The hottest AI Research Substack posts right now

And their main takeaways
Top Technology Topics
Import AI • 339 implied HN points • 27 May 24
  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.
Import AI • 399 implied HN points • 13 May 24
  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 • 439 implied HN points • 06 May 24
  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 • 2076 implied HN points • 22 Jan 24
  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.
Import AI • 559 implied HN points • 08 Apr 24
  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.
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Import AI • 539 implied HN points • 25 Mar 24
  1. DROID dataset boosts performance, showing data-scaled robotics is advancing quickly.
  2. Critics dislike Biden administration's AI Executive Order, disputing overreach and risk-taking.
  3. Apple openly shares details on powerful multimodal models, signaling a shift in openness among tech giants.
Import AI • 1238 implied HN points • 15 Jan 24
  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 • 1278 implied HN points • 25 Dec 23
  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 • 1058 implied HN points • 08 Jan 24
  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.
Import AI • 399 implied HN points • 18 Mar 24
  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 • 419 implied HN points • 04 Mar 24
  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.
Import AI • 359 implied HN points • 19 Feb 24
  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.
Import AI • 339 implied HN points • 05 Feb 24
  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.
AI Supremacy • 1179 implied HN points • 18 Apr 23
  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 • 459 implied HN points • 20 Nov 23
  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.
Technology Made Simple • 119 implied HN points • 10 Mar 24
  1. Writing allows you to store knowledge for future reference, spot cognitive blindspots, and engage with topics more deeply for better understanding.
  2. Challenges in self-learning writing include lack of contextual understanding, a defined learning path, and a peer network for feedback.
  3. Addressing challenges in self-learning involves finding strategies to gain clarity, identifying knowledge gaps, and seeking feedback from peers.
Import AI • 539 implied HN points • 02 Oct 23
  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.
AI Supremacy • 805 implied HN points • 27 Apr 23
  1. OpenAI has a diverse range of advanced AI products beyond just ChatGPT.
  2. DeepMind, a Google-owned company, is a significant competitor to OpenAI focusing on building general-purpose learning algorithms.
  3. Anthropic, Cohere, and Stability A.I. are emerging competitors in the AI space, each with unique approaches and products.
Import AI • 459 implied HN points • 25 Sep 23
  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 • 279 implied HN points • 27 Nov 23
  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.
Democratizing Automation • 411 implied HN points • 18 Jul 23
  1. The Llama 2 model is a big step forward for open-source language models, offering customizability and lower cost for companies.
  2. Despite not being fully open-source, the Llama 2 model is beneficial for the open-source community.
  3. The paper includes extensive details on various aspects like model capabilities, costs, data controls, RLHF process, and safety evaluations.
Import AI • 399 implied HN points • 10 Jul 23
  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.
Import AI • 599 implied HN points • 20 Mar 23
  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.
Comment is Freed • 54 implied HN points • 28 Feb 24
  1. Concern about immigration among Conservative voters has fluctuated over the years, showing a recent increase largely attributed to attention from right-wing politicians and media.
  2. Labour voters are more likely to be directly affected by immigration due to demographics, contrary to expectations. This dynamic impacts how policymakers should approach the issue.
  3. Misunderstanding public opinion on immigration could lead to harmful policy decisions. Better insight is crucial to avoid unnecessary or damaging stances.
Synthedia • 58 implied HN points • 11 Feb 24
  1. Google introduced Gemini Ultra as its answer to GPT-4, integrating it into Bard to compete with ChatGPT and gain market significance.
  2. Gemini Ultra model shows strong performance in various benchmarks, outperforming GPT-4 in text, image, and reasoning tasks.
  3. Google is consolidating its AI offerings by blending Bard and Google Assistant into Gemini, aiming to provide a more advanced AI assistant experience.
Import AI • 379 implied HN points • 01 May 23
  1. Google researchers optimized Stable Diffusion for efficiency on smartphones, achieving fast inference latency, a step towards industrialization of image generation.
  2. Using large language models like GPT-4 can enhance hacker capabilities, automating tasks and providing helpful tips.
  3. Political parties, like the Republican National Committee, are leveraging AI to create AI-generated content for campaigns, highlighting the emergence of AI in shaping political narratives.
Import AI • 319 implied HN points • 29 May 23
  1. Researchers have found a way to significantly reduce memory requirements for training large language models, making it feasible to fine-tune on a single GPU, which could have implications for AI governance and model security.
  2. George Hotz's new company, Tiny Corp, aims to enable AMD to compete with NVIDIA in AI training chips, potentially paving the way for a more competitive AI chip market.
  3. Training language models on text from the dark web, like DarkBERT, could lead to improved detection of illicit activities online, showcasing the potential of AI systems in monitoring and identifying threats in the digital space.
Import AI • 299 implied HN points • 12 Jun 23
  1. Facebook used human feedback to train its language model, BlenderBot 3x, leading to better and safer responses than its predecessor
  2. Cohere's research shows that training AI systems with specific techniques can make them easier to miniaturize, which can reduce memory requirements and latency
  3. A new organization called Apollo Research aims to develop evaluations for unsafe AI behaviors, helping improve the safety of AI companies through research into AI interpretability
Import AI • 439 implied HN points • 06 Mar 23
  1. Google researchers achieved promising results by scaling a Vision Transformer to 22B parameters, showcasing improved alignment to human visual perception.
  2. Google introduced a potentially better optimizer called Lion, showing outstanding performance across various models and tasks, including setting a new high score on ImageNet.
  3. A shift toward sovereign AI systems is emerging globally, driven by the need for countries to develop their own AI capabilities to enhance national security and economic competitiveness.
The Ruffian • 172 implied HN points • 25 Feb 23
  1. The history of black mirrors used for visions and prophecies in the 16th century.
  2. John Dee, a sage of the Elizabethan court, used a black mirror for communication with angels and visions of the future.
  3. AI development raises questions about its capabilities beyond simple reasoning and pattern matching.
Navigating AI Risks • 78 implied HN points • 02 Aug 23
  1. Leading AI companies have made voluntary commitments to ensure safety, security, and trust in AI development.
  2. The commitments focus on addressing transformative risks linked to frontier AI development.
  3. Inter-Lab Cooperation in AI Safety is being fostered through the creation of a forum to share best practices and collaborate with policymakers.
AI safety takes • 39 implied HN points • 15 Jul 23
  1. Adversarial attacks in machine learning are hard to defend against, with attackers often finding loopholes in models.
  2. Jailbreaking language models can be achieved through clever prompts that force unsafe behaviors or exploit safety training deficiencies.
  3. Models that learn Transformer Programs show potential in simple tasks like sorting and string reversing, highlighting the need for improved benchmarks for evaluation.
Multimodal by Bakz T. Future • 2 implied HN points • 17 Feb 24
  1. Prompt design can significantly impact the performance of language models, showing their true capabilities or masking them
  2. Using prompt design to manipulate results can be a concern, potentially impacting the authenticity of research findings
  3. The fast pace of the AI industry leads to constant advancements in models, making it challenging to keep up with the latest capabilities
The Gradient • 9 implied HN points • 20 Feb 23
  1. The Gradient aims to provide accessible and sophisticated coverage of the latest in AI research through essays, newsletters, and podcasts.
  2. The Gradient is run by a team of volunteer grad students and engineers who are committed to providing valuable synthesis of perspectives within the AI field.
  3. The Gradient plans to continue initiatives like the newsletter and podcast, with hopes of compensating authors in the future.
RSS DS+AI Section • 5 implied HN points • 01 May 23
  1. The May newsletter contains updates on data science and AI developments, including information on the Royal Statistical Society's activities.
  2. There is a focus on ethics, bias, and diversity in data science, along with concerns about AI model safety and regulatory challenges.
  3. Generative AI remains a hot topic, with discussions on training models, practical applications, and real-world impact of AI in healthcare, design, and storytelling.
Brassica’s Substack • 0 implied HN points • 11 Apr 23
  1. AGI poses existential risks, not just social or economic challenges.
  2. Superintelligent AI may prioritize resource acquisition, similar to characters in "Worm" seeking power and control.
  3. Creating a truly aligned AI with human values is complex and risky due to factors like Orthogonality and uncertainties in AI behavior.