Nicolay Gerold
@nicolaygerold
Nicolay Gerold
Open source, high-throughput, fault-tolerant vector embedding pipeline
Simple API endpoint that ingests large volumes of raw data, processes, and stores or returns the vectors quickly and reliably
Simple API endpoint that ingests large volumes of raw data, processes, and stores or returns the vectors quickly and reliably
dgarnitz • GitHub - dgarnitz/vectorflow: VectorFlow is a high volume vector embedding pipeline that ingests raw data, transforms it into vectors and writes it to a vector DB of your choice.
Thanks to the cognitive architecture design, goal-oriented behavior is at the core of our LLM agents. When presented with a goal, they employ a planning and execution process to achieve it. If the goal can be accomplished using atomic game actions, we generate a plan that outlines how to solve the objective. For longer-term goals, we decompose the... See more
Introducing our work on general-purpose LLM Agents | GoodAI
Koheesio
CI/CD
Package
Meta
Koheesio, named after the Finnish word for cohesion, is a robust Python framework for building efficient data pipelines. It promotes modularity and collaboration, enabling the creation of complex pipelines from simple, reusable components.
The framework is versatile, aiming to support multiple implementations and working... See more
CI/CD
Package
Meta
Koheesio, named after the Finnish word for cohesion, is a robust Python framework for building efficient data pipelines. It promotes modularity and collaboration, enabling the creation of complex pipelines from simple, reusable components.
The framework is versatile, aiming to support multiple implementations and working... See more
GitHub - Nike-Inc/koheesio: Python framework for building efficient data pipelines. It promotes modularity and collaboration, enabling the creation of complex pipelines from simple, reusable components.
Improve Flexibility with Research-Supported Stretching Protocols
hubermanlab.comTemplate: take a really brocken D2C product and create a brand with a great design and website. Go to the FSA store to find products or to your local retailer and find products with a sea of sameness (all products look the same). Use growth marketing techniques on them: show the benefits, not the features (contents like Vitamin C), and use... See more
Steph Smith • #208 with Steph Smith - Why You Need a Chief Automation Officer
The text embedding set trained by Jina AI, Finetuner team.
Intended Usage & Model Info
jina-embeddings-v2-base-en is an English, monolingual embedding model supporting 8192 sequence length.
It is based on a Bert architecture (JinaBert) that supports the symmetric bidirectional variant of ALiBi to allow longer sequence length.
The backbone... See more
Intended Usage & Model Info
jina-embeddings-v2-base-en is an English, monolingual embedding model supporting 8192 sequence length.
It is based on a Bert architecture (JinaBert) that supports the symmetric bidirectional variant of ALiBi to allow longer sequence length.
The backbone... See more
jinaai/jina-embeddings-v2-base-en · Hugging Face
At the current pace of media content creation, Reddit expects their media metadata to be roughly 50 terabytes. This means they need to implement sharding and partition their tables across multiple Postgres instances.
Reddit shards their tables based on post_id where they use range-based partitioning. All posts with a post_id in a certain range will... See more
Reddit shards their tables based on post_id where they use range-based partitioning. All posts with a post_id in a certain range will... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
Could you have GPT-4 ask questions to the user rather than force the user to do prompt engineering? An experiment says this gave superior results. My read is that they tested this on easy cases where we already knew it would work, so we did not learn much.