An aspiring scientist in the field of machine learning and data mining.
A sentient, curiosity-endowed entropy-preserving organic vessel trying to make some sense out of this information-rich and intelligence-scarce world that we happen to call our own.
This blog is dedicated to Art and Science, Mind and Machine.
My AILab Research Homepage is here.
Data visualization is one of the most important tools we have to analyze data. But it’s just as easy to mislead as it is to educate using charts and graphs. In this article we’ll take a look at 3 of the most common ways in which visualizations can be misleading.
Pretty basic - yet it’s surprising how many people actually fall for such misinterpretations by the virtue of being too lazy to care or think about what is being presented to them in data visualizations.
A team of Chinese scientists did an impossible-sounding thing. They created electricity simply by dragging a droplet of saltwater across a layer of graphene. No big fires, no greenhouse gases, no fuss. They created energy with just a miracle material and one of the most plentiful substances on Earth.
Five years ago, a team of researchers from Google announced a remarkable achievement in one of the world’s top scientific journals, Nature. Without needing the results of a single medical check-up, they were nevertheless able to track the spread of
A very insightful article with many examples. In short, it is not possible to entirely sidestep the need for careful inference and meaningful machine learning by simply accumulating all the data and relying on its volume to deliver the results on its own.
Researchers at The Ohio State University have found a way for computers to recognize 21 distinct facial expressions—even expressions for complex or seemingly contradictory emotions such as ‘happily disgusted’ or ‘sadly angry.’
The field of automated image analysis is still improving, one step at a time.
MIT engineers design hybrid living/nonliving materials
MIT engineers have coaxed bacterial cells to produce biofilms that can incorporate nonliving materials, such as gold nanoparticles and quantum dots.
These “living materials” combine the advantages of live cells — which respond to their environment, produce complex biological molecules, and span multiple length scales — with the benefits of nonliving materials, which add functions such as conducting electricity or emitting light.
This approach could one day be used to design more complex devices such as solar cells, self-healing materials, or diagnostic sensors, says Timothy Lu, an MIT assistant professor of electrical engineering andbiological engineering. Lu is the senior author of a paper describing this innovation in the March 23 issue of Nature Materials.