If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Apple is working on technology for the perfect selfie. The tech giant acquired Spectral Edge, a UK-based AI startup that uses machine learning to make smartphone pictures crisper, with more accurate colors. The system captures and blends an infrared shot with a standard shot to enhance a photograph's overall depth, detail and color. The startup uses a process that completely relies on machine learning that can be combined with both hardware and software to improve pictures. The news was first revealed by Bloomberg, which obtained secret documents'that Apple now controls Spectral.'
In the past few years, you might have noticed the increasing pace at which vendors are rolling out "platforms" that serve the AI ecosystem, namely addressing data science and machine learning (ML) needs. The "Data Science Platform" and "Machine Learning Platform" are at the front lines of the battle for the mind share and wallets of data scientists, ML project managers, and others that manage AI projects and initiatives. If you're a major technology vendor and you don't have some sort of big play in the AI space, then you risk rapidly becoming irrelevant. But what exactly are these platforms and why is there such an intense market share grab going on? The core of this insight is the realization that ML and data science projects are nothing like typical application or hardware development projects.
Developing prescription drugs is a high-cost, high-risk endeavor. Average research and development for an approved prescription drug requires an investment of $2.9 billion and takes more than 11 years. Clinical trials alone can cost an average of $1.1 billion over 6.6 years. In fact, clinical trials account for a staggering 40 percent of the pharmaceutical industry's research budget. To make matters worse, only 14 percent of drugs that enter clinical trials are eventually approved.
Edge computing provides groundbreaking innovations to enterprise cloud organizations, including nearly instant code transfer, reduced latency, and enhanced performance. The lightning speed of edge compute is due to the placement of the platform. Unlike public cloud, edge compute is placed as close as possible to the point of interaction with humans, electronics, and various connected devices. Edge compute becomes more and more relevant to companies as applications evolve, including virtual reality, augmented reality, and video analytics, which rely on artificial intelligence. With real-time code transfer that AI needs to be extremely precise, and as AI evolves, every millisecond counts, according to Paul Savill (pictured), senior vice president of core network and technology solutions at CenturyLink Inc.
From parts suppliers to vehicle manufacturers, service providers to rental car companies, the automotive and related mobility industries stand to gain significantly from implementing machine learning at scale. We see the big automakers investing in proof-of-concept projects at various stages, while disruptors in the field of autonomous driving are trying to build entirely new businesses on a foundation of artificial intelligence and machine learning. There are huge opportunities for machine learning to improve both processes and products all along the automotive value chain. But where do you focus? And how can you make sure your investments in machine learning aren't just expensive, "one-and-done" applications?
If you work with data in any capacity, go ahead and do yourself a favor: download KNIME Analytics Platform right here. I could dive into a quick start tutorial or show off some of the more advanced capabilities, but it's honestly very intuitive to use. KNIME Analytics Platform is 100% free. Those features allow you to automate workflow deployment, execute workflows remotely from another service, and create an interactive hub for users. The ability to automate workflows makes KNIME Server Medium an attractive option.
AI conferences are a great place for knowledge sharing about machine learning, big data, natural language processing, chatbot development, and more. In this article, we'll share our strategies for choosing the right AI conference to attend, and then making the most out of your experience at that conference. When deciding which AI conference to attend, you should think about your main goal for attending a conference. If you think about what you want to get out of attending an AI conference, that should help to narrow down your choices. If you're interested in debating and discussing machine learning trends with other data scientists, you might consider attending an intimate conference with round-table discussions.
It's that time when we start to look ahead to what next year holds for the life science sector...Lu Rahman outlines 2020s big medtech players A decade ago the healthcare advances create by AI would have seemed the stuff of dreams. But back in 2018 Theresa May announced plans to use artificial intelligence and data to transform the way certain diseases like cancer. The technology is moving at a pace – this year we heard that a team led by the University of Surrey had filed the first ever patent for inventions autonomously created by AI without a human inventor. Professor Ryan Abbott explained the implications this had for the life science sector: "These filings are important to any area of research and development as well as any area that relies on patents. Patents are more important in the life sciences than in many other areas, particularly for drug discovery. These tasks can be the foundation for patent filings. "As AI is becoming increasingly sophisticated, it is likely to play an increasing role in R&D including in the life sciences.
WIRE)--Citrine Informatics has been named an Enterprise of the Year Gold winner in the Best in Biz Awards, the only independent business awards program judged by prominent editors and reporters from top-tier publications in North America. Citrine Informatics' artificial intelligence technology is used by the world's largest materials and chemicals companies to accelerate the product development cycle. Since 2011, Best in Biz Awards' entrants have spanned the spectrum, from the most innovative local companies and start-ups to some of the most recognizable global brands. With more than 700 entries, the 9th annual program attracted a record number of entries from an impressive array of public and private companies of all sizes and spanning all geographic regions and industries in the U.S. and Canada. Best in Biz Awards 2019 honors were conferred in 80 different categories, including Company of the Year, Fastest-Growing Company, Most Innovative Company, Best Place to Work, Customer Service Department, Executive of the Year, Most Innovative Product, Enterprise Product, Best New Service, CSR Program, Event and Blog of the Year.