The video of the aftermath of the Reading Festival shows the extent of the clear-up needed.

The Mohajer-6 has the capability to carry out surveillance and reconnaissance missions, and the Shahed series is considered among the most capable of Iran's military drones, according to comments made by the Iranian military to local news media. Iran is a pioneer in drone technology, with at least four decades of design and manufacturing experience, and it has been providing combat drones to military groups and proxy militia in Yemen, Iraq, Syria, Lebanon and Gaza. Officials in Israel, the United States and some Sunni Arab countries like Saudi Arabia have said they are increasingly concerned that Iran's advancing drone technology could destabilize the region and empower militias backed by Iran. In the shadow war between Iran and Israel, Iranian drones have been involved in attacks on ships and have targeted U.S. military bases in Iraq and Syria. Israel has also attacked a secret facility in western Iran where hundreds of drones were believed to have been stored.

When you can't rely on facial recognition, you look beyond the obvious. When you can't rely on facial recognition, you look beyond the obvious.

"While technology analysis is still new, it can provide some of the needed foundations for technology as a field of its own and answer such questions as'Can AI invent?.'" Not long ago, Dr. Stephen Thaler, a member of the scientific community, began claiming that his artificial intelligence (AI) machine, DABUS, was a bona fide inventor. The outcome so far has been that the claim has been rejected in most jurisdictions. A notable exception is South Africa, which accepted Thaler's patent application under "Formalities Examination" with DABUS as named inventor. The acceptance of the patent in South Africa and the evolution of the legal field opens the possibility of further assertions and challenges with respect to AI inventorship.

With the uptake of electric vehicles (EVs) increasing across the automotive market, there is a need to ensure optimized function and reliability of the battery that is powering the vehicle. Across many industries and markets, lithium-ion (Li-ion) batteries are crucial components of devices and machinery, including smartphones, solar power storage, and power supplies. Thus, maintaining good battery health is absolutely vital in today's world. Now, a group of researchers from the University of Cambridge has recently developed a new algorithm that uses machine learning to help preserve good battery health in EVs. The algorithm is able to use pattern recognition and predictability models to see how various driving styles influence the performance of the vehicle's battery.

Earlier this year, Google unveiled AI Test Kitchen -- an Android app that lets users talk to one of its most advanced AI chatbots, LaMDA 2. Today, the company is opening up registrations for early access. You can sign up here, and Google says it will soon be letting people download the app and start chatting. It's interesting, considering that Meta made an almost identical move just earlier this month, opening up its latest and greatest AI chatbot, BlenderBot 3, for public consumption. Of course, people quickly found that they could get BlenderBot to say creepy or untruthful things (or even criticize the bot's nominal boss, Mark Zuckerberg), but that's kind of the whole point of releasing these demos. As Mary Williamson, a research engineering manager at Facebook AI Research (FAIR), told me at the beginning of the month, many companies don't like to test their chatbots in the wild because what they say will be damaging to the company, as with Microsoft's Tay.

Last year during Tesla's AI Day, the automaker unveiled its Dojo supercomputer. At the time, Tesla claimed the supercomputer was the world's most powerful training machine and would help the automaker teach its vehicles how to drive without any inputs from a human driver. While Tesla officially announced the system last year, the automaker provided more information on its Dojo supercomputer this year at the Hot Chips conference. Dojo's job is to take all of the video Tesla gathers from its fleet of Tesla cars on the road today and process it to learn how cars drive in the real world. The training process is what represents the base for Tesla's Full Self Driving System.

A Chinese language model performs better than OpenAI's GPT-3 and Google's PaLM. Huawei shows a Codex alternative. Large AI models for language, code, and images play a central role in the current proliferation of artificial intelligence. Researchers at Stanford University therefore even want to call such models "foundation models." The pioneer in the development of very large AI models is the U.S. AI company OpenAI, whose GPT-3 language model first demonstrated the usefulness of such AI systems.

Scientists and engineers are constantly developing new materials with unique properties that can be used for 3D printing, but figuring out howto print with these materials can be a complex, costly conundrum. Often, an expert operator must use manual trial-and-error -- possibly making thousands of prints -- to determine ideal parameters that consistently print a new material effectively. These parameters include printing speed and how much material the printer deposits. MIT researchers have now used artificial intelligence to streamline this procedure. They developed a machine-learning system that uses computer vision to watch the manufacturing process and then correct errors in how it handles the material in real-time.

Tech fears tend to follow a 4-step cycle fueled by politicians, scientists, and media, according to Jason Feifer's new book, Build For Tomorrow.