Here’s how to establish an AI center of excellence in your organization. Any larger company should have one in place.
Read More5 steps to creating a responsible AI Center of Excellence
Tag: AI Business
Artificial Intelligence in the Corporate Boardroom
Alphabet, the parent company of Google GOOG -0.8%, is the leading tech company that decided to invest a lot of resources and funding in artificial intelligence. So much so, that the WSJ recently announced that AI is central to Google’s future. Not surprisingly, Google has been dealing with different challenges concerning its top AI executives and researchers. Activists shareholders are also showing interest in this. Recently, there is a rise in shareholder proposals calling on boards to ensure proper AI governance.
Read MoreFocus on Data-Fueled Features to move Data Science projects forward
For all the hype around data and data-hyphenated terms (like “data-driven”), it is important to remember that data is a raw resource that has no actualized value until it is integrated into a product that uses said data to generate a meaningful output.
Read MoreA case for AI regulation
Who will benefit from advances in artificial intelligence? And should we be worried? Advances in artificial intelligence (AI) are likely to be of most benefit to three groups: the wealthy, those who have specialist skills in jobs that are not easily automated, and those who can work effectively with intelligent machines. These groups of people represent a minority that will have a marked advantage in the future over the rest of humanity. However, advances in AI could benefit everyone while still bolstering inequality.
Read MoreAIOps Tools: Dynatrace vs AppDynamics
Both AppDynamics and Dynatrace offer a wide range of features and tools. This means while some tools are ideal for you, you might find many features redundant too. You can take advantage of the tree trial offered by both vendors to get a sense of how they work and see which tool works best for you.
Read MoreSix stage gates to a successful AI governance
Responsible use of AI should start with a detailed assessment of the key risks posed by AI [1], followed by a good understanding of the principles that should be followed [2], and then the governance of AI from a top-down and end-to-end perspective [3]. We have discussed these in our previous articles [1, 2, 3]. In this article, we focus on the first line of defense and dive into the nine-step data science process [4] of value scoping, value discovery, value delivery, and value stewardship and highlight the dimensions of governance.
Read MoreArtificial Intelligence and Architecture
Role of Artificial intelligence in Architecture. Artificial Intelligence and architecture will come together to solve challenges with housing, the way we live, and cites. About 55% of the world’s population is living in urban areas or cities. By 2050, that figure is estimated to rise to 68%. Experts are expecting a dramatic upswing towards cities, which will cause countless megacities to form around the globe.
Read MoreProfit or Information?
If you’re a company, you’re continually seeking how to gain more profit. If a company is seeking to expand or change their current business (in both big or small ways), a common solution is experimentation. Companies can experiment if a change works out or not; if a change does seem to be promising, they can incorporate that change into their broader business. Especially with digital-based companies, experimentation is a driving force of innovation and growth.
Read MoreThe advantage of Personalization in Rotating Stores (part two)
In the last blog post, the goal was to explain a rotating store’s core concepts while imposing some minor personalization details. We generated a quick estimate to understand personalization’s monetary impact on a rotating store. Unfortunately, this painted a naive optimism towards personalization; this post aims to dig into the areas where the previous fell short. Let’s get started!
Read MoreThe advantage of Personalization in Rotating Stores (part one)
The concept behind a rotating store is relatively simple; only a fraction of a catalog’s items are purchasable at any given time. The store effectively hides the remaining products, and transactions on that subset are impossible until a “rotation” occurs. In most cases, a rotation takes place at some predetermined cadence known by the consumer. In this sense, a rotating store shares similarities with a “flash sale.” Under this scenario, items that were likely purchasable beforehand have now been discounted for a short time, usually 1–2 days. However, the mechanism is slightly different as the “sale” in a rotating store is the opportunity to purchase the item. While possible, it does not have to include an actual discount.
Read MoreCan’t afford Artificial Intelligence for your Small Business? Think Again.
The market for Artificial intelligence (AI) solutions has grown 54% year over year in 2020 to a $22.6 Billion market size in the United States alone. No longer considered futuristic, AI is here to stay. AI is applicable to almost every business function.
Read MoreThe Robots are Coming! – An Interview with Ilan Kasan, CEO at Exceed AI
I sat down with Ilan Kasan, Co-founder and CEO at Exceed.AI to discuss automation and groundbreaking innovation in the field of artificial intelligence and how it impacts business.
Read MoreSome thoughts on AI Design and job jatisfaction in the Future
A few days before his inauguration, President Biden outlined a bold $1.9 trillion plan to address the COVID-19 pandemic his administration would be inheriting. One quote he makes, at the 2:38 mark of the hyperlinked video, has stuck with me ever since
Read MoreMaximizing ROI for ML, Decision Management, and RPA
Early in developing a machine learning project, it is tempting to focus primarily on building the model. Faith is placed in the notion that if the model is accurate, the other details will fall into place. This neglects the most crucial fact of all — the model is created to be used in the real world. The return on your AI investment can only be achieved when people use your model.
Read MoreRule-Based AI vs. Machine Learning for Development – Which is best?
Rule-based AI systems borrow from rule-based expert system development, which tapped the knowledge of human experts to solve complex problems by reasoning through bodies of knowledge. Expert systems emerged in the 1970s and 1980s. Today rule-based AI models include a set of rules and a set of facts, described in a recent account in BecomingHuman/ Medium. “You can develop a basic AI model with the help of these two components,” the article states.
Read MoreUsing Exponential Smoothing in Algorithmic Trading
Smoothing or averaging is a form of noise reduction and traders use to get a clearer picture on the trend or on extreme moves. The Stochastic Oscillator is known to have a signal line called the %D where a simple moving average is applied to the Stochastic formula so that it smoothes it out. In this article, we will create a Stochastic Oscillator entirely made out of exponential moving averages.
Read MoreImpact of Robotic Technology on Healthcare Industry
The whole idea of robots in hospitals is not new for healthcare professionals. The idea of using robotic technologies in healthcare evolved in 1985. It started when healthcare planned to transform robots into precise machinery for surgery. “The idea came into reality in early 2000 with the invention of the DaVinci robot. Hospital management software and robotic technologies are proof of how technologies have evolved.” According to research conducted by Credence, the global market of medical robotics will grow to USD 20 billion by 2023.
Read MoreThe MLOps Turn
Artificial Intelligence (AI) is here to stay, over a decade it has been changing the industries on a very accelerated pace and despite many people, even in technology area, still been skeptical about it and some simply do not like it, there is no way back and now it is time to master it and operate AI/ML with same level of maturity industry have for software development, automating it and integrating it with all IT Eco-Systems — this is the MLOps Turn.
Read More3 ways to get into reinforcement learning
When I was in graduate school in the 1990s, one of my favorite classes was neural networks. Back then, we didn’t have access to TensorFlow, PyTorch, or Keras; we programmed neurons, neural networks, and learning algorithms by hand with the formulas from textbooks. We didn’t have access to cloud computing, and we coded sequential experiments that often ran overnight. There weren’t platforms like Alteryx, Dataiku, SageMaker, or SAS to enable a machine learning proof of concept or manage the end-to-end MLops lifecycles.
Read More3 present and future use cases of AI in Retail
Artificial intelligence in retail is being applied in new ways across the entire product and service cycle — from assembly to post-sale customer service interactions, but retail players need answers to important questions: Which AI applications are playing a role in the automation or augmentation of the retail process? How are retail companies using these technologies to stay ahead of their competitors today, and what innovations are being pioneered as potential retail game-changers over the next decade?
Read More