Introduction to Drama Exams

Our exams inspire and enable learners across the globe to be confident communicators. Exams are open to anyone looking to gain confidence and experience in speech, communication and performance. There are no age restrictions. As one of the UK’s oldest and most respected drama schools and awarding organizations, we examine over 100,000

candidates and deliver exams both online and in person in many countries across the globe.

Now we are pleased to offer free, online “Introduction to Examinations” information session. Booking is now opening for events until Summer 2024.

The 1.5-hour session will begin with an Introduction to Examinations, their history and the format of assessment. Work will then focus on the subjects available to take, and will end with a Q&A phase where participants will be invited to write in their questions to the host organizer.

If you have any questions regarding this, please email examscourses@lamda.ac.uk and we will be happy to help. Looking forward to seeing you online at this event.

Cafeterias have been filled with challenges — right from planning, purchasing, and preparing, to reducing waste, staying on budget, managing goods, and training staff. Through the tedious process, restaurateurs lacked a unified platform for efficient management. To bring consistency to the unorganised catering (餐饮) industry, childhood friends Arjun Subramanian and Raj Jain, who shared a passion for innovation, decided to partner in 2019 to explore opportunities in the cafeteria industry.

In May 2020, they co-founded Platos, a one-stop solution for restaurants with a custom technology kit to streamline all aspects of cafeteria management. The company offers end-to-end cafeteria management, staff selection and food trials to ensure smooth operations and consistent service. “We believe startups solve real problems and Platos is our shot at making daily workplace food enjoyable again. We aim to simplify the dining experience,   providing a convenient and efficient solution that benefits both restaurateurs and customers and creating a connected ecosystem,” says Subramanian, CEO and co-founder.

Platos guarantees that a technology-driven cafeteria allows customers to order, pay, pick up, and provide ratings and feedback. It also offers goods and menu management to effectively perform daily operations. Additionally, its applications connect all shareholders for a smart cafeteria experience. “We help businesses that are into catering on condition that they have access to an industrial kitchen setup where they’re making food according to certain standards,” Jain states.

Since the beginning, Platos claims to have transformed 45 cafeterias across eight cities in the country. Currently, it has over 45,000 monthly users placing more than 200,000 orders. Despite facing challenges in launching cafeterias across major cities in the initial stages, Platos has experienced a 15% increase in its month-over-month profits.

As for future plans, the startup is looking to raise $1 million from investors as strategic partners, bringing in capital, expertise, and networks. “Finding the right lead investor is the compass that points your startup toward success,” Subramanian says.

With a brain the size of a pinhead, insects possess a great sense of direction. They manage to locate themselves and move through small openings. How do they do this with their limited brain power? Understanding the inner workings of an insect’s brain can help us in our search towards energy-efficient computing, physicist Elisabetta Chicca of the University of Groningen shows with her most recent result: a robot that acts like an insect.

It’s not easy to make use of the images that come in through your eyes when deciding what your feet or wings should do. A key aspect here is the apparent motion of things as you move. “Like when you're on a train,” Chicca explains. “The trees nearby appear to move faster than the houses far away.” Insects use this information to infer how far away things are. This works well when moving in a straight line, but reality is not that simple. To keep things manageable for their limited brain power, they adjust their behaviour: they fly in a straight line, make a turn, then make another straight line.

In search of the neural mechanism (神经机制) that drives insect behaviour, PhD student Thorben Schoepe developed a model of its neuronal activity and a small robot that uses this model to find the position. His model is based on one main principle: always head towards the area with the least apparent motion. He had his robot drive through a long passage consisting of two walls and the robot centred in the middle of the passage, as insects tend to do. In other virtual environments, such as a space with small openings, his model also showed similar behaviour to insects.

The fact that a robot can find its position in a realistic environment is not new. Rather, the model gives insight into how insects do the job, and how they manage to do things so efficiently. In a similar way, you could make computers more efficient.

In the future, Chicca hopes to apply this specific insect behaviour to a chip as well. “Instead of using a general-purpose computer with all its possibilities, you can build specific hardware; a tiny chip that does the job, keeping things much smaller and energy-efficient.” She comments.

With the help from an artificial language (AL) model, MIT neuroscientists have discovered what kind of sentences are most likely to fire up the brain’s key language processing centers. The new study reveals that sentences that are more complex, because of either unusual grammar or unexpected meaning, generate stronger responses in these language processing centers. Sentences that are very straightforward barely engage these regions, and meaningless orders of words don’t do much for them either.

In this study, the researchers focused on language-processing regions found in the left hemisphere (半球) of the brain. By collecting a set of 1,000 sentences from various sources, the researchers measured the brain activity of participants using functional magnetic resonance imaging (fMRI) while they read the sentences. The same sentences were also fed into a large language model, similar to ChatGPT, to measure the model’s activation patterns. Once the researchers had all of those data, they trained the model to predict how the human language network would respond to any new sentence based on how the artificial language network responded to these 1,000 sentences.

The researchers then used the model to determine 500 new sentences that would drive highest brain activity and sentences that would make the brain less active, and their findings were confirmed in subsequent human participants. To understand why certain sentences generate stronger brain responses, the model examined the sentences based on 11 different language characteristics. The analysis revealed that sentences that were more surprising resulted in greater brain activity. Another linguistic (语言的) aspect that correlated with the brain’s language network responses was the complexity of the sentences, which was determined by how well they followed English grammar rules and bow logically they linked with each other.

The researchers now plan to see if they can extend these findings in speakers of languages other than English. They also hope to explore what type of stimuli may activate language processing regions in the brain’s right hemisphere.