The hottest AI Substack posts right now

And their main takeaways
Category
Top Technology Topics

Satya Nadella and the three stages of scientific truth

Marcus on AI • 6877 implied HN points • 23 Nov 24
🕹 Technology AI Innovation Science Computing Philosophy
  1. New ideas in science often face resistance at first. People may ridicule them before they accept the change.
  2. Scaling laws in deep learning may not last forever. This suggests that other methods may be needed to advance technology.
  3. Many tech leaders are now discussing the limits of scaling laws, showing a shift in thinking towards exploring new approaches.

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

Big Technology • 5003 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.

AI #92: Behind the Curve

Don't Worry About the Vase • 2598 implied HN points • 28 Nov 24
🕹 Technology AI Machine Learning Tech Policy Programming Innovation
  1. AI language models are improving in utility, specifically for tasks like coding, but they still have some limitations such as being slow or clunky.
  2. Public perception of AI-generated poetry shows that people often prefer it over human-created poetry, indicating a shift in how we view creativity and value in writing.
  3. Conferences and role-playing exercises around AI emphasize the complexities and potential outcomes of AI alignment, highlighting that future AI developments bring both hopeful and concerning possibilities.

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.

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

Marcus on AI • 4268 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.
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AI makes scientists more productive and less happy

Philosophy bear • 171 implied HN points • 30 Nov 24
🕹 Technology AI Research Productivity Innovation Science
  1. AI helps scientists work faster and discover more new materials, increasing their productivity significantly.
  2. However, many scientists feel less happy because they spend less time on creative idea generation, which they found enjoyable.
  3. The gap between top and bottom performers in science has widened, with skilled researchers benefiting more from AI, leading to concerns about inequality in the field.

Google Search, SearchGPT, and SerpAPI

Encyclopedia Autonomica • 19 implied HN points • 02 Nov 24
🕹 Technology Search Engines AI Information Retrieval Web Development Data science
  1. Google Search is becoming less reliable due to junk content and SEO tricks, making it harder to find accurate information.
  2. SearchGPT and similar tools are different from traditional search engines. They retrieve information and summarize it instead of just showing ranked results.
  3. There's a risk that new search tools might not always provide neutral information. It's important to ensure that users can still find quality sources without bias.

Tülu 3: The next era in open post-training

Democratizing Automation • 271 implied HN points • 21 Nov 24
🕹 Technology AI Machine Learning Open Source Data science Software Development
  1. Tulu 3 introduces an open-source approach to post-training models, allowing anyone to improve large language models like Llama 3.1 and reach performance similar to advanced models like GPT-4.
  2. Recent advances in preference tuning and reinforcement learning help achieve better results with well-structured techniques and new synthetic datasets, making open post-training more effective.
  3. The development of these models is pushing the boundaries of what can be done in language model training, indicating a shift in focus towards more innovative training methods.

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.

Getting started with AI: Good enough prompting

One Useful Thing • 1807 implied HN points • 24 Nov 24
🕹 Technology AI Software Innovation Education Workplace
  1. Most people struggle to use AI correctly because they treat it like a search engine. Instead, it works better when you give it detailed tasks and prompts.
  2. Getting to know AI takes time; spending about 10 hours using it can help you figure out what it can do for your work or daily tasks.
  3. Think of AI as a patient coworker who forgets everything after each chat. Be clear about what you want, ask for many variations, and have a conversation to get the best results.

Last week at The Lunduke Journal (Nov 3 - Nov 9, 2024)

The Lunduke Journal of Technology • 574 implied HN points • 12 Nov 24
🕹 Technology Software AI Computing Industry News Development
  1. GIMP 3.0 has been released, which is exciting for graphic design enthusiasts. It's always good to have updates that improve software!
  2. Notepad.exe is now using Artificial Intelligence, which sounds surprising. It's interesting to see simple tools getting smarter.
  3. Mozilla recently underwent mass layoffs, which is a significant shift for the company. It shows how the tech industry is always changing and sometimes facing tough decisions.

Datacenter Anatomy Part 1: Electrical Systems

SemiAnalysis • 13334 implied HN points • 14 Oct 24
🕹 Technology Datacenters AI
  1. Datacenters are crucial for AI and require significant power. As demand for AI grows, datacenters must adapt to handle higher power loads efficiently.
  2. New designs and standards are emerging in the datacenter industry. For example, Nvidia's new hardware needs liquid cooling and high power densities, which older designs can't support.
  3. Companies like Meta are making big changes to remain competitive. They scrapped older datacenters to build new ones that can handle greater energy demands and performance requirements.

AI & Python #29: Python Projects You Can Finish in a Weekend

Artificial Corner • 198 implied HN points • 31 Oct 24
🕹 Technology Programming Software AI Education Development
  1. Working on Python projects is important because it helps you apply what you've learned. It's a great way to connect theory to practice and improve your coding skills.
  2. The article suggests projects for both beginners and advanced users, which helps cater to different skill levels. Starting with easier projects can build confidence before tackling more complex ones.
  3. Completing projects can also boost your motivation and help you create a portfolio. This can be really useful when looking for job opportunities or trying to showcase your skills.

Shape, Symmetries, and Structure: The Changing Role of Mathematics in Machine Learning Research

The Gradient • 63 implied HN points • 16 Nov 24
🕹 Technology Machine Learning Mathematics Research AI
  1. Mathematics is playing a bigger role in machine learning by connecting with fields like topology and geometry. This helps researchers create better tools and methods.
  2. It's not just about scaling up current methods; there's a need for new approaches based on mathematical theories. This can lead to more innovative solutions in machine learning.
  3. Mathematicians should view advancements in machine learning as chances to explore and deepen their theoretical work, not as threats to their field. Embracing these changes can lead to new discoveries.

The Story of Nel

Deus In Machina • 36 implied HN points • 29 Nov 24
🕹 Technology Programming Software AI Startups Development
  1. Real programmers often rely on their knowledge and skills rather than on tools like AI and autocomplete features to code. It highlights the importance of understanding the code at a fundamental level.
  2. Having face-to-face conversations and collaboration among team members helped boost productivity when technology failed. Working together led to better problem-solving and learning.
  3. Using simple, effective tools that fit your needs can lead to better coding experiences. Sometimes, going back to the basics can spark creativity and innovation.

OK, I can partly explain the LLM chess weirdness now

DYNOMIGHT INTERNET NEWSLETTER • 796 implied HN points • 21 Nov 24
🕹 Technology AI LLMs Machine Learning Data science Chess
  1. LLMs like `gpt-3.5-turbo-instruct` can play chess well, but most other models struggle. Using specific prompts can improve their performance.
  2. Providing legal moves to LLMs can actually confuse them. Instead, repeating the game before making a move helps them make better decisions.
  3. Fine-tuning and giving examples both improve chess performance for LLMs, but combining them may not always yield the best results.

Open Thread 352

Astral Codex Ten • 2408 implied HN points • 21 Oct 24
🕹 Technology AI Conferences Community Networking
  1. You can join weekly open threads to discuss anything or ask questions. It's a great way to interact with others.
  2. There are various events and conferences coming up that focus on AI and social skills, which you might find interesting.
  3. If you entered a book review contest, make sure to check if you've received your prize. Email if you think you missed out.

The Knowledge Illusion

In Bed With Social • 416 implied HN points • 27 Oct 24
🚌 Education Learning Knowledge Technology AI Critical Thinking
  1. AI can provide quick answers, but this doesn't lead to real understanding. It's important to engage in learning actively to truly grasp the knowledge.
  2. The value of knowledge is changing with technology. While access to information is easier now, it can lead to shallow thinking if we rely on AI too much.
  3. Learning should be about growth, not just getting answers. We should use AI to inspire deeper questions and foster our critical thinking instead.

An epidemic of weirdly precise AI butt facts

Marcus on AI • 4703 implied HN points • 30 Oct 24
🕹 Technology AI Investments Future Trends Innovation Predictions
  1. Elon Musk and others often make bold claims about AI's future, but many of these predictions lack proper evidence and are overly optimistic.
  2. Investors are drawn to grand stories about AI that promise big returns, even when the details are vague and uncertain.
  3. The exact benefits of advanced AI, like machines being thousands of times smarter, are unclear, and it's important to question how that would actually be useful.

‘We Were Wrong’

Magic + Loss • 159 implied HN points • 29 Oct 24
🕹 Technology Internet Media AI Nostalgia Culture
  1. WIRED's first website, HotWired, launched the digital age by covering topics that traditional media missed. It helped introduce many people to the online world.
  2. The internet has evolved into a chaotic space filled with dangers like misinformation, cybercrime, and trolls. This raises the question of whether it was handled well from the start.
  3. Even though WIRED helped shape the internet, it recognizes its role in the problems that have emerged over the years and reflects on how things might have been different.

Edge 445: A New Series About Knowledge Distillation

TheSequence • 35 implied HN points • 05 Nov 24
🕹 Technology AI Data science Machine Learning Computing Engineering
  1. Knowledge distillation helps make large AI models smaller and cheaper. This is important for using AI on devices like smartphones.
  2. A key goal of this process is to keep the accuracy of the original model while reducing its size.
  3. The series will include reviews of research papers and discussions on frameworks like Google's Data Commons that support factual knowledge in AI.

JAX things to watch for in 2025

Gonzo ML • 189 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.

Looking Back: One Year Of Big Technology's Paid Edition

Big Technology • 4128 implied HN points • 22 Oct 24
🕹 Technology Tech news AI Subscriptions Journalism Events
  1. The launch of paid subscriptions for Big Technology has been a success, allowing the publication to grow and provide better content.
  2. The newsletter included valuable insights on major tech companies like Amazon and Google, highlighting important trends and changes in leadership.
  3. Engagement with subscribers has been strong, with the addition of exclusive podcasts and events, making the relationship between the writer and readers even more meaningful.

Something weird is happening with LLMs and chess

DYNOMIGHT INTERNET NEWSLETTER • 1515 implied HN points • 14 Nov 24
🕹 Technology AI LLMs Chess Gaming Research
  1. Large language models (LLMs) can somewhat play chess, but they struggle after the opening moves. They were not specifically designed for chess, yet they can manage to play using their text training.
  2. The performance of different language models varies significantly when playing chess. Some models like 'gpt-3.5-turbo-instruct' excel at it, while others perform very poorly.
  3. It seems that focusing on instruction tuning can make LLMs worse at chess, suggesting that training style impacts their ability to play games effectively.

Weekly Dose of Optimism #120

Not Boring by Packy McCormick • 116 implied HN points • 15 Nov 24
🕹 Technology AI Genomics Energy Data science
  1. The U.S. is planning to triple its nuclear power capacity by 2050, aiming for 200 gigawatts through new reactors and upgrades. This is a big move to meet rising energy demands in a safe and efficient way.
  2. Molecular nanotechnology could revolutionize production, possibly outpacing past technological shifts like the Industrial Revolution. It's an exciting frontier that stands to vastly increase our capabilities in various fields.
  3. Evo, a new AI model, shows promise in predicting and designing genomes, potentially creating new life forms. This technology could push the boundaries of biological science and genetic engineering significantly.

The Impact of the Calibration Dataset for AutoRound and AWQ Quantization

The Kaitchup – AI on a Budget • 39 implied HN points • 31 Oct 24
🕹 Technology AI Data science Machine Learning Quantization Model optimization
  1. Quantization helps reduce the size of large language models, making them easier to run, especially on consumer GPUs. For instance, using 4-bit quantization can shrink a model's size by about a third.
  2. Calibration datasets are crucial for improving the accuracy of quantization methods like AWQ and AutoRound. The choice of the dataset impacts how well the quantization performs.
  3. Most quantization tools use a default English-language dataset, but results can vary with different languages and datasets. Testing various options can lead to better outcomes.

Artwashing

Teaching computers how to talk • 131 implied HN points • 27 Nov 24
🕹 Technology AI Ethics Media Art Culture
  1. A group of artists leaked access to OpenAI's new video generator, Sora, because they feel it's being used for corporate marketing instead of true art.
  2. They published an open letter saying that AI companies often use artists' work without proper credit or compensation, which hurts the creative community.
  3. The artists believe that by helping AI models, they might be contributing to their own downfall, as AI is taking over creative spaces.

⤴⤵ Up Wing/Down Wing #26

Faster, Please! • 731 implied HN points • 23 Nov 24
🕹 Technology AI Robotics Genetics Space
  1. A robotics startup called Physical Intelligence is worth over $2 billion for creating AI-controlled robots that can do complex tasks like folding clothes. They use advanced technology that makes robots smarter and more capable.
  2. Trump is working with a startup called Anduril to improve the US military by adopting new technologies and cutting unnecessary costs. This shows a shift towards more innovative approaches in defense.
  3. Scientists have made tomatoes sweeter and bigger using a method called CRISPR. This could lead to tastier fruits in stores and lower production costs for things like tomato paste.

The Lamplighter Problem

Jeff Giesea • 718 implied HN points • 22 Oct 24
🕹 Technology AI Automation Labor Economy Politics
  1. AI is likely to displace a huge number of jobs, similar to how lamplighters lost their roles when electric lights came in. We need to prepare for these changes now to help people transition to new work.
  2. The Lamplighter Problem shows us that job loss due to automation is not just an economic issue but also a political and social one. If we don’t address it, it could lead to bigger problems in society.
  3. There are different opinions on how to handle the rise of AI. Some people think we should slow down and reconsider, while others want to speed up its development. We need to find a balanced approach that helps everyone.

What Does Hitting Scaling Law Limit Mean for US-China AI Competition

Interconnected • 215 implied HN points • 18 Nov 24
🕹 Technology AI Machine Learning International relations Global Competition Data science
  1. The scaling law for AI models might be losing effectiveness, meaning that simply using more data and compute power may not lead to significant improvements like it did before.
  2. US export controls on AI technology may become less impactful over time, as diminishing returns on AI model scaling could lessen the advantages of having the most advanced hardware.
  3. If AI development slows down, the urgency for a potential 'AI doomsday' scenario may decrease, allowing for a more balanced competition between the US and China in AI advancements.

What if AI eventually makes programmers smarter, not dumber?

Bite code! • 1467 implied HN points • 15 Nov 24
🕹 Technology AI Programming Software Development Automation
  1. AI can help programmers by reducing the amount of typing they do. This means they can focus more on solving problems instead of just writing code.
  2. As programmers use AI tools more, they might become better at understanding and defining problems instead of just following strict coding rules.
  3. In the long run, AI could make the whole community of developers smarter. It will lower the barrier for entry to coding and help people learn more about the real issues we need to solve.

How I got 27 hours in a week by installing one tool

High Growth Engineer • 1024 implied HN points • 17 Nov 24
🕹 Technology Productivity Tools Software AI Workflow Engineering
  1. Using tools like Raycast can save a lot of time by centralizing different functions on your computer. It allows you to quickly access apps and features, making your workflow smoother.
  2. Having features like an instant AI chat is really useful for quickly finding answers to questions without interrupting your flow. You can get help right when you need it, without the hassle of opening new tabs.
  3. Text expanders are great for saving time on repetitive typing. They let you create shortcuts for common phrases, making it faster to communicate and reducing effort in your daily tasks.

Please take our programming assessment with an LLM

Creating Value from Nothing • 185 implied HN points • 05 Nov 24
🕹 Technology Software Engineering AI Product Remote work
  1. Clipboard Health is using real-case programming problems in their hiring process. This helps them see how candidates actually work and fit into their async work culture.
  2. They believe that using LLMs, like chatbots or AI tools, is okay during assessments. They see these tools as standard parts of a modern engineer's toolkit, not as cheats.
  3. By allowing LLM use, they hope to create better assessments that truly evaluate a candidate's skill, helping to find the best engineers for their team.

What does slow AI look like?

The Sublime Newsletter • 1941 implied HN points • 12 Oct 24
🕹 Technology AI Productivity Software Human-Computer Innovation
  1. People often feel stressed because productivity tools are designed to make us work faster, but that doesn't match how we naturally want to create things.
  2. Instead of rushing to produce more content quickly, we should focus on making fewer things but doing them better and with more care.
  3. It's okay to take time in the creative process; in fact, taking time can help us create something truly wonderful.

Robotics is Inching Towards it ChatGPT Moment

TheSequence • 84 implied HN points • 03 Nov 24
🕹 Technology AI Robotics Innovation Data science Machine Learning
  1. Robots are getting smarter with new tech, especially using large language models, which help them learn and do tasks better.
  2. MIT's new technique helps robots understand different types of data, making them more capable and efficient in their work.
  3. There’s a big push for robots to interact more naturally with humans, like being able to feel and handle objects carefully, which can improve everyday tasks.

How Super Apps & Platforms Are Turning AI On Its Head

High ROI Data Science • 79 implied HN points • 30 Oct 24
🕹 Technology AI Platforms Apps Business Models Consumer behavior
  1. Super apps in Asia grow by offering many services to a smaller customer base, unlike Big Tech that focuses on single services for many users. This helps them cater better to local needs.
  2. The advantages of super apps include faster product development, lower costs for data collection, and a unique competitive edge through exclusive data. They can quickly adapt to market changes too.
  3. Wrtn, a South Korean startup, shows how a super app can combine multiple AI services into one platform. This model offers better value to users and keeps them engaged with ads instead of multiple expensive subscriptions.

AI #89: Trump Card

Don't Worry About the Vase • 1881 implied HN points • 07 Nov 24
🕹 Technology AI Policy Innovation Regulation Infrastructure
  1. Trump's potential return to office could change AI policy significantly. He plans to revoke existing regulations but may not have a clear replacement, which could impact the tech landscape.
  2. Language models are becoming more important in everyday tasks, but they also face challenges. While they improve productivity, they can also lead to decreased job satisfaction for users.
  3. There is growing concern about AI's influence on politics and decision-making. Studies show that AI models can affect voters' opinions, highlighting the need for caution in how they are used.

Case Study: Scaling customer intelligence

Artificial Ignorance • 88 implied HN points • 27 Nov 24
💼 Business Sales Marketing AI Data Analysis Customer Insights
  1. AI can help analyze a large number of sales calls quickly instead of relying on humans to do it manually. This makes it easier to understand customer behaviors and needs.
  2. Choosing the right AI model is important. Higher quality models may cost more, but they can provide better and more accurate results over cheaper options.
  3. It’s essential to make the data user-friendly. Organizing and making information accessible helps teams use insights from the analysis effectively.

🎭✨ Ben Affleck’s wise words on AI

Faster, Please! • 731 implied HN points • 18 Nov 24
🕹 Technology AI Economics Innovation Automation Employment
  1. New technology, like AI, can help reduce costs. This can make it easier for more people to access entertainment and creative content.
  2. There's a common fear that robots will take over jobs, but it's important to understand how technology can create new opportunities instead.
  3. Adapting to new technologies can lead to a demand for different skills. Learning and evolving with technology is key to staying relevant in the job market.