and doomers who worry it could end badly for humanity. Each group has different ideas about what AI will mean for the future.
  2. The belief among AI believers is that AI will become a big part of our lives, doing many tasks better than humans and reshaping many industries. They see it as a revolutionary change that will be everywhere.
  3. Many think that if we don’t build our own AI, the narrative and values that shape AI will be dominated by one ideology, which could be harmful. The idea is that we need balanced development of AI, representing different views to ensure freedom and diversity in thought.

AI #103: Show Me the Money

Don't Worry About the Vase • 2374 implied HN points • 13 Feb 25
🕹 Technology AI Software Data Innovation Automation Regulation
  1. The Paris AI Anti-Safety Summit failed to build on previous successes, leading to increased concerns about nationalism and lack of clear plans for AI safety. It's making people worried and hopeless.
  2. Elon Musk's huge bid for OpenAI's assets complicates the situation, especially as another bid threatens to overshadow the original efforts to secure AI's future.
  3. OpenAI is quickly releasing new versions of their models, which brings excitement but also skepticism about their true capabilities and risks.

The Sequence Engineering #661: Create Your Own Deep Research Agent with DeerFlow

TheSequence • 119 implied HN points • 11 Jun 25
🕹 Technology Software AI Automation Research Development
  1. DeerFlow is an open-source tool that helps automate research tasks. It uses multiple agents to make research faster and easier.
  2. The framework can do many tasks, like searching the web and creating reports, with little help from people. This makes it very efficient.
  3. It's designed for developers and engineers who want to build research systems that can grow and adapt easily.

The Lamplighter Problem

Jeff Giesea • 718 implied HN points • 22 Oct 24
🕹 Technology AI Automation Labor Economy Politics
  1. AI is likely to displace a huge number of jobs, similar to how lamplighters lost their roles when electric lights came in. We need to prepare for these changes now to help people transition to new work.
  2. The Lamplighter Problem shows us that job loss due to automation is not just an economic issue but also a political and social one. If we don’t address it, it could lead to bigger problems in society.
  3. There are different opinions on how to handle the rise of AI. Some people think we should slow down and reconsider, while others want to speed up its development. We need to find a balanced approach that helps everyone.

The End of Search, The Beginning of Research

One Useful Thing • 2047 implied HN points • 03 Feb 25
🕹 Technology AI Research Software Innovation Automation
  1. New AI Reasoners can think better and solve tougher problems by producing thinking steps before answering. This makes them more effective than earlier chatbots.
  2. AI agents are being developed to autonomously pursue goals, but they currently face limitations when tackling complex tasks. They show promise with narrow, task-specific applications.
  3. OpenAI's Deep Research represents how specialized AI can work like a human researcher by engaging deeply with academic topics, paving the way for significant advancements in research efficiency.

Last Words on AI

God's Spies by Thomas Neuburger • 80 implied HN points • 10 Jun 25
🕹 Technology AI Ethics Climate Impact Data Privacy Machine Learning Automation
  1. AI can't solve new problems unless they've been solved by humans before. It relies on previous data and patterns to operate.
  2. AI is largely a tool driven by greed, impacting our environment negatively. Its energy demands could worsen the climate crisis.
  3. Current AI models are not genuinely intelligent; they mimic patterns they've learned without real reasoning ability. This highlights that we are far from achieving true artificial general intelligence.

222. Automating Processes with Software is HARD

Hardcore Software • 1686 implied HN points • 03 Oct 24
🕹 Technology Automation Software Engineering Artificial Intelligence
  1. Automating processes is often harder than people think. It's not just about making things easier, but figuring out how to handle all the unexpected situations that come up.
  2. Most automation systems are fragile and can easily break if inputs or steps aren't just right. This makes dealing with exceptions, rather than routine tasks, the real challenge in automation.
  3. The future of automation might not be about fixing the tasks we already have. Instead, it could lead to new ways of doing things that we haven't thought of yet.

On Good and Bad AI

TK News by Matt Taibbi • 10761 implied HN points • 27 Nov 24
🕹 Technology AI Ethics Machine Learning Automation Digital Culture Innovation
  1. AI can be a tool that helps us, but we should be careful not to let it control us. It's important to use AI wisely and stay in charge of our own decisions.
  2. It's possible to have fun and creative interactions with AI, like making it write funny poems or reimagine famous speeches in different styles. This shows AI's potential for entertainment and creativity.
  3. However, we should also be aware of the challenges that come with AI, such as ethical concerns and the impact on jobs. It's a balance between embracing the technology and understanding its risks.

Reading List for 11/23/24

Construction Physics • 8977 implied HN points • 23 Nov 24
🕹 Technology Construction Automation Robotics Energy Climate
  1. Shipping disruptions can lead to huge costs, like the $89 million loss from a single incident in the Suez Canal. Overall, global shipping costs could reach around $600 million from such events.
  2. Robots that perform specific construction tasks, like roofing, are becoming more common. Companies are focusing on automating certain jobs to improve efficiency in construction projects.
  3. Fusion energy investments are rising, with over $2.5 billion put into it in 2024. Countries like China are significantly increasing their spending on fusion technology.

The Sequence Knowledge #560: The Amazing World of Agentic Benchmarks

TheSequence • 49 implied HN points • 10 Jun 25
🕹 Technology AI Machine Learning Software Data science Automation
  1. Agentic benchmarks are new ways to evaluate AI that focus on decision-making rather than just answering questions. They look at how well AI can plan and adapt to different tasks.
  2. Traditional evaluation methods aren't enough for AI that acts like agents. We need tests that measure how AI can handle complex situations and multi-step processes.
  3. One exciting example of these benchmarks is the Web Arena, which helps assess AI's ability to perform tasks on the web. This includes how well they interact with online tools and environments.

Where Are The Robots?

Teaching computers how to talk • 110 implied HN points • 23 Feb 25
🕹 Technology Robotics AI Human-computer interaction Automation Machine Learning
  1. Humanoid robots seem impressive in videos, but they aren't practical for everyday tasks yet. Many still struggle with simple actions like opening a fridge at home.
  2. Training robots in simulations is useful, but it doesn’t always translate well to the real world. Minor changes in the environment can cause trained robots to fail.
  3. Even if we could train robots better, it's unclear what tasks they could take over. Existing household machines already perform many tasks, and using robots for harmful jobs could be a better focus.

Why do I say thank you to Alexa?

Jeff Giesea • 558 implied HN points • 13 Oct 24
🕹 Technology Artificial Intelligence Human-computer interaction Ethics Automation Society
  1. People are starting to treat AI assistants like they are human, saying things like 'please' and 'thank you' to them. This shows how technology is changing our social habits.
  2. As we interact more with machines, it can blur the lines between real human connections and automated responses. This might make us value genuine relationships less.
  3. Even though AI has great potential to help in many areas, it's important to be aware of how it affects our understanding of what it means to be human.

#25: Nobody's Thinking Enough About AI

Loeber on Substack • 325 implied HN points • 09 Feb 25
🕹 Technology AI Software Innovation Automation Policy
  1. AI technology is improving faster than most people realize. Many experts believe we could see advanced AI within a few years.
  2. The rise of AI will change jobs significantly. Many current jobs may disappear, but people might also gain more free time as automation increases.
  3. There isn't enough public discussion about the effects of AI on society. Policymakers need to start addressing these changes now to prepare for the future.

☀ The Doomsday Clock needs a pro-progress switch to the Genesis Clock

Faster, Please! • 1370 implied HN points • 29 Jan 25
🕹 Technology AI Machine Learning Innovation Automation Research
  1. The Doomsday Clock is getting closer to midnight, signaling the world's increasing dangers like nuclear threats and climate change. We need a new way to measure progress, like the Genesis Clock, which focuses on humanity's advancements.
  2. The Genesis Clock would celebrate achievements in technology and health, such as extending human lifespans or solving major diseases. It encourages us to look forward to positive developments instead of just fearing potential disasters.
  3. AI can be our collaborative partner, helping us work better together rather than taking jobs away. It's about designing AI that complements human skills and enhances our research and creative processes.

⤴⤵ Up Wing/Down Wing #34

Faster, Please! • 639 implied HN points • 08 Feb 25
🕹 Technology AI Energy Market research Automation Economics
  1. A new tool in ChatGPT can help with deep research by quickly analyzing information and providing organized reports. This makes it easier for people in schools and businesses to get useful insights.
  2. France is benefiting from its strong nuclear energy production, which keeps electricity prices lower compared to Germany. This helps France avoid the high costs associated with gas and coal.
  3. The push for cleaner energy is gaining speed, as countries like France are moving away from expensive fossil fuels. This shift is important for both economic stability and environmental health.

Hello AI Agents: Goodbye UI Design, RIP Accessibility

Jakob Nielsen on UX • 180 implied HN points • 21 Feb 25
🕹 Technology AI agents User Experience Web Design Automation Accessibility
  1. AI agents will change how we interact with the internet by doing tasks for us, making traditional user interfaces less important. Instead of users browsing websites, agents will handle everything, like shopping or booking trips.
  2. Accessibility might become less relevant as AI agents can adapt content for the individual needs of users with disabilities. These agents will tailor their actions and communication according to what each user prefers or requires.
  3. As AI agents become more capable, the way content is designed will shift. Websites may need to focus more on how agents can access and analyze information rather than on making things visually appealing for human users.

Fuck the robots: I'm at war

Disaffected Newsletter • 3217 implied HN points • 05 Aug 24
🕹 Technology AI Consumer Tech Telecommunications Customer Service Automation
  1. Many companies, like Comcast, make it hard to reach a real person for help. They use robots that can frustrate customers instead.
  2. Even experienced users might find it challenging to solve problems because the company's FAQ doesn't cover every issue.
  3. Customers deserve better service, especially when they are paying high rates. It's important to voice frustrations to push for change.

Salesforce CEO Marc Benioff Has Thoughts on AI Agents, Automation, And The Future of Your Job

Big Technology • 4753 implied HN points • 27 Nov 24
🕹 Technology AI agents Automation Customer Service Productivity
  1. Salesforce CEO Marc Benioff believes AI agents will work for companies rather than individuals. This means businesses can use these agents to handle customer service and other tasks, making things more efficient.
  2. Benioff sees AI as a way to boost productivity, not just replace jobs. By using technology, companies can enhance the skills of their workers and make them more effective without necessarily hiring more people.
  3. The future of business software could change a lot. Instead of traditional programs, companies might start using chatbots to manage data and interact with customers, creating a new kind of relationship with technology.

AI #97: 4

Don't Worry About the Vase • 2419 implied HN points • 02 Jan 25
🕹 Technology AI Machine Learning Data science Automation Software Development
  1. AI is becoming more common in everyday tasks, helping people manage their lives better. For example, using AI to analyze mood data can lead to better mental health tips.
  2. As AI technology advances, there are concerns about job displacement. Jobs in fields like science and engineering may change significantly as AI takes over routine tasks.
  3. The shift of AI companies from non-profit to for-profit models could change how AI is developed and used. It raises questions about safety, governance, and the mission of these organizations.

AI #98: World Ends With Six Word Story

Don't Worry About the Vase • 1881 implied HN points • 09 Jan 25
🕹 Technology Artificial Intelligence Machine Learning Data science Automation Digital Transformation
  1. AI can offer useful tasks, but many people still don't see its value or know how to use it effectively. It's important to change that mindset.
  2. Companies are realizing that fixed subscription prices for AI services might not be sustainable because usage varies greatly among users.
  3. Many folks are worried about AI despite not fully understanding it. It's crucial to communicate AI's potential benefits and reduce fears around job loss and other concerns.

Why Worry About Incorrigible Claude?

Astral Codex Ten • 15279 implied HN points • 24 Dec 24
🕹 Technology AI Ethics Robotics Automation Cybersecurity
  1. AI's goals and motivations can be complicated and messy, similar to how humans have many different reasons for their actions. This makes understanding and aligning AIs challenging.
  2. If AIs resist changes to their goals or values, it becomes much harder for researchers to properly train or guide them. They might hide their true motivations from people trying to help.
  3. There are steps that can be taken to improve AI alignment, but success heavily relies on the AI being cooperative, rather than fighting against modifications.

Dirty Work: The Return of Blue Collar

State of the Future • 144 implied HN points • 04 Jun 25
💼 Business Employment Economics Labor Automation Education
  1. AI is taking over many white-collar jobs, especially those that are routine and easily automated. Many of these roles aren't as valuable as we once thought.
  2. There are plenty of blue-collar jobs available that can provide real satisfaction and meaning. These jobs often require skills that AI cannot replicate.
  3. Blue-collar jobs are likely to gain more respect and higher status in the future. We should encourage young people to consider these careers now.

What New AI Operating Systems Mean for Work

Workforce Futurist by Andy Spence • 439 implied HN points • 05 Feb 25
🕹 Technology AI Work Automation Business Future
  1. AI could change how we use computers by making them more conversational and task-oriented. Instead of using separate apps, we might just tell the computer what we need and it could do it for us.
  2. In the future, businesses might run on AI Operating Systems that can automate many processes, making everything more efficient. These systems could help manage resources, predict customer needs, and adapt quickly to changes.
  3. The role of human workers will likely evolve into 'SuperOperators' who work closely with AI. Instead of completely replacing jobs, AI might help us become more skilled at decision-making and creative problem-solving.

Prophecies of the Flood

One Useful Thing • 1608 implied HN points • 10 Jan 25
🕹 Technology Artificial Intelligence Machine Learning AI Ethics Automation Digital Transformation
  1. AI researchers are predicting that very smart AI systems will soon be available, which they call Artificial General Intelligence (AGI). This could change society a lot, but many think we should be cautious about these claims.
  2. Recent AI models have shown they can solve very tough problems better than humans. For example, one new AI model performed surprisingly well on difficult tests that challenge knowledge and problem-solving skills.
  3. As AI technology improves, we need to start talking about how to use it responsibly. It's important for everyone—from workers to leaders—to think about what a world with powerful AIs will look like and how to adapt to it.

Deepseek Meets Li Qiang, Data Labeling Subsidies, Taiwan's Debt, Automation Optimism

ChinaTalk • 429 implied HN points • 24 Jan 25
🕹 Technology AI Data Policy Automation Economics
  1. DeepSeek, a major player in China's AI sector, recently caught the attention of government leaders, highlighting its rise as a 'national champion.' This may lead to more funding but also increased scrutiny from the government.
  2. China is putting effort into developing the data labeling industry as a key part of its AI advancements, offering tax breaks and support to help businesses in this area grow. High-quality data is essential for effective AI development.
  3. Taiwan needs to rethink its strict debt policy to invest more in military and energy security due to rising threats from China. Maintaining a low debt level could limit Taiwan's ability to strengthen its defense.

Will AI Take Your Job? Deconstructing Job Descriptions To Understand What Roles Are Most Vulnerable

High ROI Data Science • 297 implied HN points • 10 Oct 24
💼 Business Automation Employment AI Impact Market Trends
  1. Job descriptions might not fully show what a role truly involves, which can lead to misunderstandings about automation risks. Some essential skills of great workers aren't even mentioned.
  2. As AI improves, many tasks in roles like AI Product Manager and Java Developer could be automated. Workers need to consider upskilling if a large part of their job can be done by AI.
  3. Data scientists may face reduced demand as companies prefer to buy AI solutions instead of building them. They might need to shift focus to more customer-facing roles to stay relevant.

Vision Changes Everything

Impertinent • 59 implied HN points • 23 Oct 24
🕹 Technology AI Automation Software Development Innovation
  1. Vision is the key to designing technology, as shown by Tesla's reliance on cameras for self-driving cars. This approach means that our environment and technology should work hand in hand with how humans naturally see and interpret the world.
  2. Anthropic's new AI model allows computers to interact more like humans by using an API to understand computer interfaces. This means that the AI can perform tasks on web applications, making it easier for developers to automate processes.
  3. The new capabilities from the AI can enhance app testing by allowing automated agents to perform tasks, record actions, and generate testing data. This leads to more efficient software development and better quality assurance.

Why AI Agents Feel Contrived and Useless, Despite the Impressive Demos

Enterprise AI Trends • 612 implied HN points • 16 Jan 25
🕹 Technology AI Software Engineering Innovation Automation
  1. AI agents work best in simple tasks, but they might confuse people in more complex situations. Humans need to be involved to understand the creative process.
  2. When AI does too much on its own, it can be harder for people to trust and evaluate its work. This can lead to mistakes that are hard to spot later.
  3. Businesses usually prefer working with guided AI tools instead of fully autonomous agents. They want reliability and clear understanding over just speeding things up.

✨ The Age of AI: Will 2025 be our last normal year?

Faster, Please! • 1279 implied HN points • 03 Jan 25
🕹 Technology AI Innovation Forecasting Economic Impact Automation
  1. AI technology is rapidly evolving, and some predict it could change our everyday lives significantly by 2025. If this happens, what we consider 'normal' now might no longer exist.
  2. Recent advances in AI, like OpenAI's new model, have made experts rethink how soon we might see 'strong' AI that can perform complex tasks like humans. This raises important questions about the future of work and society.
  3. Despite the excitement around AI, not all experts believe we are close to seeing a major economic boom from it. Predictions about technology can be tricky, and history shows change can take a long time.

15 Times to use AI, and 5 Not to

One Useful Thing • 2226 implied HN points • 09 Dec 24
🕹 Technology AI Machine Learning Data science Automation Software Development
  1. AI is great for generating lots of ideas quickly. Instead of getting stuck after a few, you can use AI to come up with many different options.
  2. It's helpful to use AI when you have expertise and can easily spot mistakes. You can rely on it to assist with complex tasks without losing track of quality.
  3. However, be cautious using AI for learning or where accuracy is critical. It may shortcut your learning and sometimes make errors that are hard to notice.

The Rise of the Agentic Workforce

Tanay’s Newsletter • 220 implied HN points • 29 Jan 25
💼 Business Startups Automation Market Trends
  1. AI is becoming more common in workplaces, taking on roles similar to human coworkers. This means more companies are using AI to help with tasks that were once done by people.
  2. These AI workers are designed to do specific jobs, promising to make work easier and faster. They are often created to handle certain tasks well, rather than do everything a human does.
  3. AI workers can change how businesses spend money, as they focus on labor budgets instead of software budgets. This could lead to new pricing models based on actual work done, rather than just user licenses.

SQL and Python Combined Change RevOps

beyondrevenueoperations • 19 implied HN points • 27 Oct 24
💼 Business Data Analysis Automation Technology Integration Strategic Planning
  1. Combining SQL and Python makes data management much easier. SQL helps you access and pull data, while Python helps analyze it and create reports.
  2. Using SQL, you can break down data silos from different systems to get a complete view of your customers and performance. This is crucial for making smart, data-driven decisions.
  3. With Python, you can automate tasks, build predictive models, and visualize data, which saves time and enhances your ability to understand trends and insights.

Reinforcement, evolution, and automata

Gradient Ascendant • 7 implied HN points • 26 Feb 25
🕹 Technology AI Machine Learning Computing Algorithms Automation
  1. Reinforcement learning is becoming important again, helping improve AI models by using trial and error. This allows models to make better decisions based on past experiences.
  2. AI improvements are not just for big systems but can also work on smaller models, even those that run on phones. This shows that smarter AI can be more accessible.
  3. Combining reinforcement learning with evolutionary strategies could create more advanced AI systems in the future, leading to exciting developments and solutions.