The hottest AI Research Substack posts right now

And their main takeaways
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Top Technology Topics

Weekly Top Picks #99

The Algorithmic Bridge • 191 implied HN points • 24 Feb 25
🕹 Technology AI Research Tech Policy Software Development Data science Innovation
  1. AI labs need to find the right balance between scaling their systems and efficiency in their processes.
  2. There's an AI model that criticized famous figures like Elon Musk and Donald Trump, showing it might lean towards leftist views.
  3. Tyler Cowen believes the slow integration of AI into our society is due to human limitations, not the technology itself.

Reinforcement learning with random rewards actually works with Qwen 2.5

Democratizing Automation • 633 implied HN points • 27 May 25
🕹 Technology AI Research Machine Learning Reinforcement Learning Open Source Computer Science
  1. Reinforcement learning using random rewards can still improve performance in models like Qwen 2.5, even when the rewards aren't perfect. This suggests that the learning process is more flexible than previously thought.
  2. Qwen 2.5 and its math-focused variants show that they might use unique reasoning strategies, like code-assisted reasoning, that help them perform better on math tasks. This means they learn in ways that other models might not.
  3. The ongoing debate about the effectiveness of reinforcement learning with verifiable rewards (RLVR) highlights the need for further research. It also suggests that scaling up the use of reinforcement learning could lead to new behaviors in models, making them more capable.

"Wouldn't It Be Cool If..." Science is a Scourge and We Will Regret It

Freddie deBoer • 9344 implied HN points • 06 Jan 25
🔬 Science Quantum physics Scientific Method AI Research Education
  1. There are tons of resources to learn about science today, but a lot of popular science content can be misleading and full of hype. It's important to be careful about what you believe, especially if you don't have a strong background in the subject.
  2. Many claims in science media, like the existence of alternate dimensions or warp drives, often lack strong evidence. It’s crucial to approach such claims with skepticism rather than taking them at face value.
  3. Real scientific work is usually slow and methodical, rather than exciting breakthroughs. Making science seem too flashy might mislead younger people about what a career in science really involves.

China’s DeepSeek Adds a Weird New Data Point to The AI Race

Am I Stronger Yet? • 282 implied HN points • 30 Jan 25
🕹 Technology AI Models Machine Learning Data Analysis AI Research Competitor Analysis
  1. DeepSeek's new AI model, r1, shows impressive reasoning abilities, challenging larger competitors despite its smaller budget and team. It proves that smaller companies can contribute significantly to AI advancements.
  2. The cost of training r1 was much lower than similar models, potentially signaling a shift in how AI models might be developed and run in the future. This could allow more organizations to participate in AI development without needing huge budgets.
  3. DeepSeek's approach, including releasing its model weights for public use, opens up the possibility for further research and innovation. This could change the landscape of AI by making powerful tools more accessible to everyone.

DeepSeek-R1: Open model with Reasoning

Gonzo ML • 126 implied HN points • 10 Feb 25
🕹 Technology AI Research Machine Learning Natural Language Processing Open Source Reinforcement Learning
  1. DeepSeek-R1 shows how AI models can think through problems by reasoning before giving answers. This means they can generate longer, more thoughtful responses rather than just quick answers.
  2. This model is a big step for open-source AI as it competes well with commercial versions. The community can improve it further, making powerful tools accessible for everyone.
  3. The training approach used is innovative, focusing on reinforcement learning to teach reasoning without needing a lot of examples. This could change how we train AI in the future.
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Universities Are Woefully Under-Resourced For AI Research. They’re Fighting To Change That.

Big Technology • 5129 implied HN points • 22 Nov 24
🕹 Technology AI Research Higher education Public Policy Data science
  1. Universities are struggling to keep up with AI research due to a lack of resources like powerful GPUs and data centers. They can't compete with big tech companies who have millions of these resources.
  2. Most AI research breakthroughs are now coming from private industry, with universities lagging behind. This is causing talented researchers to prefer jobs in the private sector instead.
  3. Some universities are trying to address this issue by forming coalitions and advocating for government support to create shared AI research resources. This could help level the playing field and foster important academic advancements.

Juicy Research Ideas and How to Find them?

AI Research & Strategy • 297 implied HN points • 01 Sep 24
🕹 Technology AI Research Idea Generation Machine Learning Data science Academic Publishing
  1. People often find AI research ideas by reading papers, talking to experts, or browsing online platforms like Twitter and GitHub. These are effective ways to spark inspiration.
  2. There are various strategies for generating AI research ideas, such as inventing new tasks, improving existing methods, or exploring gaps in current research. Each approach can lead to publishing valuable findings.
  3. Building better AI research assistants can involve encoding these idea-generation strategies into their programming. This could make them more effective in supporting researchers.

Not All Layers Are Equal

Gonzo ML • 63 implied HN points • 31 Jan 25
🕹 Technology AI Research Machine Learning Data science Neural Networks Computational Theory
  1. Not every layer in a neural network is equally important. Some layers play a bigger role in getting the right results, while others have less impact.
  2. Studying how information travels through different layers can reveal interesting patterns. It turns out layers often work together to make sense of data, rather than just acting alone.
  3. Using methods like mechanistic interpretability can help us understand neural networks better. By looking closely at what's happening inside the model, we can learn which parts are doing what.

Import AI 357: Facebook's open source AGI plan; Google beats humans at geometry problems; and Intel makes its GPUs better

Import AI • 2076 implied HN points • 22 Jan 24
🕹 Technology AI Research Machine Learning Machine Translation
  1. Facebook aims to develop artificial general intelligence (AGI) and make it open-source, marking a significant shift in focus and possibly accelerating AGI development.
  2. Google's AlphaGeometry, an AI for solving geometry problems, demonstrates the power of combining traditional symbolic engines with language models to achieve algorithmic mastery and creativity.
  3. Intel is enhancing its GPUs for large language models, a necessary step towards creating a competitive GPU offering compared to NVIDIA, although the benchmarks provided are not directly comparable to industry standards.

The Super Weight in Large Language Models

Gonzo ML • 189 implied HN points • 29 Nov 24
🕹 Technology AI Research Machine Learning Data science Computational Models Tech Innovation
  1. There's a special weight in large language models called the 'super weight.' If you remove it, the model's performance crashes dramatically, showing just how crucial it is.
  2. Super weights are linked to what's called 'super activations,' meaning they help generate better text. Without them, the model struggles to create coherent sentences.
  3. Finally, researchers found ways to identify and protect these super weights during the model training and quantization processes. This makes the model more efficient and retains its quality.

Import AI 356: China's good LLM; AI credit scores; and fooling VLMs with REBUS

Import AI • 1238 implied HN points • 15 Jan 24
🕹 Technology AI Research Language Models Compute Robotics
  1. Today's AI systems struggle with word-image puzzles like REBUS, highlighting issues with abstraction and generalization.
  2. Chinese researchers have developed high-performing language models similar to GPT-4, showing advancements in the field, especially in Chinese language processing.
  3. Language models like GPT-3.5 and 4 can already automate writing biological protocols, hinting at the potential for AI systems to accelerate scientific experimentation.

Import AI 371: CCP vs Finetuning; why people are skeptical of AI policy; a synthesizer for a LLM

Import AI • 439 implied HN points • 06 May 24
🕹 Technology AI Research Data Analysis Medical AI Image Generation Internet culture
  1. People are skeptical of AI safety policy as different views arise from the same technical information, making it important to consider varied perspectives.
  2. Chinese researchers have developed a method called SOPHON to openly release AI models while preventing finetuning for misuse, offering a solution for protecting against subsequent harm.
  3. Automating intelligence analysis through datasets like OpenStreetView-5M will enhance training machine learning systems for geolocation, leading to potential applications in both military intelligence and civilian sectors.

Import AI 374: China's military AI dataset; platonic AI; brainlike convnets

Import AI • 339 implied HN points • 27 May 24
🕹 Technology AI Research Search Engines Neural Networks Tech Policy
  1. UC Berkeley researchers discovered a suspicious Chinese military dataset named 'Zhousidun' with specific images of American destroyers, presenting potential implications for military use of AI.
  2. Research suggests that as AI systems scale up, their representations of reality become more similar, with bigger models better approximating the world we exist in.
  3. Convolutional neural networks are shown to align more with primate visual cortexes than transformers, indicating architectural biases that can lead to better understanding the brain.

Setting AIRS Free

AI Research & Strategy • 158 implied HN points • 05 Aug 24
🕹 Technology AI Research Digital Media Health tech Online Publishing Economic Models
  1. The writer has paused billing for their Substack and is offering full refunds to all paid subscribers. They believe it's fair since they haven't been able to provide valuable content recently.
  2. Health challenges impacted the writer's ability to consistently focus on their Substack. They want to put their health first instead of feeling pressured to deliver content.
  3. The writer plans to continue writing occasionally, focusing on joy instead of obligation. They appreciate the support they've received and are thankful for their subscribers.

Import AI 372: Gibberish jailbreak; DeepSeek's great new model; Google's soccer-playing robots

Import AI • 399 implied HN points • 13 May 24
🕹 Technology AI Research Language Models Deep Learning Simulation Ethics
  1. DeepSeek released a powerful language model called DeepSeek-V2 that surpasses other models in efficiency and performance.
  2. Research from Tsinghua University shows how mixing real and synthetic data in simulations can improve AI performance in real-world tasks like medical diagnosis.
  3. Google DeepMind trained robots to play soccer using reinforcement learning in simulation, showcasing advancements in AI and robotics;

Import AI 354: Distributed LLM inference; CCP-approved dataset; AI scientists

Import AI • 1278 implied HN points • 25 Dec 23
🕹 Technology AI Research Language Models Datasets
  1. Distributed inference is becoming easier with AI collectives, allowing small groups to work with large language models more efficiently and effectively.
  2. Automation in scientific experimentation is advancing with large language models like Coscientist, showcasing the potential for LLMs to automate parts of the scientific process.
  3. Chinese government's creation of a CCP-approved dataset for training large language models reflects the move towards LLMs aligned with politically correct ideologies, showcasing a unique approach to LLM training.

Import AI 368: 500% faster local LLMs; 38X more efficient red teaming; AI21's Frankenmodel

Import AI • 559 implied HN points • 08 Apr 24
🕹 Technology AI Research AI Models AI Policy Robotics Artificial Intelligence
  1. Efficiency improvements can be achieved in AI systems by varying the frequency at which GPUs operate, especially for tasks with different input and output lengths.
  2. Governments like Canada are investing significantly in AI infrastructure and safety measures, reflecting the growing importance of AI in economic growth and policymaking.
  3. Advancements in AI technologies are making it easier for individuals to run large language models locally on their own machines, leading to a more decentralized access to AI capabilities.

Import 355: Local LLMs; scaling laws for inference; free Mickey Mouse

Import AI • 1058 implied HN points • 08 Jan 24
🕹 Technology AI Robotics Programming AI Research Computing
  1. PowerInfer software allows $2k machines to perform at 82% of the performance of $20k machines, making it more economically sensible to sample from LLMs using consumer-grade GPUs.
  2. Surveys show that a significant number of AI researchers worry about extreme scenarios such as human extinction from advanced AI, indicating a greater level of concern and confusion in the AI development community than popular discourse suggests.
  3. Robots are becoming cheaper for research, like Mobile ALOHA that costs $32k, and with effective imitation learning, they can autonomously complete tasks, potentially leading to more robust robots in 2024.

In defense of vibes-based evaluations

The AI Frontier • 79 implied HN points • 01 Aug 24
🕹 Technology AI Research Product Development Evaluation Metrics User Experience Data Analysis
  1. Vibes-based evaluations are a helpful starting point for assessing AI quality, especially when specific metrics are hard to define. They allow for initial impressions based on user interactions rather than strict guidelines.
  2. Customers often have unique and unexpected requests that can't easily fit into predefined test sets. Vibes allow for flexibility in understanding real-world usage.
  3. While vibes are useful, they also have downsides, like strong first impressions and limited feedback. A mix of vibes and structured evaluations can provide a better overall understanding of an AI's performance.

OpenAI's o1 using "search" was a PSYOP

Democratizing Automation • 435 implied HN points • 04 Dec 24
🕹 Technology AI Research Machine Learning Data science Computer Science Software Development
  1. OpenAI's o1 models may not actually use traditional search methods as people think. Instead, they might rely more on reinforcement learning, which is a different way of optimizing their performance.
  2. The success of OpenAI's models seems to come from using clear, measurable outcomes for training. This includes learning from mistakes and refining their approach based on feedback.
  3. OpenAI's approach focuses on scaling up the computation and training process without needing complex external search strategies. This can lead to better results by simply using the model's internal methods effectively.

The Top AI Newsletters on Substack in 2023

AI Supremacy • 1179 implied HN points • 18 Apr 23
🕹 Technology AI Research AI Ethics
  1. The list provides a comprehensive agnostic collection of various AI newsletters on Substack.
  2. The newsletters are divided into categories based on their status, such as top tier, established, ascending, expert, newcomer, and hybrid.
  3. Readers are encouraged to explore the top newsletters in AI and share the knowledge with others interested in technology and artificial intelligence.

Import AI 365: WMD benchmark; Amazon sees $1bn training runs; DeepMind gets closer to its game-playing dream

Import AI • 399 implied HN points • 18 Mar 24
🕹 Technology AI Research Robotics AI training
  1. Alliance for the Future (AFTF) was founded in response to concerns about overreach in AI safety regulation, highlighting the importance of well-intentioned policies leading to counter-reactions.
  2. Covariant's RFM-1 shows how generative AI can be applied to industrial robots, allowing easy robot operation through human-like instructions, reflecting a shift towards faster-moving robotics facilitated by AI.
  3. DeepMind's SIMA represents a significant advancement towards a general AI agent by fusing recent AI advancements, showcasing the potential of scaling up diverse AI functions in new environments, opening possibilities for further development and complexity.

Import AI 363: ByteDance's 10k GPU training run; PPO vs REINFORCE; and generative everything

Import AI • 419 implied HN points • 04 Mar 24
🕹 Technology AI Research Reinforcement Learning Language Models Ethics
  1. DeepMind developed Genie, a system that transforms photos or sketches into playable video games by inferring in-game dynamics.
  2. Researchers found that for language models, the REINFORCE algorithm can outperform the widely used PPO, showing the benefit of simplifying complex processes.
  3. ByteDance conducted one of the largest GPU training runs documented, showcasing significant non-American players in large-scale AI research.

Weekly Dose of Optimism #130

Not Boring by Packy McCormick • 168 implied HN points • 07 Feb 25
🕹 Technology AI Research Gene-editing Health tech App Development Sports Analysis
  1. Researchers found a new drug called CT-179 that may help stop childhood brain tumors by keeping cancer stem cells dormant. This could lead to better treatments that stop the cancer from coming back.
  2. OpenAI introduced Deep Research, a new AI that can do detailed research and create expert-level reports quickly. It's designed to help with complicated subjects, making research easier for everyone.
  3. NanoCas is a tiny CRISPR system that can edit genes in muscle and heart tissues, not just the liver. This breakthrough could help treat muscle diseases and improve gene therapies.

Import AI 361: GPT-4 hacking; theory of minds in LLMs; and scaling MoEs + RL

Import AI • 359 implied HN points • 19 Feb 24
🕹 Technology AI Research Cybersecurity Multimodal models Language Models
  1. Researchers have discovered how to scale up Reinforcement Learning (RL) using Mixture-of-Experts models, potentially allowing RL agents to learn more complex behaviors.
  2. Recent research shows that advanced language models like GPT-4 are capable of autonomous hacking, raising concerns about cybersecurity threats posed by AI.
  3. Adapting off-the-shelf AI models for different tasks, even with limited computational resources, is becoming easier, indicating a proliferation of AI capabilities for various applications.

Data Science Weekly - Issue 533

Data Science Weekly Newsletter • 339 implied HN points • 09 Feb 24
🕹 Technology Data science Machine Learning Artificial Intelligence AI Research Data Engineering
  1. Satellite data is important for machine learning and should be treated as a unique area of research. Recognizing this can help improve how we use this data.
  2. Many data science and machine learning projects fail from the start due to common mistakes. Learning from past experiences can help increase the chances of success.
  3. Open source software plays a crucial role in advancing AI technology. It's important to support and protect open source AI from regulations that could harm its progress.

Import AI 359: $1 billion gov supercomputer; Apple’s good synthetic data technique; and a thousand-year old data library

Import AI • 339 implied HN points • 05 Feb 24
🕹 Technology AI Research Supercomputers Data Storage Language Models
  1. Google uses LLM-powered bug fixing that is more efficient than human fixes, highlighting the impact of AI integration in speeding up processes.
  2. Yoshua Bengio suggests governments invest in supercomputers for AI development to stay ahead in monitoring tech giants, emphasizing the importance of AI investment in the public sector.
  3. Microsoft's Project Silica showcases a long-term storage solution using glass for archiving data, which is a unique and durable alternative to traditional methods.
  4. Apple's WRAP technique creates synthetic data effectively by rephrasing web articles, enhancing model performance and showcasing the value of incorporating synthetic data in training.

Import AI 349: Distributed training breaks AI policy; turning GPT4 bad for $245; better weather forecasting through AI

Import AI • 459 implied HN points • 20 Nov 23
🕹 Technology AI Research AI Policy Language Models
  1. Graph Neural Networks are used to create an advanced weather forecasting system called GraphCast, outperforming traditional weather simulation.
  2. Open Philanthropy offers grants to evaluate large language models like LLM agents for real-world tasks, exploring potential safety risks and impacts.
  3. Neural MMO 2.0 platform enables training AI agents in complex multiplayer games, showcasing the evolving landscape of AI research beyond language models.

Import AI 342: Mistral dumps an LLM on BitTorrent; AMD vs NVIDIA; Sutton joins keen

Import AI • 539 implied HN points • 02 Oct 23
🕹 Technology AI Research Language Models
  1. AI startup Lamini is offering an 'LLM superstation' using AMD GPUs, challenging NVIDIA's dominance in AI chip market.
  2. AI researcher Rich Sutton has joined Keen Technologies, indicating a strong focus on developing Artificial General Intelligence (AGI).
  3. French startup Mistral released Mistral 7B, a high-quality open-source language model that outperforms other models, sparking discussions on safety measures in AI models.

Import AI 341: Neural nets can smell; technofeudalism via AI; China releases another solid open access model

Import AI • 459 implied HN points • 25 Sep 23
🕹 Technology AI Research Machine Learning Language Models Data Analysis Artificial Intelligence
  1. China released open access language models trained on both English and Chinese data, emphasizing safety practices tailored to China's social context.
  2. Google and collaborators created a digital map of smells, pushing AI capabilities to not just recognize visual and audio data but also scents, opening new possibilities for exploration and understanding.
  3. An economist outlines possible societal impacts of AI advancement, predicting a future where superintelligence prompts dramatic changes in governance structures, requiring adaptability from liberal democracies.

Import AI 321: Open source GPT3; giving away democracy to AGI companies; GPT-4 is a political artifact

Import AI • 599 implied HN points • 20 Mar 23
🕹 Technology AI Research Model Training Language Models Ethical Implications
  1. AI startup Assembly AI developed Conformer-1 using scaling laws for speech recognition domain, achieving better performance than other models.
  2. The announcement of GPT-4 by OpenAI signifies a shift towards a new political era in AI, raising concerns on the power wielded by private sector companies over AGI development.
  3. James Phillips highlights concerns over Western governments relinquishing control of AGI to US-owned private sector, proposing steps to safeguard democratic control over AI development.

Import AI 334: Better distillation; the UK's AI taskforce; money and AI

Import AI • 399 implied HN points • 10 Jul 23
🕹 Technology AI Research Generative models Funding AI Applications
  1. DeepMind developed Generalized Knowledge Distillation to make large models cheaper and more portable without losing performance.
  2. The UK's £100 million Foundation Model Taskforce aims to shape the future of safe AI and will host a global summit on AI.
  3. Significant financial investments in AI, like Databricks acquiring MosaicML for $1.3 billion, indicate growing strategic importance of AI in various sectors.

The Sequence Radar #472: Remember this Name: Ndea

TheSequence • 77 implied HN points • 19 Jan 25
🕹 Technology AI Research Startups Innovation Machine Learning Data science
  1. Ndea is a new AI lab aiming to create artificial general intelligence (AGI) with a unique approach called guided program synthesis. This approach allows models to learn efficiently from fewer examples.
  2. Francois Chollet, a well-known AI expert, is leading Ndea. He believes current deep learning methods have limitations and wants to explore new ideas for better AI development.
  3. The goal of Ndea is to drive quick scientific advancements by combining program synthesis with deep learning, aiming to tackle tough challenges and possibly discover new scientific frontiers.

The Sequence Research #471: One of the New Techniques Powering in OpenAI GPT-o3

TheSequence • 77 implied HN points • 17 Jan 25
🕹 Technology AI Research Model Training
  1. Deliberate Alignment is a new method to make AI safer and more trustworthy. It helps AI systems better understand and follow safety rules.
  2. This technique is different from older training methods because it teaches the AI explicitly about safety. This means the AI can use that knowledge when responding, especially in tricky situations.
  3. By focusing on this direct instruction, the AI can handle new challenges better and learn from them more efficiently.

Edge 448: Meta AI's Technique For Building LLMs that "Think Before they Speak"

TheSequence • 140 implied HN points • 14 Nov 24
🕹 Technology AI Research Machine Learning Language Models Generative AI
  1. Meta AI is developing new techniques to make AI models better at reasoning before giving answers. This could help them become more like humans in problem-solving.
  2. The research focuses on something called Thought Preference Optimization, which could lead to breakthroughs in how generative AI works.
  3. Studying how AI can 'think' before speaking might change the future of AI, making it smarter and more effective in conversation.

Import AI 350: Neural architecture search at Facebook scale; hunting cancer with PANDA; European VCs launch a science lab

Import AI • 279 implied HN points • 27 Nov 23
🕹 Technology AI Research Open Science
  1. An AI system called PANDA can accurately identify pancreatic cancer from scans, outperforming radiologists.
  2. Facebook developed Rankitect for neural architecture search, which has proven to create better models than human engineers alone.
  3. A European open science AI lab called Kyutai has been launched with a focus on developing large multimodal models and promoting open research.