Collaborating Authors


The Impact of AI on Healthcare: How to Make the Models Work?


Research into Artificial Intelligence (AI) has been ongoing for decades, with early proposals dating back to 1950. However, only in recent years, it has seen a resurgence in popularity thanks to the increased availability of computing power and the growth of big data and machine learning. AI is the ability of machines to perform tasks that ordinarily require human intelligence, such as understanding natural language and recognizing objects. With the rapid expansion of AI, there are opportunities for businesses and individuals alike to capitalize on its capabilities. AI is a field of computer science and engineering focused on the creation of intelligent agents, which are systems that can reason, learn, and act autonomously.

AI-powered legal ediscovery helps dig through data at scale


We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. If there is one thing common to all legal cases, it is documents. In decades past, the evidence collected in litigation was often confined to digging through folders and filing cabinets, in a process called discovery. Today, electronic discovery, or'ediscovery,' is the name of the game – with paper documents replaced by millions of emails, Slack messages and Zoom calls. MarketsandMarkets estimates the global ediscovery market size to grow from $9.3 billion in 2020 to $12.9 billion by 2025.

AI: The emerging Artificial General Intelligence debate


Since Google's artificial intelligence (AI) subsidiary DeepMind published a paper a few weeks ago describing a generalist agent they call Gato (which can perform various tasks using the same trained model) and claimed that artificial general intelligence (AGI) can be achieved just via sheer scaling, a heated debate has ensued within the AI community. While it may seem somewhat academic, the reality is that if AGI is just around the corner, our society--including our laws, regulations, and economic models--is not ready for it. Indeed, thanks to the same trained model, generalist agent Gato is capable of playing Atari, captioning images, chatting, or stacking blocks with a real robot arm. It can also decide, based on its context, whether to output text, join torques, button presses, or other tokens. As such, it does seem a much more versatile AI model than the popular GPT-3, DALL-E 2, PaLM, or Flamingo, which are becoming extremely good at very narrow specific tasks, such as natural language writing, language understanding, or creating images from descriptions.

Three ideas from linguistics that everyone in AI should know


Everybody knows that large language models like GPT-3 and LaMDA have made tremendous strides, at least in some respects, and powered past many benchmarks, and Cosmo recently described DALL-E but most in the field also agree that something is still missing. A growing body of evidence shows that state-of-the-art models learn to exploit spurious statistical patterns in datasets... instead of learning meaning in the flexible and generalizable way that humans do." Since then, the results on benchmarks have gotten better, but there's still something missing. Reference: Words and sentence don't exist in isolation. Language is about a connection between words (or sentence) and the world; the sequences of words that large language models utter lack connection to the external world.

Expressive Querying for Accelerating Visual Analytics

Communications of the ACM

In this work, we introduce the problem of visualization search and highlight two underlying challenges of search enumeration and visualization matching.

IKEA launches AI-powered design experience (no Swedish meatballs included)


We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. For IKEA, the latest in digital transformation is all about home design driven by artificial intelligence (AI) – minus the home furnishing and decor retailer's famous Swedish meatballs. Today, it launched IKEA Kreativ, a design experience meant to bridge the ecommerce and in-store customer journeys, powered by the latest AI developments in spatial computing, machine learning and 3D mixed reality technologies. Available in-app and online, IKEA Kreativ's core technology was developed by Geomagical Labs, an IKEA retail company, which Ingka Group (the holding company that controls 367 stores of 422 IKEA stores) acquired in April 2020. IKEA Kreativ is the next step in IKEA's long journey towards digital transformation.

Toward Verified Artificial Intelligence

Communications of the ACM

Techniques for automatically generating abstractions of systems have been the linchpins of formal methods, playing crucial roles in extending the reach of formal methods to large hardware and software systems. To address the challenges of very high-dimensional hybrid-state spaces and input spaces for ML-based systems, we need to develop effective techniques to abstract ML models into simpler models that are more amenable to formal analysis. Some promising directions include using abstract interpretation to analyze DNNs (for example, Gehr et al.12), developing abstractions for falsifying cyber-physical systems with ML components,5 and devising novel representations for verification (for instance, star sets and other examples36).

How to get started with machine learning and AI


Back in the 1950s, in the earliest days of what we now call artificial intelligence, there was a debate over what to name the field. Herbert Simon, co-developer of both the logic theory machine and the General Problem Solver, argued that the field should have the much more anodyne name of "complex information processing." This certainly doesn't inspire the awe that "artificial intelligence" does, nor does it convey the idea that machines can think like humans. However, "complex information processing" is a much better description of what artificial intelligence actually is: parsing complicated data sets and attempting to make inferences from the pile. Some modern examples of AI include speech recognition (in the form of virtual assistants like Siri or Alexa) and systems that determine what's in a photograph or recommend what to buy or watch next.

Amazon demos Alexa reading a bedtime story in the voice of a boy's deceased grandma


Amazon's intelligent, voice-enabled assistant Alexa has become an integral part of everyday experiences. Alexa gets more than 1 billion requests per week, Amazon said Wednesday, while customers have access to more than 100,000 Alexa skills. Now, the technology giant is developing a new capability for Alexa, so she can help you remember loved ones who have passed away: the ability to communicate with others' voices. On Wednesday at the re:MARS conference (Amazon's event for Machine Learning, Automation, Robotics, and Space), Amazon's Rohit Prasad briefly described the skill. He showed a short video of a boy speaking to an Amazon Echo speaker.

Machine learning benefits for business (2022) - Dataconomy


Let's delve into the machine learning benefits and drawbacks. Many job titles are included in machine learning, including business managers, data scientists, and DevOps engineers. A good grasp of the machine learning lifecycle will assist you in correctly allocating resources and determining where you stand in it. Don't worry; machine learning benefits will reward you greatly for this effort. We have a comprehensive article for you to look at the history of machine learning before you start. We hear the term "Machine Learning" a lot these days, especially after all the buzz about Big Data.