STEM Summer Programs for High School Students

STEM is a term that stands for science, technology, engineering and mathematics. Here is a list of some of the best STEM summer camps for high school students.

It is an 8-week paid summer research experience for high school students. This is a hands-on program for students interested in going after a career in medical research. Students will attend seminars led by the faculty and participate in discussions with peers.

It is a seven-week program located at Stony Brook University. Students will have the opportunity to participate in special workshops, tours and events free of charge. They will conclude the program producing a written research abstract and a research poster.

It is the first cost-free summer program of its kind. During this six-week program, students will dive deeper into the world of science and engineering by experiencing the entire research cycle. In this program students will attend classes conducted by famous professors and prepare written and oral presentations to present their research.

This is a six-week intensive mathematics program designed for students across the globe. Unlike common programs, it offers a great deal of independence for students to choose their own schedules and decide what they want to study. Besides learning, there is also “mandatory (强制的) fun time” built into the weekly schedule so that students are able to have non-math related activities.

Recently, Google researchers published a paper describing results from an artificial intelligence(AI) tool, called MusicLM, built to create music. It is not the first AI music tool to launch. But the examples Google provides demonstrate musical creative ability based on a limited set of descriptive words. AI shows how complex computer systems have been trained to behave in human-like ways. Google engineers explain the MusicLM system this way.

First, a user comes up with a word or words that describe the kind of music they want the tool to create. For example, a user could enter this short phrase into the system: “a continuous calming violin backed by a soft guitar sound.”The descriptions entered can include different music styles, instruments or other existing sounds. Several different music examples produced by MusicLM were published online. Some of the generated music came from just one-or-two-word descriptions,such as “jazz”, or “techno”. The system created other examples from more detailed descriptions containing whole sentences. In the resulting recording, the music seems to keep very close to the description. The team said that the more detailed the description is, the better the system can attempt to produce it.

In addition to generating new music from written descriptions, the team said the system can also create examples based on a person’s own singing, whistling or playing an instrument. The researchers said the tool “produces high-quality music...over several minutes, while being faithful to the text conditioning signal”.

Although MusicLM hasn’t been released for public use, Google announced it was releasing a “high-quality dataset” of more than 5,500 music-writing pairs prepared by professional musicians called MusicCaps. The researchers took that step to assist in the development of other AI music generators.

The MusicLM researchers said they believe they have designed a new tool to help anyone quickly and easily create high-quality music selections. However, the team said it also recognizes some risks linked to the machine learning process.

In habitats across the planet, animals periodically drop everything to walk, fly or swim to a new place. Wildlife such as whales and geese learn migration paths by following their parents. Others, including small songbirds, gain the distance and direction of their migration within their genetic code. And some animals use a combination of genetics and culture to guide their migration.

Another group of migrators does not quite fit either model, and researchers have only recently started to figure out how they find their way. Take the Cory’s shearwater, an oceangoing sea bird that migrates over the Atlantic every year. The young do not migrate with their parents, so culture cannot explain their journeys. And the exact paths vary wildly from individual to individual, making genetics equally unlikely.

Cory’s shearwaters are long-lived, rarely producing young successfully before age nine. This leaves an opening for learning and practice to develop their migration patterns. Researchers call this the “exploration-refinement”, and until now it has been hypothetical（假设的）because of difficulties in tracking migratory animals’ movements.

But a team of researchers has done that by attaching small geolocators to more than 150 of the birds aged four to nine. They found that younger birds traveled longer distances, for longer periods, and had more diverse paths than older birds.“We finally have evidence of the ‘exploration-refinement’ for migratory birds,” says Letizia Campioni, who led the study. Younger Cory’s shearwaters are able to fly just as fast as, the adults — but they do not, suggesting that the young do more exploring, which gradually fades as they mature and settle into a preferred course.

Although it may seem less efficient than other strategies, “exploration-refinement could be beneficial to birds and other organisms in a rapidly changing world due to unpredictable man-made changes,” says Barbara Frei. “It might be safer to repeat a behavior that was recently successful than to rely on patterns that were perfected long ago but might no longer be safe.”