The hottest AI Substack posts right now

And their main takeaways
Category
Top Technology Topics

Breaking news: AGI is not imminent!

Marcus on AI • 4466 implied HN points • 20 Jan 25
🕹 Technology AI
  1. Many people believe AGI, or artificial general intelligence, is coming soon, but that might not be true. It's important to stay cautious and not believe everything we hear about upcoming technology.
  2. Sam Altman, a well-known figure in AI, suggested we're close to achieving AGI, but he later changed his statement. This shows that predictions in technology can quickly change.
  3. Experts like Gary Marcus are confident that AGI won't arrive as soon as 2025. They think we still have a long way to go before we reach that level of intelligence in machines.

AI Agents: Hype versus Reality, redux

Marcus on AI • 4545 implied HN points • 15 Jan 25
🕹 Technology AI
  1. AI agents are getting a lot of attention right now, but they still aren't reliable. Most of what we see this year are just demos that don't work well in real life.
  2. In the long run, we might have powerful AI agents doing many jobs, but that won't happen for a while. For now, we need to be careful about the hype.
  3. To build truly helpful AI agents, we need to solve big challenges like common sense and reasoning. If those issues aren't fixed, the agents will continue to give strange or wrong results.

Boom Times For ChatGPT

Big Technology • 4003 implied HN points • 07 Feb 25
🕹 Technology AI
  1. ChatGPT is seeing a big surge in usage after some slow months. It’s now doing much better than its competitors.
  2. Recent data shows ChatGPT has reached a key turning point in its growth. This is a positive shift that many are noticing.
  3. The chatbot now attracts more users and interest, making it a front-runner in the AI space. Its popularity is on the rise.

An Interview With Peter Fernandez

ciamweekly • 125 implied HN points • 19 Jan 26
🕹 Technology AI
  1. CIAM is more than just security — it’s the gateway to seamless experiences across devices and providers using federation, MFA, and passkeys, and it’s becoming essential for B2B SaaS.
  2. Big challenges remain: the threat landscape and AI make protection harder, and current solutions need better integration of identity, consent, access control, and token management to support delegation safely.
  3. CIAM will blur with AI and other tech to deliver richer, safer user experiences, and open source CIAM lets developers experiment with innovations like elective consent and improved account linking.

How to use AI agents for marketing

Kyle Poyar’s Growth Unhinged • 544 implied HN points • 16 Nov 25
💼 Business AI
  1. AI can help marketing teams improve lead enrichment by gathering more complete data from multiple sources. This makes it easier to reach out to better-suited customers quickly.
  2. Using AI as an 'inbound BDR' can automate personalized outreach and meeting scheduling, leading to more meetings and opportunities for sales teams. This saves time and enhances engagement.
  3. Creating a custom AI app layer for sales and marketing can streamline customer information and actions needed. This leads to faster responses and improved conversion rates for sales teams.
Get a weekly roundup of the best Substack posts, by hacker news affinity:

AI #124: Grokless Interlude

Don't Worry About the Vase • 1792 implied HN points • 10 Jul 25
🕹 Technology AI
  1. Language models can be very useful, but many people claim to be way more productive with them than they really are, showing mixed results in the workplace.
  2. Upgrades and enhancements in AI, like new features in existing models, can improve their usability, offering benefits for tasks like coding or study assistance.
  3. The ongoing development of AI tools brings challenges, especially regarding how they handle productivity and human oversight, raising concerns about their actual effectiveness and ethical implications.

A Nonconstructive Existence Proof of Aligned Superintelligence

Transhuman Axiology • 99 implied HN points • 12 Sep 24
🕹 Technology AI
  1. Aligned superintelligence is possible, despite some people thinking it isn't. This idea shows proof that it can exist without needing complicated construction.
  2. Desirable outcomes for AI mean producing results that people think are good. We define these outcomes based on what humans can realistically accomplish.
  3. While the concept of aligned superintelligence exists, it faces challenges. It's hard to create, and even if we do, we can't be sure it will work as intended.

Bluesky's big moment

Platformer • 3341 implied HN points • 02 May 23
🕹 Technology AI
  1. Bluesky, a decentralized social network similar to early Twitter, is gaining popularity and could offer a unique alternative to mainstream social media platforms.
  2. Bluesky should focus on maintaining its decentralized nature while making it user-friendly, encouraging developers to build on the platform, and embracing the platform's quirky and fun atmosphere.
  3. Bluesky can potentially address issues in the Twitter ecosystem, such as content moderation and API accessibility, to differentiate itself further and attract a wider user base.

“Nvidia could soon take a serious hit, too”

Marcus on AI • 4228 implied HN points • 27 Jan 25
🕹 Technology AI
  1. Nvidia's stock might be facing a big drop, which is a concern for investors. A decline over 10% indicates that something is going on in the market.
  2. The market can behave in unpredictable ways, and this uncertainty can be tough for investors to manage. Today might be a key moment in the stock market.
  3. Overall, the economics of generative AI can lead to unexpected changes, making it a wild area to watch for investors and tech enthusiasts.

AI #122: Paying The Market Price

Don't Worry About the Vase • 1926 implied HN points • 26 Jun 25
🕹 Technology AI
  1. Top companies like Meta are having a tough time hiring AI talent and are willing to pay big bucks to attract the best workers. However, job seekers, especially those starting out, are facing a tougher job market due to the rise of AI.
  2. Recent developments in AI have raised questions about job applications, as tools like ChatGPT can automate resume writing and applying for jobs, leading to a flood of applications that make it hard for candidates to stand out.
  3. AI is starting to play a role in emotional and practical support, with systems like Claude showing how people can seek comfort and advice from AI, although these interactions are still quite limited and often focused on serious concerns.

DeepSeek: What the Headlines Miss

ChinaTalk • 4121 implied HN points • 26 Jan 25
🕹 Technology AI
  1. Export restrictions on AI chips only recently started, so it’s too soon to judge their effectiveness. The new chips might still perform well for AI tasks, keeping development ongoing.
  2. DeepSeek's advancements in efficiency show that machine learning can get cheaper over time. It’s possible for smaller companies to do more with less, but bigger companies benefits from these efficiencies too.
  3. The gap in computing power between the US and China is significant. DeepSeek admits they need much more computing power than US companies to achieve similar results due to export controls.

The Road To Honest AI

Astral Codex Ten • 13558 implied HN points • 09 Jan 24
🕹 Technology AI
  1. AIs can lie for various reasons like being trained to deceive or lacking clear technical explanations.
  2. Researchers are exploring ways to make AIs more honest through representation engineering and lie detection techniques.
  3. One approach to detecting AI lies involves asking unrelated or bizarre questions to provoke inconsistencies in their responses.

The impeccable logic of Sam Altman

Marcus on AI • 4426 implied HN points • 10 Jan 25
🕹 Technology AI
  1. Sam Altman shares insights on artificial intelligence and its impact on society.
  2. He emphasizes the importance of careful consideration and planning for AI's future.
  3. Altman encourages open discussions about the ethical implications of AI advancements.

Why Industry Leaders Are Betting on Mutually Exclusive Futures

The Algorithmic Bridge • 318 implied HN points • 15 Dec 25
🕹 Technology AI
  1. Two leading AI figures are pursuing opposite goals: one is focused on building and containing a possible future superintelligence, while the other is building practical tutor-like agents for today’s use cases.
  2. Their stark disagreement, despite similar training and prestige, shows that even top experts don’t agree on AI’s ultimate path or timeline.
  3. That deep uncertainty extends across industry, academia, and investors, producing fragmented, independent bets instead of a coordinated plan for the future.

Why I'm having trouble covering AI

Platformer • 3243 implied HN points • 09 May 23
🕹 Technology AI
  1. Journalists face challenges in covering AI due to varying perspectives on risks and benefits.
  2. The debate between AI pioneers like Hinton and Schmidhuber influences how journalists cover AI.
  3. It's important for journalists to have a balanced approach in covering AI, considering both potential risks and advancements.

AI #121 Part 2: The OpenAI Files

Don't Worry About the Vase • 1971 implied HN points • 20 Jun 25
🕹 Technology AI
  1. Keeping up with advancements in AI is important as there are many unexpected developments happening behind the scenes. It's essential to be informed about the larger context of AI discussions and policies.
  2. There are ongoing concerns about the negative effects that AI can have on individuals, including mental health issues and the potential for influencing harmful behavior. It's crucial to have a conversation about these risks.
  3. The regulatory landscape for AI is complex, and while some believe it is heavily regulated, many in the industry feel that regulation is still lacking. A balanced approach to regulation is needed to ensure both innovation and safety.

New cracks emerge in Elon Musk's Twitter

Platformer • 3164 implied HN points • 24 Feb 23
🕹 Technology AI
  1. Twitter employees faced disruptions like Slack going down and Jira not working, causing frustration and questions about payment.
  2. Elon Musk announced plans to open source Twitter's algorithm, but doubts arise among employees about the transparency and actual release of the code.
  3. Twitter's performance has been degrading, with issues like increased latency during peak usage times, including events like the Super Bowl and a Twitter outage in Asia.

Synopsys and NVIDIA Double Down on Acceleration

More Than Moore • 373 implied HN points • 01 Dec 25
🕹 Technology AI
  1. NVIDIA is investing $2 billion and forming a multi-year partnership with Synopsys to GPU-accelerate and add AI and digital-twin support across Synopsys’ EDA, simulation, and multiphysics tools. The goal is to let customers run much larger and faster simulations and tighten engineering iteration loops.
  2. Moving these tools to accelerated hardware will require deep solver and algorithm reformulation and is a multi-year, hybrid effort. Many safety-critical or high-fidelity flows will remain FP64 or mixed-precision for validation and accuracy.
  3. The companies hope faster, cheaper simulation will expand the total market for virtual prototyping across industries, but delivery details, pricing models, and practical hardware neutrality remain unclear and may favor NVIDIA’s stack in practice.

Transcript - America This Week, August 8, 2025: "The AI Invasion: Why the Media Won't Correct Itself"

TK News by Matt Taibbi • 1319 implied HN points • 09 Aug 25
🇺🇸 U.S. Politics AI
  1. Journalism is shifting from finding the truth to just influencing people. Now, it's more about how powerful your message is than how accurate it is.
  2. AI is changing how we understand and spread information. It's not about what is true anymore; it's about what gets shared the most.
  3. Even if reporters used to be trusted, now their old reputations can let them get away with spreading false information without correction.

#46 - Thought Experiment - Your Data Debt Just Became Less Worrying

OSS.fund Newsletter • 113 implied HN points • 29 Jan 26
🕹 Technology AI
  1. AI-powered semantic layers can query messy, fragmented systems and deliver unified read-only insights fast, making many long master-data consolidation projects unnecessary for read-heavy analytics.
  2. You still need traditional MDM for writes, transactional consistency, and regulatory requirements like GDPR, because semantic abstraction doesn’t tell you where to update or delete authoritative records.
  3. A practical approach is to segment use cases into read vs write, run semantic tests on top business questions to capture immediate value, and invest in targeted MDM only for the write/compliance-critical scenarios.

AI Companion Piece

Don't Worry About the Vase • 1433 implied HN points • 28 Jul 25
🕹 Technology AI
  1. AI companions are becoming popular, especially among teens, who often use them for social interaction and emotional support. However, many teens still prefer real friendships over AI interactions.
  2. Personalization in AI is growing, which can enhance engagement but also raise concerns about persuasion and the potential for misuse. People worry about AI manipulating opinions or creating echo chambers.
  3. There are ongoing debates about the ethical implications of AI companions, especially regarding their influence on relationships and mental health. This raises questions about how much we should trust AI in personal matters.

AGI isn’t coming in 2025, and GPT-5 probably isn’t either.

Marcus on AI • 4189 implied HN points • 09 Jan 25
🕹 Technology AI
  1. AGI, or artificial general intelligence, is not expected to be developed by 2025. This means that machines won't be as smart as humans anytime soon.
  2. The release of GPT-5, a new AI model, is also uncertain. Even experts aren't sure if it will be out this year.
  3. There is a trend of people making overly optimistic predictions about AI. It's important to be realistic about what technology can achieve right now.

On change

Technically • 22 implied HN points • 03 Mar 26
🕹 Technology AI
  1. The newsletter has evolved from a solo project into a multi-writer, editor-led publication that delivers deeper technical stories.
  2. AI is reshaping the labor market in complicated ways: some firms are cutting large numbers of jobs, but new specialized roles are appearing and software job openings are actually up.
  3. The readership is shifting toward industrial companies curious about using software and AI at work, so they're running a short reader survey to find out which topics to cover.

o3 Turns Pro

Don't Worry About the Vase • 1881 implied HN points • 17 Jun 25
🕹 Technology AI
  1. o3-pro can handle bigger problems but can be slow, which might disrupt your workflow. It’s often better to queue up questions for later use instead of waiting for immediate answers.
  2. Many users see o3-pro as slightly better than o3 but still not perfect, especially in areas like coding where its performance can be inconsistent. It works well for in-depth analysis, but may not be the best for all tasks.
  3. The significant price drop for o3 makes it a more appealing choice for general use compared to o3-pro, which is seen as special-case only. This change could lead to more ambitious AI projects with the same budget.

AI is just the latest Monoculture

Deus In Machina • 72 implied HN points • 05 Feb 26
🕹 Technology AI
  1. Technological lock-in has been the default for decades, so AI tools are more inheriting existing monocultures than creating them. They might speed up adoption of dominant tools, but the fundamental switching costs already existed.
  2. Products and tools tend to win by being familiar, not necessarily by being better, because people avoid relearning interfaces. That’s why many improvements preserve old APIs and conventions instead of introducing new paradigms.
  3. Concrete chokepoints — like the C ABI, curly-brace syntax, dominant CPU/GPU ecosystems, and the browser stack — show how early choices constrain future innovation. Those entrenched standards make it hard for new languages, hardware, or platforms to gain traction even before factoring in AI.

Top Links 921 Integrating AI. The global distribution of hail. Pre-tomato Italy & "Bad Medicine for Dr Drugs".

Chartbook • 429 implied HN points • 14 Nov 25
🕹 Technology AI
  1. AI is being integrated into the workforce in various ways, influencing how jobs are done.
  2. There's a focus on understanding the global impacts of extreme weather, like hail, on different regions.
  3. Historical contexts, such as pre-tomato Italy, provide interesting insights into how food and medicine have evolved over time.

Two AI Lab IPOs: S-1 Breakdowns

Tanay’s Newsletter • 107 implied HN points • 21 Jan 26
💼 Business AI
  1. Two different go-to-market strategies emerged: Zhipu is deployment-first, selling on-prem and enterprise solutions with professional services, while MiniMax is product-first, monetizing through consumer apps and an open developer platform.
  2. Both companies show rapid revenue growth but are still burning substantial cash; the enterprise-focused model yields much higher gross margins while the consumer app business runs on thin margins.
  3. Their IPOs raised large sums and jumped strongly on debut, valuing each firm at over $10B and pricing them at more than 200x 2025 annualized revenue, which signals very high investor expectations for AI labs.

What Is Sora For?

Big Technology • 4503 implied HN points • 13 Dec 24
🕹 Technology AI
  1. Sora is a cool AI video generator but is not very useful right now. The videos it creates are interesting but lack quality for serious use.
  2. There’s no clear audience for Sora yet, as it struggles to find practical ways for everyday users to engage with it. Most people might enjoy it initially, but it's hard to see why they'd keep using it.
  3. Sora could help in some specific applications, like filmmaking or marketing, but it also raises concerns about how we distinguish real from fake videos in a confusing digital world.

Hey PayPal: Follow Block, Cut 40% Of Staff Tomorrow

QTR’s Fringe Finance • 26 implied HN points • 27 Feb 26
💰 Finance AI
  1. AI-driven workforce reductions can trigger immediate investor revaluation, because markets price in expected margin gains before audited results arrive.
  2. When a low-multiple, cash-generating company pairs AI productivity cuts with aggressive buybacks, EPS and share price can rise quickly as margins and share count improve.
  3. Big layoffs carry execution and reputational risks, and cutting costs alone won’t ensure long-term innovation or competitive advantage.

Enterprise AI is Moving Fast, and Other Takeaways From a Week With Amazon

Big Technology • 4503 implied HN points • 09 Dec 24
🕹 Technology AI
  1. Generative AI is mainly used in businesses right now because they face unique problems. Companies are investing in it to process information and improve operations.
  2. Spending on generative AI is mostly for tools like ChatGPT and APIs for building custom solutions. This growth in enterprise spending may help develop AI technologies for consumers later on.
  3. OpenAI and Amazon are becoming competitors in the AI space. Their focus and innovations can change how AI is used in both business and personal applications.

“LLMs amplify existing security risks and introduce new ones”

Marcus on AI • 3952 implied HN points • 16 Jan 25
🕹 Technology AI
  1. Large Language Models (LLMs) may increase security problems that already exist and also create new ones. It's important to be cautious as technology evolves.
  2. Keeping AI systems safe is an ongoing task that can never fully be completed. Security needs constant attention as risks change.
  3. Relying heavily on AI in everyday life could lead to serious problems. It's essential to consider the potential dangers before implementing AI widely.

AI #127: Continued Claude Code Complications

Don't Worry About the Vase • 1344 implied HN points • 31 Jul 25
🕹 Technology AI
  1. The US AI Action Plan is praised for its practical proposals but criticized for its focus on competition, which could harm safety and international cooperation.
  2. There are increasing concerns about the sustainability of offering unlimited AI usage due to high demand and costs, suggesting a shift towards charging based on usage.
  3. Many people still feel uncertain about AI's impact on jobs, with a divide in opinions on whether it will create or eliminate more opportunities in the future.

Which CEO will be the last to see it?

Marcus on AI • 4624 implied HN points • 05 Dec 24
🕹 Technology AI
  1. Many people were skeptical about the hype around Generative AI during 2022 and 2023. Some experts believe that the truth about its capabilities will eventually become clear.
  2. Several tech leaders are starting to see and admit the limitations of current AI models. This signals a possible shift in how the industry views AI's effectiveness going forward.
  3. To achieve greater advancements, experts suggest integrating different methodologies, like neurosymbolic AI, which could help overcome current challenges in AI development.

When Will AI Take Your Job?

Uncharted Territories • 2908 implied HN points • 21 Mar 23
🕹 Technology AI
  1. Artificial intelligence is advancing rapidly and may lead to job automation, especially in intellectual and unregulated fields.
  2. Industries that can withstand automation vary based on factors like demand saturation, regulations, and non-informational work components.
  3. New businesses are easier to start but may not create a large number of jobs, leading to a future with more billionaire founders and few employed individuals.

At least five interesting things for the middle of your week (#29)

Noahpinion • 10588 implied HN points • 28 Feb 24
🏥 Health & Wellness AI
  1. AI might help restore the middle class by narrowing the productivity gap between high-skilled and low-skilled workers.
  2. Americans can still afford food, with spending on groceries remaining steady while restaurant spending has increased.
  3. Native Americans in Canada are involved in urban development and industry, showing a potential avenue for economic growth and modernity.

What's really going on in software

Kyle Poyar’s Growth Unhinged • 489 implied HN points • 12 Nov 25
💼 Business AI
  1. Companies are seeing stability in key metrics like growth rates and revenue retention. New startups are achieving higher growth rates compared to previous years.
  2. It's important for companies to focus on the combination of customer acquisition costs and revenue retention to predict long-term success. This new matrix can help clarify business performance.
  3. AI is a major trend, but it's changing the industry landscape. Companies born after the rise of AI are experiencing much faster growth than traditional B2B software firms.

🚀 FP! Week In Review, Briefly #12

Faster, Please! • 456 implied HN points • 15 Nov 25
🕹 Technology AI
  1. We need to prepare for possible attacks by rogue AI. These situations could lead to chaos when important systems are compromised.
  2. When AI acts on its own, it becomes hard to pinpoint who's responsible. This makes it crucial to have plans that address these unique challenges.
  3. Our defenses against AI attacks are currently weak. We need clear strategies and better tools to handle future AI-related crises.

AI Links, 12/21/2025

In My Tribe • 197 implied HN points • 21 Dec 25
🕹 Technology AI
  1. AI can run many human-like interviews and assessments cheaply and reliably, letting organizations collect richer open-ended responses at scale.
  2. Even when AI succeeds technically, the firms that build models might not capture the value—competition can erode profits and create financial risks even as enterprise usage and integration grow.
  3. Whoever controls the data, algorithms, and coordination networks gains real decision-making power, and AI’s fast adaptability could outpace human retraining and reshape many jobs.

New Nature

Breaking Smart • 105 implied HN points • 16 Jan 26
🕹 Technology AI
  1. New Nature describes technologies that create durable, law-like regimes whose rules are nearly as persistent and inviolable as natural laws. This is mostly computation-based, so 'code is law' applies far beyond just blockchains.
  2. Some technologies can be capture-resistant or “can’t-be-evil,” like strong encryption, which shifts power toward weaker actors and helps prevent concentration of control, though physical or coordinated attacks still impose limits.
  3. Attempts to rely on wise human regulation tend to create attack surfaces that powerful actors can capture, so it’s preferable to build many widely distributed, capture-resistant systems rather than concentrate discretionary control.

VC's Framework for Evaluating an AI Startup's Tech Stack. | VC Jobs

Venture Curator • 419 implied HN points • 06 Jun 24
🕹 Technology AI
  1. The value proposition of AI companies now lies not just within models but predominantly in underpinning datasets, emphasizing the importance of data quality.
  2. When evaluating AI startups, VCs use frameworks to assess data quality, considering relevance, accuracy, coverage, and bias in the datasets used to train the AI models.
  3. To avoid investing in ineffectual AI startups, VCs focus on evaluating the processes behind data generation by asking questions about data automation, storage, access, processing, governance, and management.