Current state-of-the-art solutions for motion capture from a single camera are optimization driven: they optimize the parameters of a 3D human model so that its re-projection matches measurements in the video (e.g.

Classical GNNs excel at graph learning but incur high computational costs in large-scale settings. We present a fully quantum Graph Neural Network (QGNN) that implements message passing via Parameterized Quantum Circuits (PQCs). Our Quantum Graph Convolutional Layers (QGCLs) encode features into quantum states, process graphs with NISQ-compatible unitaries, and retrieve embeddings through measurement. Applied to D2D power control for SINR maximization, our QGNN matches classical performance with fewer parameters and inherent parallelism. This end-to-end PQC-based GNN marks a step toward quantum-accelerated wireless optimization.

Current state-of-the-art solutions for motion capture from a single camera are optimization driven: they optimize the parameters of a 3D human model so that its re-projection matches measurements in the video (e.g.

For the past few nights, I've concerned myself with the private lives of autonomous vehicles. It started when I read a news story about a San Francisco apartment complex whose residents were repeatedly awoken at 4 a.m. by honking self-driving taxis. The building overlooks an open-air parking lot that Waymo recently leased to store its vehicles. In the wee hours of the morning--between ferrying home overserved bar crawlers and picking up commuters during the morning rush hour--dozens of the autonomous white sedans fill the lot, power down, and wait to be summoned. Sometimes, too many awaken at the same time and back up while trying to make their way to the exit, only to find the lanes clogged by their brethren.

Waymo's self-driving cars no longer honk when near each other, Waymo's Director of Product and Operations Vishay Nihalani said yesterday when he appeared on software engineer Sophia Tung's livestream. The vehicles were spotted honking at each other a few weeks ago, prompting Waymo to issue a software patch. As reported by NBC Bay Area, residents living near the parking lot full of Waymo taxis reported that despite the patch going live, the taxis still honked at each other. Tung, who lived near the idling taxis, set up her live stream to capture the cacophony of honking vehicles. No good stream is complete without a soundtrack, and Tung's stream included lo-fi music in the vein of the ubiquitous "LoFi Girl" on YouTube.

The TensorFlow ecosystem has evolved into many different frameworks to serve a variety of roles and functions. That flexibility is part of the reason for its widespread adoption, but it also complicates the learning curve for data scientists, machine learning (ML) engineers, and other technical stakeholders. There are so many ways to manage TensorFlow models for common tasks--such as data and feature engineering, data ingestions, model selection, training patterns, cross validation against overfitting, and deployment strategies--that the choices can be overwhelming. This pocket reference will help you make choices about how to do your work with TensorFlow, including how to set up common data science and ML workflows using TensorFlow 2.0 design patterns in Python. Examples describe and demonstrate TensorFlow coding patterns and other tasks you are likely to encounter frequently in the course of your ML project work.

Online fraud and identity theft is a global problem that has only been exacerbated with increased online transactions amid the COVID-19 pandemic. In particular, it is estimated that Brazilian companies lose over $41 billion due to fraud every year. In an attempt to tackle this problem head on, Lincoln Ando and Raphael Melo started idwall in mid-2016. São Paulo-based idwall started as an automated background check solution and has since grown into a suite of data and identity validation and risk analysis products. For the consumer market, its "MeuID" app is aimed at users who want to change the way they identify themselves and share their data.

This is a problem if we want AIs to be trustworthy. That's why Diffbot takes a different approach. It is building an AI that reads every page on the entire public web, in multiple languages, and extracts as many facts from those pages as it can. Like GPT-3, Diffbot's system learns by vacuuming up vast amounts of human-written text found online. But instead of using that data to train a language model, Diffbot turns what it reads into a series of three-part factoids that relate one thing to another: subject, verb, object.

SAN FRANCISCO – SoftBank Group Corp. is sending tremors through the tech world with a massive new venture capital fund for investing in startups that is expected to dominate the industry so thoroughly it's playfully referred to as a "gorilla." The Vision Fund's $100 billion coffers nearly equals the total amount pumped into venture capital-backed companies last year, according to market intelligence firm CB Insights, and some say it could be a game-changer for Silicon Valley. "SoftBank shows a remarkable amount of bravery, confidence and optimism to look to apply this much money in technology," said Bill Maris, who started Google Ventures nearly a decade ago and runs his own California-based investment firm Section 32. "I can't say it's a wrong bet, if you think the trends in tech will continue in the future. I would be much more worried if SoftBank was saying tech is dead."

Out of curiosity, Teresa Chen recently went to an unmanned convenience store, EasyGo, near the China Plaza shopping mall in Guangzhou, China. She used her WeChat app to scan a QR code to get into the store, where she found imported snacks, candy and soft drinks. Every product had a price tag powered by radio-frequency identification, a technology that can automatically track and identify tags attached to objects. After she selected a box of crackers, Chen stood in the payment area and the bill automatically appeared in WeChat. Once Chen paid using her WeChat Wallet (a mobile payment service developed by Tencent), the door opened to let her leave the store. "The whole experience was seamless, as I didn't even need to scan the price tag to pay," said Chen, a product manager for a nutrition supplement company in Guangzhou.