Kara Frederick, tech director at the Heritage Foundation, discusses the need for regulations on artificial intelligence as lawmakers and tech titans discuss the potential risks. An internet watchdog is sounding the alarm over the growing trend of sex offenders collaborating online to use open source artificial intelligence to generate child sexual abuse material. "There's a technical community within the offender space, particularly dark web forums, where they are discussing this technology," Dan Sexton, the chief technology officer at the Internet Watch Foundation (IWF), told The Guardian in a report last week. "They are sharing imagery, they're sharing [AI] models. Sexton's organization has found that offenders are increasingly turning to open source AI models to create illegal child sexual abuse material (CSAM) and distribute it online. Unlike closed AI models such as OpenAI's Dall-E or Google's Imagen, open source AI technology can be downloaded and adjusted by users, according to the report. Sexton said the ability to use such technology has spread among offenders, who take to the dark web to create and distribute realistic images. An internet watchdog is sounding the alarm over the growing trend of sex offenders collaborating online to use open source artificial intelligence to generate child sexual abuse material. "The content that we've seen, we believe is actually being generated using open source software, which has been downloaded and run locally on people's computers and then modified.

Two new open source AI projects will look to take advantage of space tech in a bid to solve challenges around cube satellite comms and space junk. IBM is no stranger to innovations in space, with a space flight chronology dating all the way back to 1944, when it helped to first design and build the automatic sequence Controlled Calculator for Harvard University which was used by Navy scientists to prepare ballistic tables. Almost 76 years later, IBM looks to be ready to join the space race with its latest foray into artificial intelligence (AI). According to the latest announcements from Big Blue, two new open source AI projects will look to take advantage of space technology in a bid to solve technical challenges around cube satellite communication and the growing problem of space junk.

IBM is no stranger to innovations in space, with a space flight chronology dating all the way back to 1944, when it helped to first design and build the automatic sequence Controlled Calculator for Harvard University which was used by Navy scientists to prepare ballistic tables. Almost 76 years later, IBM looks to be ready to join the space race with its latest foray into artificial intelligence (AI). According to the latest announcements from Big Blue, two new open source AI projects will look to take advantage of space technology in a bid to solve technical challenges around cube satellite communication and the growing problem of space junk. In correlation with the announcement, IBM's Space Tech Hub Team, led by engineer and space tech CTO, Naeem Altaf, unveiled the two open source projects named KubeSat and Space Situational Awareness (SSA) system. IBM's newly open sourced project KubeSat is a cognitive autonomous framework that can be used to create and control satellite swarms and support additional software they need to perform specific tasks, while also enabling the simulation and optimization of multi-satellite communications.

Arguably, the open source movement -- the idea that a group of technologists freely contributing their own work and commenting on the work of others, can create a final product that is comparable with anything that a commercial enterprise might create -- has been one of the great innovation catalysts of the technology industry. It's no wonder, then, that a group of Silicon Valley luminaries -- including Elon Musk, Peter Thiel and Reid Hoffman -- have lined up to contribute $1 billion to a new open-source AI project known as OpenAI that is led by Ilya Sutskever, one of the world's top experts in machine learning. For now, we don't really know. The OpenAI website is basically just a single blog post outlining the organization's manifesto and an "About" page detailing all the technologists and engineers working on the project. Thus far, we only have a long announcement from the founding members that they are going to do something amazing.

Blazing the web for black-boxes to reverse-engineer, I came upon the following informative and down-to-earth article. I'm sharing it, as it hasn't found its way to the general public. The open-source AI trend represents the convergence of two trends: The open-source movement and the artificial intelligence revolution. The open-source movement is the trend toward making the source code for software available to developers and users so that anyone can modify it and, theoretically, improve it. Examples of open-source software include the Linux operating system, the Mozilla Firefox browser, and the Android mobile platform.

The battle for the future of computing is a battle to bring artificial intelligence to the mainstream – and Google is quietly overhauling a machine learning tool used to improve some of its most popular services including Google Translate and Google Photos. TensorFlow can be used to help teach computers how to process data in ways similar to how the human brain handles information. It is also open source, meaning Google has published and shared the code online so that external developers can use and improve it. The latest version, released by Google on Wednesday, adds a feature many TensorFlow users have asked for since the tool made its public debut in late 2015: the ability to operate on multiple devices. Instead of being limited by the processing capabilities of a single computer, it can use distributed networks to handle more complicated tasks – as if TensorFlow will now be able to use many brain cells instead of being confined to just one.

The battle for the future of computing is a battle to bring artificial intelligence to the mainstream – and Google is quietly overhauling a machine learning tool used to improve some of its most popular services including Google Translate and Google Photos. TensorFlow can be used to help teach computers how to process data in ways similar to how the human brain handles information. It is also open source, meaning Google has published and shared the code online so that external developers can use and improve it. The latest version, released by Google on Wednesday, adds a feature many TensorFlow users have asked for since the tool made its public debut in late 2015: the ability to operate on multiple devices. Instead of being limited by the processing capabilities of a single computer, it can use distributed networks to handle more complicated tasks – as if TensorFlow will now be able to use many brain cells instead of being confined to just one.