Algorithms, Artificial Intelligence, Bacteria, Biological engineering, Biology, Brain and cognitive sciences, Broad Institute, Computational biology, Computer science and technology, CRISPR, Data, DNA, Genetic engineering, Genome, Genome editing, McGovern Institute, Microbes, National Institutes of Health (NIH), Research, RNA, School of Engineering, School of Science, UncategorizedMarch 18, 202448Views0Likes0Comments
Scientists from the McGovern Institute for Brain Research at MIT, the Broad Institute of MIT and Harvard, and the National Center for Biotechnology Information at the National Institutes of Health, have developed a new search algorithm to find enzymes of interest in vast microbial sequence databases. This algorithm, called Fast Locality-Sensitive Hashing-based clustering (FLSHclust), discovered…
Researchers at MIT, Harvard, and the National Institutes of Health have utilized a new search algorithm to identify 188 different types of rare CRISPR systems in bacterial genomes. This data holds potential to advance genome-editing technology, enabling more precise treatments and diagnostics.
The algorithm, developed in the lab of prominent CRISPR researcher, Professor Feng Zhang uses…
Scientists from the McGovern Institute for Brain Research at MIT, the Broad Institute of MIT and Harvard, and the National Center for Biotechnology Information at the National Institutes of Health have developed a new algorithm that can sift through massive amounts of genomic data to identify unique CRISPR systems. Known as Fast Locality-Sensitive Hashing-based clustering…
Audio deepfakes, although often associated with unethical practices, have potential uses that can benefit society, suggests postdoc Nauman Dawalatabad in a Q&A with MIT News. He highlights the need for technology that protects sensitive information held within speech patterns, such as age, gender, and health conditions, stating that obscuring the speaker's identity in audio deepfakes…
Machine learning models are widely used today in smart devices like smartphones, with diverse applications like autocorrecting keyboards or improved chatbot responses. However, fine-tuning these models requires considerable computational resources and transfers of data to and from cloud servers – which can pose both energy and security issues. The team of researchers from MIT and…
Microbial sequence databases hold a vast array of information about enzymes and other molecules that could be utilized in biotechnology applications. However, the sheer size of these databases has made it challenging to efficiently search for specific enzymes of interest.
Researchers from the McGovern Institute for Brain Research at MIT, the Broad Institute of MIT and…
The "Generative AI: Shaping the Future" symposium, the kickoff event of MIT’s Generative AI Week, drew hundreds of attendees both from academia and industry. Rodney Brooks, iRobot co-founder and keynote speaker, warned attendees against uncritically overestimating the capabilities of generative AI, a technology increasingly powering tools such as OpenAI’s ChatGPT and Google’s Bard.
Generative AI…
Researchers at MIT and the MIT-IBM Watson AI Lab have developed an onboarding process that efficiently combines human and AI efforts. The system educates a user when to collaborate with an AI assistant and when not. This method can find situations when a user trusts the AI model's advice, but the model is incorrect. The…
In late November, Massachusetts Institute of Technology (MIT) held a Generative AI Week involving faculty, staff, and students from the institution. The event served as a platform to discuss the opportunities and important applications of generative artificial intelligence technologies across varied disciplines. The week's agenda included a main symposium and four subject-specific symposia. MIT President…