The hottest LLMs Substack posts right now

And their main takeaways

The Q* hypothesis: Tree-of-thoughts reasoning, process reward models, and supercharging synthetic data

Democratizing Automation • 672 implied HN points • 24 Nov 23

🕹 Technology AI LLMs

Q* hypothesis involves tree-of-thoughts reasoning and process reward models for supercharging synthetic data
The method combines self-play and look-ahead planning for language models
Process Reward Models (PRMs) emphasize scoring each step of reasoning rather than the entire message

What Should Businesses Be Doing With Generative AI? High-Value Use Cases With Short Delivery Timelines.

High ROI Data Science • 58 implied HN points • 08 Feb 24

🕹 Technology AI Generative AI LLMs Startups

Businesses can utilize Generative AI for Customer Intent Detection.
Building specific use cases is more effective than broad functionality.
Avoid common myths like relying solely on chatbots with LLMs.

Graph Neural Networks in Tensorflow

MLOps Newsletter • 39 implied HN points • 10 Feb 24

🕹 Technology LLMs Chatbots Frameworks Models

Graph Neural Networks in TensorFlow address data complexity, limited resources, and generalizability in learning from graph-structured data.
RadixAttention and Domain-Specific Language (DSL) are key solutions for efficiently controlling Large Language Models (LLMs), reducing memory usage, and providing a user-friendly interface.
VideoPoet demonstrates hierarchical LLM architecture for zero-shot learning, handling multimodal input, and generating various output formats in video generation tasks.

Falcon: The Pinnacle of Open-Source LLMs

Deep (Learning) Focus • 235 implied HN points • 10 Jul 23

🕹 Technology Open Source LLMs

The Falcon models represent a significant advancement in open-source LLMs, rivaling proprietary models in quality and performance.
The creation of the RefinedWeb dataset showcases the potential of utilizing web data at a massive scale for LLM pre-training, leading to highly performant models like Falcon.
Falcon-40B, when compared to other LLMs, stands out for its impressive performance, efficient architecture modifications, and commercial usability.

Inside LangChain: The Super Popular LLM Framework You Need to Know About

TheSequence • 294 implied HN points • 13 Apr 23

🕹 Technology Frameworks Software Development Open Source LLMs Integration

LangChain integrates LLMs into mainstream software development lifecycles.
LLMs are powerful when integrated with other sources of computation or knowledge.
LangChain is an open-source framework addressing challenges of using LLMs effectively.

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Orca: Properly Imitating Proprietary LLMs

Deep (Learning) Focus • 176 implied HN points • 26 Jun 23

🕹 Technology LLMs Deep Learning Open Source Evaluation

Imitation models need a large and comprehensive dataset to perform well.
Enhancing imitation learning with detailed explanation traces can significantly improve model performance.
Orca showcases the effectiveness of learning from more complex instruction datasets and detailed explanations.

Microsoft's New Future of Work Report

Engineering Enablement • 15 implied HN points • 02 Feb 24

🕹 Technology AI Software Engineering Developer Productivity AI Tools LLMs

AI can increase developer productivity but benefits vary based on tasks
Writing effective prompts for AI tools is challenging and can lead to overreliance
Less experienced workers benefit the most from AI tools like LLMs

Levels of AGI & Autonomy

Yuxi’s Substack • 19 implied HN points • 14 Nov 23

🕹 Technology AI Autonomy AGI LLMs

DeepMind published a paper on levels of AGI and autonomy.
Current large language models are far from being Superhuman AGI.
AI as an agent is still a distant concept due to current technology limitations.

It is still early for open-source AI

John’s Contemplations • 39 implied HN points • 29 Jul 23

🕹 Technology AI Open Source LLMs Models Infrastructure

There is optimism about open-source AI catching up to closed-source in the future.
Open-source AI faces challenges like small model sizes and infrastructure limitations.
Customization is a key advantage of open-source AI over closed-source models.

Which is the Wokest AI?

Rozado’s Visual Analytics • 2 HN points • 26 Feb 24

🕹 Technology AI Wokeness LLMs Machine Learning

There are AI models being tested on their 'Wokeness' based on various dimensions like Social justice and Climate Sustainability.
Google's Gemini is not the most 'Woke' AI, with other companies having developed even more 'Woke' AIs.
Experimental fine-tuned AI models like LeftWing GPT and Depolarizing GPT have been created for specific ideological alignments.

20230416

Curious futures (KGhosh) • 4 implied HN points • 16 Apr 23

🕹 Technology Society Tech DIY LLMs

Constantly think about the services you provide and where they fit in the hierarchy of ideas.
Stay updated on various society, tech, DIY, LLM, and People and AI topics.
Luxury brands thrive on impeccable service, repairs, and customer service in times of need.

What is Meta's CodeCompose?

Machine Economy Press • 3 implied HN points • 07 Jun 23

🕹 Technology AI Programming LLMs

Meta's CodeCompose is a powerful tool using language models for code suggestions in various programming languages like Python.
CodeCompose has high user acceptance rates and positive feedback within Meta, enhancing code authoring and encouraging good coding practices.
The competitive landscape for language models in coding tools is evolving rapidly with advancements from tech giants like Google, Meta, and Amazon.

Death by RAG Evals

ScaleDown • 0 implied HN points • 31 Jan 24

🕹 Technology AI Evaluation LLMs Metrics Costs

Evaluating RAG (Retrieval-Augmented Generation) systems is challenging due to the need for assessing accuracy, relevance, and context retrieval.
Human annotation is accurate but time-consuming, error-prone, and not suitable for real-time systems.
The evaluation process for RAG systems can be resource-intensive, time-consuming, and costly, impacting latency and efficiency.

Stanford Professor Tatsu Hashimoto on AI Biases and Improving LLM Performance

Unsupervised Learning • 0 implied HN points • 10 Jul 23

🕹 Technology AI Academia LLMs Bias Research

Training high-quality LLMs requires balancing data and compute costs
Understanding different components of LLM training process impacts model performance
Academia plays a crucial role in adding diverse opinions to language models

Investment Review #1 - AI Portfolio Allocations for Q4 2023

e/alpha • 0 implied HN points • 05 Jan 24

💰 Finance Investment Portfolio AI Chips GPU LLMs

The AI portfolio performance for Q4 2023 was impressive, outperforming the S&P 500 with an IRR of 95%.
Investing in AI chips continues to be a promising choice, but there are concerns about the speed of commercialization and potential pitfalls.
The future of LLMs (Large Language Models) is uncertain, but GPU investments are expected to stay strong until more clarity emerges.