A PhD candidate who worked for OpenAI and Apple discusses natural language processing, AI hallucinations, and deep fakes.
Michelle Zhou (PhD ’99) explains what no-code AI means and presents five inflection points that led to her current work, including the impact of two professors in graduate school who helped her find her direction in AI.
Teaching AI to distinguish between causation and correlation would be a game changer— well, the game may be about to change.
The J.P. Morgan AI Research Awards 2021 partners with research thinkers across artificial intelligence.
Google Research held an online workshop on the conceptual understanding of deep learning. The workshop discussed how new findings in deep learning and neuroscience can help create better artificial intelligence systems. Christos Papadimitriou discussed how our growing understanding of information-processing mechanisms in the brain might help create algorithms that are more robust in understanding and engaging in conversations. Papadimitriou presented a simple and efficient model that explains how different areas of the brain inter-communicate to solve cognitive problems.
Shuran Song and Carl Vondrick are among the awardees chosen for their artificial intelligence (AI) research. The program aims to use AI for societal good.
Professor Kathy McKeown talks with DeepLearning.AI’s Andrew Ng about how she started in artificial intelligence (AI), her research projects, how her understanding of AI has changed through the decades, and AI career advice for learners of NLP.
Almost 400,000 babies were born prematurely—before 37 weeks gestation—in 2018 in the United States. One of the leading causes of newborn deaths and long-term disabilities, preterm birth (PTB) is considered a public health problem with deep emotional and challenging financial consequences to families and society. If doctors were able to use data and artificial intelligence (AI) to predict which pregnant women might be at risk, many of these premature births might be avoided.