Detecting Food-borne Illness in Real-Time

ZenLabs

A new computer model that uses machine learning and de-identified and aggregated search and location data from logged-in Google users was significantly more accurate in identifying potentially unsafe restaurants when compared with existing methods of consumer complaints and routine inspections, according to new research led by Google and Harvard T.H. Chan School of Public Health. The findings indicate that the model can help identify lapses in food safety in…

Read More

Detecting Computer Generated Text

ZenLabs

Harvard University researchers developing method that identifies computer generated text. The team’s central tenant was whether a system can be built to detect generated text Using that idea, Gehrmann and Strobelt developed a method that, instead of flagging errors in text, identifies text that is too predictable. “The idea we had is that as models get better and better, they go from definitely worse than humans, which is detectable, to as…

Read More

Harvard University Researchers developing models to Predict the Strength of Earth Quake

ZenLabs

Harvard research team discovered that earthquake activities are actually organized chaos rather than pure chaotic event as scientists had previously believed. The team began by examining patterns of seismic signals — transient waveforms that radiate from the first rupture in a fault, a thin seam of crushed rock separating two blocks of the earth’s crust. An earthquake occurs when the blocks break free. Scientists read these waves using an…

Read More

A Harvard University Student Startup Integrates Data Analysis Tools for Political Campaigns

ZenLabs

A group of Harvard students started a company that bring AI tools and understanding of Political Strategies to provide an analytical tool for political campaign. The startup’s goal is to identify a list of potential voters and score them. A score is based on voting history, registered party, and other relevant factors. Then the tool will determine the likelihood an individual to vote for the candidate. https://www.seas.harvard.edu/news/2019/06/running-on-data

Read More

AI to help Annotating Medical Records

ZenLabs

MIT computer scientists are hoping to accelerate the use of artificial intelligence to improve medical decision-making, by automating a key step that’s usually done by hand — and that’s becoming more laborious as certain datasets grow ever-larger. MIT News A big problem in AI is having a proper data that means data cleansing and sanitizing. Currently, most of data preparation is human intensive manual process. MIT scientists have found…

Read More

Mistaken Identity

ZenLabs

Why did my classifier just mistake a turtle for a rifle? MIT News Couple of MIT students explored how a traffic sign can be changed to trick computer vision models to make a mistaken identity. Though models are trained vigorously to identify an object correctly, there may be where models classify an object different that what it is. This topic has grown in popularity recently. Many researchers are focusing…

Read More

MIT Scientists Applying Financial Market Theories to Reduce the Cost of Cloud Infrastructure

ZenLabs

Inspired by Financial Market theories, MIT researchers in collaboration with Microsoft have developed a “risk-aware” mathematical model that could improve the performance of cloud-computing networks across the globe. Notably, cloud infrastructure is extremely expensive and consumes a lot of the world’s energy. MIT News The researchers are using risk model such Value at Risk (VaR) to predict and evaluate network risk to improve the utilization of assets that are…

Read More