Algorithms
How Humans And Machines Can Enhance Each Other’s Strengths With Collaborative Intelligence
“Artificial intelligence is transforming all sectors of the economy, but there’s no reason to fear that robots will replace all human employees. In fact, companies that automate their operations mainly to cut their workforces will see only short-term productivity gains, say the authors. Their research, involving 1,500 firms in a range of industries, shows that …
7 Sneaky Ways Hackers Are Using Machine Learning to Steal Your Data
Machine learning is famous for its ability to analyze large data sets and identify patterns. It is basically a subset of artificial intelligence. Machine learning uses algorithms that leverages previous data-sets and statistical analysis to make assumptions and pass on judgments about behavior. The best part, software or computers powered by machine learning algorithms can …
The Pain Points Of Scaling Data Science
While building a machine learning model, data scaling in machine learning is the most significant element through data pre-processing. Scaling may recognize the difference between a model of poor machine learning and a stronger one. Machine learning algorithm only recognizes numerical if there is a significant difference in the dimension, say few varying in tens …
Artificial Intelligence And Algorithmic Irresponsibility: The Devil In The Machine?
The classic 1995 crime film The Usual Suspects revolves around the police interrogation of Roger “Verbal” Kint, played by Kevin Spacey. Kint paraphrases Charles Baudelaire, stating that “the greatest trick the Devil ever pulled was convincing the world he didn’t exist”. The implication is that the Devil is more effective when operating unseen, manipulating and …
Who. What. Why. New IBM Algorithm Models How The Order Of Prior Actions Impacts Events
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. …
Recruiting Artificial Intelligence To Create A More Diverse Workforce
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 …
AI Decision Automation: Where It Works, And Where It Doesn’t
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 …
System Brings Deep Learning To “Internet Of Things” Devices
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 …
From Nudge To Hypernudge: Big Data And Human Autonomy
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 …
How Artificial Intelligence Is Revolutionizing Drug Discovery
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 …