Posts in tag

Algorithms


Actions have consequences. And typically, when something happens, the order of the causes of the event really does matter. But understanding exactly how each action affects the final result is not always easy. Our latest work, “Order-Dependent Event Models for Agent Interactions,” presented at the International Joint Conferences on Artificial Intelligence Organization (IJCAI), can help. …

In today’s highly competitive business environment, a diverse workforce has become a factor that can give an organization the edge. Winning clients, attracting talent or even securing funding to take a company public can depend on diversity. For example, Goldman Sachs Group recently announced it will no longer support initial public offerings of companies with all-male boards. The returns on …

Some companies are using AI for end-to-end decision-making, but not all decisions can be made without human intervention. Here are some real-world cases. As artificial intelligence (AI) ascends in the marketplace, the burning question remains as to how far it can be trusted when it comes to the “last mile,” the final decision that follows the analytics …

Deep learning is everywhere. This branch of artificial intelligence curates your social media and serves your Google search results. Soon, deep learning could also check your vitals or set your thermostat. MIT researchers have developed a system that could bring deep learning neural networks to new — and much smaller — places, like the tiny …

We produce data all the time. This is a not something new. Whenever a human being performs an action in the presence of another, there is a sense in which some new data is created. We learn more about people as we spend more time with them. We can observe them, and form models in …

AI technologies are catalysing the initial and most crucial step in the biopharmaceutical value chain. The process of drug discovery has been historically slow, labour-intensive, failure-prone, and costly. Its four main stages, as shown below, typically take around five to six years to attain completion. This is a huge amount of time, especially during crisis …

The Future of Neuromorphic Computing: Nabil Imam, Intel Senior Research Scientist, Explains Neuromorphic Computing Nabil Imam, a senior research scientist in Intel Labs’ neuromorphic computing group, works with olfactory neurophysiologists at Cornell University. “My friends at Cornell study the biological olfactory system in animals and measure the electrical activity in their brains as they smell odors,” …

Artificial intelligence has the potential to greatly simplify our lives – but not everyone is a data scientist and not all data scientists are experts in machine learning. Enter AutoAI – a novel approach of designing, training and optimizing machine learning models automatically. With AutoAI, anyone could soon build machine learning pipelines from raw data directly, …

Word embeddings—an algorithmic technique that can map relationships and associations between words—can measure changes in gender and ethnic stereotypes over the past century in the United States. Researchers analyzed large databases of American books, newspapers, and other texts and looked at how those linguistic changes correlated with actual US Census demographic data and major social …

Now that humans have programmed computers to learn, we want to know exactly what they’ve learned and how they make decisions after their learning process is complete. The answers to such questions could shed light on our own decision-making processes. Kate Saenko, an associate professor of computer science at Boston University, asked humans to look …