Lifeboat Foundation

In recent years, videogame developers and computer scientists have been trying to devise techniques that can make gaming experiences increasingly immersive, engaging and realistic. These include methods to automatically create videogame characters inspired by real people.

Most existing methods to create and customize videogame characters require players to adjust the features of their character’s face manually, in order to recreate their own face or the faces of other people. More recently, some developers have tried to develop methods that can automatically customize a character’s face by analyzing images of real people’s faces. However, these methods are not always effective and do not always reproduce the faces they analyze in realistic ways.

Researchers at Netease Fuxi AI Lab and University of Michigan have recently created MeInGame, a deep learning technique that can automatically generate character faces by analyzing a single portrait of a person’s face. This technique, presented in a paper pre-published on arXiv, can be easily integrated into most existing 3D videogames.

Large language models are already business propositions. Google uses them to improve its search results and language translation; Facebook, Microsoft and Nvidia are among other tech firms that make them. OpenAI keeps GPT-3’s code secret and offers access to it as a commercial service. (OpenAI is legally a non-profit company, but in 2019 it created a for-profit subentity called OpenAI LP and partnered with Microsoft, which invested a reported US$1 billion in the firm.) Developers are now testing GPT-3’s ability to summarize legal documents, suggest answers to customer-service enquiries, propose computer code, run text-based role-playing games or even identify at-risk individuals in a peer-support community by labelling posts as cries for help.

A remarkable AI can write like humans — but with no understanding of what it’s saying.

Four Emerging Technology Areas Impacting Industry 4.0: Advanced Computing, Artificial intelligence, Big Data & Materials Science.

Another call for the US government to declare a National Initiative for the USA to reach AGI by 2025.

“China Plans to Defeat US Supremacy in AI, Quantum Computing With Five-Year Plan”

Huawei and ZTE would lead the country in battling tech with tech!

Continue reading “China Plans to Defeat US Supremacy in AI, Quantum Computing With Five-Year Plan” »

A new type of supply chain attack unveiled last month is targeting more and more companies, with new rounds this week taking aim at Microsoft, Amazon, Slack, Lyft, Zillow, and an unknown number of others. In weeks past, Apple, Microsoft, Tesla, and 32 other companies were targeted by a similar attack that allowed a security researcher to execute unauthorized code inside their networks.

The latest attack against Microsoft was also carried out as a proof-of-concept by a researcher. Attacks targeting Amazon, Slack, Lyft, and Zillow, by contrast, were malicious, but it’s not clear if they succeeded in executing the malware inside their networks. The npm and PyPi open source code repositories, meanwhile, have been flooded with more than 5000 proof-of-concept packages, according to Sonatype, a firm that helps customers secure the applications they develop.

“Given the daily volume of suspicious npm packages being picked up by Sonatype’s automated malware detection systems, we only expect this trend to increase, with adversaries abusing dependency confusion to conduct even more sinister activities,” Sonatype researcher Ax Sharma wrote earlier this week.

Materials capable of performing complex functions in response to changes in the environment could form the basis for exciting new technologies. Think of a capsule implanted in your body that automatically releases antibodies in response to a virus, a surface that releases an antibacterial agent when exposed to dangerous bacteria, a material that adapts its shape when it needs to sustain a particular weight, or clothing that senses and captures toxic contaminants from the air.

Scientists and engineers have already taken the first step toward these types of autonomous materials by developing “active” materials that have the ability to move on their own. Now, researchers at the University of Chicago have taken the next step by showing that the movement in one such active material—liquid crystals—can be harnessed and directed.

This proof-of-concept research, published on February 182021, in the journal Nature Materials, is the result of three years of collaborative work by the groups of Juan de Pablo, Liew Family Professor of Molecular Engineering, and Margaret Gardel, Horace B. Horton Professor of Physics and Molecular Engineering, along with Vincenzo Vitelli, professor of physics, and Aaron Dinner, professor of chemistry.

Most of this automation is being done by companies you’ve probably never heard of. UiPath, the largest stand-alone automation firm, is valued at $35 billion — roughly the size of eBay — and is slated to go public later this year. Other companies like Automation Anywhere and Blue Prism, which have Fortune 500 companies like Coca-Cola and Walgreens Boots Alliance as clients, are also enjoying breakneck growth, and tech giants like Microsoft have recently introduced their own automation products to get in on the action.

Workers with college degrees and specialized training once felt relatively safe from automation. They aren’t.

One billion public Instagram photos were used to train an algorithm created by Facebook to learn to recognise images by itself.

The photos were used to help a Facebook algorithm learn to recognise images without supervision.