The promise and ultimate goal of artificial intelligence is to make machine intelligent. With advancement in machine learning, statistical reasoning and pattern recognition, as well as the exponential growth in big data and computing power, AI has become the front and center of technological innovation and business transformation in the second decade of 21st century and beyond. In this respect, AI is perfectly aligned to the goal of business intelligence, which is to make business more intelligent by augmenting and, in some cases, automating human intelligence. As AI is getting smarter, it is not unreasonable to expect that BI will too. Traditionally, BI, along with data warehousing and big data technologies, provides systems, tools and processes to help companies harness data from disparate sources and turn them into high quality and actionable information to drive competitive advantage.

The healthcare industry continues to be a major driver of the U.S. economy, with more than $3.5 trillion spent on healthcare in 2018 alone. Researchers believe that the industry will contribute more than $5.6 trillion to the economy by 2025. Much of this revenue comes from the medical research field, which is responsible for improving drug research, disease diagnosis and treatment protocols. Major research companies are collaborating with software development services to integrate deep learning technology into their investigations. Deep learning promises to transform the way that doctors review medical tests and make diagnoses, helping them identify diseases and start treatment quicker.

Natural Language Processing (NLP) is the study and application of techniques and tools that enable computers to process, analyze, interpret, and reason about human language. NLP is an interdisciplinary field and it combines techniques established in fields like linguistics and computer science. These techniques are used in concert with AI to create chatbots and digital assistants like Google Assistant and Amazon's Alexa. Let's take some time to explore the rationale behind Natural Language Processing, some of the techniques used in NLP, and some common uses cases for NLP. In order for computers to interpret human language, they must be converted into a form that a computer can manipulate.

In recent years, computer-driven image recognition systems that automatically recognize and classify human subjects have become increasingly widespread. These algorithmic systems are applied in many settings – from helping social media sites tell whether a user is a cat owner or dog owner to identifying individual people in crowded public spaces. A form of machine intelligence called deep learning is the basis of these image recognition systems, as well as many other artificial intelligence efforts. This essay on the lessons we learned about deep learning systems and gender recognition is one part of a three-part examination of issues relating to machine vision technology. Interactive: How does a computer "see" gender?

Data Council is the first community-powered data-platforms, science, & analytics event for software engineers, data scientists, deep learning researchers, and technical founders who want to discover tools & insights to build AI-based products. Happening on Nov 12 - 13, 2019 - @ Columbia University - Alfred Lerner Hall in NYC Click to remind me.

A UCLA research team has devised a technique that extends the capabilities of fluorescence microscopy, which allows scientists to precisely label parts of living cells and tissue with dyes that glow under special lighting. The researchers use artificial intelligence to turn two-dimensional images into stacks of virtual three-dimensional slices showing activity inside organisms. In a study published in Nature Methods, the scientists also reported that their framework, called "Deep-Z," was able to fix errors or aberrations in images, such as when a sample is tilted or curved. Further, they demonstrated that the system could take 2-D images from one type of microscope and virtually create 3-D images of the sample as if they were obtained by another, more advanced microscope. "This is a very powerful new method that is enabled by deep learning to perform 3-D imaging of live specimens, with the least exposure to light, which can be toxic to samples," said senior author Aydogan Ozcan, UCLA chancellor's professor of electrical and computer engineering and associate director of the California NanoSystems Institute at UCLA.

Explain Like I am 5. It is the basic tenets of learning for me where I try to distill any concept in a more palatable form. I couldn't reduce it to the freshman level. That means we don't really understand it. So, when I saw the ELI5 library that aims to interpret machine learning models, I just had to try it out. One of the basic problems we face while explaining our complex machine learning classifiers to the business is interpretability.

Machine Learning, especially Deep Learning technology is driving the evolution of artificial intelligence (AI). At the beginning, deep learning has primarily been a software play. Start from the year 2016, the need for more efficient hardware acceleration of AI/ML/DL was recognized in academia and industry. This year, we saw more and more players, including world's top semiconductor companies as well as a number of startups, even tech giants Google, have jumped into the race. I believe that it could be very interesting to look at them together. So, I build this list of AI/ML/DL ICs and IPs on Github and keep updating. If you have any suggestion or new information, please let me know. The companies and products in the list are organized into five categories as shown in the following table. Intel purchased Nervana Systems who was developing both a GPU/software approach in addition to their Nervana Engine ASIC. Intel is also planning in integrating into the Phi platform via a Knights Crest project.

By Dattaraj Jagdish Rao "After releasing his first movie, PK, in 2013, Shah Rukh's career has changed in a big way now. Most of his films have been successful. Recently, he had a big success in 2016 release, Khan by The Karan Johar. Shah Rukh had also signed an exclusive deal with Harshvardhan Bhardwaj Films. It was also announced a week ago that Shah Rukh Khan will make a guest appearance on a Bollywood reality show on Sunday."