Nicolay Gerold
@nicolaygerold
Nicolay Gerold
Breathing through the nose is powerful to improve hormone production by improving sleep. Focus on breathing through the nose even during training unless on max effort exercises.
Andrew Huberman • The Science of How to Optimize Testosterone & Estrogen
Very simply, Jevons Paradox states: if the demand is elastic and the price drops, the demand will more than make up for it. Normally, far more than make up for it. This is absolutely the case of the internet. You get more value and more productivity. I personally believe when it comes to any creative asset or work automation, the demand is elastic.... See more
Sarah Wang • What Builders Talk About When They Talk About AI | Andreessen Horowitz
I think this will be true for AI in general. ChatGPT starts out entering the enterprise, they get accustomed to it, they see the tangible results, and want to try it elsewhere without wanting an exact quantification in cost savings / revenue increases (which is often too hard to do for AI).
🌳 Galileo LLM Studio
Algorithm-powered LLMOps Platform
Find the best prompt, inspect data errors while fine-tuning, monitor LLM outputs in real-time. All in one powerful, collaborative platform.
Testing framework for LLM Part
Shipping to production
Before shipping to production, we think about all the different artifacts that might be affected by a new feature.
Here's a non-exhaustive list of things we ask ourselves:
Before shipping to production, we think about all the different artifacts that might be affected by a new feature.
Here's a non-exhaustive list of things we ask ourselves:
- Does the API need to be updated?
- Is the OpenAPI spec up to date now?
- Have we released all the official SDKs?
- Do we need to write a Changelog post to announce
How we ship new features · Resend
We ship often
Shipping early is not enough. We also need to keep shipping tiny iterations daily instead of waiting months to ship something big.
Having a strong sense of urgency , and making hard decisions fast is how we enable that process. Our sprints only last 1 week and are quite short when compared to the rest of the industry - this is by... See more
Shipping early is not enough. We also need to keep shipping tiny iterations daily instead of waiting months to ship something big.
Having a strong sense of urgency , and making hard decisions fast is how we enable that process. Our sprints only last 1 week and are quite short when compared to the rest of the industry - this is by... See more
How we ship new features · Resend
One of the focus areas at Together Research is new architectures for long context, improved training, and inference performance over the Transformer architecture. Spinning out of a research program from our team and academic collaborators, with roots in signal processing-inspired sequence models, we are excited to introduce the StripedHyena models.... See more
Paving the way to efficient architectures: StripedHyena-7B, open source models offering a glimpse into a world beyond Transformers
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
LLMs and
Competition increases testosterone in the short term, while winning and the subsequent release of dopamine increases testosterone further while loosing decreases it.
Andrew Huberman • The Science of How to Optimize Testosterone & Estrogen
Guideline following Large Language Model for Information Extraction
Model Card for GoLLIE 34B
We present GoLLIE, a Large Language Model trained to follow annotation guidelines. GoLLIE outperforms previous approaches on zero-shot Information Extraction and allows the user to perform inferences with annotation schemas defined on the fly. Different from... See more
Model Card for GoLLIE 34B
We present GoLLIE, a Large Language Model trained to follow annotation guidelines. GoLLIE outperforms previous approaches on zero-shot Information Extraction and allows the user to perform inferences with annotation schemas defined on the fly. Different from... See more