Tools & Platforms
Bangkok Post – AI nurses hint at future of health
For patients meeting a nurse powered by artificial intelligence (AI) technology for the first time, the process remains the same, though they are not communicating with a human.
AI nurses can quickly analyse patients’ medical records and offer recommendations and diagnoses. These machines can receive help from AI-powered diagnostic assistance, which can analyse X-ray images, helping doctors to better examine patient disorders.
Welcome to the world of AI, which is increasingly integrated into medical care services.
The Explainer looks at some AI technologies that could shape the future of the hospital business.
What is an AI nurse?
An AI nurse is not a physical robot, but an AI-powered application in nursing.
Many hospitals are using AI nurses to help human nurses with clinical decision-making, patient monitoring and carrying out administrative tasks.
Thonburi Healthcare Group (THG), which operates Thonburi Hospital, is interested in this technology and is applying it in tandem with smart registration for patients.
“Smart registration allows patients to register via tablets or kiosks at Thonburi Hospital,” said Pumipat Chatnoraset, chief financial officer of THG.
The software for this registration was jointly developed by THG and Agnos Health, a health tech company specialising in AI and healthcare automation.
While smart registration simplifies the registration process and reduces waiting time for patients, an AI nurse obtains preliminary information from patients, including their detailed symptoms and what medication they are taking, said Mr Pumipat.
The AI nurse uses its quick computing ability to analyse large datasets and automate tasks, enabling nurses to focus more on taking care of patients and helping doctors plan treatments.
Clinical decision support systems, also known as CDSS, is a key feature of AI nurses, helping medical staff analyse different kinds of patients data, including laboratory results, images and electronic health records. This leads to evidence-based advice for further examination as well as better care planning and medication management.
The goal is the technology will provide nurses more time for tasks that require direct two-way communication with patients, compassion and critical thinking, according to THG.
What other AI-driven technologies are used in hospitals?
Machine learning, a subset of AI, is a technology that plays an increasing role in helping doctors with diagnostics and treatment planning as well as operational efficiency, potentially leading to more personalised and proactive care, said Mr Pumipat.
Known as ML, the technology enables systems to learn from data and enhance their performance without the need to be programmed.
ML can identify patterns in patient data to predict diseases early and recommend personalised treatments.
The technology can carry out tasks related to medical imaging and diagnostics by increasing the accuracy of X-ray, magnetic resonance imaging (MRI) and computed tomography (CT) scans.
The ability of AI to improve CT and MRI scans can also reduce radiation exposure.
In addition, AI can help medical staff better manage data interoperability between computer systems and keep track of patients’ health, said Mr Pumipat.
Data interoperability allows different systems and software to share data, enabling providers to facilitate seamless care transitions.
AI also supports the use of wearable devices by patients for remote health monitoring by hospitals. Medical staff can continually collect patient data, which may lead to early detection of health issues.
Like many industries, hospital and healthcare businesses are using high technology and innovations to develop new treatments that meet patients’ needs, he said.
“Digital transformation through the use of AI is an effective way to make medical service providers more productive and engaged with patients,” said Mr Pumipat.
Do hospitals need to invest in new technologies, particularly AI?
The investment is crucial, though it is costly and will increase the financial burden on hospitals, he said.
Digital technologies in the medical field, including AI-powered devices, can improve customer services and provide patients with quick and easy access to medical information and treatments.
The need to invest in new technologies means hospitals, which are now encountering rising costs and increasing patient demand, will face more financial pressure, said Mr Pumipat.
However, though AI-driven automation, predictive analytics and generative AI tools are expensive, they can optimise workflows and enhance physical examination, making them cost-effective in the long term, according to media reports.
AI can help reduce healthcare spending by US$200-360 million a year, a savings of 5-10%, said the London-based Centre for Economic Policy Research.
The new technologies, including AI, are needed to support hospitals’ plans to set up “centres of excellence” to treat specific, complicated diseases, said Mr Pumipat.
These centres are important to serve growing demand from patients seeking treatments for cancer, heart and brain disorders, he said.
“Many hospitals have increased investment in special centres and modern medical equipment to serve patients who want the best treatments,” said Mr Pumipat.
Like THG, other hospitals are keen on adopting new healthcare technology and treatments to better serve patients.
Vimut Holding Hospital Co, a unit of real estate developer Pruksa Holding, announced earlier it spent 10 million baht developing a centre of excellence for the treatment of lung disease, in line with increasing respiratory disorders among the public.
According to the World Health Organization Strategy 2025-2028 and data from the Thai Health Promotion Foundation, Thailand faces a critical air pollution crisis from PM2.5 ultra-fine dust. Bangkok was ranked eighth in a global survey of cities suffering from the worst levels of air quality.
Tools & Platforms
Gelson’s adopts Upshop’s AI-powered tech
Gelson’s Markets has gone all-in on artificial intelligence with plans to deploy Uphop’s total store platform to manage forecasting, ordering, inventory, and production planning, the Austin-based tech company announced Monday.
Gelson’s, which operates 26 upscale supermarkets and one convenience store, ReCharge by Gelsons, in Southern California, said the partnership ensures that “every location is tuned into local demand dynamics.”
The Austin-based SaaS tech company has served as a leader in AI-powered inventory management with its suite of tools that streamline the process. That includes direct store delivery (DSD) future-proofing, food traceability, and food waste management, among others.
“In a competitive grocery landscape, scale isn’t everything—intelligence is,” said Ryan Adams, president and CEO of Gelson’s Markets, in a press release. “With Upshop’s embedded platform and AI-driven capabilities, we’re empowering our stores to be hyper-responsive, efficient, and focused on the guest experience. It’s how Gelson’s can compete at the highest level.”
Implementing the new technology puts Gelson’s in league with “a market dominated by national chains,” according to Upshop.
The grocery retailer’s adoption of the platform will kick off with a focus on “eliminating food waste and optimizing fresh food production—especially within foodservice,” with the goals of reducing shrink, streamlining production, and enhancing quality, according to Upshop.
The premium grocery chain’s announcement appears to build on its recent investment in technology. In January 2024, the grocer announced a partnership with Scottsdale, Ariz.-based Clear Demand, which specializes in so-called intelligent price management and optimization (IPMO). That partnership aims to manage retail pricing strategies for the grocer.
Gelson’s was sold to Tokyo-based Pan Pacific International Holdings (PPIH) from TPG Capital in 2021.
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Tools & Platforms
IT Summit focuses on balancing AI challenges and opportunities — Harvard Gazette
Exploring the critical role of technology in advancing Harvard’s mission and the potential of generative AI to reshape the academic and operational landscape were the key topics discussed during University’s 12th annual IT Summit. Hosted by the CIO Council, the June 11 event attracted more than 1,000 Harvard IT professionals.
“Technology underpins every aspect of Harvard,” said Klara Jelinkova, vice president and University chief information officer, who opened the event by praising IT staff for their impact across the University.
That sentiment was echoed by keynote speaker Michael D. Smith, the John H. Finley Jr. Professor of Engineering and Applied Sciences and Harvard University Distinguished Service Professor, who described “people, physical spaces, and digital technologies” as three of the core pillars supporting Harvard’s programs.
In his address, “You, Me, and ChatGPT: Lessons and Predictions,” Smith explored the balance between the challenges and the opportunities of using generative AI tools. He pointed to an “explainability problem” in generative AI tools and how they can produce responses that sound convincing but lack transparent reasoning: “Is this answer correct, or does it just look good?” Smith also highlighted the challenges of user frustration due to bad prompts, “hallucinations,” and the risk of overreliance on AI for critical thinking, given its “eagerness” to answer questions.
In showcasing innovative coursework from students, Smith highlighted the transformative potential of “tutorbots,” or AI tools trained on course content that can offer students instant, around-the-clock assistance. AI is here to stay, Smith noted, so educators must prepare students for this future by ensuring they become sophisticated, effective users of the technology.
Asked by Jelinkova how IT staff can help students and faculty, Smith urged the audience to identify early adopters of new technologies to “understand better what it is they are trying to do” and support them through the “pain” of learning a new tool. Understanding these uses and fostering collaboration can accelerate adoption and “eventually propagate to the rest of the institution.”
The spirit of innovation and IT’s central role at Harvard continued throughout the day’s programming, which was organized into four pillars:
- Teaching, Learning, and Research Technology included sessions where instructors shared how they are currently experimenting with generative AI, from the Division of Continuing Education’s “Bot Club,” where instructors collaborate on AI-enhanced pedagogy, to the deployment of custom GPTs and chatbots at Harvard Business School.
- Innovation and the Future of Services included sessions onAI video experimentation, robotic process automation, ethical implementation of AI, and a showcase of the University’s latest AI Sandbox features.
- Infrastructure, Applications, and Operations featured a deep dive on the extraordinary effort to bring the new David Rubenstein Treehouse conference center to life, including testing new systems in a physical “sandbox” environment and deploying thousands of feet of network cabling.
- And the Skills, Competencies, and Strategies breakout sessions reflected on the evolving skillsets required by modern IT — from automation design to vendor management — and explored strategies for sustaining high-functioning, collaborative teams, including workforce agility and continuous learning.
Amid the excitement around innovation, the summit also explored the environmental impact of emerging technologies. In a session focused on Harvard’s leadership in IT sustainability — as part of its broader Sustainability Action Plan — presenters explored how even small individual actions, like crafting more effective prompts, can meaningfully reduce the processing demands of AI systems. As one panelist noted, “Harvard has embraced AI, and with that comes the responsibility to understand and thoughtfully assess its impact.”
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Tools & Platforms
Tennis players criticize AI technology used by Wimbledon
Some tennis players are not happy with Wimbledon’s new AI line judges, as reported by The Telegraph.
This is the first year the prestigious tennis tournament, which is still ongoing, replaced human line judges, who determine if a ball is in or out, with an electronic line calling system (ELC).
Numerous players criticized the AI technology, mostly for making incorrect calls, leading to them losing points. Notably, British tennis star Emma Raducanu called out the technology for missing a ball that her opponent hit out, but instead had to be played as if it were in. On a television replay, the ball indeed looked out, the Telegraph reported.
Jack Draper, the British No. 1, also said he felt some line calls were wrong, saying he did not think the AI technology was “100 percent accurate.”
Player Ben Shelton had to speed up his match after being told that the new AI line system was about to stop working because of the dimming sunlight. Elsewhere, players said they couldn’t hear the new automated speaker system, with one deaf player saying that without the human hand signals from the line judges, she was unable to tell when she won a point or not.
The technology also met a blip at a key point during a match this weekend between British player Sonay Kartal and the Russian Anastasia Pavlyuchenkova, where a ball went out, but the technology failed to make the call. The umpire had to step in to stop the rally and told the players to replay the point because the ELC failed to track the point. Wimbledon later apologized, saying it was a “human error,” and that the technology was accidentally shut off during the match. It also adjusted the technology so that, ideally, the mistake could not be repeated.
Debbie Jevans, chair of the All England Club, the organization that hosts Wimbledon, hit back at Raducanu and Draper, saying, “When we did have linesmen, we were constantly asked why we didn’t have electronic line calling because it’s more accurate than the rest of the tour.”
We’ve reached out to Wimbledon for comment.
This is not the first time the AI technology has come under fire as tennis tournaments continue to either partially or fully adopt automated systems. Alexander Zverev, a German player, called out the same automated line judging technology back in April, posting a picture to Instagram showing where a ball called in was very much out.
The critiques reveal the friction in completely replacing humans with AI, making the case for why a human-AI balance is perhaps necessary as more organizations adopt such technology. Just recently, the company Klarna said it was looking to hire human workers after previously making a push for automated jobs.
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