Building a lucrative business without having to sweat from reinventing the wheel. Explore actionable steps with examples to use existing tech to make new impact

If you are like me, it took me a long time to understand what the JavaScript “this” keyword was all about.

AI, AR, Wearables, Fashion and Beauty Tech

Email makes a lousy to-do list — but what makes for a great one? Getting this right transformed my productivity and helped me sleep better.

My dear, priests, holy fathers, monks and other such folk. I didn’t get my CS degree so I can see you turn programming into a religion.

In the vast Universe, Why I thought I was something big ?

IMAGE: Hyundai

This article explores the innovative approach of identifying potentially relevant user responses with sentence transformer technology.

Explore the intricacies of learning from errors in AI dialog systems, uncovering challenges in extracting signals from human-human polite disagreements.

Uncover the layers of utterance, response, context, and society-level errors, gaining valuable insights into language-generation challenges.

Witness the impact of a refined Integrated Error Taxonomy through a human evaluation, shedding light on its effectiveness in human-bot dialog understanding

Embark on a comprehensive exploration of AI dialog datasets, uncovering insights into errors in system utterances and user responses.

By Deepak Chopra, MD, FACP, FRCP

Embark on a statistical expedition through the heart of AI dialog datasets, exploring the distribution of errors and user responses.

This article unveils modifications based on observed weaknesses, creating a more nuanced classification system.

Explore conversational datasets as we dissect six distinct types of dialogs, spanning task-oriented, open-domain, and knowledge-grounded interactions.

Every morning I sit down and plan the day.

Explore the landscape of dialog datasets enriched with free-text human feedback and delve into the intricacies of error taxonomies in conversational AI.

Explore the potential of synthetic dialog generation to augment existing datasets with annotations for errors and free-text human feedback.

Mario Cao from SEDA protocol provides an overview of their multi-chain native oracle and the prospects of data request bridging.

This conclusion highlights the path toward enhanced accessibility and reliability for language models.