Nicolay Gerold

💰 PayPal is planning an ad network built off your purchase history LINK

PayPal plans to create an ad network using data from billions of customer transactions to target ads more effectively.

The new ad initiative, led by Mark Grether, aims to help businesses sell more by using PayPal's detailed knowledge of users' purchasing histories.

AI technology... See more

Simply adding "Repeat the question before answering it." somehow make the models answer the trick question correctly.

Probable explanations: Repeating the question in the model's context, significantly increasing the likelihood of the model detecting any potential "gotchas."

One hypothesis is that maybe it puts the model into more of a completion... See more

data needs to be managed for quality, timeliness, consistency, reusability, and business relevance

I mostly use a UI I made myself:

https://github.com/shinomakoi/AI-Messenger

Works with llama.cpp and Exllama V2, supports LLaVA, character cards and moar.

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RYSKZ

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9 days ago

Right now, I'm using your earlier project [1]. It's proving to be incredibly helpful, thank you!.

Since it's a desktop application, it's more convenient for me... See more

Creativity has two parts:- Creative discovery mode: shuffling things around, exploring. Playful.- Implementation mode: creating something robust and concrete.- Revisit the work the next day in an alert state and assess whether it is ready for linear implementation.

Plasticity can be as large as in youth if there is a serious incentive for the plasticity to occur. How bad we want it or need it determines the rate and magnitude of plasticity. You cannot practice passively.

Clean & curate your data with LLMs

databonsai is a Python library that uses LLMs to perform data cleaning tasks.

Features

• Suite of tools for data processing using LLMs including categorization, transformation, and extraction


• Validation of LLM outputs


• Batch processing for token savings


• Retry logic with exponential backoff for handling rate limits and

... See more

Second Stage

Here, Instagram uses a Multi-Task Multi Label (MTML) neural network model. As the name suggests, this is an ML model that is designed to handle multiple tasks (objectives) and predict multiple labels (outcomes) simultaneously.

For recommendation systems, this means predicting different types of user engagement with a piece of content... See more

We consider these aspects of our problem:

• Latency : How fast does the system need to respond to user input?


• Task Complexity : What level of understanding is required from the LLM? Is the input context and prompt super domain-specific?


• Prompt Length : How much context needs to be provided for the LLM to do its task?


• Quality : What is the acceptable

... See more