Lifeboat Foundation

The U.K. government has some jolly sensible recommendations for making the most of artificial intelligence.

Are AI aliens watching Earth? An immortal machine civilization could already exist and may be BILLIONS of years old, leading expert claims…

Artificial intelligence could already exist elsewhere in the universe and may have been around for billions of years, according to a leading expert.

Continue reading “‘Postbiological’ alien civilisation that survives using AI could exist” »

AI machines injected into our bodies could give us superhuman strength and let us control gadgets using the power of THOUGHT within 20 years…

Humans could be ‘melded’ to machines, giving us huge advancements in brain power, experts told peers at the House of Lords Artificial Intelligence Committee (pictured, stock)

Continue reading “AI nano-machines could be injected into our brains within 20 years” »

Interesting article on how Google’s mismanagement took a wrecking ball to the robotics industry. Most notably almost ruining Boston Dynamics that thankfully managed to get away to Soft Banks.

Its scattered, ambiguous, frequently abandoned objectives for its string of big acquisitions have hurt the whole field.

You could drive past and never see the only farm in San Carlos, California. The tiny city of 30,000 that sits between San Francisco and Silicon Valley has all the charms of suburbia—sprawling office parks and single-story homes—but doesn’t seem a likely suspect for agriculture.

The farm, run by startup Iron Ox, is nestled between three stonemasons and a plumber in a nondescript office park building; there’s no greenhouse, no rows of freshly-tilled soil, or tractor parked outside. Only peeking in the large bay door reveals the building’s tenants: a few hundred plants and two brightly-colored robot farmers.

Iron Ox looks a lot like a tech company. One of its co-founder is an ex-Google engineer and it raised $1.5 million in pre-seed venture capital from Y Combinator, Pathbreaker, and Cherubic Ventures in April 2016. Instead of fake food, or plant-based meat meals, or even a food delivery service tethered to an app, Iron Ox is reinventing farming, raising real, not faux, food. Think hydroponically raised lettuce and basil, like what you’d get at an ordinary farmers market.

The BMW i8 is already one of the most futuristic-looking cars on the road, but it’s about to get more innovative inside, too. BMW has just announced a brand-new tech collaboration with IBM, which will see the tech giant’s Watson AI tested in four of BMW’s hybrid sports cars. The project will see BMW engineers and IBM researchers work together in Germany, as both IBM and BMW have research facilities in Munich.

The project aims to make driving assistance and information more personalised and intuitive – and Watson looks to be the perfect candidate for the job. IBM’s powerful AI should make the car’s existing systems much easier to use, and BMW has already given a few examples of how it could work. The i8’s manual will be by Watson, so drivers will be able to enquire about vehicle information in natural language, rather than select phrases. In the same way, BMW and IBM want the Watson-fitted i8 to provide updates on everything from fuel levels to traffic updates in a simple, easy way.

However, Watson’s machine learning will have another benefit, too: personalisation. By gradually learning the routes, language and needs of a driver, Watson will be able to deliver the right amount of information almost before it’s needed.

Continue reading “BMW is putting IBM’s Watson AI in the passenger seat” »

The market is definitely there. But, it needs to be able to do a minimum amount of practical things, in about this order: 1. it needs to be able to cook even the most basic of meals, being unable to cook for themselves is usually the main reason someone has to go into a nursing home; 2. being able to clean your average kitchen and bathroom; 3. being able to do basic yard tasks, operating a lawnmower and a snowblower. Those would be the most important, after those get mastered have it equipped to do more niche tasks and entertainment features.

As to when, we have clumsy humanoid robots right now, and AI will supposedly reach human level around 2029. It will just be a task of merging those two between now and then, and getting that robot down to a reasonable cost, which i think would be in the neighborhood of a brand new SUV.

As artificial intelligence advances, we humans will form relationships with our robot helpers and caregivers.

Continue reading “Your future companion in your old age could be a robot” »

Click on photo to start video.

A knock off of Boston Dynamics dog robot, but interesting to see. I’d be curious how loud it is, you know it’s usually pretty loud when there’s no audio.

#AI The Machine Learning 4 SETI Code Challenge (ML4SETI), created by the SETI Institute and IBM, was completed on July 31st 2017. Nearly 75 participants, with a wide range of backgrounds from industry and academia, worked in teams on the project. The top team achieved a signal classification accuracy of 95%. The code challenge was sponsored by IBM, Nimbix Cloud, Skymind, Galvanize, and The SETI League.

The Machine Learning 4 SETI Code Challenge (ML4SETI), created by the SETI Institute and IBM, was completed on July 31st 2017. Nearly 75 participants, with a wide range of backgrounds from industry and academia, worked in teams on the project. The top team achieved a signal classification accuracy of 95%. The code challenge was sponsored by IBM, Nimbix Cloud, Skymind, Galvanize, and The SETI League.

The ML4SETI project challenged participants to build a machine-learning model to classify different signal types observed in radio-telescope data for the search for extra-terrestrial intelligence (SETI). Seven classes of signals were simulated (and thus, labeled), with which citizen scientists trained their models. We then measured the performance of these models with tests sets in order to determine a winner of the code challenge. The results were remarkably accurate signal classification models. The models from the top teams, using deep learning techniques, attained nearly 95% accuracy in signals from the test set, which included some signals with very low amplitudes. These models may soon be used in daily SETI radio signal research.

Continue reading “Using Artificial Intelligence to Search for Extraterrestrial Intelligence” »