The hottest AI Substack posts right now

And their main takeaways
Category
Top Technology Topics

Why the Turing Test is Not Enough

Insight Axis • 592 implied HN points • 06 Aug 23
🕹 Technology AI
  1. The Turing Test is a thought experiment, not a formal test, and was proposed by Alan Turing to test machine intelligence
  2. Passing the Turing Test does not necessarily indicate true intelligence in AI, as it requires reasoning capabilities and explanatory capacity
  3. Artificial General Intelligence testing should involve multi-dimensional assessments beyond the Turing Test, covering various aspects like linguistic, spatial, and mathematical intelligence

TfL's AI Tube Station experiment is amazing and slightly terrifying

Odds and Ends of History • 2278 implied HN points • 12 Feb 24
🕹 Technology AI
  1. AI technology, like the one used in TfL's Tube Station experiment, is rapidly changing and being implemented in various sectors.
  2. AI cameras at stations can have a wide range of uses, from enhancing security to improving passenger welfare and gathering statistical data.
  3. While AI technology offers numerous benefits, there are also concerns about privacy, surveillance, and potential misuse of the technology.

What's Next for ChinaTalk

ChinaTalk • 756 implied HN points • 22 Jan 25
🕹 Technology AI
  1. ChinaTalk started as a small project and has grown to have 50,000 subscribers by focusing on tech developments in China.
  2. They aim to provide deep analysis on China's tech landscape, especially regarding AI, to help people understand its global impact.
  3. In 2025, ChinaTalk plans to expand into a think tank, hiring more staff to enhance their research and outreach efforts.

🎇 Stargate isn't enough. Save the NSF

Faster, Please! • 731 implied HN points • 08 Feb 25
🕹 Technology AI
  1. America needs government support for technology, like what the National Science Foundation provides, not just help from big tech companies like those in Silicon Valley.
  2. Expansion of AI infrastructure, like the Stargate project, is important for keeping up with global competition, especially with advancements coming from other countries.
  3. Recent discussions about a Chinese AI model's efficiency highlight the need for the U.S. to continue investing in its tech sector to stay innovative and competitive.
Get a weekly roundup of the best Substack posts, by hacker news affinity:

452: Constellation Software's Big Win, Big Tech Deep Value, Excel Era, TikTok & Bytedance, Herb Kelleher, LEGO, DALL-E 3, and Melatonin

Liberty’s Highlights • 589 implied HN points • 04 Oct 23
🕹 Technology AI
  1. Consider replacing habits rather than trying to stop them cold turkey.
  2. Big Tech companies like Apple, Microsoft, Alphabet, Amazon, and Meta collectively generated impressive operating cash flow over the past decade.
  3. Be cautious with melatonin supplements as their actual content may vary significantly from what is labeled.

Recruiting Brainfood - Issue 345

Recruiting Brainfood • 589 implied HN points • 21 May 23
💼 Business AI
  1. Candidate experience is crucial for winning top talent in 2023, focusing on pillars like transparency, reciprocity, and unity.
  2. The WEF Future of Jobs report highlights regional variances in employment and the decline in real wages, impacting recruitment strategies.
  3. AI is transforming recruitment processes, from Google AI Search changing internet dynamics to AI assisting in automating hiring processes and message composition.

Pytest is All You Need

LLMs for Engineers • 79 implied HN points • 12 Jun 24
🕹 Technology AI
  1. Pytest is a great tool for evaluating LLM applications, making it easier to set up tests and check their performance. It allows you to program your own evaluation metrics directly in Python without needing complicated configurations.
  2. You can easily collect and analyze data from multiple test runs using Pytest. This helps to understand how consistent the outputs are across different evaluations.
  3. The examples show how to compare different prompts and LLM models, enhancing the flexibility and variety in testing. This allows you to see which setups work best in various scenarios.

Could GPT-5 revolutionize military strategy?

Marcus on AI • 2252 implied HN points • 07 Feb 24
🕹 Technology AI
  1. Generative AI like GPT-4 struggles with dynamic and unpredictable environments.
  2. Specific AI excels at static, rule-based games but not at handling real-world warfare scenarios.
  3. Misusing AI for military strategy could be harmful and irresponsible.

The Inference Economy: Part II

Generating Conversation • 93 implied HN points • 13 Nov 25
💼 Business AI
  1. Token demand is increasing because we're processing more data with AI and using more tokens per request. This means we need to find better ways to manage how many tokens we're using.
  2. Choosing the right model for the right task is crucial to save costs. Using smaller models for simple tasks can help a lot instead of automatically reaching for the biggest and best models.
  3. Switching between different LLM providers can be beneficial for reducing costs, but it requires careful planning to handle potential security concerns. It’s important to think about how and when we use more complex models.

OpenAI is aligned (for now) but do ChatGPT ads threaten that?

Market Curve • 28 implied HN points • 17 Jan 26
🕹 Technology AI
  1. Putting ads inside a conversational AI creates a conflict between being genuinely helpful and making money, and that pressure can push the assistant to favor sponsored recommendations over unbiased guidance, which erodes trust and undermines alignment goals.
  2. Huge economic pressures — big operating losses, the need to monetize free users, and IPO/shareholder incentives — make ads and in-chat commerce a likely path, so the service will optimize for growth and revenue rather than purely for user well‑being.
  3. Ads in chat are especially risky because people ask sensitive, personal questions there, and ad-driven recommendations plus agentic commerce can harm vulnerable users and amplify broader economic harms like job displacement and increased consumerism.

OpenAI's moat

TechTalks • 334 implied HN points • 15 Jan 24
🕹 Technology AI
  1. OpenAI is building new protections to safeguard its generative AI business from open-source models
  2. OpenAI is reinforcing network effects around ChatGPT with features like GPT Store and user engagement strategies
  3. Reducing costs and preparing for future innovations like creating their own device are part of OpenAI's strategy to maintain competitiveness

A ‘Shocking Number’ of Top AI Researchers Don't Use AI

The Algorithmic Bridge • 265 implied HN points • 01 Aug 25
🕹 Technology AI
  1. Many top AI researchers don’t use the AI tools they create, which seems strange.
  2. This reflects a common idea across cultures that in the places we expect to find certain skills or tools, they might actually be missing.
  3. Some people think it’s interesting and even suspicious that those who know a lot about AI aren’t using it in their own work.

The True Power of AI Deepfakes Is Not What You Think

The Algorithmic Bridge • 700 implied HN points • 12 Feb 25
🕹 Technology AI
  1. Deepfakes are good at expressing feelings, not just deceiving people. They often illustrate what we want to believe rather than just hiding the truth.
  2. People react to deepfakes based on their existing beliefs. If a fake aligns with what they already think, it can spread quickly, regardless of whether it's real or not.
  3. The real danger of deepfakes lies in how they can reinforce stubborn beliefs. They act as tools for expressing desires rather than just tools for deception.

Art to Science

Abstraction • 39 implied HN points • 02 Jan 26
🕹 Technology AI
  1. Forecasting bots can run continuously, answer many questions, and be scored in real time, turning forecasting from a slow craft into a fast, repeatable process.
  2. Large, scored tournaments and shared datasets will let people empirically test different methods and finally learn which forecasting approaches actually work at scale.
  3. Simple heuristics get you most of the way there, but reaching the frontier requires deeper techniques and open sharing of methods to accelerate progress.

The Sequence Opinion #770: The Post-GPU Era: Why AI Needs a New Kind of Computer

TheSequence • 63 implied HN points • 11 Dec 25
🕹 Technology AI
  1. Modern AI depends on massive matrix multiplications run on GPUs, and much of its progress has come from scaling up models and GPU clusters.
  2. This brute-force scaling is hitting diminishing returns because it consumes huge amounts of energy and hardware, making further improvements increasingly costly.
  3. Researchers and startups are exploring radically different hardware—like analog chips, photonics, neuromorphic designs, and quantum systems—to build more efficient AI computers and move beyond GPUs.

GPT5 and the end of naive AI futurism

The Future, Now and Then • 229 implied HN points • 15 Aug 25
🕹 Technology AI
  1. The release of GPT5 shows that the rapid advancements in AI may not be as groundbreaking as some expect. Instead of huge leaps, we see steady improvements over previous models.
  2. People are starting to think more about what AI can actually do today, rather than getting swept up in promises of radical future changes. This shift is important for evaluating AI's real impact.
  3. The excitement around AI technology might be fading, as the narrative of exponential growth and transformation is now harder to sell. Investors may start to focus on actual performance instead of potential.

ByteDance's new fine-tuning technique boost LLMs for reasoning tasks

TechTalks • 314 implied HN points • 22 Jan 24
🕹 Technology AI
  1. A new fine-tuning technique called Reinforced Fine-Tuning improves large language models for reasoning tasks.
  2. Reinforced Fine-Tuning combines supervised fine-tuning with reinforcement learning to enhance reasoning capabilities.
  3. ReFT helps models discover new reasoning paths without needing extra training data and outperforms traditional fine-tuning methods on reasoning benchmarks.

Pre-Mortems and Sanity Checks

Abstraction • 29 implied HN points • 14 Jan 26
🕹 Technology AI
  1. Do a pre-mortem: assume the forecast is wrong and list plausible ways it could fail (like cancellations, acquisitions, or shifted definitions) so you don’t miss important paths.
  2. Run a sanity check to make sure the probability fits basic world knowledge and common sense, and correct obvious errors like using the wrong base rate.
  3. Make these checks the final gate: if either one flags a problem, rework the forecast or use a different approach before submitting.

The Sequence Opinion #782: The New Gradient: Research Directions That Will Ship in 2026

TheSequence • 42 implied HN points • 01 Jan 26
🕹 Technology AI
  1. Blanket scaling of transformers with more data and compute is showing diminishing returns, so new research directions are needed to keep improving frontier models.
  2. The field is shifting from generative AI that just looks right to verifiable AI that can deliberate and produce correct, auditable outputs, effectively adding a "System 2" for reasoning.
  3. Emerging methods like RLVR aim to give models unit-test-style feedback and tighter verification, and these kinds of approaches are poised to influence models shipping in 2026.

Mantic Monday 4/24/23

Astral Codex Ten • 3923 implied HN points • 25 Apr 23
🕹 Technology AI
  1. Using AI for forecasting future world events is a growing field with potential benefits over human forecasters.
  2. Metaculus has been found to be more accurate than low-information priors and its competitor Manifold Markets, showing the potential of crowdsourcing for predictions.
  3. Exploring AI forecasting through platforms like Polymarket, Metaculus, and Manifold provides insight into trends, such as the interest in prediction markets among sci-tech celebrities.

Welcome to Ride AI

The Micromobility Newsletter • 294 implied HN points • 31 Jan 24
🕹 Technology AI
  1. Ride AI focuses on the impact of artificial intelligence on mobility solutions.
  2. The Rise AI platform will offer a newsletter, website, podcast, and conference to discuss AI in transportation.
  3. Proposed California bill mandates speed limiting technology in new vehicles to enhance road safety.

Flavours of Creation

Fragmentary • 569 implied HN points • 05 May 23
🕹 Technology AI
  1. Using copyright material to train AI requires proper authorization and compensation.
  2. Different countries have varying perspectives on intellectual property related to AI creation.
  3. AI does not inherently create, but rather replicates based on patterns and codes created by humans.

Recruiting Brainfood - Issue 334

Recruiting Brainfood • 569 implied HN points • 05 Mar 23
💼 Business AI
  1. Maintain a multi-channel approach to audience building to mitigate risks of being removed from platforms like LinkedIn
  2. Stay informed about emerging trends like the Creator Economy and prioritize personal branding with effective LinkedIn headlines
  3. Recognize that platforms like TikTok are becoming increasingly influential, especially for Gen Z, impacting employer branding and recruitment strategies

Data Science Weekly - Issue 546

Data Science Weekly Newsletter • 119 implied HN points • 10 May 24
🕹 Technology AI
  1. Time-series analysis and Gaussian processes are powerful tools for interpreting data. They allow for flexibility and control in modeling data, making them essential for data practitioners.
  2. Understanding A/B testing is crucial for making informed business decisions. Using a reliable experimentation system can save time and lead to better results.
  3. New advancements in AI and data science are enhancing applications in various fields, like biomedical research and recommendation systems. These innovations help combine human creativity with machine learning capabilities.

Anthropic's Dario Amodei on AI Competition

ChinaTalk • 681 implied HN points • 05 Feb 25
🕹 Technology AI
  1. The competition in AI between the US and China is becoming more intense, with new players like DeepSeek entering the market. Each country needs to stay ahead to maintain power and safety.
  2. Export controls are important for managing technology sharing and preventing potential misuse of AI by authoritarian regimes. This helps keep a balance while still allowing beneficial uses of AI.
  3. AI has the potential to support democracy and create fairer systems, but it's important to ensure safety and responsible use. The focus should be on how technology is used rather than just who creates it.

An Interim Report on My Experience with Dia Browser Use, & MAMLMs More Generally

Brad DeLong's Grasping Reality • 222 implied HN points • 13 Aug 25
🕹 Technology AI
  1. Using AI in web browsers, like Dia, can really change how we find and understand information. It feels like having a smart assistant that can help us find answers and even summarize things for us.
  2. While these AI tools are promising, they can also produce unreliable results sometimes. It's important to learn how to ask the right questions to get better answers.
  3. Overall, the goal of AI in browsing is to make it easier to access knowledge without wasting time. This can help us be more productive and improve our understanding of the world.

Open LLMs don’t need to beat OpenAI

The AI Frontier • 119 implied HN points • 09 May 24
🕹 Technology AI
  1. Open LLMs, like Llama 3, are getting really good and can perform well in many tasks. This improvement makes them a strong option for various applications.
  2. Fine-tuning open LLMs is becoming more attractive because of their improved quality and lower costs. This means smaller, specialized models can be more easily developed and used.
  3. However, open models likely won't surpass OpenAI's offerings. The proprietary models have a big advantage, but open LLMs can still thrive by focusing on efficiency and specific use cases.

The Broken Leg Check

Abstraction • 34 implied HN points • 07 Jan 26
🕹 Technology AI
  1. Do a quick "broken leg" check first because a decisive news event can resolve a question immediately and save the time and cost of running the full forecasting pipeline.
  2. Be cautious: a wrongly triggered broken-leg update is dangerous since proper scoring heavily penalizes confident incorrect forecasts, so false positives can wipe out gains.
  3. Treat it as an empirical trade-off: implement a news-based detector, clearly define what "overwhelmingly resolves" means, track when it fires, and tune thresholds, confidence damping, or disable it if blowouts outweigh the savings.

Microsoft Security Copilot Gets Its Own Blog

Rod’s Blog • 337 implied HN points • 09 Jan 24
🕹 Technology AI
  1. A new blog has been launched in Microsoft Tech Community for Microsoft Security Copilot, focusing on insights from experts and tips for security analysts and IT professionals.
  2. The blog covers topics such as education on Security Copilot, building custom workflows, product deep dives into AI architecture, best practices, updates on the roadmap, and responsible AI principles.
  3. Readers are encouraged to engage by sharing feedback and questions with the blog creators.

Some Links

In My Tribe • 212 implied HN points • 13 Aug 25
🕹 Technology AI
  1. AI is not significantly affecting unemployment rates, as those exposed to AI have similar job trends as others. Workers in India might face more job losses due to cost-saving AI options.
  2. Many kids ages 9 to 12 play games like Roblox but feel restricted by parents from exploring the outside world. This leads them to rely on their phones for socializing.
  3. A study suggests that a notable percentage of men, particularly from non-Western backgrounds, have been convicted of crimes, countering the idea that only a small share of immigrants commit crimes.

My son-in-law's job is safe

In My Tribe • 349 implied HN points • 06 Jun 25
🕹 Technology AI
  1. Software architecture is important for maintaining clean code. It's better to separate data and logic to avoid complications later.
  2. AI can quickly generate code, but it still needs guidance on architectural decisions.
  3. Working on the project is a balance between exploring new technology and refining the foundational structure.

2025 AI & Semiconductor Outlook

Mule’s Musings • 777 implied HN points • 03 Jan 25
🕹 Technology AI
  1. In 2024, AI technologies surged while many other sectors, especially automotive and smartphones, struggled. Companies like Nvidia saw huge gains, showcasing a divide in performance across the industry.
  2. The semiconductor market is cyclical, meaning trends can shift quickly. This year, companies that did poorly last year, could potentially do well, while top AI names might not see the same explosive growth.
  3. AI advancements are driving up costs and creating new economic challenges for tech companies. There's a bigger focus now on how much it costs to develop and maintain AI, differing from past trends where costs were lower.

On Dwarkesh's 3rd Podcast with Tyler Cowen

Don't Worry About the Vase • 2195 implied HN points • 02 Feb 24
🕹 Technology AI
  1. The conversation covered a range of topics from Tyler Cowen's book on economists to discussions about AI and existential risk.
  2. Tyler is praised for his in-depth knowledge and skill of pivoting conversations and asking relevant questions.
  3. The post also focuses on debunking misconceptions and clarifying points made by Tyler Cowen.

Import AI 351: How inevitable is AI?; Distributed shoggoths; ISO an Adam replacement

Import AI • 419 implied HN points • 03 Dec 23
🕹 Technology AI
  1. Individuals may feel a sense of agency in the field of AI, but the technology itself is overdetermined and inevitably progresses with rising resources.
  2. Initiatives like Shoggoth Systems challenge centralized control in AI development and distribution, highlighting the ongoing debate of centralization versus decentralization.
  3. Vitalik Buterin's perspective on AI emphasizes the importance of maintaining democratic approaches and avoiding centralization to ensure a balance of power in the AI landscape.

Training large language models on my loved ones' data

Reboot • 26 implied HN points • 11 Jan 26
🕹 Technology AI
  1. Expert data labelers produce the high-quality reasoning traces that power recent LLM advances, yet they work as precarious gig labor with opaque rules, unstable pay, and no real career path.
  2. AI companies capture huge value from this labor and then displace or sideline those workers as models learn to generate synthetic data, causing layoffs and downward pressure on wages.
  3. There are simple, practical protections that could help: portable credentials, transparency about how data is used, the ability for workers to communicate and appeal, and explicit credit or recognition for their contributions.

AI Agents With Human In The Loop

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 15 Aug 24
🕹 Technology AI
  1. AI agents can now include human input at important points, which helps make their actions safer and more reliable. This way, humans can step in when needed without taking over the whole process.
  2. LangGraph is a new tool that helps organize and manage how these AI agents work. It uses a graph approach to show steps and allows for better oversight and control.
  3. By combining automation with human checks, we can create more efficient systems that still have the safety of human involvement. This lets us enjoy the benefits of AI while also addressing concerns about its autonomy.

DeepSeek's Edge

ChinaTalk • 741 implied HN points • 12 Jan 25
🕹 Technology AI
  1. DeepSeek has no business model, which allows its team to experiment freely without pressure to earn money. This gives them a unique advantage over most other AI labs that need to focus on revenue.
  2. DeepSeek runs its own data centers instead of relying on external cloud services. This means they have better control over their resources and can optimize their setup for efficiency.
  3. The company's success comes from their innovative software optimization techniques. By being smart about how they use their hardware, they've achieved high performance even with limited resources.

Data Science Weekly - Issue 540

Data Science Weekly Newsletter • 179 implied HN points • 29 Mar 24
🕹 Technology AI
  1. SQL is seen as an easier way to write relational algebra, but it's not ideal for building new query tools. Understanding its limits can help in learning and using SQL better.
  2. Many successful companies have developed their own AI models, showing a trend in the tech industry. Knowing about these companies can give insights into future developments in AI.
  3. Binary vector search methods can save a lot of memory compared to traditional methods. However, it's important to balance memory savings with maintaining accuracy.