Blog tagged as Gen AI Research

A new study from Harvard University reveals how LLMs can be manipulated to boost a product's visibility and ranking in recommendations.

It is crucial for business leaders to understand the limitations and potential pitfalls of current approaches to measuring AI capabilities.

To accelerate development of advanced conversational AI applications, Microsoft recently introduced AutoGen, an open-source Python library that streamlines orchestrating multi-agent conversations.

MemGPT, applies OS principles like virtual memory and process management to unlock more powerful applications of LLMs - all while staying within their inherent memory limits.

Rumors are swirling that GPT-4 may use an advanced technique called Mixture of Experts (MoE) to achieve over 1 tr parameters. This offers an opportunity to demystify MoE

"Symbolic knowledge distillation" that automates common sense acquisition for AI.

Protecting the Copyright of Large Language Models Using Waterrmarks

Enhancing AI's Compositional Language Skills

Researchers are exploring new techniques to improve AI's ability to grasp diverse sentence structures and indirect meaning.

In their research paper, AI21 Labs demonstrates that frozen LLMs have untapped potential that can match or exceed fine-tuning approaches, without the downsides.

A new perspective paper argues that we must evaluate LLMs along two dimensions: formal linguistic competence and functional linguistic competence.

Researchers are exploring how to combine LLMs with neurosymbolic methods that incorporate logical reasoning and structure.

AI research from 2019 explored how to automatically generate reasonable suggestions for missing sections of text.

In 2019, researchers explored how artificial intelligence could use hierarchical models to improve computer-generated stories.

Books may seem like straightforward stories, but researchers are finding fascinating mathematical patterns hidden in the text.

Researchers developed a tool called Storywrangler that leveraged Twitter data to create an "instrument for understanding our world through the lens of social media."

A 2016 study analyzed over a thousand stories to uncover the basic emotional arcs that form the building blocks of narratives.

New research explores how integrating structured knowledge into AI systems can enhance storytelling abilities.

New research from Stanford University demonstrates how "emotion maps" could improve story generation.

While machine translation has improved dramatically for major languages, quality translation still lags for thousands of smaller languages.