Exploring AI safety, adaptability, and efficiency for the real world Next week marks the start of the 40th International Conference on Machine Learning (ICML 2023), taking place 23-29 July in Honolulu, Hawai’i. ICML brings together the artificial intelligence (AI) community to share new ideas, tools, and datasets, and make connections to advance the field. From …
Have you ever wondered what happens behind the scenes when you chat with an AI? While you’re getting instant answers, something else is happening: generative AI power consumption soars with each interaction. It turns out, that seemingly simple exchange is part of a massive, energy-hungry system that’s quietly reshaping our world – and our power …
Stable Diffusion 1.5/2.0/2.1/XL 1.0, DALL-E, Imagen… In the past years, Diffusion Models have showcased stunning quality in image generation. However, while producing great quality on generic concepts, these struggle to generate high quality for more specialised queries, for example generating images in a specific style, that was not frequently seen in the training dataset. We …
Six Ways to Control Style and Content in Diffusion Models Read More »
How we’re applying the latest AI developments to help fight climate change and build a more sustainable, low-carbon world AI is a powerful technology that will transform our future, so how can we best apply it to help combat climate change and find sustainable solutions? Our climate & sustainability lead, Sims Witherspoon, who recently spoke …
Which Outcome Matters? Here is a common scenario : An A/B test was conducted, where a random sample of units (e.g. customers) were selected for a campaign and they received Treatment A. Another sample was selected to receive Treatment B. “A” could be a communication or offer and “B” could be no communication or no …
The Gamma Hurdle Distribution | Towards Data Science Read More »
Our next iteration of the FSF sets out stronger security protocols on the path to AGI AI is a powerful tool that is helping to unlock new breakthroughs and make significant progress on some of the biggest challenges of our time, from climate change to drug discovery. But as its development progresses, advanced capabilities may …
Metric collection is an essential part of every machine learning project, enabling us to track model performance and monitor training progress. Ideally, Metrics should be collected and computed without introducing any additional overhead to the training process. However, just like other components of the training loop, inefficient metric computation can introduce unnecessary overhead, increase training-step …
In December, we kicked off the agentic era by releasing an experimental version of Gemini 2.0 Flash — our highly efficient workhorse model for developers with low latency and enhanced performance. Earlier this year, we updated 2.0 Flash Thinking Experimental in Google AI Studio, which improved its performance by combining Flash’s speed with the ability …
In the world of machine learning, we obsess over model architectures, training pipelines, and hyper-parameter tuning, yet often overlook a fundamental aspect: how our features live and breathe throughout their lifecycle. From in-memory calculations that vanish after each prediction to the challenge of reproducing exact feature values months later, the way we handle features can …
ML Feature Management: A Practical Evolution Guide Read More »
Research Published 28 July 2023 Authors Yevgen Chebotar, Tianhe Yu Robotic Transformer 2 (RT-2) is a novel vision-language-action (VLA) model that learns from both web and robotics data, and translates this knowledge into generalised instructions for robotic control High-capacity vision-language models (VLMs) are trained on web-scale datasets, making these systems remarkably good at recognising visual …
RT-2: New model translates vision and language into action Read More »
