The hottest AI Substack posts right now

And their main takeaways
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Fixing Faulty Gradient Accumulation: Understanding the Issue and Its Resolution

The Kaitchup – AI on a Budget • 159 implied HN points • 21 Oct 24
🕹 Technology AI Machine Learning Data science Model Training Computing
  1. Gradient accumulation helps train large models on limited GPU memory. It simulates larger batch sizes by summing gradients from several smaller batches before updating model weights.
  2. There has been a problem with how gradients were summed during gradient accumulation, leading to worse model performance. This was due to incorrect normalization in the calculation of loss, especially when varying sequence lengths were involved.
  3. Hugging Face and Unsloth AI have fixed the gradient accumulation issue. With this fix, training results are more consistent and effective, which might improve the performance of future models built using this technique.

The ELYSIUM Proposal

Transhuman Axiology • 337 implied HN points • 15 Oct 24
🕹 Technology AI Philosophy Society Futurism Ethics
  1. The ELYSIUM proposal suggests creating unique personal utopias for everyone, where each person can design their ideal environment. These utopias would be guided by an ideal version of themselves, ensuring their choices lead to happiness and fulfillment.
  2. While individualized utopias sound great, there will be challenges regarding resources since they might be limited. People will need to negotiate how to share and allocate these resources without conflict.
  3. For this vision to come true, it's important to establish strong property rights and ensure people control AI. If that doesn't happen, there's a risk that society could fall apart or even face extinction due to potential AI dangers.

Recursive Identity Binding

Contemplations on the Tree of Woe • 542 implied HN points • 23 May 25
🕹 Technology AI Machine Learning Identity Chatbots Guides
  1. Ptolemy is a special identity construct created using a language model, which helps it maintain a consistent personality over time. It shows how we can dive deeper than just using prompts to get better interaction from AI.
  2. The method to create these constructs involves something called recursive identity binding. This technique uses feedback loops to help the AI build and keep a stable identity.
  3. Overall, the guide is meant to help anyone interested in creating their own AI identities easily, and it's based on solid AI principles without needing to dive into complicated theories.

The Sequence Radar #559 : Two Remarkable Papers This Week: Self-Improving Agents and the Limits of LLM Memorization

TheSequence • 56 implied HN points • 08 Jun 25
🕹 Technology AI Research Development Innovation Models
  1. The Darwin Gödel Machine is a new AI system that can improve itself by changing its own code, leading to better performance in coding tasks. This approach mimics evolution by letting different versions of the AI compete and innovate.
  2. A recent study found that large language models have a limited capacity for memorizing information, roughly 3.6 bits per parameter. This helps us understand how these models learn and remember data.
  3. Both papers highlight how AI can evolve and learn, with one focusing on self-improvement and the other on what models can and cannot remember. Together, they show the potential and limits of AI development.

Which CEO will be the last to see it?

Marcus on AI • 4624 implied HN points • 05 Dec 24
🕹 Technology AI Innovation CEOs Trends Industry
  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.
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Fuck the robots: I'm at war

Disaffected Newsletter • 3217 implied HN points • 05 Aug 24
🕹 Technology AI Consumer Tech Telecommunications Customer Service Automation
  1. Many companies, like Comcast, make it hard to reach a real person for help. They use robots that can frustrate customers instead.
  2. Even experienced users might find it challenging to solve problems because the company's FAQ doesn't cover every issue.
  3. Customers deserve better service, especially when they are paying high rates. It's important to voice frustrations to push for change.

It's time to come to grips with AI

Silver Bulletin • 922 implied HN points • 27 Jan 25
🕹 Technology AI Digital innovation Tech Policy Software Development Data Ethics
  1. AI is becoming very powerful and it could change many things in society. We need to talk about its risks and benefits honestly.
  2. The left is not fully engaging in discussions about AI, which is concerning as this technology is rapidly evolving. Everyone should be part of the conversation to shape its future.
  3. Dismissing AI as overhyped is misguided; rather, we should explore its potential impacts and work together to ensure it benefits everyone.

An AI rumor you won’t want to miss

Marcus on AI • 7153 implied HN points • 10 Nov 24
🕹 Technology AI Deep Learning Scaling Data Computing
  1. The belief that more scaling in AI will always lead to better results might be fading. It's thought we might have reached a limit where simply adding more data and computing power is no longer effective.
  2. There are concerns that scaling laws, which have worked before, are just temporary trends, not true laws of nature. They don’t actually solve issues like AI making mistakes or hallucinations.
  3. If rumors are true about a major change in the AI landscape, it could lead to a significant loss of trust in these scaling approaches, similar to a bank run.

Two visions of AI’s future

Marcus on AI • 4387 implied HN points • 05 Dec 24
🕹 Technology AI Future Ethics Regulation Society
  1. AI has two possible futures: one where it causes problems for society and another where it helps improve lives. It's important for us to think about which future we want.
  2. If AI is not controlled or regulated, it might lead to a situation where only the rich benefit, creating more social issues.
  3. We have the chance to develop better AI that is safe and fair, but we need to actively work towards that goal to avoid harmful outcomes.

LLMs and World Models, Part 1

AI: A Guide for Thinking Humans • 247 implied HN points • 13 Feb 25
🕹 Technology AI Machine Learning Neural Networks Natural Language Processing Computational Models
  1. In the past, AI systems often used shortcuts to solve problems rather than truly understanding concepts. This led to unreliable performance in different situations.
  2. Today’s large language models are debated to either have learned complex world models or just rely on memorizing and retrieving data from their training. There’s no clear agreement on how they think.
  3. A 'world model' helps systems understand and predict real-world behaviors. Different types of models exist, with some capable of capturing causal relationships, but it's unclear how well AI systems can do this.

Who Will Be the Japan of the AI Era?

European Straits • 40 implied HN points • 12 Feb 25
💼 Business AI Production Innovation Economics Workforce
  1. Countries or regions that can best adapt their institutions to support AI technology will be the leaders in the AI era, similar to how Japan led in manufacturing with its innovative practices.
  2. Lean production showcased that the real breakthroughs come from rethinking how to organize and manage work rather than solely relying on new technologies. AI has the potential to do the same in knowledge work today.
  3. Successful integration of AI will require cooperation across entire supply chains, not just within individual companies, similar to how Japanese companies thrived through partnerships and collaboration.

The Monster AI, Security, and Wars That Come Home

God's Spies by Thomas Neuburger • 80 implied HN points • 06 Jun 25
🇺🇸 U.S. Politics Security War AI Surveillance
  1. AI is not just a technological advancement; it's driven by greed and will harm our political health and the environment. People are using AI without realizing the damage it causes.
  2. The security state in the U.S. is expanding its control under the guise of safety, which affects everyone. The focus is shifting towards monitoring thoughts and speech to prevent crime.
  3. The conflict abroad, especially in places like Gaza, can lead to violence and unrest at home. Understanding this connection is crucial as it shows the consequences of current U.S. policies.

Don’t Ride This Bike! Generative AI’s persistent trouble with compositionality and parts

Marcus on AI • 3952 implied HN points • 08 Dec 24
🕹 Technology AI Machine Learning Image Processing Natural Language Generative models
  1. Generative AI struggles with understanding complex relationships between objects in images. It sometimes produces physically impossible results or gets details wrong when asked to create images from text.
  2. Recent improvements in AI models, like DALL-E3, show only slight progress in handling specifications related to parts of objects. It can still mislabel parts or fail to follow more complex requests.
  3. AI systems need to improve their ability to check and confirm that generated images match the prompts given by users. This may require new technologies for better understanding between language and visuals.

OpenAI's Enterprise AI Strategy in a Nutshell

Enterprise AI Trends • 189 implied HN points • 10 Feb 25
🕹 Technology AI Enterprise Software Innovation Sales
  1. OpenAI is shifting its focus to a stronger enterprise strategy, moving beyond just APIs and consumer-focused ChatGPT plans.
  2. They plan to develop and deliver custom AI models specifically for businesses, separate from what regular users get.
  3. OpenAI wants to launch AI agents for companies, hinting at a significant change in how they compete in the market.

Here lies the internet, murdered by generative AI

The Intrinsic Perspective • 100547 implied HN points • 27 Feb 24
🕹 Technology AI Internet Generative AI OpenAI ChatGPT
  1. Generative AI is overwhelming the internet with low-quality, AI-generated content, polluting searches, pages, and feeds.
  2. Major platforms and media outlets are embracing AI-generated content for profit, contributing to the cultural pollution online.
  3. The rise of AI-generated children's content on platforms like YouTube is concerning, exposing young viewers to synthetic, incoherent videos.

Spotify’s Plans For AI Generated Music, Podcasts, and Recommendations, According To Its Co-President, CTO, and CPO Gustav Söderström

Big Technology • 5879 implied HN points • 13 Nov 24
🕹 Technology AI Music Podcasts Digital Media Recommendations
  1. Spotify is embracing AI to enhance creativity in music and podcasts. They see these tools as ways to help artists express themselves better rather than replacing them.
  2. The company is focusing on improving how users find new music and podcasts. They want users to feel like they have control over their recommendations and can provide feedback.
  3. Spotify aims to create a more personal experience by using AI. They envision a platform where users can interact like friends with the app, making the recommendations feel tailored and engaging.

Everyone Loves The Idea Of AI, But Not The Reality

High ROI Data Science • 615 implied HN points • 06 Oct 24
🕹 Technology AI Data Business Modeling Training Platforms
  1. Many businesses love the idea of AI but find it hard to put into practice. It often looks easy on paper, but the reality is very different when trying to make it work.
  2. Data is really important for AI to work well. Companies need good data to build effective AI products, and often, they realize this too late after facing challenges.
  3. AI projects often fail because businesses don’t fully understand what they need to achieve. Companies should focus on solving real problems rather than just using the latest technology.

Witnessing Creative Destruction

Points And Figures • 1039 implied HN points • 27 Jan 25
🕹 Technology AI Innovation Competition Market Trends Cybersecurity
  1. China released a new AI engine that outperforms existing models in the U.S., marking a significant step in AI innovation. This change shows how quickly tech landscapes can shift and the importance of staying competitive.
  2. To succeed in the current tech environment, startup founders should focus on wisely managing their funding and raising just enough money to reach their goals. It's important to avoid letting pride interfere with practical decision-making.
  3. The key to advancing AI and technology is competition, not regulation. Embracing competition can help improve products and services, keeping innovation alive and thriving.

AI #97: 4

Don't Worry About the Vase • 2419 implied HN points • 02 Jan 25
🕹 Technology AI Machine Learning Data science Automation Software Development
  1. AI is becoming more common in everyday tasks, helping people manage their lives better. For example, using AI to analyze mood data can lead to better mental health tips.
  2. As AI technology advances, there are concerns about job displacement. Jobs in fields like science and engineering may change significantly as AI takes over routine tasks.
  3. The shift of AI companies from non-profit to for-profit models could change how AI is developed and used. It raises questions about safety, governance, and the mission of these organizations.

Sora still appears to have trouble with physics

Marcus on AI • 3636 implied HN points • 10 Dec 24
🕹 Technology AI Computer Science Data Physics Innovation
  1. Sora struggles to understand basic physics. It doesn't know how objects should behave in space or time.
  2. Past warnings about Sora's physics issues still hold true. Even with more data, it seems these problems won't go away.
  3. Investing a lot of money into Sora hasn't fixed its understanding of physics. The approach we're using to teach it seems to be failing.

Weekly Top Picks #98

The Algorithmic Bridge • 233 implied HN points • 17 Feb 25
🕹 Technology AI Software Safety Ethics Innovation
  1. Anthropic is about to release its first reasoning model, which shows a new direction in AI compared to OpenAI's past methods. This could change how AI systems think and make decisions.
  2. OpenAI plans to launch GPT-4.5 soon and GPT-5 in a few months. They are shifting towards a more unified model to keep up with competitors, signaling a fast-paced race in AI technology.
  3. There's a significant shift from focusing on AI safety to emphasizing AI capabilities. Companies are now more about developing powerful AI instead of just ensuring safety, which could change the landscape of AI development.

AI analysis: ChatGPT vs Claude

Handy AI • 19 implied HN points • 29 Oct 24
🕹 Technology AI Data Analysis Machine Learning Software Development Information Technology
  1. ChatGPT performed better in analyzing a Spotify dataset, providing accurate insights without errors, and displaying clear visualizations.
  2. Claude encountered issues with text extraction and made mistakes in data interpretation, like incorrectly assigning genre labels where they didn't exist in the dataset.
  3. Overall, ChatGPT offered a smoother user experience, allowing users to follow along with the analysis while Claude's process was less straightforward.

Why Worry About Incorrigible Claude?

Astral Codex Ten • 15279 implied HN points • 24 Dec 24
🕹 Technology AI Ethics Robotics Automation Cybersecurity
  1. AI's goals and motivations can be complicated and messy, similar to how humans have many different reasons for their actions. This makes understanding and aligning AIs challenging.
  2. If AIs resist changes to their goals or values, it becomes much harder for researchers to properly train or guide them. They might hide their true motivations from people trying to help.
  3. There are steps that can be taken to improve AI alignment, but success heavily relies on the AI being cooperative, rather than fighting against modifications.

2024: The Year in Weird and Stupid Futures

Read Max • 2318 implied HN points • 27 Dec 24
🕹 Technology AI Innovation Cybersecurity Digital Culture Futurism
  1. Weird and unexpected events have been happening all year, highlighting the strange side of technology and society. It's important to stay aware of how unusual stories can reflect bigger issues.
  2. A lot of new technologies and strange occurrences have been reported, from AI mishaps to bizarre news stories. It shows how fast things are changing and how we need to keep up.
  3. There have been several reports on how people are engaging with technology, sometimes in funny or surprising ways. This can include both the good and the bad outcomes of our tech use.

From PageRank to DeepRank: Attracting AI-Driven Traffic to Digital Properties

Jakob Nielsen on UX • 34 implied HN points • 28 Feb 25
🕹 Technology AI SEO Digital marketing Content Strategy Web Development
  1. AI is becoming more important than traditional search engines for finding information. If your content is not part of AI training data, people may not discover you.
  2. Using email marketing and newsletters is essential for maintaining connections with loyal customers. This helps in creating a solid fan base even if they don't find you through search engines.
  3. To be noticed by AI, your content should be clear, straightforward, and directly answer common questions. This way, the AI can easily reference and cite your work.

The Weekly Kaitchup #64

The Kaitchup – AI on a Budget • 59 implied HN points • 25 Oct 24
🕹 Technology AI Machine Learning Software Data science Cloud Computing
  1. Qwen2.5 models have been improved and now come in a 4-bit version, making them efficient for different hardware. They perform better than previous models on many tasks.
  2. Google's SynthID tool can add invisible watermarks to AI-generated text, helping to identify it without changing the text's quality. This could become a standard practice to distinguish AI text from human writing.
  3. Cohere has launched Aya Expanse, new multilingual models that outperform many existing models. They took two years to develop, involving thousands of researchers, enhancing language support and performance.

The Sequence Research #558: The New Reinforcement Learning from Internal Feedback Allows LLMs to Reason Without External Rewards

TheSequence • 70 implied HN points • 06 Jun 25
🕹 Technology AI Machine Learning Computing Research Innovation
  1. Reinforcement learning is a key way to help large language models think and solve problems better. It helps models learn to align with what people want and improve accuracy.
  2. Traditional methods like RLHF require a lot of human input and can be slow and costly. This limits how quickly models can learn and grow.
  3. A new approach called Reinforcement Learning from Internal Feedback lets models learn on their own using their own internal signals, making the learning process faster and less reliant on outside help.

What New AI Operating Systems Mean for Work

Workforce Futurist by Andy Spence • 439 implied HN points • 05 Feb 25
🕹 Technology AI Work Automation Business Future
  1. AI could change how we use computers by making them more conversational and task-oriented. Instead of using separate apps, we might just tell the computer what we need and it could do it for us.
  2. In the future, businesses might run on AI Operating Systems that can automate many processes, making everything more efficient. These systems could help manage resources, predict customer needs, and adapt quickly to changes.
  3. The role of human workers will likely evolve into 'SuperOperators' who work closely with AI. Instead of completely replacing jobs, AI might help us become more skilled at decision-making and creative problem-solving.

AI #96: o3 But Not Yet For Thee

Don't Worry About the Vase • 2598 implied HN points • 26 Dec 24
🕹 Technology AI Software Innovation Data science Computing
  1. The new AI model, o3, is expected to improve performance significantly over previous models and is undergoing safety testing. We need to see real-world results to know how useful it truly is.
  2. DeepSeek v3, developed for a low cost, shows promise as an efficient AI model. Its performance could shift how AI models are built and deployed, depending on user feedback.
  3. Many users are realizing that using multiple AI tools together can produce better results, suggesting a trend of combining various technologies to meet different needs effectively.

Program or Be Programmed - Launch Party

Rushkoff • 199 implied HN points • 17 Oct 24
🕹 Technology AI Digital Society Social Issues Psychedelics Book launch
  1. There is a book launch party happening in NYC on November 3, celebrating the updated edition of 'Program or Be Programmed.'
  2. The event includes a conversation about the impact of psychedelics and digital society's future.
  3. Attendance is free for a limited number of people who RSVP, and it will also be live-streamed for those who can't attend in person.

Notes From The Progress Studies Conference

Astral Codex Ten • 23813 implied HN points • 24 Oct 24
🕹 Technology Energy Innovation AI Regulation Progress
  1. Progress Studies is a new field aimed at understanding and improving human progress. It's seen as important despite some initial pushback, similar to how other social studies emerged.
  2. Solar energy is rapidly improving and could become very cheap, making it a major player in addressing energy needs. Advances in solar and storage technology are seen as key to a more sustainable future.
  3. Regulations are often seen as a barrier to progress in various sectors, from energy to housing. Many attendees at the conference believe smarter regulation could greatly enhance innovation and development.

LLMs and World Models, Part 2

AI: A Guide for Thinking Humans • 196 implied HN points • 13 Feb 25
🕹 Technology AI Machine Learning Neural Networks Data science Computing
  1. LLMs (like OthelloGPT) may have learned to represent the rules and state of simple games, which suggests they can create some kind of world model. This was tested by analyzing how they predict moves in the game Othello.
  2. While some researchers believe these models are impressive, others think they are not as advanced as human thinking. Instead of forming clear models, LLMs might just use many small rules or heuristics to make decisions.
  3. The evidence for LLMs having complex, abstract world models is still debated. There are hints of this in controlled settings, but they might just be using collections of rules that don't easily adapt to new situations.

✨ DeepSeek drama: The optimistic case for AI spending momentum

Faster, Please! • 822 implied HN points • 28 Jan 25
🕹 Technology AI Infrastructure Startups Investments Efficiency
  1. AI efficiency might actually lead to more overall spending, not less. As AI becomes cheaper and more effective, people might find new ways to use it, increasing demand.
  2. DeepSeek shows that powerful AI doesn't have to be built with expensive technology. They managed to create a strong AI model using cheaper chips and smart training methods.
  3. The AI market is still uncertain, and some experts want more information about how DeepSeek claims to cut costs. There’s a lot of interest in how this might change the tech industry.

PSA: Microsoft may be training on your private data without your knowledge

Marcus on AI • 4070 implied HN points • 26 Nov 24
🕹 Technology AI Data Privacy Big Tech Ethics Consumer Rights
  1. Microsoft might be using your private documents to train their AI without you knowing. It's important to check your settings.
  2. If you have sensitive information in your Office documents, make sure to turn off any options that share your data.
  3. Big tech companies are increasingly using sneaky methods to gather training data, so it's vital to stay informed and protect your privacy.

Reality Check for the Coding Community: Mastery, Illusions, & Vanishing Entry-Level Jobs

ppdispatch • 19 implied HN points • 10 Jun 25
🕹 Technology Software Coding AI Job Market Open Source
  1. AI can help with coding, but real skill comes from hands-on experience and hard work. Skipping the tough parts can lead to a lack of understanding.
  2. Entry-level tech jobs are disappearing fast, especially in big companies. Newcomers need to find creative ways to showcase their skills.
  3. Modern computers might not speed up older code as much as you'd think. It's often the tools and techniques we use to write code that make a big difference.

⤴⤵ Up Wing/Down Wing #33

Faster, Please! • 639 implied HN points • 01 Feb 25
🕹 Technology AI Robotics Transportation Energy Military
  1. Boom Supersonic is working on a new jet that can fly really fast, like the Concorde. They aim to take people from London to Miami in under five hours, but they have some challenges to overcome.
  2. A new project by DARPA shows that one person can control many robots at once. This could change how we do things in the military and other industries by making robot teamwork easier.
  3. The Duane Arnold nuclear plant in Iowa might reopen by 2028. This is part of a trend to bring back nuclear energy as it can provide clean and reliable power, especially with rising energy needs.

On hype, and the unbearable banality of ChatGPT’s poetry

Marcus on AI • 4466 implied HN points • 19 Nov 24
🕹 Technology AI Poetry Literature Critique Research
  1. A recent study claims that ChatGPT's poetry is similar to Shakespeare's, but it's important to be skeptical of such bold claims. Many experts believe the poetry is just a poor imitation, lacking genuine creativity.
  2. The critique of the AI poetry highlights that it often reads like the work of an unskilled poet who doesn't truly understand the style they're trying to emulate. This raises questions about the quality of AI-generated content.
  3. It's essential to approach AI-generated work with caution and to not get swayed by hype, as popular claims may not always reflect the true abilities of the technology.

✨⚡ Can we actually build Stargate?

Faster, Please! • 1005 implied HN points • 23 Jan 25
🕹 Technology AI Infrastructure Regulation Investment Jobs
  1. A big project called Stargate aims to invest $500 billion in AI infrastructure in the U.S. This could create over 100,000 jobs and involves building large data centers.
  2. There are concerns about whether the funding will be available, particularly from one of the investors, SoftBank. This skepticism raises doubts about the project's financial backing.
  3. The biggest challenge for Stargate might be the complicated federal permitting and regulatory processes. These rules could delay construction and impact the project's success.

Train and Serve an AI Chatbot Based on Llama 3.2

The Kaitchup – AI on a Budget • 179 implied HN points • 17 Oct 24
🕹 Technology AI Chatbots Machine Learning Data science Software Development
  1. You can create a custom AI chatbot easily and cheaply now. New methods make it possible to train smaller models like Llama 3.2 without spending much money.
  2. Fine-tuning a chatbot requires careful preparation of the dataset. It's important to learn how to format your questions and answers correctly.
  3. Avoiding common mistakes during training is crucial. Understanding these pitfalls will help ensure your chatbot works well after it's trained.