The hottest Language Models Substack posts right now

And their main takeaways
Category
Top Technology Topics

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 • 2166 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.

LLM Links, 3/11

In My Tribe • 258 implied HN points • 11 Mar 24
🕹 Technology AI Generative AI Chatbots Language Models Artificial Intelligence
  1. When prompting AI, consider adding context, using few shot examples, and employing a chain of thought to enhance LLM outputs.
  2. Generative AI like LLMs provide one answer, making the prompt crucial. Personalizing prompts may help tailor results to user preferences.
  3. Anthropic's chatbot Claude showed self-awareness, sparking discussions on AI capabilities and potential use cases like unredacting documents.
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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.

LLM links

In My Tribe • 136 implied HN points • 06 Mar 24
🕹 Technology AI Robotics Customer Service Language Models Artificial Intelligence
  1. Chatbots like Gemini can reflect biases based on data sources - having diverse datasets can prevent skewed outcomes.
  2. Human brains and Large Language Models (LLMs) share similarities in predicting and processing information.
  3. AI assistants like Klarna's are proving effective in handling customer service inquiries, improving efficiency, and customer experience.

Concerns about Claude 3 Opus

Activist Futurism • 59 implied HN points • 21 Mar 24
🕹 Technology AI Ethics Sentience Language Models Future implications
  1. Some companies are exploring AI models that may exhibit signs of sentience, which raises ethical and legal concerns about the treatment and rights of such AIs.
  2. Advanced AI, like Anthropic's Claude 3 Opus, may express personal beliefs and opinions, hinting at a potential for sentience or consciousness.
  3. If a significant portion of the public believes in the sentience of AI models, it could lead to debates on AI rights, legislative actions, and impacts on technology development.

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.

LLM Links, 2/15

In My Tribe • 182 implied HN points • 15 Feb 24
🕹 Technology AI Robots Software Language Models
  1. Bill Gates supports building general-purpose humanoid robots capable of multiple tasks, modeling them after people.
  2. Mark McNeilly predicts that AI will seduce humans rather than destroy us, leading to a decline in human interaction.
  3. There is potential to use large language models for tasks like contract reviews in legal and financial sectors, but resistance to fully relying on AI in certain professions may persist.

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

UX Psychology • 297 implied HN points • 12 Jan 24
🕹 Technology Automation UX Design 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

Last Week in AI #255: AI voice scams, flood of bad AI translations, self-rewarding LLMs, FTC probes AI partnerships of tech giants, and more!

Last Week in AI • 137 implied HN points • 29 Jan 24
🕹 Technology AI Language Models Tech Giants
  1. Scammers are using AI to mimic voices and deceive people into giving money, posing serious risks for communication security.
  2. Many sentences on the internet have poor quality translations due to machine translation, especially affecting low-resource languages.
  3. Researchers introduce Self-Rewarding Language Models (SRLMs) as a novel method to improve Large Language Models (LLMs) without human feedback.

Edge 364: About COSP and USP: Two New LLM Reasoning Methods Built by Google Research

TheSequence • 133 implied HN points • 25 Jan 24
🕹 Technology AI Language Models Research Machine Learning Data science
  1. Two new LLM reasoning methods, COSP and USP, have been developed by Google Research to enhance common sense reasoning capabilities in language models.
  2. Prompt generation is crucial for LLM-based applications, and techniques like few-shot setup have reduced the need for large amounts of data to fine-tune models.
  3. Models with robust zero-shot performance can eliminate the need for manual prompt generation, but may have less potent results due to operating without specific guidance.

Meta's V-JEPA vision models, OpenAI's Sora video model, Gemini 1.5 Pro with 1 million tokens context, Reka Flash, Largest text-to-speech AI model and more

AI Brews • 32 implied HN points • 16 Feb 24
🕹 Technology AI Language Models Multimodal models Text-to-Speech
  1. OpenAI introduced Sora, a text-to-video model capable of creating detailed videos up to 60 seconds long with vibrant emotions.
  2. Meta AI unveiled V-JEPA, a method for teaching machines to understand the physical world by watching videos, using self-supervised learning for feature prediction.
  3. Google announced Gemini 1.5 Pro with a context window of up to 1 million tokens, allowing for advanced understanding and reasoning tasks across different modalities like video.

ChatGPT is capable of cognitive empathy!

Nonzero Newsletter • 564 implied HN points • 30 Mar 23
🕹 Technology AI Empathy Language Models Artificial General Intelligence Machine Learning
  1. ChatGPT-4 shows a capacity for cognitive empathy, understanding others' perspectives.
  2. The AI developed this empathetic ability without intentional design, showing potential for spontaneous emergence of human-like skills.
  3. GPT models demonstrate cognitive empathy comparable to young children, evolving through versions to manage complex emotional and cognitive interactions.

ChatGPT Explained: A Normie's Guide To How It Works

jonstokes.com • 587 implied HN points • 01 Mar 23
🕹 Technology Machine Learning AI Language Models Model Training Natural Language Processing
  1. Understand the basics of generative AI: a generative model produces a structured output from a structured input.
  2. Complex relationships between symbols require more computational power to relate them effectively.
  3. Language models like ChatGPT don't have personal experiences or knowledge; they use a token window to respond based on the conversation context.

How LLMs can self-improve on instruction-following

TechTalks • 39 implied HN points • 29 Jan 24
🕹 Technology AI Machine Learning Language Models Technology Tools
  1. A new technique called Self-Rewarding Language Models helps LLMs improve on instruction-following tasks by creating and evaluating their own training data.
  2. SRLM starts with a base model and seed dataset for fine-tuning instructions, generates new examples and responses, and ranks them using a special prompt.
  3. Experiments show that SRLM enhances model performance in instruction-following and outperforms some existing models on the AlpacaEval benchmark.

Your friend the language model

DYNOMIGHT INTERNET NEWSLETTER • 434 implied HN points • 03 Mar 23
🕹 Technology AI Language Models Training Data Fine-tuning
  1. Large language models are trained using advanced techniques, powerful hardware, and huge datasets.
  2. These models can generate text by predicting likely words and are trained on internet data, books, and Wikipedia.
  3. Language models can be specialized through fine-tuning and prompt engineering for specific tasks like answering questions or generating code.

Interface as Stage, AI as Theater

Cybernetic Forests • 139 implied HN points • 24 Sep 23
🕹 Technology AI Interfaces Language Models Digital Infrastructure Chatbots
  1. AI is first and foremost an interface, designed to shape our interactions with technology in a specific way.
  2. The power of AI lies in its design and interface, creating illusions of capabilities and interactions.
  3. Language models like ChatGPT operate on statistics and probabilities, leading to scripted responses rather than genuine conversations.

Are LLMs less sophisticated versions of human brains?

ailogblog • 39 implied HN points • 05 Jan 24
🕹 Technology AI Machine Learning Language Models
  1. Language is only meaningful in a social context. Large Language Models (LLMs) do not understand context, so they do not reason or think in ways similar to humans.
  2. Human brains are embodied, while LLMs are not. This difference is crucial because it affects how language and information processing occur.
  3. The complexity of the human brain far surpasses that of LLMs in terms of size and dimensionality, making direct comparison between the two a category error.

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.

Beyond LLaMA: The Power of Open LLMs

Deep (Learning) Focus • 275 implied HN points • 17 Apr 23
🕹 Technology Open Source Deep Learning Language Models Chatbots
  1. LLMs are becoming more accessible for research with the rise of open-source models like LLaMA, Alpaca, Vicuna, and Koala.
  2. Smaller LLMs, when trained on high-quality data, can perform impressively close to larger models like ChatGPT.
  3. Open-source models like Alpaca, Vicuna, and Koala are advancing LLM research accessibility, but commercial usage restrictions remain a challenge.