The hottest Large Language Models Substack posts right now

And their main takeaways
Category
Top Technology Topics

My review of THE COMING WAVE

Ground Truths • 7567 implied HN points • 09 Sep 23
🕹 Technology AI Genomics Large Language Models
  1. AI is on the brink of transforming our lives with the majority of interactions being with AIs, not people.
  2. The book 'THE COMING WAVE' by Mustafa Suleyman discusses the future of AI integrating life science and digital applications.
  3. The book offers a balanced perspective on AI's potential, historical context, and the challenges and opportunities it presents.

How In-Context Learning Emerges

Last Week in AI • 432 implied HN points • 21 Jul 23
🕹 Technology AI Large Language Models Neural Networks Machine Learning
  1. In-context learning (ICL) allows Large Language Models to learn new tasks without additional training.
  2. ICL is exciting because it enables versatility, generalization, efficiency, and accessibility in AI systems.
  3. Three key factors that enable and enhance ICL abilities in large language models are model architecture, model scale, and data distribution.

Gig Economy, AI, and LLM: Friends or Foes?

Gad’s Newsletter • 47 implied HN points • 05 Feb 24
🕹 Technology AI ML Gig Economy Artificial Intelligence Large Language Models
  1. The gig economy connects freelancers with businesses through digital platforms for flexible, temporary work.
  2. Advancements in AI, particularly LLM and ML, are empowering gig workers by automating tasks, providing data-driven insights, and improving service quality.
  3. Challenges in the gig economy arise from the potential job displacement due to automation and AI advancements, along with ethical concerns about bias and privacy.
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How's that AI tsunami looking, a year on?

Social Warming by Charles Arthur • 117 implied HN points • 28 Jul 23
🕹 Technology AI Content Generation Chatbots Large Language Models
  1. The AI landscape has rapidly evolved in the past year with the emergence of tools like ChatGPT and AI illustration programs.
  2. AI systems are being used for various creative tasks like generating content, illustrations, and even entire videos.
  3. Challenges arise as AI-generated content seeps into different aspects of society, raising concerns about identification and integrity.

Tokenomics 101: Navigating the Nuances of LLM Product Pricing

ScaleDown • 3 implied HN points • 20 Feb 24
🕹 Technology AI Tokenomics Generative AI Large Language Models
  1. Token-based pricing for LLM applications can be complex as it involves more than just input and output tokens. Consider additional factors like system prompts, context tokens, and evaluation tokens for accurate cost estimation.
  2. Estimating the price of a GenAI chatbot involves considering not only the direct input and output tokens but also context tokens, system prompts, and real-world applications like regeneration and error handling.
  3. When budgeting for GenAI applications, remember to include overheads like evaluation of outputs and guardrails in your cost analysis. These additional requirements can significantly increase the total token costs.

Can Perplexity Improve Search Experience with LLMs?

Machine Economy Press • 3 implied HN points • 01 Dec 23
🕹 Technology AI Machine Learning Search Engine Generative AI Large Language Models
  1. Perplexity AI is working on improving search experience with large language models (LLMs).
  2. Their models offer real-time access to internet data and aim to provide accurate and up-to-date information.
  3. Perplexity's funding and partnerships with major companies like Amazon are crucial for their success and competitiveness in the search engine market.

The Four Fundamental Quantities of LLMs: Part Zero - 📜 What are Large Language Models?

Intuitive AI • 1 HN point • 21 May 23
🕹 Technology Machine Learning Neural Networks Training Data Large Language Models
  1. Large language models (LLMs) are neural networks with billions of parameters trained to predict the next word using large amounts of text data.
  2. LLMs use parameters learned during training to make predictions based on input data during the inference stage.
  3. Training an LLM involves optimizing the model to predict the next token in a sentence by feeding it billions of sentences to adjust its parameters.

How AI is changing education; Bard and ChatGPT are reshaping our relationship with the internet; tech companies chase wearable AI; Gemini goes into Google Cloud

Computerspeak by Alexandru Voica • 0 implied HN points • 15 Dec 23
🕹 Technology AI Education Wearable Tech Cloud Computing Large Language Models
  1. AI is transforming education by personalizing learning, making it more engaging, and accessible to all.
  2. Advances in AI models like ChatGPT are creating opportunities for teachers to focus on building meaningful relationships and inspiring curiosity in students.
  3. While AI tutors can offer personalized lessons and feedback, they currently lack emotional intelligence and reasoning, making human teachers and classrooms irreplaceable for now.

How Far Are We From Being Able to Generate Whatever 3D Objects On the Fly?

I'll Keep This Short • 0 implied HN points • 17 Jul 23
🕹 Technology AI 3D Modeling Generative models Neural Networks Large Language Models
  1. AI-generated 3D objects are still far from being created instantly in real 3D
  2. Shap-E improves upon previous models by generating 3D objects using Neural Radiance Fields
  3. Although new technologies show promise, limitations like resource-intensive processes and lack of fine details still exist

The generative AI boom is hitting some turbulence; the BBC mulls opening its archives to AI companies; AI spots tiny cancers missed by doctors; UN adopts first AI resolution

Computerspeak by Alexandru Voica • 0 implied HN points • 22 Mar 24
🕹 Technology AI Tech Giants Funding Open Source Large Language Models
  1. The generative AI boom is facing challenges with startups burning through cash quickly and struggling to find sustainable business models.
  2. Developing and operating compute-intensive large language models is costly, making it difficult for many startups to sustain long-term operations.
  3. Generative AI startups are racing to pivot towards enterprise applications and differentiate their value to survive in the changing landscape of the AI industry.

The AI War: Ethical Struggles and Technological Challenges in the Era of Language Models

Transitions • 0 implied HN points • 13 May 23
🕹 Technology Ethics Large Language Models Artificial Intelligence
  1. The AI war involves technological advancements like integrating language models into various products, driven by competition among tech giants.
  2. Ethical concerns arise with large language models generating erroneous or problematic content, sparking debates about bias and ethical controls.
  3. There's a shift towards training efficient smaller models in the open-source community, showing that size doesn't always correlate with effectiveness in large language models.