Nicolay Gerold
@nicolaygerold
Nicolay Gerold
Why is Continuous Delivery for ML/AI hard(er)?
Since the challenge is not new and many valid solutions exist targeting traditional software projects, is there a reason to treat ML/AI systems any differently? Consider these three core challenges that are endemic in ML, AI, and data projects:
Since the challenge is not new and many valid solutions exist targeting traditional software projects, is there a reason to treat ML/AI systems any differently? Consider these three core challenges that are endemic in ML, AI, and data projects:
- Development and debugging cycles are more tedious due to
How To Organize Continuous Delivery of ML/AI Systems: a 10-Stage Maturity Model | Outerbounds
- GitHub stars: 1.5k
- Features:
- Supports multiple notification types (e.g., toasts, snackbars, alerts).
- Can render notifications inside custom elements.
- Supports custom notification renderers.
- GitHub link: GitHub – LouisBarranqueiro/reapop
The ultimate guide to React notification libraries
Here's a list of those log levels from lowest precedence to highest:
notset (0) - Indicates that ancestor loggers should be consulted for the log level or that all events are logged (default setting)
debug (10) - Detailed information that would be of interest to the developer for diagnostic purposes
info (20) - Information that confirms that your... See more
notset (0) - Indicates that ancestor loggers should be consulted for the log level or that all events are logged (default setting)
debug (10) - Detailed information that would be of interest to the developer for diagnostic purposes
info (20) - Information that confirms that your... See more
Shortwave — The smartest email app on planet Earth
Large Language Model State Machine (llmstatemachine)
Introduction
llmstatemachine is a library for creating agents with GPT-based language models and state machine logic.
Introduction
llmstatemachine is a library for creating agents with GPT-based language models and state machine logic.
- Chat History as Memory : Leverages large context window models, making chat history the primary source of agent memory.
- Custom Python Functions with JSON Generation : Allows the
GitHub - robocorp/llmstatemachine: A Python library for building GPT-powered agents with state machine logic and chat history memory.
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Salad - GPU Cloud | 10k+ GPUs for Generative AI
Enable developer self-service
Free developers from time-consuming, unnecessary tasks that slow your work, so you and your team can focus on writing code.
Remote Development Environments for every developer
Develop and debug locally while running environments remotely in the cloud, and see your changes live, precisely as they would look in... See more
Free developers from time-consuming, unnecessary tasks that slow your work, so you and your team can focus on writing code.
Remote Development Environments for every developer
Develop and debug locally while running environments remotely in the cloud, and see your changes live, precisely as they would look in... See more
Bunnyshell - Self-service Cloud Development Environments
Tabby
Opensource, self-hosted AI coding assistant
Opensource, self-hosted AI coding assistant
Home | Tabby
ColBERT is a
fast
and
accurate
retrieval model, enabling scalable BERT-based search over large text collections in tens of milliseconds.
Figure 1: ColBERT's late interaction, efficiently scoring the fine-grained similarity between a queries and a passage.
As Figure 1 illustrates, ColBERT relies on fine-grained contextual late interaction : it... See more
fast
and
accurate
retrieval model, enabling scalable BERT-based search over large text collections in tens of milliseconds.
Figure 1: ColBERT's late interaction, efficiently scoring the fine-grained similarity between a queries and a passage.
As Figure 1 illustrates, ColBERT relies on fine-grained contextual late interaction : it... See more
stanford-futuredata • GitHub - stanford-futuredata/ColBERT: Stanford ColBERT: state-of-the-art neural search (SIGIR'20, TACL'21, NeurIPS'21, NAACL'22, CIKM'22)
Ghrelin is released from the GI tract and stimulates your desire to eat. It is triggered by low glucose levels in the blood and triggers anticipatory food signals making you think about food you would like to eat. Your ghrelin secretion will start to match your eating schedule. It can be shifted by about 45 minutes a day.