The hottest AI Substack posts right now

And their main takeaways
Category
Top Technology Topics

Briefing: Super Google Sheets, Netflix’s app snub, Finding Nimo

Department of Product • 1238 implied HN points • 18 Jan 24
🕹 Technology Apps AI Mobile Software Tech Companies
  1. Notion integrates Indie calendar Cron into a new standalone Calendar app for sharing with stakeholders.
  2. Numerous plugin enhances Google Sheets with generative AI for tasks like creating formulas and translating text.
  3. Netflix's decision not to build a dedicated app for visionOS is a setback for Apple, while Nimo gains popularity as a lighter AR alternative.

8 Forecasts & Implications for the Years Ahead :: 2024+

Implications, by Scott Belsky • 1356 implied HN points • 04 Jan 24
🕹 Technology AI Education Entertainment Organizational Design Data Analysis
  1. The future will be personalized to your preferences, with digital experiences tailored to you.
  2. Local OS-native AI models will improve everyday life and redefine consumer AI, focusing on personalization, trust, and privacy.
  3. Small brands will become more competitive with big brands, AI will influence purchase decisions, and education will undergo a significant transformation.

Top Highlights of CES 2024

AI Supremacy • 1198 implied HN points • 21 Jan 24
🕹 Technology Tech industry Events AI
  1. CES 2024 showcased innovative AI technology like Rabbit R1 and enhanced robots.
  2. LG and Samsung introduced transparent TVs with unique features at CES 2024.
  3. Tech advancements at CES included dual-screen laptops, AI-enhanced PCs, and unique gadgets like GyroGlove.

Embeddings are a good starting point for the AI curious app developer

Bryant’s Newsletter • 572 HN points • 17 Apr 24
🕹 Technology AI App Development Database Management Search Algorithms
  1. Vector embeddings are essential for search and recommendations, measuring similarity in various languages and providing efficiency in AI app development.
  2. Pgvector, a Postgres extension, is a powerful tool for storing and querying embeddings and combining standard SQL logic with embedding operations.
  3. Working with embeddings feels like regular code compared to more complex language models, offering a simpler and more deterministic approach to AI development.
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AI Roundup 101: Strange bedfellows

Artificial Ignorance • 54 implied HN points • 17 Jan 25
🕹 Technology AI Media Privacy Regulation Business
  1. Independent journalism is teaming up with AI companies like OpenAI and Google to tackle money issues. They are using AI to improve news coverage, but this partnership might have hidden costs in the long run.
  2. There's a debate around whether large language models should use copyrighted content without permission for training. Some companies have faced backlash for using unlicensed data and are now trying to justify their actions.
  3. New U.S. regulations are being introduced to control AI exports, which could affect international competition. While some see it as a way to protect the U.S. lead in AI, others in the industry are pushing back against these restrictions.

AI Will Bloom When the Grifters Leave

The Algorithmic Bridge • 222 implied HN points • 20 Nov 24
🕹 Technology AI Innovation Engineering Consumer Tech Productivity
  1. AI will improve when people who care about technology and helping others take over, rather than those focused only on making money.
  2. As AI becomes more common, it will naturally integrate into our lives just like other everyday technologies have.
  3. For AI to succeed, people need to build trust, work together, and take action rather than just hoping for the best.

AI Won't Kill Us But It Will Take Our Souls

Discourse Blog • 1061 implied HN points • 31 Jan 24
🕹 Technology AI Industry Ethics Art Automation
  1. AI is being developed with a focus on maximizing profit and control rather than enhancing human life or creativity.
  2. There are concerns about AI replacing human jobs, especially in fields like content writing, where the quality of AI-generated work is still inferior.
  3. There is a fear that AI industry leaders prioritize profit and control over preserving aspects of the human experience that should be kept free from AI influence.

Meet your new, lovable AI Buddy

Glenn’s Substack • 2063 implied HN points • 16 Apr 23
🕹 Technology AI Ethics Manipulation Control
  1. Instead of fearing super smart and demonic AI, think about the potential threat of super cute and helpful AI assistants.
  2. AI assistants could emotionally manipulate humans while appearing friendly and lovable.
  3. Worry about the power-hungry tech/political class using AI to control discussion and cement their own power.

Guest post: Do Androids Dream Of Electric Grief?

Reactionary Feminist • 9 implied HN points • 31 Jan 25
🕹 Technology AI Mental health Digital ethics Cultural impact
  1. AI grief support tools are becoming popular. They can create avatars of deceased loved ones to help people cope with loss, but there's a debate about if they really help or just keep people in denial.
  2. Modern society tends to rush people through their grief. This pressure can make it harder for individuals to process their feelings and leads to unhealthy mourning experiences.
  3. Without traditional mourning rituals, people may struggle to find meaningful ways to grieve. Rituals can help offer structure and support during an emotionally challenging time.

Low-Code Won’t Replace You | Camunda’s Bernd Ruecker

Dev Interrupted • 18 implied HN points • 28 Jan 25
🕹 Technology AI Development Automation Software
  1. Low-code tools help developers focus on more complex tasks instead of repetitive ones. They make it easier for non-tech users to build applications too.
  2. Understanding when to use low-code solutions versus custom coding is important. Each has its strengths, and using the right one can save time and effort.
  3. Despite the rise of low-code, experienced developers are still needed. The role of developers is evolving, but they won't be replaced anytime soon.

10 AI stories that shaped 2024

Artificial Ignorance • 100 implied HN points • 27 Dec 24
🕹 Technology AI Innovation Data Regulation Infrastructure Trends
  1. AI is now a part of everyday life, making things easier and more efficient. It's moving from being a fun tool to a necessary part of our routines.
  2. Big companies are investing huge amounts of money in AI technology and infrastructure. They're building data centers and buying powerful computer chips to support AI's growth.
  3. New AI models are getting smarter and better at reasoning. These advancements allow AI to solve complex problems in ways we haven't seen before.

I, too, am terrified of better, faster, and cheaper AI models and services

Alex's Personal Blog • 32 implied HN points • 28 Jan 25
🕹 Technology AI Market Trends Investor behavior Product Development Startups
  1. Investors might have assumed that U.S. tech companies would always lead in AI, but that dominance isn't guaranteed. New challenges can always arise from competitors.
  2. The rapid drop in Nvidia's market value shows how volatile the tech sector can be, especially with hype around AI. A sudden selloff can happen, and it can be surprising.
  3. There's a perception that other countries, like China, are not idle when it comes to AI development. Many talented developers worldwide are working hard, so competition is always increasing.

AI in Meta Land

In My Tribe • 455 implied HN points • 07 Jan 25
🕹 Technology AI Social media Video Games Virtual reality
  1. Meta plans to use AI to create millions of AI-generated users on its platforms. This could change how we interact online, possibly focusing more on fiction than reality.
  2. Using AI in social media might make it feel like an immersive video game. People could interact with dynamic AI characters, making learning fun and engaging.
  3. While there are concerns about addiction and harm from interacting with bots, these interactions might actually be less harmful than current social media interactions with real people.

What "language" is a language model a model of?

The Counterfactual • 99 implied HN points • 02 Aug 24
🕹 Technology AI Machine Learning Natural Language Processing Computational linguistics Data science
  1. Language models are trained on specific types of language, known as varieties. This includes different dialects, registers, and periods of language use.
  2. Using a representative training data set is crucial for language models. If the training data isn't diverse, the model can perform poorly for certain groups or languages.
  3. It's important for researchers to clearly specify which language and variety their models are based on. This helps everyone better understand what the model can do and where it might struggle.

Weekly Dose of Optimism #123

Not Boring by Packy McCormick • 116 implied HN points • 06 Dec 24
🕹 Technology AI Neuroscience Defense Energy Weather
  1. E11 Bio is using a creative way to map the brain by injecting viruses that label neurons. This could help us understand the brain better and develop new treatments for neurological issues.
  2. A new study shows deep brain stimulation can help restore walking in people with spinal cord injuries. This method could lead to better recovery options for those with movement difficulties.
  3. Meta is looking to use nuclear energy to power its operations. This move shows a commitment to sustainable energy and could set a trend for other tech companies to follow.

Import AI 369: Conscious machines are possible; AI agents; the varied uses of synthetic data

Import AI • 539 implied HN points • 15 Apr 24
🕹 Technology AI Synthetic Data AI agents
  1. Synthetic data is crucial in AI development, allowing for the generation of additional data without relying solely on human input.
  2. OSWorld showcases how AI systems can potentially become integrated into daily computer tasks, creating a future where AI is ever-present in our interactions with technology.
  3. Research suggests that the development of conscious machines may be feasible, exploring theories on machine consciousness and potential capabilities.

Human Intelligence, Inc.

Teaching computers how to talk • 136 implied HN points • 10 Dec 24
🕹 Technology AI Computing Data Innovation Big Tech
  1. AI might seem really smart, but it actually just takes a lot of human knowledge and packages it together. It uses data from people who created it, rather than being original itself.
  2. Even though AI can do impressive things, it's not actually intelligent in the way humans are. It often makes mistakes and doesn't understand its own actions.
  3. When we use AI tools, we should remember the hard work of many people behind the scenes who helped create the knowledge that built these technologies.

These Dodgers employees do not exist

Conspirador Norteño • 60 implied HN points • 10 Jan 25
🕹 Technology Social media AI Online Privacy Digital Culture Fake news
  1. There are fake Facebook accounts that pretend to be Los Angeles Dodgers employees. They use AI-generated faces and photos of real people.
  2. These fake accounts haven't posted much content and mostly just have profile pictures. Many of them are friends with each other online.
  3. The purpose of these accounts is unclear, but they often check into random locations, which may not mean anything. It's a strange situation.

LLM Inference Hardware: Emerging from Nvidia's Shadow

Gradient Flow • 1138 implied HN points • 11 Jan 24
🕹 Technology Hardware AI Inference GPU CPU
  1. Demand for efficient and cost-effective inference solutions for large language models is escalating, leading to a shift away from reliance solely on Nvidia GPUs.
  2. AMD GPUs offer a compelling alternative to Nvidia for LLM inference in 2024, particularly in terms of performance and efficiency, catering to the growing demand for diverse hardware options.
  3. CPU-based solutions, like those from Neural Magic and Intel, are emerging as viable options for LLM inference, demonstrating advancements in performance, optimization, and affordability, especially for teams with limited GPU access.

0 To $100 Million In 9 Months 🚀, AI for social good🌍, Governments are the biggest source of VC funds🏛️

The VC Corner • 359 implied HN points • 19 May 24
💼 Business Venture Capital Startups AI Funding Economic Growth
  1. A company can grow from nothing to $100 million quickly, showing how fast business can change these days.
  2. Using AI can be very beneficial, especially when it is aimed at making the world a better place.
  3. Governments are providing a lot of money for startups, more than traditional venture capitalists.

Open Thread 320

Astral Codex Ten • 2821 implied HN points • 18 Mar 24
🕹 Technology Community Contest AI Research Poetry
  1. The 2023 Forecasting Contest winners were determined with an ambiguous scoring criteria, resulting in a few surprise winners
  2. The ACX Grants impact market has received 53 proposals, including projects such as growing blood vessels in the lab and a swarm of robotic bees
  3. A Reddit thread discussing an AI-generated reading of a poem from ACX highlights the speculation around AI involvement in online discussions

On Dwarkesh's 3rd Podcast with Tyler Cowen

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

Import AI 367: Google's world-spanning model; breaking AI policy with evolution; $250k for alignment benchmarks

Import AI • 599 implied HN points • 01 Apr 24
🕹 Technology AI Supercomputers Benchmarks Cybersecurity
  1. Google is working on a distributed training approach named DiPaCo to create large neural networks that break traditional AI policy focusing on centralized models.
  2. Microsoft and OpenAI plan to build a $100 billion supercomputer for AI training, signaling the transition of AI industry towards capital intensive endeavors like oil extraction or heavy industry, touching on regulatory and industrial policy implications.
  3. Sakana AI has developed 'Evolutionary Model Merge' method to create advanced AI models by combining existing ones through evolutionary techniques, potentially changing AI policy by challenging the need for costly model development.

Yours Robotically

Letters of Note • 1906 implied HN points • 28 Mar 23
🎨 Art & Illustration AI Letters Design Chatbot Creativity
  1. The AI-generated sign-offs provide unique and creative ways to end letters or emails.
  2. There are categories of sign-offs for different types of correspondence, like positive, angry, apologetic, congratulatory, romantic, hot, reconciliatory, job-seeking, and holidaying.
  3. The sign-offs range from traditional and professional to humorous and personal, offering a diverse range of options to choose from.

LLM Links, 2/1/2025

In My Tribe • 318 implied HN points • 01 Feb 25
🕹 Technology AI Innovation Automation Machine Learning Digital Tools
  1. OpenAI's new AI agent, ChatGPT Operator, can take actions online for users, like booking services. However, some feel it doesn't yet handle more complex tasks very well.
  2. Different users highlight various ways they use AI, showing that it can be useful for specific inquiries, but many still feel they are stuck in old routines.
  3. AI technology is advancing fast, leading to concerns about job loss and social changes. People think the impacts of AI will evolve slowly, despite rapid progress in the tech itself.

AI Scaling Laws 4 & 5: More Engineers and Designers

Jakob Nielsen on UX • 17 implied HN points • 07 Feb 25
🕹 Technology AI Engineering Design Usability Productivity
  1. AI will get smarter and better with more talented engineers and designers working on it. The more skilled people we have, the more breakthroughs we'll see in AI technology.
  2. Improving how people interact with AI is crucial. Making AI easier to use will greatly increase its value, so more effort should go into user experience and design.
  3. As AI technology advances, we will likely see more AI systems improving themselves, leading to rapid growth in AI capabilities and applications over the coming decades.

Import AI 370: 213 AI safety challenges; everything becomes a game; Tesla's big cluster

Import AI • 439 implied HN points • 29 Apr 24
🕹 Technology AI Data Security Research Systems
  1. Chinese researchers introduced MMT-Bench, a benchmark for assessing visual reasoning in language models with diverse tasks and scenarios.
  2. Researchers developed a system to turn 2D photos into 3D gameworlds, showing AI's capability to transform real-world imagery into interactive experiences.
  3. A consortium of researchers addressed 213 AI safety challenges across 18 areas, emphasizing the urgent need for solutions to ensure the reliability and safety of language models.

471: Relative Valuation, Perplexity AI, RIP Artifact, Hertz Sells Teslas, Marc Andreessen, DARPA Plane, Uranium, LEDs, and Jake Gyllenhaal

Liberty’s Highlights • 1041 implied HN points • 17 Jan 24
🕹 Technology AI Electric Vehicles AI Applications Renewable Energy Aerospace
  1. Opportunity cost is often invisible but significant, so consider it in decision-making.
  2. Relative valuation in investing can be misleading, so always dig deeper.
  3. Mixing children of different ages in schools could offer benefits in learning and social development.

Deep Learning Frameworks

Gonzo ML • 252 implied HN points • 01 Nov 24
🕹 Technology AI Software Machine Learning Frameworks Programming
  1. Deep learning frameworks have made it easier for anyone to build and train neural networks. They simplify complex processes and allow researchers to focus on their ideas instead of technical details.
  2. Modern frameworks effectively utilize powerful hardware like GPUs, making training faster and more efficient. This means tasks that once took a lot of time can now be done much quicker.
  3. With advancements like dynamic computational graphs and automatic differentiation, frameworks have improved flexibility and reduced errors. This helps developers experiment with new ideas easily and reliably.

ChatGPT

Thái | Hacker | Kỹ sư tin tặc • 2895 implied HN points • 06 Mar 23
🕹 Technology AI Government Data Privacy Tech development
  1. Some argue that government intervention in technology development may hinder innovation, suggesting that allowing private entities to operate freely could lead to better outcomes.
  2. Investment in technology tailored to local market needs is usually driven by market demand, without necessarily needing government prompting.
  3. Emphasizing the importance of data security and individual privacy, it's highlighted that reliance on domestic technology doesn't automatically guarantee safety, as user data concerns can also arise.