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Tesla CEO Elon Musk described the electric automaker’s factories in Austin and Berlin as “money furnaces” that were losing billions of dollars because supply chain breakdowns were limiting the number of cars they can produce.

In a May 30 interview with a Tesla owners club that was just released this week, Musk said that getting the Berlin and Austin plants functional “are overwhelmingly our concerns. Everything else is a very small thing,” Musk said, but added that “it’s all gonna get fixed real fast.”

It’s not clear how much has changed in the three weeks since the interview, but last week Musk tweeted congratulations to his Berlin team for producing 1,000 cars in a week.

While electric vehicles promise a green future, the batteries that power them don’t boast the same level of sustainability.


While driving electric vehicles is a step towards a greener future, the car batteries that power them are not as sustainable. Though the battery is at the heart of any EV, most are made from lithium-ion and have a limited lifespan that starts to degrade from the first time you charge them. So what happens when they reach capacity?

The cycle of charging and discharging causes them lose energy and power. The more charge cycles a battery goes through, the faster it will degrade. Once batteries reach 70 or 80% of their capacity, which happens around either 5 to 8 years or after 100,000 miles of driving, they have to be replaced, according to Science Direct.

Due to electric vehicles’ rising popularity, it goes without saying that their battery waste will become a major issue. Experts estimate that 12 million tons of batteries will be thrown away by 2030, The Guardian reported. The conundrum that manufacturers and consumers have is that although they can be recycled, there are not enough facilities to handle them. To date, there are only four lithium-ion recycling centers in the United States (via WCNC). However, this number must grow exponentially in the next few years as Industry experts predict there will be 85 million electric vehicles on the road by 2030 (via Science Direct).

In 2009, a computer scientist then at Princeton University named Fei-Fei Li invented a data set that would change the history of artificial intelligence. Known as ImageNet, the data set included millions of labeled images that could train sophisticated machine-learning models to recognize something in a picture. The machines surpassed human recognition abilities in 2015. Soon after, Li began looking for what she called another of the “North Stars” that would give AI a different push toward true intelligence.

She found inspiration by looking back in time over 530 million years to the Cambrian explosion, when numerous land-dwelling animal species appeared for the first time. An influential theory posits that the burst of new species was driven in part by the emergence of eyes that could see the world around them for the first time. Li realized that vision in animals never occurs by itself but instead is “deeply embedded in a holistic body that needs to move, navigate, survive, manipulate and change in the rapidly changing environment,” she said. “That’s why it was very natural for me to pivot towards a more active vision [for AI].”

Today, Li’s work focuses on AI agents that don’t simply accept static images from a data set but can move around and interact with their environments in simulations of three-dimensional virtual worlds.

Cerebras Systems, maker of the world’s largest processor, has broken the record for the most complex AI model trained using a single device.

Using one CS-2 system, powered by the company’s wafer-sized chip (WSE-2), Cerebras is now able to train AI models with up to 20 billion parameters thanks to new optimizations at the software level.

The firm says the breakthrough will resolve one of the most frustrating problems for AI engineers: the need to partition large-scale models across thousands of GPUs. The result is an opportunity to drastically cut the time it takes to develop and train new models.

An autonomous vehicle is able to navigate city streets and other less-busy environments by recognizing pedestrians, other vehicles and potential obstacles through artificial intelligence. This is achieved with the help of artificial neural networks, which are trained to “see” the car’s surroundings, mimicking the human visual perception system.

But unlike humans, cars using have no memory of the past and are in a constant state of seeing the world for the first time—no matter how many times they’ve driven down a particular road before. This is particularly problematic in adverse weather conditions, when the car cannot safely rely on its sensors.

Researchers at the Cornell Ann S. Bowers College of Computing and Information Science and the College of Engineering have produced three concurrent research papers with the goal of overcoming this limitation by providing the car with the ability to create “memories” of previous experiences and use them in future navigation.

Swedish truck manufacturer Volvo Trucks has unveiled a hydrogen fuel cell truck which the company claims will have a range of up to 1,000 kilometres and a refuelling time of less than 15 minutes.

The hydrogen fuel cell truck will join other zero-emission truck options already on offer, battery-electric trucks and trucks that run on renewable fuels such as biogas.

“We have been developing this technology for some years now, and it feels great to see the first trucks successfully running on the test track,” said Roger Alm, president of Volvo Trucks.

AUSTIN, TexasTexas is planning to add enough electric vehicle charging stations throughout the state to support 1 million electric vehicles with dozens of new stations to allow for easier long-distance travel.

In a draft plan released this month, the Texas Department of Transportation broke down a five-year plan to create a network of chargers throughout the state, starting along main corridors and interstate highways before building stations in rural areas.

The plan is to have charging stations every 50 miles along most non-business interstate routes.