Artificial Intelligence News - Page 3
The 749 gross ton container ship completed a 491-mile (790 kilometers) journey from Tokyo Bay to Ise Bay, Suzaka.
The vessel, called the Suzaka, was powered by Orca AI, and traveled without any human intervention for 99% of the 40-hour trip. Suzaka was chosen by the Designing the Future of Full Autonomous Ships (DFFAS) project. Orca AI has previously conducted tests with its Automatic Ship Target Recognition System on Nippon Yusen Kabushiki Kaisha (NYK Line) ships.
The voyage involved the Suzaka traversing some of the most congested waters in the world in Tokyo Bay before arriving at the port of Tsumatsusaka in the Ise Bay. On its way, the ship autonomously performed 107 collision avoidance maneuvers unassisted, avoiding between 400 and 500 other vessels in the water during its outbound trip alone.
A paper on the artificial intelligence (AI) traffic system titled "Fully-Autonomous, Vision-based Traffic Signal Control: from Simulation to Reality" is being presented at the Proceedings of the 21st International Conference on Autonomous Agents and Multi-agent Systems (AAMAS 2022).
Researchers from Aston University have developed an AI system capable of managing traffic flow through intersections with traffic lights. The system uses deep reinforcement learning, allowing it to understand when it isn't performing well and adjust accordingly, and continue to improve when making progress.
The current main form of traffic light automation uses manually-designed phase transitions triggered by cars passing over magnetic induction loops embedded in the road. The AI system uses this data and is fed with live camera footage to react to traffic conditions more quickly and adjust traffic lights accordingly.
A man has engineered artificial intelligence into a common household item which later turned on him to seemingly kill him.
Lucas Rizzotto is a YouTuber that runs his YouTube channel called Lucas Builds The Future, and in one of his recent videos he engineered and documented the process of recreating an imaginary childhood friend through artificial intelligence he programmed into a microwave. Rizzotto purchased a new microwave and implemented text-based artificial intelligence "GPT-3", which was developed by OpenAI, an AI research company founded by Elon Musk.
The GPT-3 artificial intelligence has been designed to interpret and mimic human language, and with its received data, it can form original sentences when given the correct prompt. Notably, the GPT-3 has already been fed a large swath of data from news articles, Wikipedia pages, and more. So far, the AI has already proven capable of creating poetry, news posts, and entire conversations between fictional characters.
OpenAI has recently released the successor to its previous AI system, DALL-E 1.
The DALL-E 2 system is a generative adversarial network (GAN), which according to the OpenAI website, "can create realistic images and art from a description in natural language." Using short, simple descriptions, DALL-E 2 can create not just one but a variety of slightly different images that match the provided caption.
DALL-E 2 can also edit images to add or remove elements while taking the relevant shadows, reflections, and textures into account in photorealistic images. On the OpenAI website, a number of interactive elements demonstrate this function in action, as well as the AI's ability to illustrate numerous novel and bizarre concepts to produce rather excellent artworks.
Hackers have attempted to spread disinformation by deep-faking Ukrainian president Volodymyr Zelenskyy.
The video shows Zelenskyy requesting his country's army to surrender to Russian forces and was displayed on the website of a Ukrainian television channel, Ukraine 24 after it suffered a hack. A transcript of the video was also displayed briefly on the channel's televised broadcast. The video is not among the most convincing deep-fakes out there but marks one of the first uses of the disinformation tactic in the current conflict.
"The running line of the "Ukraine 24" TV channel and the "Today" website were hacked by enemy hackers and broadcast Zelensky's message about alleged "capitulation" THIS IS FAKE! FAKE! Friends, we have repeatedly warned about this. No one is going to give up. Especially, in the circumstances when the Russian army suffers losses in battles with the Ukrainian army!" Ukraine 24 wrote in a Facebook post.
A study on the deep learning approach has been published in the journal Nature.
DeepMind Technologies, based in Britain, is a subsidiary of Alphabet Inc., which also owns Google. It has recently used its DeepMind artificial intelligence (AI) to control a tokamak, a magnetic confinement device used for nuclear fusion reactor experiments involving plasma. The plasmas in a tokamak are highly unstable, complicating their experiments and requiring careful control.
A tokamak control system has to coordinate all of its nineteen magnetic coils and adjust their voltage thousands of times per second to stop the plasma from touching the vessel's walls, which would result in heat loss and potential damage. DeepMind and the Swiss Plasma Center at EPFL collaborated to create the first deep reinforcement learning (RL) system to control these processes for the Variable Configuration Tokamak (TCV) in Lausanne, Switzerland.
Well, the moment has come... our AI "xenobot" self-replicating robots are going to rule us all and we won't be able to stop it.
But seriously, researchers have just announced they've created tiny living robots capable of self-replicating themselves inside of a dish by pushing loose cells together. They're called "xenobots" and they're made from frog cells, representing the first time a multicellular organism has found a way to reproduce in this particular way.
The cells collect together in clumps where they'll form a sphere that would have around 3000 cells, taking around 5 days to happen. Each individual clump is around half a millimeter wide and is covered in a minuscule hair-like structure, which sounds weird but the hair-like structure acts like flexible oars in water... they move the xenobots forwards in corkscrew paths, explains Joshua Bongard, senior author and computer scientist at the University of Vermont.
My name is Ganesh [Venkataramanan, Tesla director and Dojo boss] and I lead Dojo. It's an honor to present this project on behalf of the multi-disciplinary Tesla team that is working on this project.
As you saw from Milan, there's an insatiable demand for speed, actualized capacity for neural network training -- and Elon prefetched this, and a few years back he asked us to design a super-fast training computer, and that's how we started Project Dojo.
Our goal is to achieve best AI training performance and support all these larger, more complex models that Andre's team are dreaming of and be power-efficient, and cost-effective at the same time. So we thought about how to build this, and we came up with a Distributed Compute Architecture.
The Pentagon is using an experimental artificial intelligence program that allows it to see "days in advance" and look into the future.
The new experimental program is called the Global Information Dominance Experiments (GIDE), and it combines artificial intelligence with cloud computing and large data pools. The newest version of GIDE is GIDE 3, and according to General Glen VanHerck, the commander of the US Northern Command, the idea behind the new program is to "achieve information dominance" and "decision making superiority".
VanHerck stated to the press conference that the Pentagon is currently living in a "reactive environment" where it will respond to rival nations' actions. Now, VanHerck says, "What we've seen is the ability to get way further what I call left of being reactive to actually being proactive. And I'm talking not minutes and hours, I'm talking days."
A bipedal robot named Cassie has achieved what no other robot has achieved -- successfully completing a 5K run on a single charge.
Oregon State University engineers have managed to teach Cassie to run using a deep reinforcement learning algorithm. The project is led by Agility Robotics who is attempting to combine robot controls with machine learning tools, and as a result of the engineers' efforts, we are presented with Cassie. The team of engineers said that Cassie taught itself to upright, which meant that it didn't require any tethering device to stabilize it as it ran.
Cassie ran around the Oregon State University campus for five kilometers or about 3.11 miles, and during the test, the running robot fell down twice, once due to a computer overheating and a second time when it when around a corner too fast. Cassie completed the five-kilometer run in 53 minutes, 3 seconds, and according to Jeremy Dao, a project team member, they were able to "reach the limits of the hardware and show what it can do."