jaq

jaq (pronounced like Jacques1) is a clone of the JSON data processing tool jq. jaq aims to support a large subset of jq's syntax and operations.
jaq focuses on three goals:
Correctness: jaq aims to provide a more correct and predictable implementation of jq, while preserving compatibility with jq in most cases.
Examples of surprising jq behaviour
Performance: I created jaq originally because I was bothered by jq's long start-up time, which amounts to about 50ms on my machine. This can particularly show when processing a large number of small files. jaq starts up about 30 times faster than jq 1.6 and outperforms jq also on many other benchmarks.
Simplicity: jaq aims to have a simple and small implementation, in order to reduce the potential for bugs and to facilitate contributions.
I drew inspiration from another Rust program, namely jql. However, unlike jql, jaq aims to closely imitate jq's syntax and semantics. This should allow users proficient in jq to easily use jaq.
link : https://github.com/01mf02/jaq
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KuCoin, a leading cryptocurrency exchange, has announced the introduction of 7.5% VAT on transaction fees for Nigerian users starting July 8, 2024.

This has sparked discontent among Nigerian traders, who believe the government should not tax cryptocurrency transactions because they are not recognized as legal tender.

Some users are threatening to boycott KuCoin. 😐

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JPMorgan Launches AI Tool for Analysts 🤖

JPMorgan Chase has launched #LLM Suite, an AI tool designed to assist its asset and wealth management division by performing tasks typically done by research analysts, such as writing, idea generation, and document summarization.

Introduced through an internal memo by top executives, the tool is similar to #ChatGPT and integrates with internal systems handling sensitive financial information to enhance productivity. Initially rolled out to 15% of JPMorgan's workforce, the tool aims to support research analysts by providing information, solutions, and advice.

A survey by #JPMorgan found that 61% of institutional traders view AI as the most impactful technology for the future of trading.

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RagaAI Inc. has launched RagaAI LLM Hub, an open-source package for the AI community. The tool offers 100+ evaluation metrics and guardrails to evaluate and diagnose LLM and RAG application performance. It assesses various aspects of LLM application building, including relevance, content quality, and more.

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