The hottest AI Substack posts right now

And their main takeaways
Category
Top Technology Topics

207. When a Business Pleads to be Regulated

Hardcore Software • 456 implied HN points • 18 May 23
🕹 Technology AI
  1. Companies can either try to work with regulators or fight against regulation.
  2. New approach for AI and big tech is to ask to be regulated to gain control and power.
  3. When companies beg for regulation, they may be trying to manipulate the system for their own benefit.

The Cogsec Chronicles

Investing 101 • 96 implied HN points • 02 Aug 25
🕹 Technology AI
  1. Cognitive security, or cogsec, is about protecting your mind from manipulation. It's important to actively choose your beliefs instead of letting outside influences shape them.
  2. Propaganda has been around forever and can be used for good or bad. The key is to be aware of the stories being told and to take responsibility for the narratives we accept.
  3. Writing and critical thinking are powerful tools for understanding and transforming our beliefs. Engaging deeply with ideas helps us resist being programmed by others.

Moving From Natural Language Understanding To Mobile UI Understanding

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 11 Jul 24
🕹 Technology AI
  1. Natural Language Understanding (NLU) helps machines grasp and respond to human language, making sense of unstructured conversations.
  2. The shift to Mobile UI Understanding means we are now focused on understanding what's on mobile screens instead of just conversations.
  3. The Ferret-UI model enables devices to interact with users in a more meaningful way, allowing for richer and more context-aware conversations.

Shaping Light, Visualizing Sound, and The Generative Shift

Generative Arts Collective • 131 implied HN points • 21 Jun 25
🕹 Technology AI
  1. AI is changing how we create art and media by combining different styles and concepts to make something new. This gives more people the tools to express their creativity.
  2. Even though AI can generate impressive content, it lacks genuine human experience and thought. True creativity and original ideas still come from human minds.
  3. As technology evolves, society will need to adapt how we understand and engage with artistic expression. This shift may lead to exciting new forms of entertainment and creativity.
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Is GPT-4 getting worse over time?

AI Snake Oil • 1342 implied HN points • 19 Jul 23
🕹 Technology AI
  1. Chatbots have capabilities and behaviors that can change over time.
  2. There is no evidence of GPT-4's capabilities degrading, just changes in behavior.
  3. Behavior changes in language models like GPT-4 can impact the reliability of products built on top of them.

Searching for Posthumanist AI

Cybernetic Forests • 259 implied HN points • 26 Mar 23
🔬 Science AI
  1. Large Language Models are anthropocentric and pose challenges to moving beyond human-centric ideologies
  2. Post-humanism emphasizes decentering humanity and focusing on the health of the planet and interconnected natural systems
  3. AI's current state reflects human biases and design decisions, and a posthumanist approach would require a shift towards technologies that facilitate listening and understanding the world outside ourselves

🧪⚛🧬 Broken promises: CHIPS Act funding for science research falls short

Faster, Please! • 822 implied HN points • 13 Mar 24
🕹 Technology AI
  1. Despite promises made in the CHIPS and Science Act, Congress significantly underfunded key agencies and programs for scientific research, hindering progress in fields like artificial intelligence.
  2. Investment in basic scientific research, often a public good with long-term benefits beyond immediate financial gains, is essential for innovation and societal advancement.
  3. Government-funded R&D has historically played a crucial role in business sector productivity growth, supporting the argument for increased federal spending on research and development.

Generative AI, Bullshit as a Service

The Algorithmic Bridge • 891 implied HN points • 06 Feb 24
🕹 Technology AI
  1. Generative AI technology is often used for negative purposes like spamming, cheating, and faking.
  2. The democratization of creative freedom through AI may not be beneficial as it can lead to misuse by those who don't truly value it.
  3. Despite the potential of AI to revolutionize the world, its primary current use is for mundane and simplistic tasks, highlighting the complexities and limitations of humanity.

Spreadsheet, Not Skynet: Microdoses, Not Microprocessors

Brad DeLong's Grasping Reality • 130 implied HN points • 24 Jun 25
🕹 Technology AI
  1. AI tools like GPT are not as powerful as some say; they're more like useful spreadsheets than super intelligent machines. This means their impact on the economy is real but not world-changing.
  2. The benefits of AI on human welfare will be positive but limited. It's important to use AI wisely and not let it distract us.
  3. AI models are great for processing language, but they aren't complex enough to be truly revolutionary. They function similarly to simple input-output machines rather than groundbreaking technologies.

JAX things to watch for in 2025

Gonzo ML • 378 implied HN points • 26 Nov 24
🕹 Technology AI
  1. The new NNX API is set to replace the older Linen API for building neural networks with JAX. It simplifies the coding process and offers better performance options.
  2. The shard_map feature improves multi-device computation by allowing better handling of data. It’s a helpful evolution for developers looking for precise control over their parallel computing tasks.
  3. Pallas is a new JAX tool that lets users write custom kernels for GPUs and TPUs. This allows for more specialized and efficient computation, particularly for advanced tasks like training large models.

Last Week in AI #255: AI voice scams, flood of bad AI translations, self-rewarding LLMs, FTC probes AI partnerships of tech giants, and more!

Last Week in AI • 139 implied HN points • 29 Jan 24
🕹 Technology AI
  1. Scammers are using AI to mimic voices and deceive people into giving money, posing serious risks for communication security.
  2. Many sentences on the internet have poor quality translations due to machine translation, especially affecting low-resource languages.
  3. Researchers introduce Self-Rewarding Language Models (SRLMs) as a novel method to improve Large Language Models (LLMs) without human feedback.

If It Fits, Gemma Sits 💎

Sector 6 | The Newsletter of AIM • 99 implied HN points • 23 Feb 24
🕹 Technology AI
  1. Google has integrated its new model, Gemini, into Google Workspace, showing its focus on developing AI tools for users.
  2. While Google has released a model called Gemma, it is not truly open-source, which raises questions about its commitment to the open-source community.
  3. This year, Google is heavily promoting its Gemini brand, including recent updates and changes to its existing AI products like Bard.

OpenAI WebSocket Mode, 0x Cross-Chain API, TradeStation + Capitalize

The API Changelog • 1 implied HN point • 03 Mar 26
🕹 Technology AI
  1. APIs are shifting from stateless REST to low‑latency, persistent connections so AI agents can orchestrate complex actions in real time.
  2. New one‑to‑many and aggregator APIs hide provider complexity behind a single, normalized endpoint, cutting integration work and speeding product development.
  3. APIs are becoming programmable operational metrics that let teams embed visibility and decision signals directly into workflows so data drives immediate action.

TheSequence Radar #674: Transformers in the Genome: How AlphaGenome Reimagines AI-Driven Genomics

TheSequence • 133 implied HN points • 29 Jun 25
🕹 Technology AI
  1. AlphaGenome is a new AI model that helps understand the genome better. It predicts various functions in DNA, enabling quick analysis of genetic variants.
  2. This model combines different types of data into one system, making it easier and faster to see how genetic changes might affect health.
  3. DeepMind is offering early access to AlphaGenome for researchers, encouraging collaboration between academia and industry to unlock more discoveries in genetics.

NVIDIA: Waiting on Blackwell, and the Networking Question

Mule’s Musings • 372 implied HN points • 21 Nov 24
🕹 Technology AI
  1. Nvidia's recent earnings report showed lighter-than-expected guidance, meaning some investors were disappointed but it also indicates the company is stabilizing as it grows larger.
  2. The focus is now on Nvidia's new product, Blackwell, which is expected to greatly impact revenue, and there's anticipation about how successful it will be as it ramps up.
  3. Networking sales have surprisingly dropped as a percentage of revenue, even though overall networking demand is still strong, raising questions about the reasons behind this change.

Scaling Laws Meet Economics, but Adoption is still Accelerating

Mule’s Musings • 333 implied HN points • 19 Dec 24
🕹 Technology AI
  1. Economics are very important when it comes to scaling tech, and while costs are rising, tools like ChatGPT are still becoming more popular. Understanding the balance of cost and usage is crucial.
  2. Scaling laws are changing, and relying solely on large pre-trained models may not be the best strategy anymore. Businesses might need to explore smaller models or alternative methods to improve efficiency and reduce costs.
  3. Adoption of AI technologies is still growing rapidly, which shows that despite challenges, many people are eager to use and integrate these tools into their lives.

The Only Three Products in the Universe

Ulysses • 159 implied HN points • 15 Dec 23
🕹 Technology AI
  1. The three primary products in the universe are information, matter, and energy. These are the fundamental components of economic activity.
  2. Software businesses focus on processing and disseminating information, which can disrupt social activities that involve thinking and language.
  3. The ultimate value in economic activity is derived from manipulating matter and energy efficiently, with the mastery of synthetic biology predicted to have a greater impact than AI.

Imperfect, but sometimes on the money

imperfect offerings • 179 implied HN points • 24 Nov 23
🕹 Technology AI
  1. Peter Thiel's Palantir has taken over the federated data service for the NHS, impacting data sharing opt-outs for patients and raising concerns about private interests in public health data.
  2. In the education sector, AI's influence, particularly in EdTech, raises issues around data governance, privacy regulations, and the challenge of regulating online platforms.
  3. AI's expansion into various sectors, including recruitment, poses challenges such as potential bias, pricing out of students, and the use of AI for assessments, leading to a possible 'AI-driven race to the middle' in hiring practices.

Is Earth A Computational Process?

Surfing the Future • 119 implied HN points • 28 Jan 24
🔬 Science AI
  1. Stephen Wolfram's TED talk on computational thinking explores AI, the universe, and more, opening up new possibilities for the future.
  2. Earth being a computing process is a fascinating concept with implications for sustainability and AI.
  3. The work of James Lovelock, especially his Gaia theory, holds significance and influences the thinking of many individuals.

Data Points

Technically Optimistic • 59 implied HN points • 19 Apr 24
🕹 Technology AI
  1. Data is essential for AI; you can't have AI without massive amounts of data.
  2. Our relationship with data is complex - it enhances our efficiency and personalization but also raises privacy concerns.
  3. Surveillance capitalism is a reality where tech companies profit from capturing and shaping our private experiences, showcasing the lack of user power and awareness.

AI safety is not a model property

AI Snake Oil • 796 implied HN points • 12 Mar 24
🕹 Technology AI
  1. AI safety is not a property of AI models, but depends heavily on the context and environment in which the AI system is deployed.
  2. Efforts to fix AI safety solely at the model level are limited, as misuses can still occur since models lack necessary context for decision-making.
  3. Defenses against AI model misuse should focus primarily outside models, on attack surfaces like email scanners and URL blacklists, and red teaming should shift towards early warning of adversary capabilities.

It’s GPT-5 Day!

Alex's Personal Blog • 98 implied HN points • 07 Aug 25
🕹 Technology AI
  1. Smartsheet was recently sold for $8.4 billion, but its former CEO left the company shortly after due to changes that frustrated staff. This suggests challenges that can arise with private equity ownership.
  2. AI continues to grow, especially in coding, and companies see huge revenue potential in this area. Predictions about its rapid growth can sometimes sound unbelievable but may turn out to be true.
  3. The financial model for AI companies can look strange because they often spend a lot upfront on developing new models, but eventually, they can become profitable as they ramp up revenue from these models.

An AI Haunted World

One Useful Thing • 972 implied HN points • 19 Dec 23
🕹 Technology AI
  1. The development of open source AI models is democratizing AI usage and allowing for easier modification and widespread deployment.
  2. The efficiency and affordability of LLMs will lead to AI being incorporated into various products for troubleshooting, monitoring, and interaction, potentially creating an 'AI haunted world'.
  3. Future AI integration may involve hierarchies of various AI models working together, with smart generalist AIs delegating tasks to cheaper, specialized AIs.

Time to ChatGPT/Gemini/Claude/Grok Oneself.

The Future Does Not Fit In The Containers Of The Past • 24 implied HN points • 30 Nov 25
🕹 Technology AI
  1. Using AI tools can help you better understand yourself. You can ask it personal questions like your worth or analyze your past appraisals to get insight.
  2. Having deep conversations with other people can reveal a lot. You can ask about their most impactful experiences and compare their answers to what AI might say.
  3. It's important to think about how AI will change jobs and industries. Asking challenging questions to yourself, others, and AI can help you adapt and prepare for the future.

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
  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.

OpenAI Sora: One Step Away From The Matrix

The Algorithmic Bridge • 849 implied HN points • 16 Feb 24
🕹 Technology AI
  1. OpenAI's Sora is a revolutionary text-to-video AI model that excels in generating high-quality videos with various resolutions and aspect ratios.
  2. Sora is a diffusion transformer model that leverages a mix of diffusion model (DALL-E 3) and transformer architecture (ChatGPT) to process videos like ChatGPT processes text.
  3. Sora serves as a generalist, scalable model of visual data, capable of creating images and videos, transforming them, and simulating physically sound scenes, albeit in a primitive manner.

2024 Predictions from the Condensing the Cloud Team

Condensing the Cloud • 137 implied HN points • 05 Jan 24
🕹 Technology AI
  1. In 2024, AI will be integrated in more products, making AI-powered experiences common.
  2. The observability market is set for changes, with new companies emerging to address current challenges.
  3. Privacy and compliance will become more crucial for enterprises, particularly with the introduction of new AI-related legislation.

Q&A With Marvell CEO Matt Murphy

More Than Moore • 303 implied HN points • 13 Jan 25
🕹 Technology AI
  1. Marvell is focusing on custom chip design to meet the growing demand from large tech companies, helping them create tailored solutions without needing extensive in-house resources. This trend is important for optimizing performance and costs in data centers.
  2. The company recently announced a new high-performance memory interface called HBM, which is in high demand for advanced computing. They are offering innovative designs to enhance speed and reduce power usage.
  3. Marvell sees significant growth opportunities in the AI sector, believing there are still many product cycles ahead. They are committed to investing in R&D to stay competitive in this rapidly evolving market.

Lessons from customer evaluations of an AI product

The AI Frontier • 59 implied HN points • 18 Apr 24
🕹 Technology AI
  1. Customers who have experience with AI products often have a better understanding of what to look for. They know what works and what doesn't, so they can more easily evaluate new AI tools.
  2. The quality of data is super important for AI performance. If the data is good, the answers will be better, so paying attention to data quality is key.
  3. Expectations around AI products can be tricky. Some people think AI is not useful, while others expect it to know everything. It's important to set clear expectations about what AI can do.

Genesis, Quatrovision, War/Peace & Disclosure

Dr. Pippa's Pen & Podcast • 29 implied HN points • 26 Nov 25
🕹 Technology AI
  1. Genesis aims to open national labs and mix classified research with outside scientists, supercomputers, and AI to rapidly create huge breakthroughs—potentially including game-changing energy technologies.
  2. A long-standing "invisible wall" has kept many discoveries secret through NDAs, clearances, and control of publishing; once locked-away scientists meet external researchers, suppressed ideas will surface and become hard to control.
  3. Officials appear to be slowly releasing taxpayer-funded breakthroughs to test public reaction and boost the economy, a shift that could quickly rewrite textbooks and scientific norms.

Google's Gemini Advanced: Tasting Notes and Implications

One Useful Thing • 861 implied HN points • 08 Feb 24
🕹 Technology AI
  1. Gemini Advanced is a GPT-4 class model, offering strengths and weaknesses compared to other advanced AI models.
  2. Gemini Advanced reveals the potential for emergent properties in large AI models, showing hints of 'ghosts' or unique intelligence.
  3. Google's Gemini Advanced hints at a future where AI serves as powerful integrated personal assistants, differentiating itself from other AI models.

Will AI-Written Books Destroy Publishing?

Notes from a Small Press • 23 implied HN points • 02 Dec 25
📚 Literature AI
  1. It's hard to find reliable ebook editions of classic books online, with many low-quality versions flooding sites like Amazon. This long-standing issue shows that poor quality content has always existed, even before AI.
  2. AI can't replace human authors because you can't copyright a book without a human behind it. Reputable publishers will still focus on quality and likely avoid purely AI-generated work.
  3. While some authors might use AI as a tool for writing and editing, it's not a new problem for publishing. There's always been a mix of good and bad quality books, and AI doesn't change that.

The Sequence Knowledge #764: Wanna do Synthetic Data? Learn About Rephrasing

TheSequence • 28 implied HN points • 02 Dec 25
🕹 Technology AI
  1. Rephrasing is important for creating synthetic data. It involves rewriting data samples to keep the meaning while changing the words.
  2. This method helps to make data more diverse and reduces the risk of machines just memorizing it instead of understanding.
  3. You can use rephrasing for different types of data, like text, code, or images, and it saves time and costs compared to getting new data labeled.

RAG, Hallucination & Structure: Research By ServiceNow

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 59 implied HN points • 18 Apr 24
🕹 Technology AI
  1. ServiceNow is using a method called Retrieval-Augmented Generation (RAG) to help transform user requests in natural language into structured workflows. This aims to improve how easily users can create workflows without needing deep technical knowledge.
  2. By using RAG, they want to reduce 'hallucination', which is when AI generates wrong or irrelevant info, and make the AI more reliable. This is important for gaining user trust in AI systems.
  3. The study also suggests future improvements, like changing output formats for efficiency and streamlining processes so that users can see steps one at a time, making it easier to follow along.