Mathew

You Gotta Pump Those Dimensions: DreamEditor is an AI Model That Edits 3D Scenes Using Text-Prompts

The 3D computer vision domain was flooded with NeRFs in recent years. They emerged as a groundbreaking technique and enabled the reconstruction and synthesis of novel views of a scene. NeRFs capture and model the underlying geometry and appearance information from a collection of multi-view images. By leveraging neural networks, NeRFs offer a data-driven approach…

Read More

Google AI Open-Sources Flan-T5: A Transformer-Based Language Model That Uses A Text-To-Text Approach For NLP Tasks

Large language models, such as PaLM, Chinchilla, and ChatGPT, have opened up new possibilities in performing natural language processing (NLP) tasks from reading instructive cues. The prior art has demonstrated that instruction tuning, which involves finetuning language models on various NLP tasks organized with instructions, further improves language models’ capacity to carry out an unknown…

Read More

AI vs. Human-generated Content: Which Is Better for SEO?

Following all the buzz around AI, Google has finally confirmed that it’s not important how the content is created. Quality is what matters most. That means an appropriate use of AI is allowed considering you follow Google’s guidelines. Although AI has great potential, there are still some significant differences between AI-generated and human-written content that…

Read More

This Artificial Intelligence Research Confirms That Transformer-Based Large Language Models Are Computationally Universal When Augmented With An External Memory

The remarkable results achieved by transformer-based models like GPT-2 and GPT-3 gravitated the research community toward exploring large language models (LLMs). Additionally, ChatGPT’s recent success and popularity have only served to increase people’s interest in LLMs. In-context learning and chain-of-thought prompting are two other major discoveries that have significantly improved the accuracy of the models….

Read More

A New Artificial Intelligence (AI) Research Approach Presents Prompt-Based In-Context Learning As An Algorithm Learning Problem From A Statistical Perspective

In-context learning is a recent paradigm where a large language model (LLM) observes a test instance and a few training examples as its input and directly decodes the output without any update to its parameters. This implicit training contrasts with the usual training where the weights are changed based on the examples.  Here comes the…

Read More

New York City Mayor Eric Adams At Google

The Mayor of New York City, Eric Adams, was at Google’s NYC offices for an event. Here is a photo of Mayor Adams, Chancellor Banks, and Chancellor Matos-Rodriguez all came together this morning to announce the expansion of Future Ready NYC, a groundbreaking program aimed at equipping New York City students with the skills they…

Read More

Researchers at Stanford Introduce Parsel: An Artificial Intelligence AI Framework That Enables Automatic Implementation And Validation of Complex Algorithms With Code Large Language Models LLMs

Though recent advances have been made in large language model (LLM) reasoning, LLMs still have a hard time with hierarchical multi-step reasoning tasks like developing sophisticated programs. Human programmers, in contrast to other token generators, have (usually) learned to break down difficult tasks into manageable components that work alone (modular) and work together (compositional). As…

Read More