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Electric Vehicles coming to the market from both new and older more established car marques are driving a new wave of investment in the automotive industry. EV’s are much simpler to build than tradition internal combustion engine cars as they obviously do not require the petrol- or diesel-powered engine itself and the complicated series of connections it requires with the rest of the chassis. Also, the trend towards software-defined car ‘options’ means there is less physical variability needed between cars of the same type in the same factory.

Together, these factors mean that even the older manufacturers with hundreds of manufacturing plants between them globally have realized the need for new state of the art manufacturing lines. Automated manufacturing processes can greatly reduce the current cost of EV’s which cost more than internal combustion engine cars due to their constituent components even though they are simpler to build.

The North American robotics market set all-time records in both robots sold and value in 2022. According to a report from the Association for Advancing Automation (A3), North American companies ordered 44,196 robots valued at $2.38 billion in 2022, representing increases of 11% and 18%, respectively, over 2021, the previous record.

Much of this growth was driven by the US automotive industry which ordered 23,807 robots, +42% yoy in 2022. While orders from non-automotive industries slowed, unique applications continued to emerge in industries like food service (cooking and serving robots) and construction (dry walling robots).

The Technical University of Berlin and researchers from Google have unveiled the PaLM-E, (Pathways Language Model with Embodied), which is an advancement in human and robot interaction. They claim that it has the ability to control different robots across multiple environments, showing a level of flexibility previously unseen in robotics. PaLM-E integrates AI-powered vision and language to enable autonomous control, allowing the robot to perform a task based on human voice commands, without the need for constant retraining.

The model is able to make use of visual data to enhance its language processing capabilities, resulting in an embodied language model that is both versatile and quantitatively competent. It has been trained on a mixture of tasks across multiple robot embodiments and general vision-language tasks.

Their largest model, PaLM-E-562B, shows capabilities like “multimodal chain of thought reasoning”, over multiple images, despite being trained on only single-image prompts.

Researchers claim that the model uses “positive transfer,” which basically means it can transfer knowledge and skills learned from prior tasks to new ones, leading to higher performance than single-task robot models. In also displays ‘multimodal chain-of-thought reasoning,’ meaning it can analyse a sequence of inputs (both language and visual), as well as “multi-image inference,” where it uses multiple images as an input to make inference or predict something.

While researching the capabilities of OpenAI's artificial intelligence-enhanced text generator, a professor at the University of Pennsylvania's Wharton School found that the company's GPT-3 chatbot was able to pass a final exam for the school's Master of Business Administration program.

Professor Christian Terwiesch, said that the chatbot passed the exam with a score between a B- and B. He said the score is proof of the bot's " ability to automate some of the skills of highly compensated knowledge workers in general and specifically the knowledge workers in the jobs held by MBA graduates including analysts, managers, and consultants."

Terwiesch noted that GPT-3 did an "amazing job at basic operations management and process analysis questions including those that are based on case studies." It was also "remarkably good at modifying its answers in response to human hints," he concluded.

The experiment was conducted with the GPT-3 model, a predecessor of OpenAI's viral ChatGPT bot. The advanced capabilities of the newer, viral model have sparked debates about whether generative AI signals the end for human employees. Educators have also expressed concern that the program could inspire widespread and virtually undetectable cheating.

In November 2022, Kevin Bryan, an associate professor at the University of Toronto, tested ChatGPT's ability to write graduate-level responses and concluded that "the OpenAI chat is frankly better than the average MBA at this point." Open AI, the creators of ChatGPT, are reportedly working on a watermarking system to potentially address these concerns.

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