The hottest Language Models Substack posts right now

And their main takeaways
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Top Technology Topics

Measuring Political Preferences in AI Systems – An Integrative Approach

Rozado’s Visual Analytics • 183 implied HN points • 23 Jan 25
🇺🇸 U.S. Politics Political Bias AI Ethics Language Models Policy Analysis
  1. Large language models (LLMs) like ChatGPT may show political biases, but measuring these biases can be complicated. The biases could be more visible in detailed AI-generated text rather than in straightforward responses.
  2. Different types of LLMs exist, like base models that work from scratch and conversational models that are fine-tuned to respond well to users. These models often lean towards left-leaning language when generating text.
  3. By using a combination of methods to check for political bias in AI systems, researchers found that most conversational LLMs lean left, but some models are less biased. Understanding AI biases is essential for improving these systems.

Lit mag Guernica implodes, LLMs beat neuroscientists, CS vs. Philosophy deathmatch, AI pollution reaches science

The Intrinsic Perspective • 4805 implied HN points • 15 Mar 24
🔬 Science AI Neuroscience Ethics Language Models
  1. AI data pollution in science is a concerning issue, with examples of common AI stock phrases being used in scientific literature without real contribution.
  2. AI language models outperformed human neuroscientists in predicting future neuroscientific results, raising questions on the importance of understanding linguistic modifications versus actual predictions.
  3. Literary magazine Guernica faced backlash after a controversial essay led to writers withdrawing pieces, staff resigning, and social media condemnation, stressing the importance of careful reading and understanding context.

Gemini: how did we end up here?

lcamtuf’s thing • 2652 implied HN points • 02 Mar 24
🕹 Technology AI Ethics Language Models Big Tech Content Moderation
  1. The development of large language models (LLMs) like Gemini involves mechanisms like reinforcement learning from human feedback, which can lead to biases and quirky responses.
  2. Concerns arise about the use of LLMs for automated content moderation and the potential impact on historical and political education for children.
  3. The shift within Big Tech towards paternalistic content moderation reflects a move away from the libertarian culture predominant until the mid-2010s, highlighting evolving perspectives on regulating information online.

Why I build open language models

Democratizing Automation • 261 implied HN points • 30 Oct 24
🕹 Technology AI Development Open Source Language Models Ethics Regulation
  1. Open language models can help balance power in AI, making it more available and fair for everyone. They promote transparency and allow more people to be involved in developing AI.
  2. It's important to learn from past mistakes in tech, especially mistakes made with social networks and algorithms. Open-source AI can help prevent these mistakes by ensuring diverse perspectives in development.
  3. Having more open AI models means better security and fewer risks. A community-driven approach can lead to a stronger and more trustworthy AI ecosystem.
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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 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.

Most Impactful Generative AI Papers of 2023

AI Supremacy • 1022 implied HN points • 06 Jan 24
🕹 Technology AI Generative AI Research Language Models Papers
  1. The post discusses the most impactful Generative AI papers of 2023 from various institutions like Meta, Stanford, and Microsoft.
  2. The selection criteria for these papers includes both objective metrics like citations and GitHub stars, as well as subjective influence across different areas.
  3. The year 2023 saw significant advancements in Generative AI research, with papers covering topics like large language models, multimodal capabilities, and fine-tuning methods.

Tokenization in large language models, explained

The Counterfactual • 239 implied HN points • 02 May 24
🕹 Technology AI Language Models Tokenization Machine Learning Natural Language Processing
  1. Tokens are the building blocks that language models use to understand and predict text. They can be whole words or parts of words, depending on how the model is set up.
  2. Subword tokenization helps models balance flexibility and understanding by breaking down words into smaller parts, so they can still work with unknown words.
  3. Understanding how tokenization works is key to improving the performance of language models, especially since different languages have different structures 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.

Import AI 333: Synthetic data makes models stupid; chatGPT eats MTurk. Inflection shows off a large language model

Import AI • 898 implied HN points • 26 Jun 23
🕹 Technology AI Language Models AI Policy Data Training Ethical Implications
  1. Training AI models exclusively on synthetic data can lead to model defects and a narrower range of outputs, emphasizing the importance of blending synthetic data with real data for better results.
  2. Crowdworkers are increasingly using AI tools like chatGPT for text-based tasks, raising concerns about the authenticity of human-generated content.
  3. The UK is taking significant steps in AI policy by hosting an international summit on AI risks and safety, showcasing its potential to influence global AI policies and safety standards.

Import AI 353: AI bootstrapping; LLMs as inventors; Facebook releases a free moderation tool

Import AI • 559 implied HN points • 18 Dec 23
🕹 Technology AI Machine Learning Moderation Research Language Models
  1. AI bootstrapping is advancing, with techniques like ReST^EM by Google DeepMind showing ways to make models smarter iteratively.
  2. Language models like LLMs are being used for groundbreaking tasks, such as extending human knowledge through techniques like FunSearch by DeepMind.
  3. Facebook has released a free moderation LLM, Llama Guard, highlighting the use of powerful models to control and monitor outputs of other AI systems.

Import AI 360: Guessing emotions; drone targeting dataset; frameworks for AI alignment

Import AI • 379 implied HN points • 12 Feb 24
🕹 Technology AI Datasets Security Language Models Ethics
  1. Teaching AI to understand complex human emotions like joy, surprise, and anger can help in applications like surveillance and advertising.
  2. AI systems, like other software, are vulnerable to attacks, as shown by a demonstration breaking MoE models with a buffer overflow attack.
  3. Frameworks are being developed to ensure AI systems align with diverse human values, considering various perspectives and how to measure alignment.
  4. The development of AI systems is advancing in areas like emotion recognition, system security, and value alignment.
  5. Researchers are pushing the boundaries of AI capabilities, from emotion recognition to security to ethical alignment.
  6. Current AI trends indicate growth in researching human emotions, security vulnerabilities, and ethical considerations.

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.

The Top 10 Generative AI Advancements in 2023

Rod’s Blog • 515 implied HN points • 22 Dec 23
🕹 Technology AI Language Models Image Generation
  1. Generative AI has seen significant advancements in 2023, with breakthroughs like GPT-4, DALL-E, and open-source models like Llama 2 democratizing access to this technology.
  2. Technological innovations like Mistral 7B for text embedding, StyleGAN3 for image synthesis, and Jukebox 2.0 for music composition showcase the diverse applications of generative AI.
  3. Models such as AlphaFold 3 for protein structure prediction, DeepFake 3.0 for face swapping, and BARD for poetry writing highlight the versatility and impact of generative AI in various fields.

Import AI 362: Amazon's big speech model; fractal hyperparameters; and Google's open models

Import AI • 299 implied HN points • 26 Feb 24
🕹 Technology AI Models Language Models Fiction
  1. The full capabilities of today's AI systems are still not fully explored, with emerging abilities seen as models scale up.
  2. Google released Gemma, small but powerful AI models that are openly accessible, contributing to the competitive AI landscape.
  3. Understanding hyperparameter settings in neural networks is crucial as the fine boundary between stable and unstable training is found to be fractal, impacting the efficiency of training runs.

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.

The Rise of Indian Llamas

Sector 6 | The Newsletter of AIM • 399 implied HN points • 25 Dec 23
🕹 Technology AI Language Models Open Source Innovation Enterprise
  1. Llama 2 is a popular open-source language model with many downloads worldwide. In India, people are using it to create models that work well for local languages.
  2. A new Hindi language model called OpenHathi has been released, which is based on Llama 2. It offers good performance for Hindi, similar to well-known models like GPT-3.5.
  3. There is a growing interest in using these language models for business in India, indicating that the trend of 'Local Llamas' is just starting to take off.

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 338: Consciousness and AI; self-improving language models; maps of thought.

Import AI • 539 implied HN points • 28 Aug 23
🕹 Technology AI Language Models Consciousness Reinforcement Learning AI Ethics
  1. Facebook introduces Code Llama, large language models specialized for coding, empowering more people with access to AI systems.
  2. DeepMind's Reinforced Self-Training (ReST) allows faster AI model improvement cycles by iteratively tuning models based on human preferences, but overfitting risks need careful management.
  3. Researchers identify key indicators from studies on human and animal consciousness to guide evaluation of AI's potential consciousness, stressing the importance of caution and a theory-heavy approach.

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.

The Automation Paradox: How More Tech Can Mean More Human Challenges

UX Psychology • 297 implied HN points • 12 Jan 24
🕹 Technology Automation UX Design Human factors Autonomous Vehicles Language Models
  1. Increased automation can lead to unexpected complications for human tasks, creating a paradox where reliance on technology may actually hinder human performance.
  2. The 'Irony of Automation' highlights unintended consequences like automation not reducing human workload, requiring more complex skills for operators, and leading to decreased vigilance.
  3. Strategies like enhancing monitoring systems, maintaining manual and cognitive skills, and thoughtful interface design are crucial for addressing the challenges posed by automation and keeping human factors in focus.

What is Retrieval Augmented Generation (RAG)

What's AI Newsletter by Louis-François Bouchard • 275 implied HN points • 10 Jan 24
🕹 Technology Artificial Intelligence AI Models Language Models Ethics Innovation
  1. Retrieval Augmented Generation (RAG) enhances AI models by injecting fresh knowledge into each interaction
  2. RAG works to combat issues like hallucinations and biases in language models
  3. RAG is becoming as crucial as large language models (LLMs) and prompts in the field of artificial intelligence

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.

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 329: Compute IS data; don't build AI agents; AI needs a precautionary principle

Import AI • 399 implied HN points • 15 May 23
🕹 Technology AI Data Ethics Language Models AI Development
  1. Building AI scientists to advise humans is a safer alternative to building AI agents that act independently
  2. There is a need for a precautionary principle in AI development to address threats to democracy, peace, safety, and work
  3. Approaches like Self-Align show the potential for AI systems to self-bootstrap using synthetic data, leading to more capable models

LLMs and the "not" problem

The Counterfactual • 119 implied HN points • 19 Mar 24
🕹 Technology AI Language Models Cognitive Science Image Generation Human-computer interaction
  1. LLMs, like ChatGPT, struggle with negation. They often don't understand requests to remove something from an image and can still include it.
  2. Human understanding of negation is complex, as people process negative statements differently than positive ones. We might initially think about what is being negated before understanding the actual meaning.
  3. Giving LLMs more time to think, or breaking down their reasoning, can improve their performance. This shows that they might need support to mimic human understanding more closely.

Import AI 325: Automated mad science; AI vs democracy; and a 12B parameter language model

Import AI • 419 implied HN points • 17 Apr 23
🕹 Technology AI Democracy Language Models Robotics Legal analysis
  1. Prompt injection could be a major security risk in AI systems, making them vulnerable to unintended actions and compromising user privacy.
  2. The concentration of AI development in private companies poses a threat to democracy, as these language models encode the normative intentions of their creators without democratic oversight.
  3. The rapid race to build 'god-like AI' in the private sector is raising concerns about the lack of understanding and oversight, with experts warning about potential dangers to humanity.

Chain of Thought Prompting for LLMs

Deep (Learning) Focus • 294 implied HN points • 24 Apr 23
🕹 Technology AI Deep Learning Language Models Reasoning Prompting
  1. CoT prompting leverages few-shot learning in LLMs to improve their reasoning capabilities, especially for complex tasks like arithmetic, commonsense, and symbolic reasoning.
  2. CoT prompting is most beneficial for larger LLMs (>100B parameters) and does not require fine-tuning or extensive additional data, making it an easy and practical technique.
  3. CoT prompting allows LLMs to generate coherent chains of thought when solving reasoning tasks, providing interpretability, applicability, and computational resource allocation benefits.