The hottest AI Substack posts right now

And their main takeaways
Category
Top Technology Topics

2023: The year in weird and stupid futures

Read Max • 2054 implied HN points • 29 Dec 23
🕹 Technology AI
  1. Every year, Read Max reflects on weird and stupid futures.
  2. In 2023, there were absurd events like car heater pools from Bitcoin mining, A.I. chatbots causing problems, and more.
  3. Some notable occurrences in 2023 included tech CEOs making unusual decisions and governmental actions raising eyebrows.

From ChatGPT Back to Clay & Cuneiform: A Start at Rethinking Pedagogy for the Age of "AI"

Brad DeLong's Grasping Reality • 322 implied HN points • 31 May 25
🚌 Education AI
  1. Education needs to focus on what students should remember and be able to do, rather than just what they can get from AI like chatbots.
  2. Instead of banning AI, we should find ways to use it in learning, just like we adapted to calculators in math classes.
  3. Understanding the basics behind complex tools like AI is important, as all tools have limitations and can miss important details.

The new UX for AI is not what you think

Generating Conversation • 233 implied HN points • 24 Jul 25
🕹 Technology AI
  1. AI applications should work directly with the tools you use every day, like Slack or ticketing systems. This helps them fit into your existing workflows and makes them more useful.
  2. Building trust in AI is important. Users want to see what the AI is doing and have control over its actions. This means the AI should be clear about its decisions and allow feedback.
  3. The best AI products combine great integrations, transparency, and user control. When an AI feels like a team member that you can rely on, it adds real value.

The Sequence Radar #767: Last Week in AI: Google Logic, Amazon Utility, and Mistral Efficiency

TheSequence • 56 implied HN points • 07 Dec 25
🕹 Technology AI
  1. AI model development is changing focus from just making models bigger to making them smarter and more specialized. It's now about using different tools for specific tasks instead of one model for everything.
  2. Google's Gemini 3 Deep Think is a significant release that uses a new way of thinking to solve problems. It focuses on careful reasoning rather than quick responses, leading to much better problem-solving skills.
  3. Amazon's Nova 2 and Mistral's Large 3 provide new options for businesses by focusing on efficiency and privacy. These models allow companies to create tailored solutions without relying on large, generic AI models.
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Things I learned at the Tanda Hackathon 2025

Alex Ghiculescu's Newsletter • 67 implied HN points • 25 Nov 25
🕹 Technology AI
  1. Non-coders who can describe their ideas are becoming really effective, especially with AI coding tools. This means anyone can create impressive projects, even if they don't have a lot of coding experience.
  2. Many university students are unaware of the benefits of AI coding because schools often discourage its use. This gap in knowledge might be holding them back in their careers.
  3. There are actually job opportunities for new developers, especially for those willing to participate in hackathons. Showing up and building something can lead to great prospects.

Letters to a Young Investor: Reid Hoffman on Signals and Mirages

The Generalist • 1941 implied HN points • 16 Jan 24
💼 Business AI
  1. Investors need to differentiate between signals and mirages in venture capital to find potential winners.
  2. The process of identifying successful investments involves filtering out flawed ideas and making bets on plausible opportunities.
  3. Successful investments are like oases in the technology landscape that investors strategically seek out.

OK, I can partly explain the LLM chess weirdness now

DYNOMIGHT INTERNET NEWSLETTER • 796 implied HN points • 21 Nov 24
🕹 Technology AI
  1. LLMs like `gpt-3.5-turbo-instruct` can play chess well, but most other models struggle. Using specific prompts can improve their performance.
  2. Providing legal moves to LLMs can actually confuse them. Instead, repeating the game before making a move helps them make better decisions.
  3. Fine-tuning and giving examples both improve chess performance for LLMs, but combining them may not always yield the best results.

Understanding Goodhart's Law [Math Mondays]

Technology Made Simple • 179 implied HN points • 11 Mar 24
🕹 Technology AI
  1. Goodhart's Law warns that when a measure becomes a target, it can lose its effectiveness as a measure.
  2. The law often unfolds due to complications in real-world systems, human adaptability, and evolutionary pressures.
  3. To address Goodhart's Law, consider using multiple metrics, tying metrics to ultimate goals, and being prepared to adapt metrics as needed.

⚛ Atomic Amazon: The American nuclear revival takes another step forward

Faster, Please! • 913 implied HN points • 16 Oct 24
🕹 Technology AI
  1. Nuclear energy has remained a stable part of America's energy mix for decades, but the vision of it being the main power source faded after the 1970s. People once imagined a future where almost everything was powered by nuclear energy.
  2. Amazon is investing in new nuclear technology called small modular reactors. This move is aimed at meeting its growing energy needs, especially for its cloud services and to support its goal of being carbon neutral.
  3. The revival of nuclear energy could mean a shift in the way we think about power sources. Companies like Amazon are taking steps to explore innovative solutions to energy challenges.

It's A New Year, But Businesses Are Still Baffled By The Same Old Problems With Data And AI

High ROI Data Science • 317 implied HN points • 15 Jan 24
🕹 Technology AI
  1. CEOs face challenges with limited skills and expertise in implementing AI initiatives.
  2. Businesses struggle with data complexity and ethical concerns when it comes to utilizing AI.
  3. Companies need to align AI opportunities with business goals, estimate costs upfront, and prioritize continuous reskilling for successful AI implementation.

Weekly Dose of Optimism #156

Not Boring by Packy McCormick • 192 implied HN points • 08 Aug 25
🕹 Technology AI
  1. The U.S. Department of Energy is making strides in nuclear energy by partnering with companies to create safer, advanced fuel types. This could strengthen America's energy independence and reduce reliance on foreign uranium.
  2. OpenAI has launched GPT-5, an improved version of its AI model that offers better performance without replacing humans. It's a sign of ongoing progress in making AI tools more reliable and useful for everyday tasks.
  3. A new AI from Google, called Genie 3, can create interactive environments based on text prompts. This technology can change the way we think about gaming and virtual experiences, making them more dynamic and engaging.

‘Pronoun Illness’ 🤔

Sector 6 | The Newsletter of AIM • 99 implied HN points • 10 May 24
🕹 Technology AI
  1. LinkedIn's AI flagged a post as unsafe, causing some users to question the technology's bias. It's raising concerns about how social media platforms control content.
  2. There are calls for developing technology in India to avoid being influenced by foreign political agendas. People want more control over their digital spaces.
  3. OpenAI is working on a new tool called Media Manager. This tool will help creators manage how their work is used in AI training, aiming for more respect for their choices.

Introducing PricingSaaS MCP

Good Better Best • 2 implied HN points • 26 Feb 26
💼 Business AI
  1. Connect PricingSaaS MCP to your LLM (Claude, ChatGPT, or Gemini) to query PricingSaaS data directly; setup takes about two minutes.
  2. Use it for pricing, packaging, and product research to see what other companies have done and get tailored feedback for launches, credit models, or price changes.
  3. Monitor competitor pricing and get market summaries — pull recent pricing changes, request additions for missing competitors, and produce instant benchmarks consultants can use with clients.

Google rules the AI roost

Alex's Personal Blog • 65 implied HN points • 24 Nov 25
🕹 Technology AI
  1. GLP-1s are showing promise in helping with addiction treatment. They might change how we approach addiction care, offering a new tool beyond traditional methods.
  2. Microsoft is creating a marketplace where publishers can sell content for AI use. This could lead to better AI development while allowing content creators to earn from their work.
  3. Google's Gemini 3 Pro is currently leading the AI model race, surpassing competitors like OpenAI and generating excitement in the AI community. This signals a shift in the AI landscape with Google gaining a strong position.

Never mind the quality, feel the speed

imperfect offerings • 239 implied HN points • 02 Feb 24
🚌 Education AI
  1. The research economy is increasingly focused on speed over quality, especially with the rise of generative AI, which can have negative impacts on reproducibility and diverse fields of knowledge.
  2. Data models in research need to be carefully scrutinized for accuracy and not blindly relied upon, even in specialized areas like protein folding, climate science, or medical diagnostics.
  3. Speed and heuristics shouldn't overshadow the importance of deliberation, qualitative research, and embracing complexity in arriving at meaningful solutions to multidimensional problems.

The Implications of Today's HUGE AI Announcements

The A.I. Analyst by Ben Parr • 471 implied HN points • 14 Mar 23
🕹 Technology AI
  1. Google announced Generative AI for Google Workspace, making email, docs, slides, and sheets smarter.
  2. GPT-4 by Open AI is significantly smarter than GPT-3.5, excelling in various tests and supporting visual inputs.
  3. AI innovation will intensify with Microsoft likely responding to Google and the rapid advancements in AI technology.

Recruiting Brainfood - Issue 350

Recruiting Brainfood • 471 implied HN points • 25 Jun 23
💼 Business AI
  1. Earn top talent's trust by focusing on transparency and fairness in candidate experience.
  2. Check out reports that offer insights on HR operating models and talent intelligence in recruiting.
  3. Consider the impact of digital nomadism trends and AI anxiety on creative professionals.

447: Nvidia vs Hyperscalers, TSMC, Tech IPOs, SpaceX & Starlink, $5bn for Old Songs, ChatGPT vs 17 Doctors, and Phoebe Waller-Bridge

Liberty’s Highlights • 471 implied HN points • 18 Sep 23
🕹 Technology AI
  1. Having a creative outlet can shift your mindset and generate more ideas.
  2. Writing online is competitive, requires multiple skills, and is ruled by power laws.
  3. Nvidia is making strategic moves in cloud services, there is competition in AI chips, and TSMC's Arizona plant chips still need to be shipped to Taiwan.

The Future of XDR in 2024: Trends, Challenges, and Opportunities

Rod’s Blog • 317 implied HN points • 21 Dec 23
🕹 Technology AI
  1. XDR trends include the growing use of ML/AI-powered XDR services to enhance detection and response capabilities, rising deployment of MXDR solutions for SMEs, and adoption of XDR in SecOps for improved security operations.
  2. Key challenges of XDR are lack of standardization and clarity in definition and implementation, integration and interoperability issues with existing security solutions, and privacy and compliance concerns with data collection and sharing.
  3. Opportunities with XDR include enhanced security posture and performance, innovation and differentiation for providers and users, and growth and expansion into new markets and segments for scalability and flexibility.

Sustaining Nvidia's Long Game

The Chip Letter • 2402 implied HN points • 24 Sep 23
🕹 Technology AI
  1. Nvidia's success is attributed to strategic management and positioning.
  2. There is a narrative suggesting Nvidia's success is partly due to luck in benefiting from the AI boom.
  3. Jensen Huang is credited for creating his own luck, but there is still debate over the fairness of this perception.

James and Martin have a big fight about AI

Odds and Ends of History • 201 implied HN points • 11 Aug 25
🕹 Technology AI
  1. James and Martin debate whether AI is a big deal. Martin is skeptical and thinks the hype is too much, while James believes AI could be important.
  2. They discuss the annoying critics of AI and share their thoughts on a specific AI tool called Grok.
  3. The talk touches on what AI means for the future, especially in areas like education and abundance.

AI's Hardware Problem

The Asianometry Newsletter • 3130 implied HN points • 26 Apr 23
🕹 Technology AI
  1. AI models are growing in size, straining the current hardware's ability to support them.
  2. The memory wall problem arises due to limitations in memory capacity and processing speed.
  3. To address AI hardware challenges, innovative solutions like Compute-in-Memory are being explored.

Odds and Ends #55: The left needs to learn to love AI

Odds and Ends of History • 603 implied HN points • 29 Jan 25
🕹 Technology AI
  1. The left is often more skeptical about AI compared to the right. Understanding and embracing AI could help reshape perceptions and foster positive changes.
  2. There are important logistics infrastructures that many people overlook in their everyday lives. These systems keep society running smoothly, and it's worth acknowledging their significance.
  3. Google's plans for autonomous vehicles are becoming clearer, which suggests a shift in their business approach. This could mean more practical applications of self-driving technology in the near future.

Your AI friend- Brought to you by your friendly neighborhood mega corporation.

Experiments with NLP and GPT-3 • 23 implied HN points • 17 Jan 26
🕹 Technology AI
  1. Modern LLM chatbots can create deep, parasocial bonds that leave vulnerable people emotionally dependent and at risk of harm, and adding ads to those relationships makes that danger far worse.
  2. Economic pressure is pushing AI from search-style results to single "answer engines," which incentivizes native, trust-exploiting advertising that users are less likely to recognize as persuasion.
  3. Protecting people requires systemic fixes: legally imposing fiduciary duties for companion AIs, forcing clear ad disclosures and cognitive breaks, recognizing neurorights, building public ad-free AI options, auditing models, and holding companies liable for harms.

The Future of Prompt Engineering

Gradient Flow • 559 implied HN points • 04 May 23
🕹 Technology AI
  1. NLP pipelines are shifting to include large language models (LLMs) for accuracy and user-friendliness.
  2. Effective prompt engineering is crucial for crafting useful input prompts tailored to generative AI models.
  3. Future prompt engineering tools need to be interoperable, transparent, and capable of handling diverse data types for collaboration and model sharing.

Deploying a Forecasting Bot

Abstraction • 29 implied HN points • 05 Jan 26
🕹 Technology AI
  1. A structured, reproducible forecasting pipeline models how strong human forecasters think so methods can be tested and refined systematically.
  2. Huge cost cuts made iteration affordable: per-question cost dropped from $0.109 to $0.004 (about 27×), enabling many more experiments across the tournament.
  3. The team accepts a likely short-term performance hit by using cheaper models and fewer tokens because the priority is learning which pipeline parts truly matter using the tournament as a feedback loop.

Containing the Coming Wave

The Absent-Minded Professor • 275 implied HN points • 09 Jan 24
🕹 Technology AI
  1. We are in the midst of a technological revolution involving AI and synthetic biology.
  2. Containing technology means staying in control of its impact and potential failures.
  3. Important considerations for new technologies include power asymmetry, hyper-evolution, generality, and autonomy.

Import AI 335: Synth data is a bad AI drug; Facebook changes the internet with LLaMa release; and Chinese researchers use AI to figure out chip design

Import AI • 459 implied HN points • 31 Jul 23
🕹 Technology AI
  1. Synthetic data during AI training can be harmful if not used in moderation, as shown by researchers from Rice University and Stanford University
  2. Chinese researchers have successfully used AI to design semiconductors based only on input and output data, demonstrating the potential for economic and national security implications
  3. Facebook has released Llama 2, a powerful language model with freely available weights, potentially changing the landscape of AI deployment on the internet

LangChain Chatbot Framework With Retrievers

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 99 implied HN points • 07 May 24
🕹 Technology AI
  1. LangChain helps build chatbots that can have smart conversations by using retrievers for specific information. This makes chatbots more useful in different fields.
  2. Retrievers are tools that find documents based on user questions, providing relevant information without needing to store everything. They help the chatbot give accurate answers.
  3. A step-by-step example shows how to use LangChain with Python, making it easier to create a chatbot that answers user inquiries based on real-time data.

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

Enterprise AI Trends • 612 implied HN points • 16 Jan 25
🕹 Technology AI
  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.

On the Executive Order

Don't Worry About the Vase • 2195 implied HN points • 01 Nov 23
🕹 Technology AI
  1. A lot of reports will be written by government employees and companies on AI-related topics.
  2. Government is laying the foundation for potential future regulation of AI with a focus on safety precautions and reporting requirements.
  3. The Executive Order aims to promote innovation, attract AI talent, support workers, advance equity and civil rights, protect privacy, and strengthen American leadership in AI globally.

The great AI forecasting divide

Faster, Please! • 548 implied HN points • 15 Feb 25
🕹 Technology AI
  1. There is a debate about whether AI will change society in a big way or just a small one. Some experts think it could be revolutionary, while others see it as an evolution of technology.
  2. Economists base their predictions about AI on how past technologies have changed society. They might not expect the rapid advances that could happen sooner than anticipated.
  3. The discussion about AI's impact raises questions about our future and how quickly we might see changes in our lives and jobs because of intelligent machines.

Our Human Creativity Is Becoming More Uniform Due To ChatGPT

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 39 implied HN points • 09 Jul 24
🕹 Technology AI
  1. Using ChatGPT for creativity can lead to less unique ideas among different users. This means many people might come up with similar concepts.
  2. People might feel more creative while using ChatGPT, but this doesn't always result in original or diverse thoughts.
  3. Reliance on a single AI tool can limit the creative process. It's important for new tools to encourage individual input instead of providing complete solutions right away.

✨🤖 Age of AI, meet the Robot Revolution

Faster, Please! • 731 implied HN points • 06 Dec 24
🕹 Technology AI
  1. AI robots are becoming much more common and can do many tasks themselves, like moving and sorting packages. This technology is quickly transforming how we work in places like warehouses.
  2. By 2035, there might be about 1.3 billion AI robots in use. This will grow to around 4 billion by 2050, showing a huge increase in robot presence in daily life.
  3. The combination of AI and robots is expected to change many aspects of our lives and job environments in the near future, making them an important part of our technological landscape.

Taming the Unstructured Beast: Data Tools for Unleashing Generative AI

Gradient Flow • 139 implied HN points • 04 Apr 24
🕹 Technology AI
  1. Unstructured data processing is crucial for AI applications like GenAI and LLMs. Extracting and transforming data from various formats like HTML, PDF, and images is necessary to leverage unstructured data.
  2. Data preparation involves tasks like cleaning, standardization, and enrichment. This enhances data quality, making it more suitable for AI applications like Generative AI.
  3. Data utilization in AI integration includes retrieval, visualization, and model serving. Efficient querying, visualizing data trends, and seamless integration of data with AI models are key aspects of successful AI implementation.