Despite the buzz around artificial intelligence (AI), most industry insiders know that the use of machine learning (ML) in drug discovery is nothing new. For more than a decade, researchers have used computational techniques for many purposes, such as finding hits, modeling drug-protein interactions, and predicting reaction rates. What is new is the hype. As AI has taken off in other industries, countless start-ups have emerged promising to transform drug discovery and design with AI-based technologies for things such as virtual screening, physics-based biological activity assessment, and drug crystal-structure prediction. Investors have made huge bets that these start-ups will succeed.

Artificial Intelligence based innovations, machine learning, and big data are quickly turning into a fundamental piece of our day-to-day routines. This is as of now not the future, yet a reality that has proactively shown up. In spite of the fact that people might have mixed feelings about AI, it's difficult to deny that it opens up great opportunities for us. This is particularly obvious in economic terms, where this field is fascinating for both government organizations and private businesses. Today, in this blog, we will mention the top benefits of implementing AI in business. These are probably the most important advantages for Artificial Intelligence, which can have a great influence on business.

There is fair amount of excitement and hype about the ongoing emergence of artificial intelligence (AI) and the potential promise of the technology in improving diagnostic accuracy and increasing workflow efficiencies in radiology. However, as Nina Kottler, MD, points out in a recent video interview with Diagnostic Imaging, there are challenges as well when it comes to assessment and implementation of AI into one's practice. While there are "hundreds of FDA-cleared and approved algorithms in radiology alone," she notes that it is "early on in the maturity of the technology of AI with respect to health care" so choosing the right AI vendor for your practice is critical. While technical prowess is important, 80 percent of what an AI vendor does is help create the workflow around the algorithm to ensure it works well, according to Dr. Kottler, the Associate Chief Medical Officer for Clinical AI and VP of Clinical Operations at Radiology Partners. Dr. Kottler says cultural alignment is an important consideration as you are seeking a vendor that values your input as a radiologist and is on a similar wavelength with you on future directions of AI in radiology. For pertinent insights on the assessment and implementation of AI technology, watch the video below.

DeepMap leverages cutting-edge technologies like artificial intelligence to enhance mapping capabilities for the autonomous vehicle industry. It is a part of NVIDIA for scaling worldwide map operations and expanding the full-self driving expertise of NVIDIA. AI models are used to build high-definition maps to navigate the world without any potential accident. AI strategies of DeepMap are useful for NVIDIA to keep up with the unique vision and technology. Let's explore the implementation of AI in DeepMap to enhance the automotive industry efficiently. The integration of artificial intelligence in mapping can help in proper localization with constant upgradations.

Artificial intelligence (AI) is one of the hottest topics in marketing right now. Raj Venkatesan and Jim Lecinski recently published a book entitled "The AI Marketing Canvas: A Five-Stage Road Map to Implementing Artificial Intelligence in Marketing". To better understand what an AI marketing canvas is, I sought insight from Raj Venkatesan, a professor at the Darden School of Business. In full disclosure, I work with Raj and find his research and work fascinating. Below is insight on the AI marketing canvas.

Artificial intelligence (AI) and machine-learning (ML) have quickly grown beyond a few major tech companies and hardcore academic researchers. Every marketing organization can tap into the power of AI to streamline operations and grow the business. The new book The AI Marketing Canvas: A Five-Stage Road Map to Implementing Artificial Intelligence in Marketing provides a growth framework for business and marketing leaders to implement AI using a five-stage model called the "AI Marketing Canvas." On this episode of Marketing Smarts, I speak with co-author Rajkumar Venkatesan about how he and his co-writer developed those stages by studying leading global brands. We cover examples of brands―including Google, Lyft and Coca-Cola―that have successfully woven AI into their marketing strategies. This is not a conversation about coding for AI models. Raj and I talk about how marketing leaders can go from "zero to hero" with AI in marketing, and what that means for your team and your company culture. Listen to the entire show now from the link above, or download the mp3 and listen at your convenience.

Once the stuff of science fiction, artificial intelligence is fast becoming an integral technology for the federal government. While agencies today use AI to comb through and analyze piles of data and automate time-consuming processes, federal officials are aware they've only scratched the surface of AI's true capabilities and its most promising advances somewhere in the future. Federal agencies are preparing for that future with a series of strategic actions, both agency-specific and under the direction of the new administration. The Department of Health and Human Services, for example, created the position of "chief AI officer" in part to ascertain the ways the technology could improve mission delivery, culminating with an AI strategy for the agency. Along broader lines, the White House and Pentagon have launched hubs for AI research and policymaking that could dramatically impact how agencies and the military seek to procure and implement AI for years to come.

What’s the bigger challenge in implementing Artificial Intelligence within your enterprise? Risk or uncertainty? Hang on a minute, you say, aren’t they sort of the same thing? They’re related, but I’m going to argue uncertainty is emotional. We’ll play a game, You may be familiar with it from your undergraduate studies. Imagine I’ve got a jar with 100 balls in it. 50 red and 50 black. The jar is opaque and you can’t see inside. Pick a color; red or black. I’ll draw out a ball from the jar. If it’s your color I pay you $10,000. If it’s not your color, you get nothing. And I’m only going to let you play this game with me once.

Artificial intelligence (AI) is the crown of every tech-powered business enterprise -- whether small or big. And embracing new opportunities with AI is something every business must do to stay relevant in their industry. Implementing artificial intelligence in business will provide a direct impact on the success of the companies ranging from improved decision-making to better use of the extensive data generated. However, business-friendly it may sound; the path to implementing artificial intelligence in business is not a smooth ride. While larger businesses find themselves in a better position, the same cannot be said about startups.

Learning by doing is a great thing unless it's costing you money, then it may not seem worth it. In the business world when new technologies come around it may be tempting to take a "wait and see" approach to them, watching your competitors' successes and failures before taking the time to implement new technologies. Unfortunately when it comes to artificial intelligence (AI), the potential payoff is too big to ignore, and waiting to see how your competitors do implementing this technology could leave your business in the dust. Taking the right steps toward implementing AI is crucial. Some companies know that they need to hire a data scientist but they don't know what they expect the person to do and they will try to hire someone with no framework or plan in place. The first step toward integrating artificial intelligence into your business strategy is to take it seriously and make a plan for how it will work.