We have created a radial basis function network that allocates a new computational unit whenever an unusual pattern is presented to the network. The network learns by allocating new units and adjusting the parameters of existing units. If the network performs poorly on a presented pattern, then a new unit is allocated which memorizes the response to the presented pattern. If the network performs well on a presented pattern, then the network parameters are updated using standard LMS gradient descent. For predicting the Mackey Glass chaotic time series, our network learns much faster than do those using back-propagation and uses a comparable number of synapses.

Visualizing abstract stuff using Midjourney. “This Is How AI Thinks My Poem Looks” is published by Krupesh Raikar in ILLUMINATION.

In fall 2020, MIT's School of Engineering and Takeda Pharmaceuticals Company Limited launched the MIT-Takeda Program, a collaboration to support members of the MIT community working at the intersection of artificial intelligence and human health. Housed at the Abdul Latif Jameel Clinic for Machine Learning in Health, the collaboration aims to use artificial intelligence to both benefit human health and aid in drug development. Combining technology with cutting-edge health research, the program's participants hope to improve health outcomes across the world. Thus far, the partnership has supported joint research efforts focused on topics such as automated inspection in sterile pharmaceutical manufacturing and machine learning for liver phenotyping. Every year, the program also funds graduate fellowships to support students pursuing research on a broad range of issues tied to health and AI.

I scrapped all their webpages categorized under "stories". AllSides is a brilliant initiative that takes a news event and collects articles written on it by a left leaning, right leaning and center leaning media outlet. They write a summary on this event and briefly mention what is being emphasized on by each of the three outlets. An example of this can be viewed here. They publish pre-established metrics for the contemporary political bias of all major media outlets.