LLMs
Memory Considerations
Since co-occurrence matrices are square, they grow exponential with the number of entities being embedded. For 50k entities and a 32-bit data format, a dense matrix will already be at 10GB. 100k entities puts it at 40GB.
If you are trying to embed even more entities than that or have limited RAM available, you may need to use a... See more
Since co-occurrence matrices are square, they grow exponential with the number of entities being embedded. For 50k entities and a 32-bit data format, a dense matrix will already be at 10GB. 100k entities puts it at 40GB.
If you are trying to embed even more entities than that or have limited RAM available, you may need to use a... See more
What I've Learned Building Interactive Embedding Visualizations
What’s the best way for an end user to organize and explore millions of latent space features?
I’ve found tens of thousands of interpretable features in my experiments, and frontier labs have demonstrated results with a thousand times more features in production-scale models. No doubt, as interpretability techniques advance, we’ll see feature maps... See more
I’ve found tens of thousands of interpretable features in my experiments, and frontier labs have demonstrated results with a thousand times more features in production-scale models. No doubt, as interpretability techniques advance, we’ll see feature maps... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
Matei Zaharia, Omar Khattab, Lingjiao Chen, et al. • The Shift From Models to Compound AI Systems
To do this, we employ a technique known as AI-assisted evaluation, alongside traditional metrics for measuring performance. This helps us pick the prompts that lead to better quality outputs, making the end product more appealing to users. AI-assisted evaluation uses best-in-class LLMs (like GPT-4) to automatically critique how well the AI's... See more
Developing Rapidly with Generative AI
I’ve been giving talks and speaking with engineers and non-technical audiences about interpretability since 2022, and I still struggle to explain exactly what a “feature” is. I often use words like “concept” or “style”, or establish metaphors to debugging programs or making fMRI scans of brains. Both metaphors help people outside of the subfield... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
LLM-PowerHouse: A Curated Guide for Large Language Models with Custom Training and Inferencing
Welcome to LLM-PowerHouse, your ultimate resource for unleashing the full potential of Large Language Models (LLMs) with custom training and inferencing. This GitHub repository is a comprehensive and curated guide designed to empower developers,... See more
Welcome to LLM-PowerHouse, your ultimate resource for unleashing the full potential of Large Language Models (LLMs) with custom training and inferencing. This GitHub repository is a comprehensive and curated guide designed to empower developers,... See more
ghimiresunil • GitHub - ghimiresunil/LLM-PowerHouse-A-Curated-Guide-for-Large-Language-Models-with-Custom-Training-and-Inferencing: LLM-PowerHouse: Unleash LLMs' potential through curated tutorials, best practices, and ready-to-use code for custom training and inferencing.
we’re in a capability overhang - the AI tech that already exists has huge potential impact, whether you engage or not, so get ahead by exploring
the appropriate approach is pathfinding which uses experiments to learn and, critically, artefacts to tell the organisation what to do next.
the appropriate approach is pathfinding which uses experiments to learn and, critically, artefacts to tell the organisation what to do next.
.png?table=block&id=5cffd615-f82a-4e84-b2ff-4f4e496e2d3e&spaceId=996f2b3b-deaa-4214-aedb-cbc914a1833e&width=1330&userId=&cache=v2)
![Thumbnail of Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]](https://shortwaveimages.com/proxy/https%3A%2F%2Fsubstackcdn.com%2Fimage%2Ffetch%2Fw_2912%2Cc_limit%2Cf_auto%2Cq_auto%3Agood%2Cfl_progressive%3Asteep%2Fhttps%253A%252F%252Fsubstack-post-media.s3.amazonaws.com%252Fpublic%252Fimages%252F949e68ed-9f0c-47c2-9f12-38155122e288_2156x1212.png)