Machine Learning
Machine learning is Big Data being used at its most extreme level, processing vast and disparate data sets at a machine level to find patterns buried within, producing insights beyond human recognition.

Hackathons and action groups: how tech is responding to the COVID-19 pandemic
The global COVID-19 pandemic has generated a wide variety of responses from citizens, governments, charities, organizations, and the startup community worldwide. At the time of writing, the number of confirmed cases has now exceeded 1,000,000, affecting 204 countries and territories. From mandated lockdowns to applauding health workers from balconies, a

How Coronavirus can make open-source movements flourish and fix our healthcare systems
Five experts went live with educational sessions at our community site DN Club and told us about technology in times of coronavirus. Where are we heading in the crisis and how can the tech community contribute to finding solutions? Even though we are moving towards difficult times, there might be

How ensembles can reduce machine learning’s carbon footprint
Commercial and industrial applications of artificial intelligence and machine learning are unlocking economic opportunities, transforming the way we do business, and even helping to solve complex social and environmental problems. In fact, generative applications of this technology have become tools for environmental sustainability. With machine learning’s capability to analyze and

How to Stop Fetishizing AI
Our misguided perceptions of AI confuse the vital public debate about AI’s role in society by mitigating its severity and exaggerating its impact. Artificial Intelligence is sexy. It’s been able to translate between languages, recommend us new TV shows to watch, and beat humans at everything from Go to Jeopardy.

Can Femtech deliver radically personalized care to women?
Patient privacy and safety have always been cornerstones of the U.S. healthcare system. But in today’s digital era, there are apps tracking the most sensitive information such as the female menstrual cycle and fertility window. The collection of this data might be valuable for the future of healthcare – the

Why over one-third of AI and Analytics Projects in the Cloud fail?
How are various organizations handling the accelerating transition of data to the cloud? What are the obstacles in data cleaning for analytics and the time constraints companies face when preparing data for analytics, AI and Machine Learning (ML) initiatives? Here is a look at some insights from a recent report

2020: The Decade of Intelligent, Democratized Data
From wild speculation that flying cars will become the norm to robots that will be able to tend to our every need, there is lots of buzz about how AI, Machine Learning, and Deep Learning will change our lives. However, at present, it seems like a far-fetched future. As we

This NY based AI Startup Wants Amy & Andrew to Take Care of Meeting Schedules. Would You Sign Up?
Here is a look at an AI startup that raised $44.3 million in venture capital funding and built a product that has a vision to not only scheduling a “time” for meetings but also take care of every little detail that comes along. Find out how intelligent these AI assistants

Five Ways to Make Better Data-Driven Decisions in 2020
Is your organization data-driven? Across industries, data has become a core component of most modern businesses. Here is how budgets and corporate planning reflect this trend. A McKinsey study found that 36% of companies say data has had an impact on industry-wide competition, while 32% report actively changing their long-term

MLOps can help overcome risk in AI and ML projects
Aleksandar Kovačević, Sales Engineer at InterSystems, shares how companies use MLOps combined with a central multi-model database to get the most out of their machine learning initiatives. Artificial Intelligence (AI) and Machine Learning (ML) are hot topics at the moment. But when it comes to producing quantifiable results, there is