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MIT Teaches Kids How To Build AI Models
- Written by Kiara Fabbri Former Tech News Writer
- Fact-Checked by Justyn Newman Former Lead Cybersecurity Editor
In a Rush? Here are the Quick Facts!
- Little Language Models helps kids learn AI by building small-scale models themselves.
- Program uses dice to teach probabilistic thinking, a core concept in AI.
- Demonstrates AI bias by simulating diverse datasets and adjusting probabilities.
In a press release published today, MIT unveiled a new educational tool developed by MIT researchers Manuj and Shruti Dhariwal.
Their application, Little Language Models, invites children to explore how AI works by allowing them to create simplified, small-scale models. This hands-on approach provides an alternative to the often abstract or lecture-based introductions to AI, making concepts accessible through interactive learning.
The program starts by using a pair of dice to introduce probabilistic thinking—one of the foundational concepts behind language models (LLMs). In AI, probabilistic thinking enables a model to predict the most likely next word in a sentence, accounting for uncertainty and making decisions based on likelihoods, notes MIT Review.
By adjusting dice to visualize this process, students can grasp that a model’s output isn’t always flawless but is based on probabilities. With Little Language Models, children can modify each side of the dice to represent different variables and adjust the probability of each side appearing, mimicking the decision-making process behind AI models.
By doing so, students can see how varying conditions lead to different outputs, helping to clarify that AI models, like their dice experiment, rely on probabilistic reasoning rather than deterministic rules.
Beyond illustrating AI fundamentals, the program also addresses bias in machine learning. Educators can use the tool to explain how bias can emerge in AI by having students assign colors to each side of the dice to represent different skin tones.
Initially, students might set the probability of a white hand at 100%—a scenario meant to reflect an imbalanced dataset containing only images of white hands. In response, the AI model generates only white hands when prompted.
Afterward, students can adjust the probabilities to include a more diverse range of skin tones, simulating a balanced dataset. This helps demonstrate how data diversity influences AI outputs and how biases can be mitigated through better data representation.
This feature is particularly timely as AI ethics and transparency become key issues in technology education. By introducing children to these concepts early on, the Dhariwals hope to foster a generation of tech-savvy individuals who understand AI’s strengths and limitations.
Emma Callow, a learning experience designer who collaborates with schools on integrating new technology into curricula, praised the program’s approach. “There is a real lack of playful resources and tools that teach children about data literacy and about AI concepts creatively,” Callow explained.
“Schools are more worried about safety rather than the potential to use AI. But it is progressing in schools, and people are starting to kind of use it. There is a space for education to change,” she added.
Little Language Models will launch on the Dhariwals’ online education platform, coco.build , in mid-November. The program will also be piloted in various schools over the next month, providing educators with early feedback and refinement opportunities, as noted by MIT Review.
Photo by Pascal Bernardon on Unsplash
Chinese Self-Driving Startup WeRide Raises $440.5 Million in U.S. IPO
- Written by Andrea Miliani Former Tech News Expert
- Fact-Checked by Justyn Newman Former Lead Cybersecurity Editor
In a Rush? Here are the Quick Facts!
- WeRide raised $320.5 million in private placement and $120 million in IPO
- The startup is now valued at $4 billion
- The autonomous vehicle startup offered 7,742,400 shares at $15.50
The Chinese autonomous vehicle startup WeRide raised $440.5 million during its initial public offering and a private placement in the United States this Friday.
According to the press release , WeRide made its initial public offering of 7,742,400 American depositary shares approved at $15.50 to trade at the Nasdaq Global Select Market under the symbol WRD. The offering is expected to close on Monday, October 28.
@WeRide is now officially listed on #NASDAQ , as the world’s first publicly listed universal #autonomousdriving technology company and the first publicly listed Robotaxi company. A huge thank you to our investors, clients, and partners! https://t.co/bhxv0WBNV6 — WeRide.ai (@WeRide_ai) October 25, 2024
Investors purchased $320.5 million through private placement, and WeRide expects to reach $458.5 million in total, including additional shares.
According to Reuters , the number of Chinese companies entering the American stock market has significantly decreased in the past few years due to Chinese regulations, especially after the ridesharing company Didi Global was forced to exit the New York Stock Exchange.
After China’s regulations softened, more companies are coming back to join the American stock market and WeRide is an example. After this IPO, the startup’s valuation surpassed $4 billion.
WeRide develops multiple kinds of autonomous driving vehicles but has been standing out in the robotaxi sphere. In China, the boom of robotaxis is making drivers worry about their future and WeRide’s vehicles have been taking the streets along with the competitor’s vehicles.
China has been quickly approving permits and documentation for multiple startups like Apollo Go, AutoX, and Pony.ai. But WeRide is one of the companies making large efforts to reach the American market, despite U.S. strict regulations on its products operating in the country.
Due to national concerns, the Biden administration proposed a rule to forbid Chinese hardware and software in autonomous vehicles on American territory.
