Nicolay Gerold

rerankers

A lightweight unified API for various reranking models. Developed by @bclavie as a member of answer.ai

Welcome to rerankers ! Our goal is to provide users with a simple API to use any reranking models.

Updates

• v0.3.1: T5 bugfix and native default support for new Portuguese T5 rerankers.


• v0.3.0: 🆕 Many changes! Experimental support for

... See more

1. Scalability is crucial - systems need to be designed with the assumption that query volume, document corpus size, indexing complexity etc. could increase by 10x. What works at one scale may completely break at a higher scale.


2. Sharding the index, either by document or by word, is important to distribute the indexing and querying load across machines.

... See more

We are excited to release the first version of our multimodal assistant Yasa-1, a language assistant with visual and auditory sensors that can take actions via code execution.

We trained Yasa-1 from scratch, including pretraining base models from ground zero, aligning them, as well as heavily optimizing both our training and serving infrastructure.... See more

5. Prioritizing Quality Data From The Start

Source:https://pair.withgoogle.com/guidebook/patterns

The foundation of any successful AI project is good data. Poor data management can lead to “data cascades,” where one issue leads to another, impacting the user experience. Investing in robust data practices early on can prevent these pitfalls.

Aim For:... See more

latest research on text embeddings!

TLDR: Vector databases are NOT safe. Text embeddings can be inverted. We can do this exactly for sentence-length inputs and get very close with paragraphs...

Service firms are hired for two reasons:

• Do a job that the client doesn’t have the bandwidth or expertise to do.


• Offer third-party expertise in decisions (cynically, to cover the client’s a**.)

That execution-oriented first bucket tends to include IT implementations (like cloud migration projects), financial audits, and outsourced customer support –... See more

(1) Tasks (a) Data collection, cleaning & labeling: human annotators , exploratory data analysis (b) Embeddings & feature engineering: normalization , bucketing / binning , word2vec (c) Data modeling & experimentation: accuracy , F1-score , precision , recall (d) Testing: scenario testing , AB testing , adaptive test-data (2) Biz/Org Management (a)... See more

Free AI - Text prompt to SVG

Discover the power of AI with our Free Text-to-SVG Generator! Effortlessly convert your text prompts into stunning SVG images using our advanced AI technology.

Analyze user queries and feedback to identify topic clusters, capabilities, and areas of user dissatisfaction. This will help you prioritize improvements.

Why should we do this? Let me give you an example. I once worked with a company that provided a technical documentation search system. By clustering user queries, we identified two main issues:

1. Top

... See more