LLMs
TorchMultimodal (Beta Release)
Introduction
TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale. It provides:
Introduction
TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale. It provides:
- A repository of modular and composable building blocks (models, fusion layers, loss functions, datasets and utilities).
- A repository of examples that show how to combine these building
facebookresearch • GitHub - facebookresearch/multimodal at a33a8b888a542a4578b16972aecd072eff02c1a6
The exact metrics we use depend on the application — our main goal is to understand how users use the feature and quickly make improvements to better meet their needs. For internal applications, this might mean measuring efficiency and sentiment. For consumer-facing applications, we similarly focus on measures of user satisfaction - direct user... See more
Developing Rapidly with Generative AI
The AI engineering framework
Marvin is a lightweight AI engineering framework for building natural language interfaces that are reliable, scalable, and easy to trust.
Sometimes the most challenging part of working with generative AI is remembering that it's not magic; it's software. It's new, it's nondeterministic, and it's incredibly powerful - but... See more
Marvin is a lightweight AI engineering framework for building natural language interfaces that are reliable, scalable, and easy to trust.
Sometimes the most challenging part of working with generative AI is remembering that it's not magic; it's software. It's new, it's nondeterministic, and it's incredibly powerful - but... See more
PrefectHQ • GitHub - PrefectHQ/marvin: ✨ Build AI interfaces that spark joy
We generally lean towards picking more advanced commercial LLMs to quickly validate our ideas and obtain early feedback from users. Although they may be expensive, the general idea is that if problems can't be adequately solved with state-of-the-art foundational models like GPT-4, then more often than not, those problems may not be addressable... See more
Developing Rapidly with Generative AI
When it comes to identifying where generative AI can make an impact, we dig into challenges that commonly:
- Involve analysis, interpretation, or review of unstructured content (e.g. text) at scale
- Require massive scaling that may be otherwise prohibitive due to limited resources
- Would be challenging for rules-based or traditional ML approaches
Developing Rapidly with Generative AI
ANY
LLM of your choice, statistical methods, or NLP models that runs
locally on your machine
:
- G-Eval
- Summarization
- Answer Relevancy
- Faithfulness
- Contextual Recall
- Contextual Precision
- RAGAS
- Hallucination
- Toxicity
- Bias
- etc.
GitHub - confident-ai/deepeval: The LLM Evaluation Framework
core components of Deep RL that enabled success like AlphaGo: self-play and look-ahead planning.
Self-play is the idea that an agent can improve its gameplay by playing against slightly different versions of itself because it’ll progressively encounter more challenging situations. In the space of LLMs, it is almost certain that the largest portion... See more
Self-play is the idea that an agent can improve its gameplay by playing against slightly different versions of itself because it’ll progressively encounter more challenging situations. In the space of LLMs, it is almost certain that the largest portion... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
These two components might be some of the most important ideas to improve all of AI.
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
Highlights
👉 Top AI use cases are code intelligence, data extraction and workflow... See more
Paul Venuto • feed updates
In addition to using our built-in capabilities, you can also define custom actions by making one or more APIs available to the GPT. Like plugins, actions allow GPTs to integrate external data or interact with the real-world. Connect GPTs to databases, plug them into emails, or make them your shopping assistant. For example, you could integrate a... See more