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Machine learning

Empowering individuals who have issues to resolve by providing them access to Artificial Intelligence.

In 2010, Karthik Dinakar and Birago Jones began a project to develop a tool helping content moderation teams at companies like Twitter and YouTube. The aim was to assist these teams in identifying inappropriate or harmful content. The project created considerable interest and the researchers were invited to present their work at a cyberbullying summit…

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Google AI suggests LANISTR: A Machine Learning Framework that leverages attention-based mechanisms to learn from Language, Image, and Structured Data.

Google Cloud AI researchers have unveiled a novel pre-training framework called LANISTR, designed to effectively and efficiently manage both structured and unstructured data. LANISTR, which stands for Language, Image, and Structured Data Transformer, addresses a key issue in machine learning; the handling of multimodal data, such as language, images, and structured data, specifically when certain…

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Assessing Anomaly Detection in Time Series: Awareness of Proximity in Time Series Anomaly Assessment (PATE)

Anomaly detection in time series data, which is pivotal for practical applications like monitoring industrial systems and detecting fraudulent activities, has been facing challenges in terms of its metrics. Existing measures such as Precision and Recall, designed for independent and identically distributed (iid) data, fail to entirely capture anomalies, potentially leading to flawed evaluations in…

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A novel method allows AI chatbots to engage in conversations throughout the day without experiencing system failures.

A group of researchers from MIT and other institutions have pinpointed a key issue that causes performance degradation in AI chatbots during long conversations and have developed a simple solution to rectify it. Large language machine-learning models such as the ChatGPT use key-value cache to store data. However, when the cache needs to hold more…

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This small, secure identification label has the ability to verify nearly everything.

Researchers at MIT have developed a highly advanced anti-tampering ID tag that is significantly smaller and cheaper than traditional Radio Frequency Identification (RFID) tags. It leverages the power of terahertz waves to improve upon conventional security tools and offers an innovative solution to safeguard items from counterfeit. Traditional security tags, much like this one, use radio…

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The new design recognizes medications that are incompatible when taken concurrently.

Researchers from MIT, Brigham and Women’s Hospital, and Duke University have developed a research approach to identify how different drugs exit the digestive tract. The method uses tissue models and machine-learning algorithms to understand which transporters are used by drugs, revealing how a commonly prescribed antibiotic and blood thinners can interfere with each other. Transporter…

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Implementing AI for individuals who are seeking solutions to their issues.

In 2010, Karthik Dinakar and Birago Jones, while working on a class project at Media Lab, developed a tool targeting content moderation for social media. The project, aimed at identifying harmful posts on platforms such as Twitter and YouTube, landed them a presentation at a White House cyberbullying summit. They realized before the event, however,…

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Microsoft Research Presents Gigapath: A Groundbreaking Vision Transformer for Digital Histopathology

Digital pathology is transforming the analysis of traditional glass slides into digital images, accelerated by advancements in imaging technology and software. This transition has important implications for medical diagnostics, research, and education. The ongoing AI revolution and digital shift in biomedicine have the potential to expedite improvements in precision health tenfold. Digital pathology can be…

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A novel method enables AI chatbots to engage in conversation all day without experiencing a system shutdown.

Researchers from MIT and other institutions have devised an innovative solution to prevent chatbots from crashing during prolonged dialogues. The method, known as StreamingLLM, makes a simple adjustment to the key-value cache, essentially the 'conversation memory,' of well-developed machine-learning models. By ensuring the first few data points don't get bumped out, the chatbot can maintain…

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This small, secure identification label has the ability to verify nearly everything.

Researchers from the Massachusetts Institute of Technology (MIT) have developed a microchip identification tag that works with terahertz waves to offer a more secure verification method than traditional radio frequency identification (RFID) tags. Terahertz waves are smaller in wavelength, yet much higher in frequency than radio waves, which make the tag more difficult to clone…

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The latest model recognizes medications that should not be concurrently administered.

Researchers from MIT, Brigham and Women’s Hospital, and Duke University have developed a novel approach combining machine-learning algorithms and tissue models to identify the specific transporters used by drugs in the gastrointestinal tract. This breakthrough could lead to improvements in patient treatment and drug development. Transporter proteins within the gastrointestinal system enable drug absorption. These proteins…

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Implementing artificial intelligence to assist individuals in resolving their issues.

In 2010, Karthik Dinakar and Birago Jones, two students from the Media Lab at the Massachusetts Institute of Technology, collaborated on a project aimed at supporting content moderation teams for social media companies such as Twitter and YouTube. Their ambition was to develop a tool capable of identifying concerning posts online. Despite some initial struggles,…

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