MIT researchers have created a microscopic, low-cost cryptographic ID tag, designed to protect products from counterfeiting by providing improved security compared to traditional radio frequency tags (RFIDs). The technology, developed using terahertz waves, can offer a highly secure, low-cost, and easy-to-implement solution in preventing tampering and ensuring product authenticity.
RFID tags typically use radio waves to…
Researchers from the Massachusetts Institute of Technology (MIT), Brigham and Women’s Hospital, and Duke University have used tissue models and machine-learning algorithms to identify how specific drugs pass through the digestive tract. The knowledge can help improve patient treatments, as certain drugs could interfere with each other if they depend on the same protein transporters.…
Researchers from the Massachusetts Institute of Technology (MIT), Brigham and Women’s Hospital, and Duke University have developed an innovative strategy to identify the transporter proteins used by different drugs in the body’s gastrointestinal (GI) tract. The method, which employs tissue models and machine-learning algorithms, aims to improve drug administration by enabling predictions of drug interactions…
In 2010, Karthik Dinakar SM ’12, PhD ’17, and Birago Jones SM ’12, students at the Media Lab, embarked on a project aimed at helping content moderation teams at major companies like Twitter (now X) and YouTube. Their work ignited a great deal of interest and they were invited to present their project at a…
Large Multimodal Models (LMMs) use multiple data types, including text, images, and more in their training process, thus allowing a more comprehensive understanding and processing of diverse data types. Models like Claude3, GPT-4V, and Gemini Pro Vision are more adept at handling a broad range of real-world tasks that involve text and non-text inputs. This…
Historically, image captioning and text-to-image search have fascinated machine-learning practitioners and businesses. The open-source models, Contrastive Language-Image Pre-training (CLIP) and Bootstrapping Language-Image Pre-training (BLIP), were the first to produce near-human results. Recently, multimodal models using generative models are being used to map text and images to the same embedding space for best results. Amazon has…
Last year, tech giant Meta launched Galactica, an artificial intelligence (AI) tool designed to write articles, solve complex math problems, generate computer code, and aid in scientific research. However, despite being pitched as an AI-powered asset to scientific inquiries, Galactica faced severe criticism for inaccurate generation of factual data, an issue that can be a…
Marketing agencies are integrating artificial intelligence (AI) platforms into their operations to stay competitive, increase efficiency, and provide superior results for clients. One of these platforms is Robotic Marketer, offering a unique solution to harness the benefits of AI.
There are several AI tools used by agencies:
- HubSpot: Inbound marketing and sales platform offering AI chatbots,…
Franchise marketing presents a unique set of challenges, including maintaining a consistent brand image across numerous locations and ensuring localized marketing strategies appeal to diverse audiences. Franchisees often find it difficult to see the direct benefits of their contributions to collective marketing funds if these strategies don't resonate with their specific local markets. Therefore, creating…
Artificial intelligence (AI) is expected to become a standard piece of the healthcare puzzle, despite the common misconceptions of what it actually entails. It's not intended to automate call centers or replace physicians, but rather to assist them, augmenting their capabilities and helping to bring a health system’s full potential into reality.
Healthcare systems face a…
Biomedical data is increasingly complex, spanning various sources such as electronic health records (EHRs), imaging, omics data, sensors, and text. Traditional data mining and statistical methods struggle to extract meaningful insights from this high-dimensional, heterogeneous data. Recent advancements in deep learning offer a transformative solution, enabling models that can directly process raw biomedical data. Such…
