Respawn Entertainment CEO Vince Zampella and game developer Stig Asmussen give the latest details about Star Wars Jedi: Fallen Order. Cal Kestis is the main character in the upcoming video game "Star Wars Jedi: Fallen Order," due out November 15 on Xbox One, PlayStation 4, and PC (you can pre-order now). He's a young Padawan – a Jedi in training – when then-Chancellor Palpatine issues Order 66, a purge to kill all Jedi, an event that takes place in the 2005 film "Episode III – Revenge of the Sith." In'Star Wars Jedi: Fallen Order,' the Jedi Padawan Cal Kestis is forced into action against the Empire. In hiding at the game's beginning, Cal (who is played by "Gotham" star Cameron Monaghan) is forced to use his Jedi skills and now is among the hunted.

Ecoprosus India Pvt. Ltd. and Nymo Technologies have signed a US $20 Million deal to deliver a next-generation video analytics platform powered by deep-learning algorithms, coupled with energy efficient and new age technologies. Ecoprosus, has developed a Smart Poles solution for the Smart City infrastructure projects across India. This deployment is centered around a socially responsible philosophy and will endeavour to not only meet the technological challenges of Smart City projects, but provide safe and sustainable solutions that will last for years to come. "Our collective aim in this joint venture was to leverage each-other's strengths and deliver a truly world-class end to end solution that addresses a broad range of socially responsible edicts," remarked BR Anand, CSO and co-founder of Ecoprosus. Ecoprosus specialises in Smart City infrastructure projects and is providing Smart Pole hardware and software designed to be energy efficient and sustainable from inception.

Giant technology companies might cause significant disruption to the world's financial system, the head of the International Monetary Fund has warned. Christine Lagarde said just a few firms with big data access and artificial intelligence could run the global payment and settlement arrangements. Her warning came as the G20 finance ministers met in Japan. The summit is also discussing the need to close tax loopholes for internet giants like Facebook and Google. One of the options being considered is to tax such companies where they make their profits - rather than where they base their headquarters.

Tech giants like Facebook and governments around the world are struggling to deal with disinformation, from misleading posts about vaccines to incitement of sectarian violence. As artificial intelligence becomes more powerful, experts worry that disinformation generated by A.I. could make an already complex problem bigger and even more difficult to solve. In recent months, two prominent labs -- OpenAI in San Francisco and the Allen Institute for Artificial Intelligence in Seattle -- have built particularly powerful examples of this technology. Both have warned that it could become increasingly dangerous. Alec Radford, a researcher at OpenAI, argued that this technology could help governments, companies and other organizations spread disinformation far more efficiently: Rather than hire human workers to write and distribute propaganda, these organizations could lean on machines to compose believable and varied content at tremendous scale.

Mobile developers have a great deal to pick up from progressive changes that on-device ML can offer. This is a result of the innovation's capacity to reinforce mobile applications--in particular, taking into consideration smoother customer experiences equipped for utilizing incredible highlights, for example, giving exact area-based recommendations or promptly detecting plant illnesses. This fast improvement of mobile machine learning has occurred as a response to various basic issues that traditional machine learning has toiled with. In truth, the composing is on the divider. Future mobile applications will require faster preparing paces and lower latency.

Academically, he is using them to understand the mechanics of person-to-person interaction. But his true quest is to untangle the ineffable nature of connection itself. It is summer 2002, mid-morning in a university research lab on the edge of Osaka, Japan. Two girls--both dressed in pale yellow, with child-puffy cheeks, black shoulder-length hair, and bangs--stand opposite each other under fluorescent lights. More precisely: One is a girl, 5 years old; the other is her copy, her android replica.

As followers of Christ, we are called to engage the world around us with the unchanging gospel message of hope and reconciliation. Tools like technology are able to aid us in this pursuit. We know they can also be designed and used in ways that dishonor God and devalue our fellow image-bearers. Evangelical Christians hold fast to the inerrant and infallible Word of God, which states that every human being is made in God's image and thus has infinite value and worth in the eyes of their Creator. This message dictates how we view God, ourselves, and the tools that God has given us the ability to create.

Most television stations still rely on human transcription to generate the closed captioning for their live broadcasts. Yet even with the benefit of human fluency, this captioning can vary wildly in quality, even within the same broadcast, from a nearly flawless rendition to near-gibberish. At the same time, automatic speech recognition has historically struggled to achieve sufficient accuracy to entirely replace human transcription. Using a week of television news from the Internet Archive's Television News Archive, how does the station-provided primarily human-created closed captioning compare with machine-generated transcripts generated by Google's Cloud Speech-to-Text API? Automated high-quality captioning of live video represents one of the holy grails of machine speech recognition. While machine captioning systems have improved dramatically over the years, there has still been a substantial gap holding them back from fully matching human accuracy.

In the previous blog, I discussed Visual Perception and its both biological and computational aspects. This blog is specifically about computational Visual Perception, also known as Computer Vision. Computer vision has been around for more than 50 years, but recently, we see a major resurgence of interest in how machines'see' and how computer vision can be used to build products for consumers and businesses. The key driving factor behind all these is Computer Vision. In the simplest terms, Computer Vision is the discipline under a broad area of Artificial Intelligence which teaches machines to see.