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Graduate student Aruna Sankaranarayanan speaks with Mashable reporter Cecily Mauran the impact of political deepfakes and the importance of AI literacy, noting that the fabrication of important figures who aren’t as well known is one of her biggest concerns. “Fabrication coming from them, distorting certain facts, when you don’t know what they look like or sound like most of the time, that’s really hard to disprove,” says Sankaranarayanan.
Researchers at MIT have developed a new model for training robots dubbed Heterogeneous Pretrained Transformers (HPT), reports Brain Heater for TechCrunch. The new model “pulls together information from different sensors and different environments,” explains Heater. “A transformer was then used to pull together the data into training models. The larger the transformer, the better the output. Users then input the robot design, configuration, and the job they want done.”
MIT researchers have developed a new training technique called Heterogeneous Pretrained Transformers (HPT) that could help make general-purpose robots more efficient and adaptable, reports Christopher Isak for TechAcute. “The main advantage of this technique is its ability to integrate data from different sources into a unified system,” explains Isak. “This approach is similar to how large language models are trained, showing proficiency across many tasks due to their extensive and varied training data. HPT enables robots to learn from a wide range of experiences and environments.”
MIT researchers have developed a security protocol that utilizes quantum properties to ensure the security of data in cloud servers, reports Andrew Corselli for Tech Briefs. “Our protocol uses the quantum properties of light to secure the communication between a client (who owns confidential data) and a server (that holds a confidential deep learning model),” explains postdoc Sri Krishna Vadlamani.
Liquid AI, an MIT startup, is unveiling a new AI model based on a liquid neural network that “has the potential to be more efficient, less power-hungry, and more transparent than the ones that underpin everything from chatbots to image generators to facial recognition systems, reports Will Knight for Wired.
Researchers at MIT have demonstrated “fully 3D-printed semiconductor-free resettable fuses,” reports Jesse Allen for Semiconductor Engineering. “The researchers plan to further develop the technology to print fully functional electronics and aim to fabricate a working magnetic motor using only extrusion 3D printing,” writes Allen.
Graduate student Nouran Soliman speaks with NBC Boston about the use of “personhood credentials,” a new technique that can be used to verify online users as human beings to help combat issues such as fraud and misinformation. “We are trying to also think about ways of implementing a system that incorporates personal credentials in a decentralized way,” explains Soliman. “It's also important not to have the power in one place because that compromises democracy.”
Researchers at MIT and elsewhere have developed a 3D printing method that allows “precise control over color, shade, texture, all with just a single material,” reports Vanesa Listek for 3Dprint.com. This technique “promises a faster and more sustainable solution than traditional approaches relying on multiple materials and nozzle changes,” explains Listek.
Researchers at MIT and elsewhere have developed “a new method of 3D printing that uses heat-responsive materials to print multi-color and multi-textured objects in one step,” reports Laura Griffiths for TCT Magazine. “The method has so far been tested using three heat-responsive filaments including a foaming polymer with particles that expand as they are heated, and wood and cork fiber-filled filaments,” explains Griffiths.
Researchers at MIT have developed GenSQL, a new generative AI system that can be used “to ease answering data science questions,” reports Allison Proffitt for Bio-It World. “Look how much better data science could be if it was easier to use,” says Research Scientist Mathieu Huot. “It’s not perfect yet, but we believe it’s quite an improvement over other options.”
Profs. Canan Dagdeviren and Hugh Herr speak with CNN discuss their work aimed at empowering patients and doctors. Inspired by her aunt’s experience with breast cancer, Dagdeviren and her students are developing new wearable devices that could help detect cancer at an earlier stage. Says Herr of his work developing prosthetics that can be controlled by the human nervous system: “There will be a point where technology is so sophisticated that we can actually rebuild limbs after amputation that will be as good and, ultimately, they will be better than intact biological limbs.” Herr adds that in the future he hopes “the conversation will not be about human limitation anymore. It will be about human ability and human expression.”
Researchers at MIT have found large language models “often struggle to handle more complex problems that require true understanding,” reports Kirimgeray Kirimli for Forbes. “This underscores the need for future versions of LLMs to go beyond just these basic, shared capabilities,” writes Kirimli.
Writing for The Washington Post, Prof. Daniela Rus, director of CSAIL, and Nico Enriquez, a graduate student at Stanford, make the case that the United States should not only be building more efficient AI software and better computer chips, but also creating “interstate-type corridors to transmit sufficient, reliable power to our data centers.” They emphasize: “The United States has the talent, investor base, corporations and research institutions to write the most advanced AI models. But without a powerful data highway system, our great technology advances will be confined to back roads.”
CNN visits the lab of Prof. Canan Dagdeviren to learn more about her work developing wearable ultrasound devices that could help screen for early-stage breast cancer, monitor kidney health, and detect other cancers deep within the body. “Wearable technology will grow rapidly in the near future,” says Dagdeviren. “But in the far future, they will be one of the most powerful tools that we will be seeing in our daily life.”
In an article for Forbes, Robert Clark spotlights how MIT researchers developed a new model to predict irrational behaviors in humans and AI agents in suboptimal conditions. “The goal of the study was to better understand human behavior to improve collaboration with AI,” Clark writes.