Quick Buzz Feed

Blog Image

Your Money | Developments in artificial intelligence making waves in transportation

Jun 01,26 | 01:45 EST

News 8's financial expert Mark Grywacheski is showing us more about AI and how it's being used to create new modes of transportation around the world. This report examines the financial aspects and innovative applications of AI across various transportation sectors globally.

... read more
Blog Image

Overcoming Skepticism and Driving AI Adoption in Nursing

Jun 01,26 | 01:43 EST

Nursing documentation has become an operational bottleneck that AI cannot fix without deep workflow alignment and disciplined change‑management. Nurses now spend up to 41% of their time on EHRs, according to the U.S. Department of Health and Human Services, and validated stress‑monitoring studies show they spend more time interacting with the EHR than on any other task during a four‑hour shift. Systematic reviews link EHR burden directly to clinical burnout, with roughly 40% of studies reporting negative or inconclusive impacts on clinician well‑being. At the same time, the American Nurses Association and the Online Journal of Issues in Nursing emphasize that AI improves nursing practice only when it is deliberately integrated, continuously, and with sustained frontline involvement. Nearly half of clinical decision support evaluations show mixed or negative results — underscoring why AI adoption fails when organizations underestimate workflow complexity or skip change‑management fundamentals. Emerj’s Matthew DeMello was joined by Umesh Rustogi, General Manager of Dragon for Nursing at Microsoft Health & Life Sciences, to examine what it actually takes to scale AI safely and effectively across clinical environments — from accuracy tuning to frontline adoption — on the AI in Business podcast. This article examines three critical insights from health system deployments on how AI can reduce nursing burden and scale safely across clinical environments: AI‑driven ambient documentation for nursing workflows: Capturing structured flow‑sheet data directly from bedside conversations removes manual entry, reduces cognitive load, and returns meaningful time to patient care. Continuous AI accuracy tuning within clinical systems: Allowing health systems to align schemas, adjust model behavior, and feed real‑world corrections back into the engine ensures reliable performance and prevents accuracy ceilings from stalling adoption. AI‑enabled change‑management frameworks for frontline teams: Embedding AI through protected training time, care‑out‑loud practices, and unit‑level champions accelerates clinician trust and drives consistent use across diverse nursing roles. Episode: Overcoming Skepticism and Driving AI Adoption – with Umesh Rustogi of Microsoft. Guest: Umesh Rustogi, General Manager of Dragon for Nursing, Microsoft Health & Life Sciences. Expertise: Healthcare AI, Clinical Workflow Innovation, Enterprise Product Leadership, Cloud and Data Platforms. Brief Recognition: Umesh Rustogi is an enterprise technology and product leader with experience spanning healthcare AI, cloud platforms, and enterprise software. Prior to Microsoft, he spent more than thirteen years at SAP in senior engineering, product management, and corporate strategy leadership roles focused on cloud and enterprise platform innovation. Earlier in his career, he held solution strategy roles at i2 Technologies and began as a software engineer at IBM. Rustogi holds a B.Tech. from IIT Delhi and a Master’s degree from North Carolina State University.

... read more
Blog Image

The Thermodynamics of Capital: Artificial Intelligence, Energy Crisis, and Ecological Crisis

Jun 01,26 | 01:40 EST

The article, 'The Thermodynamics of Capital: Artificial Intelligence, Energy Crisis, and Ecological Crisis,' published by Monthly Review, delivers a trenchant and vital critique of the modern technological landscape, specifically honing in on the pervasive societal impact of Artificial Intelligence (AI). Authored by Te Li, the piece meticulously deconstructs the prevalent myth of 'digital dematerialization' – a narrative zealously championed by the tech industry, particularly Silicon Valley and its AI boosters. This myth erroneously posits that AI and other digital technologies exist in an ethereal, immaterial realm, seemingly detached from the physical laws and material constraints that govern all other human activities and natural systems. Li argues forcefully that such a romanticized view dangerously obfuscates the profound, tangible, and often devastating environmental and energy costs inextricably linked to the design, development, training, and operational deployment of AI systems. The core intellectual framework underpinning this article is the 'thermodynamics of capital,' a concept that applies the fundamental principles of energy, work, and entropy to the analysis of economic systems, particularly within the context of capitalism. This perspective inherently suggests that the relentless drive for capitalist accumulation, characterized by an insatiable demand for exponential growth and profit, inevitably leads to a perpetually escalating consumption of energy and raw materials. In the domain of AI, this translates into an immense and ever-growing demand for electricity to power vast, climate-controlled data centers, sophisticated cooling infrastructures, and the incredibly energy-intensive manufacturing processes required for advanced hardware components, from microprocessors to intricate network architectures. The article posits that the continuous increase in computational power and data processing capacities of AI systems are emphatically *not* 'clean,' 'green,' or 'weightless' endeavors; rather, they are deeply rooted in and reliant upon a concrete material reality that imposes escalating strains on finite planetary resources. Moreover, Te Li's incisive analysis is designed to forge undeniable links between the rapid advancement of AI technology, the intensifying global energy crisis, and the accelerating, multifaceted ecological crisis. Through the thermodynamic lens, the article illuminates how the inherent inefficiencies in energy conversion and the inevitable dissipation of energy, compounded by the linear 'take-make-dispose' model of resource extraction and waste generation intrinsic to capitalist production, are gravely exacerbated by AI's escalating demands. This perspective offers a stark, reality-grounded counter-narrative to the often-optimistic, even utopian, visions propagated about AI, exposing its substantial ecological footprint and its significant contribution to environmental degradation, biodiversity loss, climate change, and the depletion of critical resources. The article challenges readers to transcend superficial understandings of technological progress and to critically scrutinize the systemic, macroeconomic, and planetary implications of digital transformation when embedded within a capitalist economic framework. It stands as a vital and urgent call to acknowledge the profound material truth underlying our increasingly digital age, prompting a serious consideration of alternative pathways for technological development that prioritize genuine sustainability and social justice. Ultimately, the piece advocates for a radical re-evaluation of how capital currently interacts with natural limits and human well-being, emphasizing the urgent necessity to address the material basis of digital technologies and their far-reaching consequences for the health and future of our planet.

... read more
Blog Image

AI tools need repeated instructions to stay on brand, experts say

Jun 01,26 | 01:35 EST

Businesses using AI can get better results by relying on structured workflows, repeatable prompts and clear formatting rules to keep marketing, branding and communication more consistent over time.

... read more
Blog Image

Artificial Intelligence Is Here To Stay. Are Hawaiʻi Schools Ready?

Jun 01,26 | 01:34 EST

From preschoolers to high school seniors, Hawaiʻi students share how artificial intelligence is shaping their learning and plans for the future. For many schools, it’s a race to keep up. Others are leading the pack. And some are unsure what to do with it. Artificial intelligence is playing an increasingly prominent role in Hawaiʻi education, from the recent opening of the state’s first AI-focused charter school to the development of new coursework teaching students how to navigate rapidly changing technology. Teachers are also coming face-to-face with new technology, whether it’s using AI avatars to test students’ grasp of Mandarin Chinese vocabulary or confronting kids who are submitting assignments written by ChatGPT. But there’s wide variation in how much teachers and students are willing to engage with the new technology. This article explores experiences with AI in schools across Hawaiʻi, from administrators and educators to students.

... read more
Blog Image

UB hosts national artificial intelligence leaders this week

Jun 01,26 | 01:32 EST

Conference is set to draw over 170 participants from universities and organizations nationwide and around the world, including UB experts.

... read more
Blog Image

How is LFUCG using artificial intelligence? Council will review city's AI policy this week

Jun 01,26 | 01:31 EST

An existing LFUCG policy broadly outlines acceptable and prohibited uses for artificial intelligence for local government business. Here's what's in it.

... read more
Blog Image

Beyond Books: Can we opt out of the artificial intelligence era?

May 31,26 | 01:44 EST

Library Director James Hill reflects on the ubiquity of AI and asks if we can still choose to opt out of the digital tide.

... read more
Blog Image

Battle to regulate artificial intelligence grows in DC

May 31,26 | 01:43 EST

The article, prominently titled 'Battle to regulate artificial intelligence grows in DC,' casts a critical eye on the intensifying debate and burgeoning legislative efforts surrounding the control and governance of Artificial Intelligence within the political epicenter of Washington D.C. This discourse is characterized by a dual and often conflicting dynamic: on one side, influential figures and thought leaders from the technology industry itself are increasingly vocal in their appeals for stringent safety regulations and ethical guidelines. Their advocacy stems from a deep-seated understanding and firsthand experience of AI's profound and rapidly expanding capabilities, which, while promising immense societal benefits, also pose significant risks. These risks span a wide spectrum, including critical ethical considerations, pervasive data privacy concerns, the potential for malicious misuse of AI technologies, and broader societal impacts such as algorithmic bias, job market disruption, and the erosion of democratic processes through misinformation. These industry insiders, having witnessed the rapid evolution and growing autonomy of sophisticated AI systems, recognize the critical need for a structured and anticipatory regulatory framework to guide its development responsibly, emphasizing the paramount importance of preventing unforeseen and potentially catastrophic consequences, and crucially, rebuilding and ensuring sustained public trust in AI technologies. Conversely, the highly politicized corridors of power in D.C. are bustling with incessant activity from well-funded and strategically positioned lobbying groups representing a diverse array of technology giants and their vested interests. These powerful lobbyists are actively engaging with key legislators, influential policymakers, and various regulatory bodies to shape the content, scope, and ultimate direction of proposed bills and foundational policies related to AI. Their primary objectives typically revolve around influencing the regulatory landscape to align favorably with their corporate interests, which may include advocating for less restrictive innovation policies to foster rapid technological advancement, robustly protecting proprietary algorithms and intellectual property, safeguarding existing market dominance, or minimizing burdensome compliance requirements that could impede growth or profitability. This often creates a complex and challenging web of influence where the more altruistic calls for universal safety and ethical deployment from some tech leaders can frequently clash with the entrenched economic and strategic imperatives aggressively pushed by corporate lobbying efforts, leading to protracted legislative battles. The burgeoning legislative momentum highlighted in the article signifies a broader, interconnected global trend as governments and international organizations worldwide urgently grapple with how to effectively manage the exponential growth of AI without inadvertently stifling the very innovation it represents. Key areas of intense concern in D.C. currently include establishing clear and enforceable accountability mechanisms for autonomous AI-driven decisions, developing universally accepted technical standards for robust data security and privacy within AI systems, proactively addressing the profound societal implications of advanced automation, and formulating coherent national strategies to maintain a competitive edge in the global race for AI leadership. The article unequivocally implies that this is not merely a technical discussion confined to laboratories but a deeply political and socio-economic one, involving high-stakes negotiations, complex ethical dilemmas, and the delicate balancing of unprecedented economic opportunities against potentially existential risks. The ultimate outcome of this multifaceted 'battle' will undoubtedly shape the fundamental trajectory of AI development and its ubiquitous integration into nearly every facet of human life, meticulously determining whether it evolves under controlled, transparent, and ethical guidelines or in a more fragmented, laissez-faire environment driven primarily by unfettered commercial interests. The ongoing legislative efforts in Washington D.C. are therefore undeniably crucial for defining the future relationship between transformative technology, democratic governance, and the well-being of society at large.

... read more