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
Disruptive innovation comes in two flavors: (1) New-market disruption, where the company creates and claims a new segment in an existing market by catering to an underserved customer base, or (2) Low-end disruption, in which a company uses a low-cost business model to enter at the bottom of an existing market and claim a segment.
Copilots don’t... See more
Copilots don’t... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
Take a look at our official page for user documentation and examples: langtest.org
Key Features
Key Features
- Generate and execute more than 50 distinct types of tests only with 1 line of code
- Test all aspects of model quality: robustness, bias, representation, fairness and accuracy.
- Automatically augment training data based on test results (for select models)
- Sup
GitHub - BrunoScaglione/langtest: Deliver safe & effective language models
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
“I think a lot of people obviously want to talk about the sexy kind of new consumer applications. I would tell you that I think that the earliest and most significant effect that AI is going to have on our company is actually going to be as it relates to our developer productivity. Some of the tools that we’re seeing are going to allow our devs to... See more
Adam Huda • The Transformative Power of Generative AI in Software Development: Lessons from Uber's Tech-Wide Hackathon
The Gemini API context caching feature is designed to reduce the cost of requests that contain repeat content with high input token counts.
When to use context caching
Context caching is particularly well suited to scenarios where a substantial initial context is referenced repeatedly by shorter requests. Consider using context caching for use cases... See more
When to use context caching
Context caching is particularly well suited to scenarios where a substantial initial context is referenced repeatedly by shorter requests. Consider using context caching for use cases... See more
Context caching guide | Google AI for Developers | Google for Developers
When we deliver a model we make sure we don't reach X seconds of latency in our API. Before even going into performance of LLMs for classification, I can tell you that with the current available tech they are just infeasible.
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LinuxSpinach
•
5h ago
^ this. And especially classification as a task, because businesses don’t want to pay llm... See more
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LinuxSpinach
•
5h ago
^ this. And especially classification as a task, because businesses don’t want to pay llm... See more
r/MachineLearning - Reddit
We're doing NER on hundreds of millions of documents in a specialised niche. LLMs are terrible for this. Slow, expensive and horrifyingly inaccurate. Even with agents, pydantic parsing and the like. Supervised methods are the way to go. Hell, I'd take an old school rule based approach over LLMs for this.
no reason to build any kind of software product these days that doesn't have a significant UX/domain knowledge component
Discord - A New Way to Chat with Friends & Communities
𝘱𝘦𝘳𝘧𝘰𝘳𝘮𝘢𝘯𝘤𝘦: it will improve your LLM performance on given use cases (e.g., coding, extracting text, etc.). Mainly, the LLM will specialize in a given task (a specialist will always beat a generalist in its domain)
𝘤𝘰𝘯𝘵𝘳𝘰𝘭: you can refine how your model should behave on specific inputs and outputs, resulting in a more robust product
𝘮𝘰𝘥𝘶𝘭𝘢𝘳𝘪𝘻𝘢𝘵𝘪𝘰𝘯:... See more
𝘤𝘰𝘯𝘵𝘳𝘰𝘭: you can refine how your model should behave on specific inputs and outputs, resulting in a more robust product
𝘮𝘰𝘥𝘶𝘭𝘢𝘳𝘪𝘻𝘢𝘵𝘪𝘰𝘯:... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
Motivation for finetuning