UC Berkeley – The Shift from Models to Compound AI Systems

AI caught everyone’s attention in 2023 with Large Language Models (LLMs) that can be instructed to perform general tasks, such as translation or coding, just by prompting. This naturally led to an intense focus on models as the primary ingredient in AI application development, with everyone wondering what capabilities new LLMs will bring. As more…

Latest from MIT Tech Review – OpenAI teases an amazing new generative video model called Sora

OpenAI has built a striking new generative video model called Sora that can take a short text description and turn it into a detailed, high-definition film clip up to a minute long. Based on four sample videos that OpenAI shared with MIT Technology Review ahead of today’s announcement, the San Francisco-based firm has pushed the…

Latest from MIT Tech Review – Google’s new version of Gemini can handle far bigger amounts of data

Google DeepMind today launched the next generation of its powerful artificial intelligence model Gemini, which has an enhanced ability to work with large amounts of video, text, and images. It’s an advancement from the three versions of Gemini 1.0 that Google announced back in December, ranging in size and complexity from Nano to Pro to…

Latest from MIT Tech Review – Responsible technology use in the AI age

The sudden appearance of application-ready generative AI tools over the last year has confronted us with challenging social and ethical questions. Visions of how this technology could deeply alter the ways we work, learn, and live have also accelerated conversations—and breathless media headlines—about how and whether these technologies can be responsibly used. Responsible technology use,…

Latest from Google AI – Learning the importance of training data under concept drift

Posted by Nishant Jain, Pre-doctoral Researcher, and Pradeep Shenoy, Research Scientist, Google Research The constantly changing nature of the world around us poses a significant challenge for the development of AI models. Often, models are trained on longitudinal data with the hope that the training data used will accurately represent inputs the model may receive…

Latest from MIT : Using AI to discover stiff and tough microstructures

Every time you smoothly drive from point A to point B, you’re not just enjoying the convenience of your car, but also the sophisticated engineering that makes it safe and reliable. Beyond its comfort and protective features lies a lesser-known yet crucial aspect: the expertly optimized mechanical performance of microstructured materials. These materials, integral yet…

Latest from MIT Tech Review – Providing the right products at the right time with machine learning

Whether your favorite condiment is Heinz ketchup or your preferred spread for your bagel is Philadelphia cream cheese, ensuring that all customers have access to their preferred products at the right place, at the right price, and at the right time requires careful supply chain organization and distribution. Amid the proliferation of e-commerce and shifting…

Latest from Google AI – DP-Auditorium: A flexible library for auditing differential privacy

Posted by Mónica Ribero Díaz, Research Scientist, Google Research Differential privacy (DP) is a property of randomized mechanisms that limit the influence of any individual user’s information while processing and analyzing data. DP offers a robust solution to address growing concerns about data protection, enabling technologies across industries and government applications (e.g., the US census)…

Latest from MIT Tech Review – Why Big Tech’s watermarking plans are some welcome good news

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. This week I am happy to bring you some encouraging news from the world of AI. Following the depressing Taylor Swift deepfake porn scandal and the proliferation of political deepfakes, such as AI-generated robocalls…