The hottest AI Substack posts right now

And their main takeaways
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Top Technology Topics

AI Companies Have Lost the Mandate of Heaven

The Algorithmic Bridge • 339 implied HN points • 04 Dec 24
🕹 Technology AI Software Data Computing Innovation
  1. AI companies are realizing that simply making models bigger isn't enough to improve performance. They need to innovate and find better algorithms rather than rely on just scaling up.
  2. Techniques to make AI models smaller, like quantization, are proving to have their own problems. These smaller models can lose accuracy, making them less reliable.
  3. Researchers have discovered limits to both increasing and decreasing the size of AI models. They now need to find new methods that work better while balancing cost and performance.

Data Science Weekly - Issue 560

Data Science Weekly Newsletter • 139 implied HN points • 15 Aug 24
🕹 Technology Data science AI Machine Learning Software Development Programming
  1. The Turing Test raises questions about what it means for a computer to think, suggesting that if a computer behaves like a human, we might consider it intelligent too.
  2. Creating a multimodal language model involves understanding different components like transformers, attention mechanisms, and learning techniques, which are essential for advanced AI systems.
  3. A recent study tested if astrologers can really analyze people's lives using astrology, addressing the ongoing debate about the legitimacy of astrology among the public.

JAX things to watch for in 2025

Gonzo ML • 378 implied HN points • 26 Nov 24
🕹 Technology AI Software Programming Data science Machine Learning
  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.

Will Robot Girlfriends Save Humanity, or Just Speed Up The Collapse?

OK Doomer • 114 implied HN points • 12 Jan 25
🕹 Technology AI Robotics Loneliness Society Relationships
  1. A lot of people, including some men, are seriously considering having romantic relationships with AI and robot girlfriends. This shows how lonely and disconnected people are feeling today.
  2. Tech companies are seeing a huge rise in interest and money making potential from AI girlfriends, pointing to a bigger issue of loneliness in society. People crave connection, but often look for it in tech instead of with real relationships.
  3. The overall trend suggests a shift where people might prefer comfort from technology over real human connections, which could lead to bigger problems in society as our relationships with each other weaken.
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Is This Really Happening?

New World Same Humans • 91 implied HN points • 12 Jan 25
🕹 Technology AI Social media Politics Trends Society
  1. 2025 is expected to be a significant year for change, especially with new political alliances forming around technology.
  2. There's a growing divide between those wanting to speed up technological advancements and those wanting to slow them down due to concerns about their impact on society.
  3. AI is becoming more powerful, possibly leading to major shifts in many aspects of life, and we might soon agree that we are nearing a stage called Artificial General Intelligence.

Is the AI Boom Real?

The Asianometry Newsletter • 3553 implied HN points • 07 Mar 24
🕹 Technology AI Semiconductors Tech Giants Financial sustainability AI Applications
  1. The trillion-dollar investment in AI chips does raise skepticism, with questions about its sustainability and impact on the semiconductor industry.
  2. The concept of scaling laws, driving investments, presents interesting parallels to Moore's Law in the semiconductor industry, suggesting potential future impact on AI.
  3. Competition in AI chips, particularly against Nvidia, is heating up as tech giants aim for vertical integration, potentially shifting the landscape of AI chip design and market dynamics.

Weighing in on Casey Newton's "AI is fake and sucks" debate

The Future, Now and Then • 237 implied HN points • 10 Dec 24
🕹 Technology AI Skepticism Innovation Criticism Tech Ethics
  1. AI is real, but there's a lot of hype around it. It's important to be skeptical and not just believe everything that's promised.
  2. Critics of AI might have valid concerns even if they sometimes say things that sound extreme. Their worries come from seeing the tech's limitations and potential dangers.
  3. When tech leaders make big promises about AI, we should be cautious. Just because some progress has been made doesn't mean all their predictions will come true.

Bullet Points: 2025 is going great so far

The Future, Now and Then • 121 implied HN points • 03 Jan 25
🕹 Technology AI Social media Content creation
  1. An explosion of a Cybertruck in Las Vegas might symbolize the wild unpredictability of 2025. It reflects how many unexpected and chaotic events define the year.
  2. Meta is trying to push AI chatbots that seem out of touch with what people actually want. This decision raises questions about the company's direction and understanding of its users.
  3. A recent debate about Elon Musk's management of Twitter showed how polarized opinions can be. Many arguments are rooted in personal biases, rather than objective analysis of the impacts.

Keeping up with the State-of-the-Art in TechBio

Kesav’s Lab • 9 implied HN points • 21 Feb 25
🕹 Technology Bioinformatics AI Automation Biotechnology Software
  1. The Nobel Prize in Chemistry was awarded for breakthroughs in understanding protein structures, which can lead to better medicines and solutions to major health challenges.
  2. There’s a growing community focused on TechBio, which merges technology and biology. Events like meetups can help people learn and connect over important topics.
  3. Staying informed about the latest in TechBio is important, and contributing to community newsletters helps track new tools and research developments.

My review of THE COMING WAVE

Ground Truths • 7567 implied HN points • 09 Sep 23
🕹 Technology AI Genomics Future of AI Large Language Models
  1. AI is on the brink of transforming our lives with the majority of interactions being with AIs, not people.
  2. The book 'THE COMING WAVE' by Mustafa Suleyman discusses the future of AI integrating life science and digital applications.
  3. The book offers a balanced perspective on AI's potential, historical context, and the challenges and opportunities it presents.

There's Probably Nothing We Can Do About This Awful Deepfake Porn Problem

Freddie deBoer • 4238 implied HN points • 02 Feb 24
🕹 Technology Internet Censorship Communication AI Deepfake
  1. In the age of the internet, censoring content is extremely challenging because of the global spread of digital infrastructure.
  2. Efforts to stop the spread of harmful content like deepfake porn may not be entirely successful due to the structure of the modern internet.
  3. Acknowledging limitations in controlling information dissemination doesn't equate to a lack of will to address concerning issues.

When AI Promises Speed but Delivers Debugging Hell

Nick Savage • 40 implied HN points • 26 Jan 25
🕹 Technology AI Development Programming Software Innovation
  1. Codescribble is a new shared text editor that lets multiple people work on the same document at once. It's designed to be fast and easy to use, similar to Google Docs.
  2. Using AI to help build software can be frustrating and messy, especially if you don’t fully understand how it works. This can lead to a lot of debugging and wasted time.
  3. It's crucial to keep a broader perspective while coding. Getting too focused on small tasks can lead to mistakes and delays, so step back and see the bigger picture.

No, Sora has not “learned physics”

Marcus on AI • 3596 implied HN points • 02 Mar 24
🕹 Technology AI Physics Modeling
  1. Sora is not a reliable source for understanding how the world works, as it focuses more on how things look visually.
  2. Sora's videos often depict objects behaving in ways that defy physics or biology, indicating a lack of understanding of physical entities.
  3. The inconsistencies in Sora's videos highlight the difference between image sequence prediction and actual physics, emphasizing that Sora is more about predicting images than modeling real-world objects.

Part Skis, Part Scooter: Urban Carving on the Skwheel

The Micromobility Newsletter • 2044 implied HN points • 22 Jan 24
🕹 Technology Micromobility Electric Vehicles AI
  1. The Skwheel is a unique urban mobility solution that combines skiing, roller blades, and an electric scooter.
  2. Innovative DIY projects in micromobility include a mountain bike powered by sled dogs and a hand truck converted into a go-kart.
  3. Mobility companies are exploring AI-driven solutions, such as Shimano's suspension components that adjust based on terrain and rider habits.

What I'm preparing for in 2025

next big thing • 76 implied HN points • 08 Jan 25
🕹 Technology AI Crypto Startups Hardware Efficiency
  1. AI is becoming a big part of software development, allowing small teams to create successful products quickly and efficiently. By 2025, we will see a lot more companies thriving because of this.
  2. We are moving towards using AI not just as helpers but as real team members. In 2025, AI will be more about collaboration rather than just assistance.
  3. There will be breakthroughs in other technologies like healthcare or energy that could surprise us, just as AI did in the past. These advancements will create new opportunities for startups.

AI Hallucinations on the Decline

Jakob Nielsen on UX • 21 implied HN points • 13 Feb 25
🕹 Technology AI Usability UX Design Data Analysis
  1. AI models are getting better at reducing false information, called hallucinations. This means they are less likely to make things up over time.
  2. Bigger AI models generally make fewer mistakes. As AI technology improves, we can expect even fewer errors from future models.
  3. While waiting for better AI, improving user experience can help users spot and double-check misleading information, making it easier to trust AI outputs.

China’s AI Boyfriends

ChinaTalk • 444 implied HN points • 29 Oct 24
🕹 Technology AI Companionship Startups Social media Consumer Trends
  1. AI companions are becoming popular in China, especially among young women. They offer emotional support and can fill gaps that real relationships might not fulfill.
  2. Startups like MiniMax are creating AI apps that gather user data while providing companionship. This helps improve their AI models, even if the immediate profits are not high.
  3. The AI companion market faces challenges from strict regulations and data privacy concerns. Many users share personal feelings with these apps, making safety an important issue.

Compound AI is AGI

Generating Conversation • 233 implied HN points • 13 Dec 24
🕹 Technology AI Machine Learning Software Engineering Philosophy Emerging Tech
  1. The debate about whether we've achieved AGI (Artificial General Intelligence) is ongoing. Many people don't agree on what AGI really means, making it hard to know if we've reached it.
  2. The argument is that current AI models can work together to perform tasks at a human-like level. This teamwork, or 'compound AI,' could be seen as a form of general intelligence, even if it's not from a single AI model.
  3. Not all forms of intelligence are the same, and AI systems can do things that humans can’t, but that doesn't mean they can't be considered intelligent. The future potential of AI isn't just about mimicking human intellect; it may also involve different types of skills and knowledge.

AI predictions for 2025

Artificial Ignorance • 126 implied HN points • 08 Jan 25
🕹 Technology AI Predictions Innovation Models Regulation
  1. In 2025, AI will focus more on improving reasoning abilities rather than just building larger models. This means smarter, more capable AI that can think through problems better.
  2. Expect personalized AI experiences to get better, with chatbots that can truly remember and learn about you. This could change how we interact with AI in our daily lives.
  3. There will likely be more AI 'agents' in workplaces, especially for customer service and sales, but many won't live up to the hype. We may see both benefits and gaps in their performance.

Holding two thoughts

Sunday Letters • 139 implied HN points • 11 Aug 24
🕹 Technology AI Computation Software Innovation Tech Culture
  1. AI is a big change, and it's hard to label it just good or bad. We're still figuring out how to use it effectively, but it has a lot of potential.
  2. In everyday life, AI is starting to prove useful in small ways, like transcribing recipes quickly or helping create survey questions.
  3. Just like with e-commerce and search engines, AI will gradually become more integrated into our lives as people find ways to use it better.

Big Tech Myths And Facts: Vision Pro, Google Culture, Digital Ad Market Edition

Big Technology • 3878 implied HN points • 02 Feb 24
🕹 Technology Big Tech AI Digital Advertising Company Culture Revenue
  1. Big Tech companies are experiencing a mix of record revenue and deep layoffs as they navigate the costs of developing new technologies like AI and mixed reality.
  2. Apple may face challenges with the Vision Pro as it might not reach mass-market success until 2030 or beyond, despite initial hype.
  3. Google is acknowledging the need to address its slow-moving culture by simplifying its organizational structure and removing layers to improve efficiency.

Diffusion Models are Evolutionary Algorithms

Gonzo ML • 441 implied HN points • 09 Nov 24
🕹 Technology AI Algorithms Evolution Machine Learning Data science
  1. Diffusion models and evolutionary algorithms both involve changing data over time through processes like selection and mutation, which can lead to new and improved results.
  2. The new algorithm called Diffusion Evolution can find multiple good solutions at once, unlike traditional methods that often focus on one single best solution.
  3. There are exciting connections between learning and evolution, hinting that they may fundamentally operate in similar ways, which opens up many questions about future AI developments.

Odds and Ends #55: The left needs to learn to love AI

Odds and Ends of History • 603 implied HN points • 29 Jan 25
🕹 Technology AI Infrastructure Autonomous Vehicles Logistics Government
  1. The left is often more skeptical about AI compared to the right. Understanding and embracing AI could help reshape perceptions and foster positive changes.
  2. There are important logistics infrastructures that many people overlook in their everyday lives. These systems keep society running smoothly, and it's worth acknowledging their significance.
  3. Google's plans for autonomous vehicles are becoming clearer, which suggests a shift in their business approach. This could mean more practical applications of self-driving technology in the near future.

It's time to change how we cover Elon Musk

Platformer • 3537 implied HN points • 08 Aug 23
🕹 Technology AI Social media Digital Media Antitrust AI Ethics
  1. It's important to approach coverage of Elon Musk with skepticism due to his history of broken promises and exaggerations.
  2. Journalists should be more skeptical and critical of Musk's statements, especially those that could impact markets or public perception.
  3. Musk's tendency to make bold announcements without following through highlights the need for increased scrutiny in media coverage of his statements.

LLMs Know More Than What They Say

LLMs for Engineers • 120 HN points • 15 Aug 24
🕹 Technology AI Machine Learning Data science Software Development Computing
  1. Using latent space techniques can improve the accuracy of evaluations for AI applications without requiring a lot of human feedback. This approach saves time and resources.
  2. Latent space readout (LSR) helps in detecting issues like hallucinations in AI outputs by allowing users to adjust the sensitivity of detection. This means it can catch more errors if needed, even if that results in some false alarms.
  3. Creating customized evaluation rubrics for AI applications is essential. By gathering targeted feedback from users, developers can create more effective evaluation systems that align with specific needs.

Hunting for a Flywheel | Refactoring’s Luca Rossi

Dev Interrupted • 18 implied HN points • 04 Feb 25
🕹 Technology AI Engineering Software Leadership Research
  1. Developer success depends on feeling happy and respected. When developers are motivated, they can work faster and better.
  2. AI is becoming important for all industries, not just tech. Companies like Goldman Sachs are hiring AI experts to improve efficiency.
  3. Automating tasks like code reviews can help teams focus on important work. Tools that make this easy can boost a team's productivity.

AI Stigma: Why Some Users Resist AI’s Help

Jakob Nielsen on UX • 36 implied HN points • 05 Feb 25
🕹 Technology AI User Experience Human factors Collaboration Ethics
  1. Many people are still skeptical about using AI, even when it often performs better than humans. They might rate AI-generated work poorly because they don't trust it.
  2. Collaboration between humans and AI can succeed when they complement each other's strengths. For example, AI can handle data quickly while humans provide deeper understanding.
  3. User attitudes toward AI are influenced by emotions and past experiences. If people have anxiety or distrust toward AI, they might avoid using it or not use it effectively.

Which Jobs will AI Take?

In My Tribe • 653 implied HN points • 23 Jan 25
🕹 Technology AI Jobs Automation Industry Productivity
  1. AI will change many jobs, especially in sectors like transportation and finance, where automation is expected to replace a lot of workers.
  2. Some industries, like health care and entertainment, will likely grow and adapt to include both humans and AI, creating new types of jobs.
  3. The future job market will be different, with many traditional roles disappearing, but it’s believed there will still be plenty of new jobs created in emerging fields.

The AI is eating itself

Platformer • 3419 implied HN points • 27 Jun 23
🕹 Technology AI Social media E-commerce AR Cybersecurity
  1. Generative AI is dramatically impacting the internet with a variety of changes to platforms and services.
  2. The increasing use of AI-generated content poses challenges such as misinformation, disruption, and a dilution of human wisdom.
  3. Research shows that relying on AI systems to generate data can lead to degradation and collapse of models, raising concerns for the future of the web.

OLMo 2 and building effective teams for training language models

Democratizing Automation • 245 implied HN points • 26 Nov 24
🕹 Technology AI Machine Learning Software Development Data science Open Source
  1. Effective language model training needs attention to detail and technical skills. Small issues can have complex causes that require deep understanding to fix.
  2. As teams grow, strong management becomes essential. Good managers can prioritize the right tasks and keep everyone on track for better outcomes.
  3. Long-term improvements in language models come from consistent effort. It’s important to avoid getting distracted by short-term goals and instead focus on sustainable progress.

A Nonconstructive Existence Proof of Aligned Superintelligence

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

Bluesky's big moment

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

Sora Can’t Handle the Truth

Marcus on AI • 3398 implied HN points • 17 Feb 24
🕹 Technology AI Data Errors Training Data Images
  1. Large language models like Sora often make up information, leading to errors like hallucinations in their output.
  2. Systems like Sora, despite having immense computational power and being grounded in both text and images, still struggle with generating accurate and realistic content.
  3. Sora's errors stem from its inability to comprehend global context, leading to flawed outputs even when individual details are correct.