Prellis Bio successfully generated 300 human IgG antibodies against SARS-CoV2, leveraging its Externalized Human Immune System technology. This achievement demonstrates the potential of the technology for rapid antibody production, reducing time to one month compared to traditional methods.
Researchers at Numenta describe a framework for understanding how the brain produces intelligence based on grid cells in the neocortex. They propose that cortical grid cells allow the neocortex to learn models of objects, enabling generalization and compositionality.
Prellis Biologics has developed record speed and resolution technology for printing human tissue with viable capillaries, a major hurdle in organ engineering. This breakthrough enables the production of thick, functioning tissue for drug testing and ultimately human organs.
Researchers at Numenta propose a new theory for how the brain learns models of objects through movement, pairing sensory input with location signals. The theory predicts that even the first levels of processing in the brain are learning and recognizing complete objects.
Prellis Biologics has received $1.8 million in funding to develop patent-pending technologies for creating viable human organs using 3D printing. The company aims to solve the challenge of creating microvasculature, a crucial component of functional organs.
Researchers at Numenta have developed an online sequence memory algorithm called Hierarchical Temporal Memory (HTM) that can detect anomalies in real-time streaming data without supervision. The technique is based on the principles of how the brain works and has been tested using the Numenta Anomaly Benchmark.
Researchers at Numenta compared their biologically-derived HTM sequence memory to traditional machine learning algorithms, demonstrating comparable prediction accuracy. The new paper highlights the algorithm's properties, including continuous online learning and robustness to sensor noise, making it ideal for streaming data applications.
Researchers at Numenta Inc. have published a new theory on how networks of neurons in the neocortex learn sequences, providing a breakthrough in understanding neural circuits.