Even during an actual pandemic, Flynn's focus struck many Oregonians as far-fetched and foreign. Perhaps unsurprisingly, he ended up losing the 2022 primary to the more politically experienced Democrat, Andrea Salinas. But despite Flynn's lackluster showing, he made history as effective altruism's first political candidate to run for office. Since its birth in the late 2000s, effective altruism has aimed to answer the question "How can those with means have the most impact on the world in a quantifiable way?"--and supplied clear methodologies for calculating the answer. Directing money to organizations that use evidence-based approaches is the one technique EA is most known for.

Back in 1982, computers meant one of two things in the popular imagination. Either they were room-sized machines used by the military-industrial complex to crunch data on stuff like nuclear wars and stock markets, or they were fridge-sized arcade games such as Space Invaders and Pac-Man. Kraftwerk were singing about home computers, but if you owned one at all, it was probably a Sinclair ZX81, which was only marginally more sophisticated than a calculator. And yet, that summer, cinemagoers were catapulted into the digital future. Few appreciated it at the time but with 40 years' hindsight, Steven Lisberger's sci-fi adventure Tron was the shape of things to come: in cinema, in real life, and in virtual life.

A British artificial intelligence (AI) company has recreated Hollywood actor Val Kilmer's voice – with amazingly realistic results. London-based firm Sonantic used the actor's voice recordings from throughout his career, which were fed to their AI to create the lifelike yet artificial mock-up. Film producers could potentially use the tool – described as'Photoshop for voice' – for voiceovers if they have a role in mind that would be suited to Kilmer's tones. Kilmer, whose career has spanned nearly four decades, has starred in blockbusters such as Top Gun, Willow, The Doors, Tombstone and Batman Forever. But after undergoing a tracheotomy in 2014 as part of his treatment for throat cancer, Kilmer's voice is now barely recognisable.

Jennifer Flynn had a problem. Shortly after joining LeadCrunch as a senior data scientist, she wanted to push out one small update of the company's software, which uses machine learning to find sales leads for its business customers. The data science team consisted of just five engineers, including her. That simple update took days and required help from the company's product development team, too. "It wasn't tenable," Flynn said, now LeadCrunch's principal data scientist.

Hewlett Packard Enterprise Tuesday unveiled a breakthrough cloud-based machine learning platform that slashes the time it takes to do custom sales proposals from 45 days to just 45 seconds, said HPE Storage Senior Vice President and General Manager Tom Black. Black--the hard-charging leader of HPE's storage business who conceived of the new cloud-based machine learning platform--said the Software Defined Opportunity Engine (SDOE) quickly analyzes a customer's IT environment and delivers the optimal IT solution. Specifically, SDOE analyzes a customer's IT environment, runs it through a cloud-based data lake of 1,250 trillion data points and provides the optimal solution scenario. "This is a massive productivity increase for partners looking to get to the sales close meeting and get the PO [purchase order]," said Black. "When you partner with HPE, we help you go fast. We help you increase your revenue. We help you increase the velocity of your growth and increase your customer relevancy in a way that our competitors currently do not have the ability to do. Sales productivity goes up substantially with the SDOE. What used to take 45 days can now be done in 45 seconds."

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Gray Eagle drones were armed with HELLFIRE missiles and GBU-69 glide bombs, 155mm artillery weapons fired rounds 60km (37.3 miles) to destroy SA-22 enemy air defenses and armored ground combat vehicles directly hit multiple T-72 tanks during the Army's Project Convergence 2020 at Yuma Proving Grounds, Ariz. The real story, however, according to senior Army leaders attending the service's transformational combat experiment, was about data sharing, networked targeting and a cutting edge AI system called FIRESTORM. "The bullet flying through the air and exploding is interesting, but that is not what is compelling about Project Convergence. It is everything that happens before the trigger is pulled. We did not come out here for a precision-fires exercise, what we came out here to do is increase the speed of information between sensing the target and passing that information to the effector," Brig.

Amazon calculates a product's star ratings based on a machine learned model instead of a raw data average. The model takes into account factors including the age of a rating, whether the ratings are from verified purchasers, and factors that establish reviewer trustworthiness.

Artificial Intelligence and Machine Learning are increasingly seen as key technologies for buildin g more decentralised and resilient energy grids, but researchers must consider the ethical and social implications of their use E nergy grids are undergoing rapid changes, requiring new ways both to process the large amounts of data generated from the power system, but also - increasingly - to take smart operational decisions [1]. On the data side, the UK and most EU countries have committed to a target of offering a smart meter to every home by 2020 [ 2 ], with similar monitoring being installed in other parts of the energy network. This has led to some to refer to a "data tsunami", requiri ng development of new machine learning techniques to deal with the e nsuing challenge of extracting useful information from this data - often in real time. Another trend is the use of AI techniques (such as those from multi - agent systems, computational gam e theory and decision making under uncertainty) to take autonomous allocation and control decisions. This is driven increasingly by the moves towards more decentralised energy systems, where prosumers (consumers with own micro - generation and storage) can g enerate and source their own electricity through peer - to - peer (P2P) trading in local energy markets and community energy schemes.

Imagine a scene, set in the future, where a child in Burning Man–style punk clothing is standing in front of a yurt powered by solar panels. There weren't many books with scenes like that in 2014, when Sarena Ulibarri, an editor, first grew interested in a genre of science fiction that imagines a renewable and sustainable future. Welcome to solarpunk, a new genre within science fiction that is a reaction against the perceived pessimism of present-day sci-fi and hopes to bring optimistic stories about the future with the aim of encouraging people to change the present. The first book that explicitly identified as solarpunk was Solarpunk: Histórias ecológicas e fantásticas em um mundo sustentável (Solarpunk: Ecological and Fantastic Stories in a Sustainable World), a Brazilian book published in 2012. In 2014, author Adam Flynn wrote Solarpunk: Notes Toward a Manifesto.

Once upon a time if I wanted to find my way to somewhere unfamiliar, I would have pulled out a map and plotted my route. These days I just put the destination into my smartphone and let it make all the decisions. Is this a simple, practical thing to do or, by relying on increasingly smarter phones, are we allowing them to make us, day by day, a little bit dumber? I've spent the last few days at an international conference on artificial intelligence pondering just this question. We were discussing, among other things, the effect that the rise of machine intelligence is having on our brains.