Nicolay Gerold

@nicolaygerold

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Microalgae oil for DHA Omega-3s.

Andrew Huberman • Dr. Rhonda Patrick: Micronutrients for Health & Longevity

baserun.ai💪💪💪

Testing & Observability Platform for LLM Apps

From prompt playground to end-to-end tests, baserun helps you ship your LLM apps with confidence and speed.

Testing framework for LLM Part

Sugarcane AI is an open-source framework designed to simplify and accelerate LLM app development. With a focus on fine-tuned Language Models (LLMs), prompt management, and Workflow Plugins, Sugarcane AI empowers developers to build, train, and manage complex LLM applications effortlessly. 🎉

Why Sugarcane AI? : Key Features of Microservices Framework... See more

sugarcane-ai • GitHub - sugarcane-ai/sugarcane-ai.github.io

Overview

Loki is our open-source solution designed to automate the process of verifying factuality. It provides a comprehensive pipeline for dissecting long texts into individual claims, assessing their worthiness for verification, generating queries for evidence search, crawling for evidence, and ultimately verifying the claims. This tool is... See more

Libr-AI • GitHub - Libr-AI/OpenFactVerification: Open-source solution designed to automate the process of verifying factuality

LLMs

Dr. Charles Zuker: The Biology of Taste Perception & Sugar Craving

hubermanlab.com

Neuroscience

There is no AI Strategy without a Data Strategy

Training AI models requires data. Whether you’re training existing models, developing models from scratch, or simply testing theories, high-quality data is crucial.

Incumbents have the data because they have the customers. They can immediately leverage customers’ data to train models and tune... See more

Jason Cohen • AI startups require new strategies: This time it's actually different

I would differentiate between data for existing behaviors vs new behaviors. The world and our tools are constantly changing. I think AI is one of those drivers. I think the startups who can either facilitate new behaviors the best (e.g. Cursor for AI-assisted coding) or who can create entirely new behaviors have a great way to generate unique training data.

Taking existing data and making it workable with AI is a lot of work and takes skilled labor (AI + domain expertise). I wouldn’t say incumbents have the complete edge. They have the edge in certain applications and behaviors under the assumptions these behaviors are not changing to render their applications useless.

pair-preference-model-LLaMA3-8B by RLHFlow: Really strong reward model, trained to take in two inputs at once, which is the top open reward model on RewardBench (beating one of Cohere’s).

DeepSeek-V2 by deepseek-ai (21B active, 236B total param.): Another strong MoE base model from the DeepSeek team. Some people are questioning the very high MMLU... See more