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Arimbr

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投稿

AI's Event Backbone

altertable.ai
1 ポイント·投稿者 Arimbr·14 日前·0 コメント

Bootstrapping AI Evals from Context (Why 'Just Asking Claude' Fails)

scorable.ai
1 ポイント·投稿者 Arimbr·3 か月前·0 コメント

My Data Quality Tools List: Tried Any?

toolsfordata.com
1 ポイント·投稿者 Arimbr·4 か月前·0 コメント

Metadata Is the New Oil Fueling AI

selectstar.com
4 ポイント·投稿者 Arimbr·10 か月前·0 コメント

Why LLMs Struggle with Text-to-SQL

selectstar.com
1 ポイント·投稿者 Arimbr·12 か月前·0 コメント

Maintaining API Connectors

airbyte.com
1 ポイント·投稿者 Arimbr·2 年前·0 コメント

How Airbyte 1.0 orchestrates data movement jobs

airbyte.com
2 ポイント·投稿者 Arimbr·2 年前·0 コメント

Resumable Full Refresh Data Syncs

airbyte.com
1 ポイント·投稿者 Arimbr·2 年前·0 コメント

Speech-to-Emoji with OpenAI Whisper and GPT-4o

speech-to-emoji.vercel.app
1 ポイント·投稿者 Arimbr·2 年前·0 コメント

Literal AI: multi-modal LLM app observability and evaluation

literalai.com
4 ポイント·投稿者 Arimbr·2 年前·0 コメント

Conduktor 2.0: Kafka Development Platform

v2.conduktor.io
1 ポイント·投稿者 Arimbr·2 年前·0 コメント

[untitled]

1 ポイント·投稿者 Arimbr·2 年前·0 コメント

Productizing Data Services

arch.dev
2 ポイント·投稿者 Arimbr·2 年前·0 コメント

Processing Kafka event streams in Python

pathway.com
6 ポイント·投稿者 Arimbr·2 年前·1 コメント

Linux Terminal Reimagined with AI

warp.dev
5 ポイント·投稿者 Arimbr·2 年前·1 コメント

Pathway: Python stream processing framework for logistics and supply chain data

arxiv.org
1 ポイント·投稿者 Arimbr·2 年前·0 コメント

From Data Engineer to YAML Engineer

juhache.substack.com
2 ポイント·投稿者 Arimbr·2 年前·0 コメント

Writing Fewer Data Tests

elementary-data.com
2 ポイント·投稿者 Arimbr·3 年前·0 コメント

Fastest data processing engine on the market – 2023 benchmarks

pathway.com
2 ポイント·投稿者 Arimbr·3 年前·0 コメント

dbt Cloud or dbt Core for enterprise data platform

datacoves.com
1 ポイント·投稿者 Arimbr·3 年前·0 コメント

コメント

Arimbr
·2 年前·議論
I like the YAML abstraction. This should make it easier to programmatically try and evaluate multiple configurations for the whole AI pipeline (not just the LLM) against a dataset or real users through an API deployment.

Some feedback: It would be great to see in one place all the supported fields and values for the YAML config.
Arimbr
·2 年前·議論
What is an hybrid index?
Arimbr
·2 年前·議論
Nice, thanks! I was reading https://pathway.com/developers/user-guide/deployment/persist.... If I understand correctly you persist both source data and internal state, including the intermediary state of the computational graph. And you only rely on the backend to recover from failures and upgrades. So if I want to clone a Pathway instance, I don't need to reprocess all source data, I can recover the intermediary state from the snapshot.

Is it the same logic for the VectorStoreServer? https://pathway.com/developers/user-guide/llm-xpack/vectorst...
Arimbr
·2 年前·議論
If all the pipeline and the vector index is keep in memory... does Pathway still persist state somewhere?
Arimbr
·2 年前·議論
The AI Connector Builder from API docs is insane! Which API doc specifications will it support? Or does it even matter?
Arimbr
·2 年前·議論
Interesting implementation! For complex stream and text processing, I also prefer processing data in memory with Python (ETL) rather than SQL in the warehouse (ELT).
Arimbr
·3 年前·議論
I see the ingested documents in the data folder don't have an id field, only a doc field.

{"doc": "Using Large Language Models in Pathway is simple: just call the functions from `pathway.stdlib.ml.nlp`!"}

What if I pass two contradictory statements? Is there a way to remove (or better update) a document with a new version?

For example, if I am ingesting some public docs, and I update a doc page. How do I make so that it only takes the answer from the latest document version?
Arimbr
·3 年前·議論
Hi, interesting!

> Then it processes and organizes these documents by building a 'vector index' using the Pathway package.

What is the Pathway package?
Arimbr
·3 年前·議論
Nice list of resources!
Arimbr
·4 年前·議論
Thanks for the feedback! Recently a community member created a Terraform provider: https://github.com/eabrouwer3/terraform-provider-airbyte
Arimbr
·4 年前·議論
Know that there is also a CLI to manage configurations defined in YAML files. And a few options to deploy Airbyte in "one click". It's all in the README, sorry to hear you didn't find your way around our docs... There are a number of growing features and deployment options now.
Arimbr
·4 年前·議論
My bet: Data testing, data monitoring and data catalog solutions will consolidate to cover data quality all together.
Arimbr
·4 年前·議論
The future is EtLT! t for data privacy transformations and T for the rest.
Arimbr
·4 年前·議論
Oh, declarative doesn't necessarily mean no-code. Airbyte data integration connectors are built with an SDK in Python, Java, and a low-code SDK that was just released...

You can then build custom connectors on top of these and many users actually need to modify an existing connector, but would rather start from a template than from scratch.

Airbyte also provides a CLI and YAML configuration language that you can use to declare sources, destinations and connections without the UI: https://github.com/airbytehq/airbyte/blob/master/octavia-cli...

I agree with you that code is here to stay and power users need to see the code and modify it. That's why Airbyte code is open-source.