Posted by Timothy Nguyen1, Research Engineer and Jaehoon Lee, Senior Research Scientist, Google Research For a machine learning (ML) algorithm to be effective, useful features must be extracted from (often) large amounts of training data. However, this process can be made challenging due to the costs associated with training on such large datasets, both in…
In November 2018, MIT Professor Sangbae Kim brought his mini cheetah robot onto “The Tonight Show’s” Tonight Show-botics segment. Much to the delight of host Jimmy Fallon, the mini cheetah did some yoga, got back up after falling, and executed a perfect backflip. Behind the stage, Benjamin Katz ’16, SM ’18 was remotely controlling the cheetah’s…
This code pattern is part of the Getting started with IBM Maximo Visual Inspection learning path. Level Topic Type 100 Introduction to computer vision Article 101 Introduction to IBM Maximo Visual Inspection Article 201 Build and deploy an IBM Maximo Visual Inspection model and use it in an iOS app Tutorial 202 Locate and count…
This code pattern is part of the Getting started with IBM Maximo Visual Inspection learning path. Level Topic Type 100 Introduction to computer vision Article 101 Introduction to IBM Maximo Visual Inspection Article 201 Build and deploy an IBM Maximo Visual Inspection model and use it in an iOS app Tutorial 202 Locate and count…
This code pattern is part of the Getting started with IBM Maximo Visual Inspection learning path. Level Topic Type 100 Introduction to computer vision Article 101 Introduction to IBM Maximo Visual Inspection Article 201 Build and deploy an IBM Maximo Visual Inspection model and use it in an iOS app Tutorial 202 Locate and count…
Businesses that want to be digital leaders in their markets need to embrace automation, not only to augment existing capabilities or to reduce costs but to position themselves to successfully maneuver the rapid expansion of IT demand ushered in through digital innovation. “It’s a scale issue,” says John Roese, global chief technology officer at Dell…
Posted by Sercan O. Arik, Research Scientist and Tomas Pfister, Engineering Manager, Google Cloud Multi-horizon forecasting, i.e. predicting variables-of-interest at multiple future time steps, is a crucial challenge in time series machine learning. Most real-world datasets have a time component, and forecasting the future can unlock great value. For example, retailers can use future sales…
Waiting for a holiday package to be delivered? There’s a tricky math problem that needs to be solved before the delivery truck pulls up to your door, and MIT researchers have a strategy that could speed up the solution. The approach applies to vehicle routing problems such as last-mile delivery, where the goal is to…
Posted by Xinying Song, Staff Software Engineer and Denny Zhou, Senior Staff Research Scientist, Google Research Tokenization is a fundamental pre-processing step for most natural language processing (NLP) applications. It involves splitting text into smaller units called tokens (e.g., words or word segments) in order to turn an unstructured input string into a sequence of…
Posted by Andrew M Dai and Nan Du, Research Scientists, Google Research, Brain Team Large language models (e.g., GPT-3) have many significant capabilities, such as performing few-shot learning across a wide array of tasks, including reading comprehension and question answering with very few or no training examples. While these models can perform better by simply…