LLMs

We identified 30 types of tasks that UX professionals used generative AI tools for in their work. We grouped these tasks under four roles: content editor, research assistant, ideation partner, or design assistant.

• Content editor : Generating and editing text, from microcopy to social media posts, based on specifications or copy given by UX

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Principles for growable tools

There are three critical pieces to building a tool that can grow around its users over time.

1. Design around play . Sometimes I call this design around experimentation . Using the tool for day-to-day work should involve playing and experimenting with what’s possible with the tool. Whether that’s writing small programs to

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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

Jail-Breaked & Offline Appliances: It’s becoming increasingly clear that we’ll be able to interact with everyday appliances and devices with natural language. As locally run LLMs become more efficient and powerful, the prospects of having a conversation with your coffee machine in the morning aren’t unreasonable. After all, who wants to tinker with... See more

LLMTuner

LLMTuner: Fine-Tune Llama, Whisper, and other LLMs with best practices like LoRA, QLoRA, through a sleek, scikit-learn-inspired interface.

Giskard is a Python library that automatically detects vulnerabilities of AI models, from tabular models to LLM, including: performance biases, data leakage, spurious correlation, hallucination, toxicity, security issues and many more.

It's a powerful tool that helps data scientists save time and effort drilling down on model issues, and produce... See more

a couple of the top of my head:

• LLM in the loop with preference optimization


• synthetic data generation


• cross modality "distillation" / dictionary remapping


• constrained decoding

Amplify Partners was running a survey among 800+ AI engineers to bring transparency to the AI Engineering space. The report is concise, yet it provides a wealth of insights into the technologies and methods employed by companies for the implementation of AI products.

Highlights

👉 Top AI use cases are code intelligence, data extraction and workflow... See more