KW 34: Energy transition: AI to quickly find critical metals, Tesla is developing an AI training system called Dojo, Sensors, infrared and AI: How cars automatically stop in front of pedestrians


Energy transition: AI to quickly find critical metals: US exploration company KoBold Metals wants to use AI to meet the demand for metals and minerals such as lithium, cobalt, graphite, and nickel used in electric vehicle batteries and the power grid. Mining companies are increasingly using AI to analyze parallel datasets from geology, geochemistry and geophysics to speed up the discovery process.

Tesla is developing an AI training system called Dojo: Tesla has released plans for an artificial intelligence training system dubbed Dojo. The in-house designed device would tackle the “insatiable demand for speed as well as capacity for neural-network training,” Tesla’s Ganesh Venkataramanan said. The project aims to “achieve best AI training performance” and “enable larger and more complex neural net models,” while still being power and cost-efficient. Dojo would be powered by a distributed computing architecture, which would feature a large compute plane and facilitate high bandwidth and low latencies. The device would include several layers, including a chip, the system, a compute cluster and additional software.

Sensors, infrared and AI: How cars automatically stop in front of pedestrians: „Pedestrian detection with emergency braking function“ is the name of a system that automatically brakes if it detects a pedestrian and the driver fails to brake in time. The system is now available in almost all new vehicles. Many manufacturers combine this feature with other advances, such as systems that recognize objects on the road, such as a cyclist or a deer, and help the driver to achieve the correct steering angle to avoid hitting them.

– Advertisement –
Blockchain – Ticker – With our weekly newsletter we provide you with the most important developments in blockchain technology and scene.

Scientists warn of racism: AI determines skin color from X-ray images: After researchers fed X-rays of various patients to an artificial intelligence, the system was able to determine the ethnicity of the patients, even though no other data was provided. The research team itself could not see why the AI was able to determine the patients‘ ethnicity. The team wants this to be understood as a warning to the scientific community. It must always be considered that self-learning algorithms could be used in medicine to treat people of different skin color differently.

AI alone is not a silver bullet: Artificial intelligence is very helpful in the fight against hackers – but only with the help of human intelligence. A combination of continuously learning algorithms and well-trained experts makes it possible to detect and respond to new threats from hackers and other cyberattacks in near real time. And even though AI solutions can process information in nanoseconds and derive valuable suggestions from it, not all information is truly relevant. The systems therefore need analyst input to understand the context of a security incident.

Tesla is working on humanoid robots: Tesla CEO Elon Musk said the company expects to build a humanoid robot with artificial intelligence next year that would complete simple physical tasks most workers detest. Musk, who has spoken repeatedly about his fears of runaway artificial intelligence, said the Tesla Bot is “intended to be friendly,” but that the company is designing the machine at a “mechanical level” so that “you can run away from it, and most likely overpower it.”,

Leipzig: Mega AI computing power made in Saxony
Research: State promotes AI research project in electrical manufacturing
EU regulates AI: What insurance companies need to be aware of
Research: China loses leading AI minds
Rules: Who says what’s fair?

– Advertisement –
IoT – Ticker -The physical world meets the digital one. Internet of Things as an interface that revolutionizes both the industry and everyday life. Get a weekly update from the world of „Internet of Things“.


A machine-learning researcher at the University of Cambridge and his colleagues zoomed in on deep-learning models for diagnosing COVID-19 and predicting patient risk from medical images, such as chest x-rays and chest computer tomography (CT) scans. They looked at 415 published tools and concluded that none were fit for clinical use.


Using AI to detect and treat diseases sooner: Scientists at the Chair of Optoelectronics at Dresden University of Technology have succeeded for the first time in developing a biocompatible implantable AI platform that classifies healthy and pathological patterns in biological signals such as heartbeats in real time and thus detects pathological changes even without medical supervision. In the future, diagnostic patient data could be analyzed using machine learning so that diseases can be found based on subtle changes. For example, this could be used to monitor cardiac arrhythmias or complications after surgeries and report them to doctors and patients via smartphone, enabling rapid medical assistance.

Study: Young people feel overwhelmed by a data-driven world: A study shows that many young people in Europe have only a rudimentary knowledge of how artificial intelligence (AI) applications collect, analyze and process data on the web. Emilija Gagrcin conducted an international investigation with six other researchers into the attitudes of young people in Europe toward the use of AI. They surveyed 3,000 young adults aged 18 to 30 in Germany, France, Greece, Italy, Poland and Sweden. 70 percent fear that their data could be misused online and shared unlawfully between companies. At the same time, 40 percent believe that users have little influence over what happens to their data online. „Our findings underscore that young people underestimate the reach of modern data collection practices,“ says co-author Nadja Schaetz. „As a result, they also lack the knowledge to properly assess the consequences and potential dangers of datafication.“


Mimicking the human brain with magnetic nanodisks: In neuromorphic computing, researchers are trying to mimic the dynamic processing of signals from the human brain. To ensure that the system of neurons communicating via synapses also works in AI, researchers at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) have now discovered an alternative method: Nano-disks show similar activity patterns of neurons in the brain communicating with each other through oscillating magnetic vortices. The artificial synapses and neurons are virtually capable of sparking on multiple channels. The researchers see great potential for a wide range of applications. Magnetic vortex technologies are used, for example, in commercial magnetic storage devices and for new wireless technologies.


„In medicine, AI technologies have great potential to improve patient care.“
BVMed digital expert Natalie Gladkov warns against overregulating AI applications in the field of medicine and healthcare.


Val Kilmer’s voice was re-created by AI after throat cancer took it away: Hollywood actor Val Kilmer lost his natural voice after a surgery for throat cancer in 2015. Five years after Kilmer’s surgery, his representatives contacted Sonantic, a UK-based software firm that clones voices for actors and studios, to digitally restore his lost voice. A team cleaned up the available audio to remove as much noise as possible and attempted to build a model for Kilmer’s voice with only about one-tenth of the audio normally required. When the results were subpar, Sonantic developed new algorithms to work with less data and wound up creating over 40 different models of Kilmer’s voice. Kilmer’s voice can be controlled by a desktop application that allows him to type whatever he wants the model to say and then fine tune aspects of the delivery like pitch and pacing.,

Newsletter subscription

Subscribe to our free weekly newsletter for a compact overview of Artificial Intelligence topics:


More digital news briefings

Our political briefings