The hottest AI Substack posts right now

And their main takeaways
Category
Top Technology Topics

Want to play AAA Games in Your Car?

More Than Moore • 233 implied HN points • 04 Jan 24
🕹 Technology AI
  1. At CES, AMD announced new automotive APUs for in-car entertainment, driver safety, and autonomous driving.
  2. The new AMD chips support a gaming experience in cars, with potential for multiple displays and better graphics performance.
  3. AMD's acquisition of Xilinx enhances their presence in automotive technology, particularly in ADAS with their Versal AI Edge processors.

Synthesizing Introspection: The AI Mediated Self

Cybernetic Forests • 99 implied HN points • 04 Dec 22
🕹 Technology AI
  1. The challenge of using AI for introspection is knowing what you are really asking and understanding the limitations of the technology.
  2. Conversing with AI to simulate interactions with younger versions of oneself may not provide personalized or beneficial insights.
  3. Relying on AI for deep introspection or personal growth may present risks of misunderstanding, projection, and avoidance of true self-care.

Microsoft Security Copilot Demos from Microsoft Ignite 2023

Rod’s Blog • 39 implied HN points • 15 Dec 23
🕹 Technology AI
  1. Microsoft Ignite 2023 highlighted the importance of securing AI and using AI for security, with these topics being top of mind for many organizations and individuals.
  2. The Microsoft Security Copilot, still in its early adopter program, was a popular topic at the event, drawing significant interest and overflowing demos.
  3. Key demo areas for Microsoft Security Copilot at Ignite included lifecycle workflows, sign-in logs, identity access troubleshooting, and risky user summary.

AI Safety: A Technical & Ethnographic Overview

jonstokes.com • 391 implied HN points • 30 Mar 23
🕹 Technology AI
  1. The AI safety debate involves technical details about AI systems like GPT-4 and cultural dynamics around the issue.
  2. The discussion includes concerns about regulating and measuring AI capabilities, as well as the divisions and allegiances within different groups.
  3. Some groups, like the Intelligence Deniers, have strong beliefs about AI being a scam and hold firm against AI progress, leading to potential divisions among AI safety proponents.

New newsletter, as suspicious of technology as ever

Technology, Environment, and Art • 39 implied HN points • 14 Dec 23
🕹 Technology AI
  1. The author warns against AI and advocates for a cautious approach towards technology, believing AI is a significant danger to humanity
  2. Not all AI developments are beneficial; the author strongly objects to AI taking over creative tasks and emphasizes the importance of human connection over AI-driven efficiency
  3. The author calls for resistance against the advancement of AI, encouraging individuals to avoid AI tools and take a stand against the pervasive use of technology for the sake of genuine human interaction and creativity
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Chinese AI’s Sputnik Moment

Taipology • 69 implied HN points • 24 Jan 25
🕹 Technology AI
  1. DeepSeek-R1 is a new AI model from China that performs on par with top models at a much lower cost. This is surprising and changing the AI landscape.
  2. It uses a special 'DeepThink' mode that makes it think about responses more deeply, which helps it give better answers compared to other models.
  3. The competition is heating up, with concerns that Chinese AI could take over. DeepSeek aims not just to match the West but to innovate and lead in technology.

The Post-Work AI Utopia We Are Racing Toward: A 7-Minute Video Intro

Crypto Good • 6 implied HN points • 11 Dec 25
🎭️ Culture AI
  1. People are reacting to AI in three main ways: some fear it will destroy us, some ignore it, and some expect a vague future of abundance.
  2. Rapid AI progress is driving us toward a world where machines do most or all work, but we currently lack a roadmap for governance, money, poverty, and human purpose in that world.
  3. Thoughtful fiction and distilled briefings can offer practical blueprints for how post-scarcity societies and superintelligent AIs might be governed, helping guide real-world policy and design.

Claude Plays Pokémon

Teaching computers how to talk • 62 implied HN points • 28 Feb 25
🕹 Technology AI
  1. AI playing games like Pokémon can show us how smart it really is. It might be better than other tests because games need quick thinking and problem solving.
  2. Recent projects like Claude playing Pokémon on Twitch highlight how slow and confused current AI can be. It took Claude a long time to beat just one part of the game.
  3. Today's AI tests often focus on math or coding, but playing games might give a clearer picture of intelligence. We should use games to see if AI can think and adapt like humans do.

Side Effects of outsourcing our Thinking

Poems, Short stories and other things.. • 29 implied HN points • 08 Jul 25
🕹 Technology AI
  1. Relying too much on smart tools makes us lazy thinkers. We should still use our brains to analyze and understand things instead of just taking shortcuts.
  2. AI can help us save time but it's important to keep our memories and reasoning sharp. We shouldn't let AI do all the thinking for us.
  3. While AI has the ability to remember everything, it's not always a good idea. Sometimes forgetting helps us move on and making tools that remember everything can be harmful.

Prompt Engineering for AI: A Valuable Skill for Security Professionals?

Rod’s Blog • 39 implied HN points • 13 Dec 23
🕹 Technology AI
  1. Prompt engineering is a valuable skill for leveraging the power of AI in creative and efficient ways by improving the quality and accuracy of AI outputs.
  2. Effective prompt engineering can expand the capabilities and applications of AI systems, enabling them to perform tasks beyond their pre-defined scope using general knowledge and reasoning abilities.
  3. Prompt engineering is important for enhancing interaction and collaboration between humans and AI systems, making AI more human-like and relatable by crafting well-designed prompts.

AI Foundations Part 1: Transformers, Pre-Training and Fine-Tuning, and Scaling

Mule’s Musings • 378 implied HN points • 11 Apr 23
🕹 Technology AI
  1. The Transformer model revolutionized Large Language Models (LLMs) with its parallel and scalable architecture.
  2. Pre-training and fine-tuning, as seen in GPT-1 and BERT, significantly improved model performance for various tasks.
  3. Bigger models, more data, and computing power have shown to lead to better performance in LLMs, but the relationship between model size, training tokens, and performance is more complex than initially thought.

Mixtral: The best open model, MoE trade-offs, release lessons, Mistral raises $400mil, Google's loss, vibes vs marketing

Democratizing Automation • 237 implied HN points • 11 Dec 23
🕹 Technology AI
  1. Mixtral model is a powerful open model with impressive performance in handling different languages and tasks.
  2. Mixture of Expert (MoE) models are popular due to their better performance and scalability for large-scale inference.
  3. Mistral's swift releases and strategies like instruction-tuning show promise in the open ML community, challenging traditional players like Google.

Prompt-RAG

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 20 Mar 24
🕹 Technology AI
  1. Prompt-RAG is a new method that improves language models without using complex vector embeddings. It simplifies how we retrieve information to answer questions.
  2. The process involves creating a Table of Contents from documents, selecting relevant headings, and generating responses by injecting context into prompts. It makes handling data easier.
  3. While this method is great for smaller projects and specific needs, it still requires careful planning when constructing the documents and managing costs related to token usage.

Intel Pushes the Nitro Button

Sector 6 | The Newsletter of AIM • 39 implied HN points • 11 Dec 23
🕹 Technology AI
  1. Intel is planning a big event where they might announce new AI products to compete with NVIDIA and AMD. This shows how competitive the tech industry has become.
  2. One exciting product expected is the Gaudi3 AI accelerator chip, which will be much faster and better than the previous version. It promises improved performance with higher compute power and memory capacity.
  3. Looking ahead, Intel has plans for even more advanced chips, combining their AI technology with GPU power. This hints at more innovations coming in the future.

What is Generative AI?

Technically • 27 implied HN points • 22 Jul 25
🕹 Technology AI
  1. Generative AI predicts not just numbers or yes/no answers but creates full sentences, images, and even videos from prompts.
  2. There are various types of Generative AI models, with the main ones being Transformers for text and Diffusion models for images.
  3. Despite its advancements, Generative AI is still rooted in the basic principles of machine learning, which involves learning patterns from data.

Digital Twins in Supply Chain Management

philsiarri • 22 implied HN points • 11 Aug 25
🕹 Technology AI
  1. Digital twins are real-time models that reflect physical objects or systems. They help businesses keep track of operations and respond to changes quickly.
  2. Using digital twins can help companies test different scenarios and spot issues before they become big problems. This leads to better decision-making in logistics.
  3. However, challenges like data quality and costs can make it hard to use digital twins effectively. Still, they are becoming popular tools for improving supply chain management.

The 6 reasons why your AI strategy is stalling

Dev Interrupted • 28 implied HN points • 10 Jul 25
🕹 Technology AI
  1. It's not just about having the right tools for AI, but having a solid foundation of knowledge and data. If your information is messy or outdated, the AI won't work well.
  2. Your infrastructure needs to be set up for AI to work smoothly. If it's too complex or manual, it can slow everything down rather than speeding things up.
  3. Governance is important for AI. You need to make sure there are clear rules and oversight to build trust in the system and ensure AI helps rather than harms your workflow.

How soon until we can afford robot butlers?

Alex's Personal Blog • 65 implied HN points • 13 Feb 25
🕹 Technology AI
  1. Robot butlers may become affordable in the near future due to advancements in technology. This could change how we manage household tasks.
  2. Recent investments in AI and robotics indicate a growing market. Companies are receiving significant funding to improve technology and services.
  3. The political landscape is affecting tech policies and decisions. Changes in leadership might lead to new directions for tech regulations and innovations.

The Most Amazing Week in Gen AI Releases

TheSequence • 84 implied HN points • 15 Dec 24
🕹 Technology AI
  1. Several major tech companies like OpenAI, Google, and Microsoft launched new AI models in a single week. This shows how quickly AI technology is progressing.
  2. OpenAI's Sora model allows users to create videos from text descriptions, but it has some limitations. It's an exciting step for video generation!
  3. Google's Gemini 2.0 has improved capabilities, allowing it to handle more complex tasks and interact more effectively with users.

AI, Institutions, and the Future of Human Flourishing with Sam Hammond

Moral Mayhem Podcast • 19 implied HN points • 19 Mar 24
🕹 Technology AI
  1. AI can greatly impact how we organize and run our institutions. It's important for us to think about the good and bad effects AI might have on these systems.
  2. Human flourishing should be a priority in discussions about AI. We need to make sure that technology helps people live better lives.
  3. The role of institutions is crucial in shaping a positive future with AI. Strong institutions can guide the development of technology in a way that benefits society.

New decisions in a cloudy world

do clouds feel vertigo? • 99 implied HN points • 08 Apr 23
🕹 Technology AI
  1. AI is creating new divisions in society, leading to more debates about our future and survival. It's making conversations about technology very heated and complex.
  2. Deepfakes and manipulated images are changing how we perceive reality. We can no longer trust everything we see, which can have big implications for privacy and reputation.
  3. In a world full of uncertainty, having a clear mind and being skeptical about information is essential. Embracing ambiguity instead of fearing it can help us navigate changes better.

Clouded Judgement 11.20.25 - The AI Platform Wars

Clouded Judgement • 8 implied HN points • 21 Nov 25
🕹 Technology AI
  1. AI companies are shifting their focus from just improving model quality to creating strong platforms. This means they're not just making better models but also figuring out how to distribute and integrate their services more effectively.
  2. Google is bundling its new Gemini model with all its services, making it a central part of its ecosystem, while OpenAI is creating a super app with ChatGPT to attract users directly to its platform.
  3. Anthropic is aiming for a trusted spot in the enterprise market by prioritizing safety and reliability, while Meta is pushing open-source models to make competition tougher at the base level, encouraging differentiation at higher moments.

Performing Multiple LLM Calls & Voting On The Best Result Are Subject To Scaling Laws

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 19 Mar 24
🕹 Technology AI
  1. Making more calls to Large Language Models (LLMs) can help with simple questions but may actually make it harder to answer tough ones.
  2. Finding the right number of calls to use is crucial for getting the best results from LLMs in different tasks.
  3. It's important to design AI systems carefully, as just increasing the number of calls doesn't always mean better performance.

Alignment-as-a-Service: Scale AI vs. the new guys

Democratizing Automation • 205 implied HN points • 07 Feb 24
🕹 Technology AI
  1. Scale AI is experiencing significant revenue growth from data services for reinforcement learning with human feedback, reflecting the industry shift towards RLHF.
  2. Competition in the market for human-in-the-loop data services is increasing, with companies like Surge AI challenging incumbents like Scale AI.
  3. Alignment-as-a-service (AaaS) is a growing concept, with potential for startups to offer services around monitoring and improving large language models through AI feedback.

AI Dropped the Mic at the Nobel Party

TheSequence • 105 implied HN points • 13 Oct 24
🔬 Science AI
  1. AI scientists won two Nobel Prizes, one in physics and one in chemistry, marking a big moment for the field.
  2. Some scientists are upset about machine learning winning in physics, saying it's not really physics but computer science.
  3. Many see this as a sign of how science and tech are blending together, showing that knowledge connects different fields in exciting ways.

The $20k decision that turned into $7m...

Grant & Co • 39 implied HN points • 09 Dec 23
💼 Business AI
  1. Investors appreciate regular updates from entrepreneurs to stay informed about their investments.
  2. Market research costing $20k before launching a company can save millions by avoiding building the wrong product and lead to significant revenue growth.
  3. Distinguishing between VC and PE funding strategies, along with the importance of having a clear exit plan, is crucial for successful investments in the business world.

Moderator

davidj.substack • 35 implied HN points • 05 Jun 25
🕹 Technology AI
  1. When moderating a discussion, it's important to let the conversation flow naturally instead of trying to control it too much. This approach helps participants engage more actively.
  2. In regulated industries like banking and healthcare, there's a cautious approach to adopting AI technologies. Firms often take their time to evaluate the security risks before implementing new tools.
  3. Startups focusing on specific use cases often create better tools compared to big companies adding features to existing products. However, larger firms have more resources to advance AI development over time.

Agent Evaluation Playbook

Pratik’s Pakodas 🍿 • 27 implied HN points • 08 Jul 25
🕹 Technology AI
  1. To make good AI agents, it's important to have a solid evaluation process. This can help ensure they're performing well in real-world situations.
  2. Creating a system that tracks and measures the agents' performance can lead to better results. Like building a pipeline that continuously tests and improves agents.
  3. Using a leaderboard to compare agents based on performance, cost, and speed can help guide improvements and make smarter decisions.

Rabbit Holes 🕳️ #122

Creative Destruction • 30 implied HN points • 02 Jul 25
💼 Business AI
  1. Using AI tools like ChatGPT is changing how we communicate. We're starting to sound more robotic and losing some of our human touch in conversations.
  2. There's a big gap between how much CEOs make compared to average workers. This inequality is growing and is often ignored, but it's important to recognize and address it.
  3. Startups are shifting from focusing on rapid growth and hiring to being lean and efficient, using AI to achieve more with fewer employees. This new approach is called 'botscaling.'

Model merging lessons in The Waifu Research Department

Democratizing Automation • 209 implied HN points • 29 Jan 24
🕹 Technology AI
  1. Model merging is a way to blend two model weights to create a new model, useful for experimenting with large language models.
  2. Model merging is popular in creating anime models by merging Stable Diffusion variants, allowing for unique artistic results.
  3. Weight averaging techniques in model merging aim to find more robust solutions by creating models centered in flat regions of the loss landscape.

Welcome to the HyperMink Community

HyperMink Newsletter • 19 implied HN points • 19 Mar 24
🕹 Technology AI
  1. HyperMink Community offers insights into the world of AI in simple language for everyone to understand
  2. The goal is to make AI understandable and accessible to all, not just the tech elite
  3. HyperMink aims to empower individuals to control their own destiny in the world of AI

My End of 2024 Update

Human Programming • 77 implied HN points • 03 Jan 25
🕹 Technology AI
  1. Human programming research is shifting focus to work with AI models instead of humans. This means developing systems that help AI operate more efficiently.
  2. The author has been involved in several software projects, including a consulting role where they created tools to enhance AI and web products. These experiences allowed them to explore different collaborative environments.
  3. They plan to take some time for exploration and research in AI, particularly focusing on self-modifying programs. This will allow them to deepen their understanding of both AI concepts and practical product development.

This Week: OpenAI, Figma, Calendly

Good Better Best • 4 implied HN points • 19 Dec 25
💼 Business AI
  1. OpenAI made Projects free for all ChatGPT users, pushing a habit-forming feature downstream to boost engagement, stickiness, and likely retention that can be monetized later.
  2. Figma set explicit AI credit limits (150/day, 500/month), following a daily-cap + monthly-ceiling play that trades near-term margin for platform growth, but the proliferation of different credit systems risks confusing customers and causing credit fatigue.
  3. Calendly moved its AI Notetaker out of beta and joins a wide race to own meeting transcripts and summaries, since notes are highly sticky and embed tools into workflows; pricing and packaging of these features will reveal each company’s strategy.

#16 - A "Cautious Coalition" of Democracies: What Grand Strategy for AI Safety? + Sycophancy

Navigating AI Risks • 39 implied HN points • 07 Dec 23
🕹 Technology AI
  1. The idea that democracies should be in control of transformative AI over authoritarian states like China is well-grounded.
  2. A 'cautious coalition' strategy suggests that democracies should lead in AI to reduce risks associated with states that do not regulate AI for safety.
  3. It is important for democratic governments to balance the desire to maintain AI lead with global governance arrangements that involve all key players, including China and other autocracies.

The "AI-first" trap 🪤

Year 2049 • 26 implied HN points • 22 Jul 25
🕹 Technology AI
  1. Sometimes we focus too much on technology instead of solving real problems. It's important to ask if there’s a simpler way to deal with the issue at hand.
  2. Over-relying on familiar tools can lead us to use them in situations where they don’t fit, like the Juicero juicer which was overly complex.
  3. To avoid getting stuck in the 'AI-first' trap, we should start with simple solutions and really understand the problems we're trying to solve.

What You Can't Say (About AI)

The Algorithmic Bridge • 212 implied HN points • 26 Jan 24
🕹 Technology AI
  1. Moral fashions restrict what can be said and thought about, and going against them can lead to serious consequences.
  2. In AI communities, there are unspoken beliefs and ideas that people hesitate to express publicly, even within their own groups.
  3. Challenging current moral fashions in AI can lead to uncovering important future truths and insights.

Winter is Here, And So is Gemini

Sector 6 | The Newsletter of AIM • 39 implied HN points • 07 Dec 23
🕹 Technology AI
  1. Google's Gemini is finally here after a delayed launch, and it aims to outperform other models like GPT-4 in language tasks.
  2. Gemini has three versions: Ultra for complex tasks, Pro for various tasks, and Nano for efficient on-device use.
  3. The Gemini Ultra version scored impressively high in tests, even beating human experts at some language understanding tasks.

Q&A with IBM CEO Arvind Krishna

More Than Moore • 93 implied HN points • 08 Nov 24
💼 Business AI
  1. IBM is focusing on consulting, cloud services, AI, and research, as it no longer has a consumer division. Companies turn to IBM for help in improving efficiency and upgrading their technology.
  2. The launch of new AI models, like Granite, shows IBM's commitment to innovation in AI. They believe smaller, more efficient models are the future, making AI cheaper and easier to use.
  3. IBM is changing its approach to partnerships, focusing on collaboration with other companies instead of competing. This strategy helps enhance their offerings and build stronger business relationships.

We Are the Robots

Breaking Smart • 79 implied HN points • 14 Dec 24
🕹 Technology AI
  1. Robots today are moving in more fluid and organic ways, unlike the stiff, mechanical movements we used to see. They can express emotions that feel similar to human feelings, showing a blend of technology and life.
  2. The arts and technology are evolving together, with artists often inspired by new machine capabilities. This relationship highlights how our understanding of what is human or machinic is gradually shifting.
  3. As machines become more complex and organic, people may feel anxious or fearful of them. Our interactions with technology can influence how we view ourselves and what it means to be human.

We're hiring: Daily newsletter writer

The Works in Progress Newsletter • 24 implied HN points • 31 Jul 25
🕹 Technology AI
  1. There's a job opening for a daily newsletter writer. The role includes finding and sharing interesting news about science, technology, and economic progress.
  2. The newsletter will focus on linking to articles, podcasts, and videos that people interested in progress will love. It's like a daily update for curious minds.
  3. To apply, you'll need a resume, a writing sample, and some links to content you think others should see. They want someone who enjoys exploring the internet and sharing cool finds.