The UK government has released a report on the capabilities and risks of frontier AI models, which will be discussed at the upcoming AI Safety Summit. The report acknowledges the potential benefits of AI but also highlights the risks and doomsday scenarios associated with it. These risks include AI pursuing autonomy and humans becoming irreversibly…

Large language models (LLMs) like GPT-4 and PaLM 2 struggle with mathematical problem-solving due to the need for imagination, reasoning, and computation. However, with multiple attempts, LLMs show potential for improvement. Fine-tuning techniques such as supervised step-by-step solution fine-tuning, solution-cluster reranking, and sequential multi-tasking fine-tuning can enhance LLMs’ ability to generate and evaluate solutions. The…

Danish urban oasis, JOE & THE JUICE, has expanded to over 250 European locations and is now making its mark in the US and the Middle East. They turned to Pixis, an AI solution, to streamline their marketing efforts and target audiences effectively. By leveraging Pixis’ AI infrastructure, Joe & The Juice achieved a 14%…

A recent collaborative study by IBM Research, Princeton University, and Virginia Tech highlights the security risks associated with fine-tuning large language models (LLMs). The research reveals that even a small number of harmful entries in a seemingly benign dataset can compromise the security of LLMs. The study emphasizes the need for developers to balance customization…

According to Bill Gates, Generative AI like ChatGPT has reached its peak and may not see significant improvements, even with the release of GPT-5. However, Gates acknowledges that he could be wrong. He believes AI will become more accurate and affordable in the next 2-5 years, benefiting people in poor countries. Gates is particularly excited…

Generative models are advancing in the field of Artificial Intelligence (AI). The concept of intelligent interaction with the physical environment requires planning at low and high levels. A research team from Google Deepmind, MIT, and UC Berkeley has proposed Video Language Planning (VLP) to combine text-to-video and vision-language models. VLP aims to facilitate visual planning…

Researchers have developed a few-shot-based tuning framework called LAMP for text-to-video (T2V) generation. Existing methods for T2V either require extensive data or result in aligning with template videos. LAMP addresses this challenge by using a few-shot approach, allowing a text-to-image diffusion model to learn motion patterns. It significantly improves video quality and generation freedom. LAMP…

Woodpecker is a new approach that aims to fix hallucinations in Multimodal Large Language Models (MLLM), such as GPT-4V. By connecting the MLLM to the internet, Woodpecker allows the model to validate its generated descriptions using relevant internet data, leading to self-correction. It builds a visual knowledge base from the image and uses it to…

This article discusses the evolution of Data/ML platforms and their support for complex MLOps practices. It explains how data infrastructures have evolved from simple systems like online services and OLTP/OLAP databases to more sophisticated setups like data lakes and real-time data/ML infrastructures. The challenges and solutions at each stage are described, as well as the…