​Posted by Junfeng He, Senior Research Scientist, and Kai Kohlhoff, Staff Research Scientist, Google Research People have the remarkable ability to take in a tremendous amount of information (estimated to be ~1010 bits/s entering the retina) and selectively attend to a few task-relevant and interesting… Read More »Enabling delightful user experiences via predictive models of human attention Google AI Google AI Blog

​ This is a guest post by Dr. Naoki Okada, Lead Data Scientist at BrainPad Inc. Founded in 2004, BrainPad Inc. is a pioneering partner in the field of data utilization, helping companies create business and improve their management through the use of data. To… Read More »How BrainPad fosters internal knowledge sharing with Amazon Kendra Dr. Naoki Okada AWS Machine Learning Blog

​ The well-famous ChatGPT developed by OpenAI is one of the best examples of Large Language Models (LLMs) that have been recently released. LLMs like ChatGPT have taken the world by storm with their unmatchable potential and ability to imitate humans in performing various tasks.… Read More »Exploring Instruction-Tuning Language Models: Meet Tülu-A Suite of Fine-Tuned Large Language Models (LLMs) Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​ The size of the machine learning (ML) models––large language models (LLMs) and foundation models (FMs)––is growing fast year-over-year, and these models need faster and more powerful accelerators, especially for generative AI. AWS Inferentia2 was designed from the ground up to deliver higher performance while… Read More »AWS Inferentia2 builds on AWS Inferentia1 by delivering 4x higher throughput and 10x lower latency Samir Araujo AWS Machine Learning Blog

​ Last week, Technology Innovation Institute (TII) launched TII Falcon LLM, an open-source foundational large language model (LLM). Trained on 1 trillion tokens with Amazon SageMaker, Falcon boasts top-notch performance (#1 on the Hugging Face leaderboard at time of writing) while being comparatively lightweight and… Read More »Deploy Falcon-40B with large model inference DLCs on Amazon SageMaker James Park AWS Machine Learning Blog

​ Rendered.ai is easing AI training for developers, data scientists and others with its platform-as-a-service for synthetic data generation, or SDG. Training computer vision AI models requires massive, high-quality, diverse and unbiased datasets. These can be challenging and costly to obtain, especially with increasing demands… Read More »Rendered.ai Integrates NVIDIA Omniverse for Synthetic Data Generation Katja Reitemeyer – Archives Page 1 | NVIDIA Blog

​ A few months ago, I wrote about some experiments with prime numbers. I generated a 16-digit non-prime number by multiplying two 8-digit prime numbers, and asked ChatGPT (using GPT -3.5) whether the larger number was prime. It answered correctly that the number was non-prime, but when… Read More »ChatGPT, Now with Plugins Mike Loukides AI & ML – Radar

​ The remarkable zero-shot learning capabilities demonstrated by large foundation models (LFMs) like ChatGPT and GPT-4 have sparked a question: Can these models autonomously supervise their behavior or other models with minimal human intervention? To explore this, a team of Microsoft researchers introduces Orca, a… Read More »Microsoft AI Introduces Orca: A 13-Billion Parameter Model that Learns to Imitate the Reasoning Process of LFMs (Large Foundation Models) Niharika Singh Artificial Intelligence Category – MarkTechPost

​ Whenever someone talks about artificial intelligence, the first thing that comes to mind is a robot, an android, or a humanoid that can do things humans do with the same effect, if not better. We have all seen such specific miniature robots deployed in… Read More »Meet PANOGEN: A Generation Method that can Potentially Create an Infinite Number of Diverse Panoramic Environments Conditioned on Text Anant shahi Artificial Intelligence Category – MarkTechPost

​We study the fundamental question of how to define and measure the distance from calibration for probabilistic predictors. While the notion of perfect calibration is well-understood, there is no consensus on how to quantify the distance from perfect calibration. Numerous calibration measures have been proposed… Read More »A Unifying Theory of Distance from Calibration Apple Machine Learning Research