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Oregon State expert to lead soil health workshop
Oct. 29 event free for farmers; Registration deadline Oct. 22 The registration deadline is fast approaching for a free soil health training in Aumsville, Ore. The event, held by Oregon […]
Medical students in Savannah showcase hands-on training for health leaders
Executives visited the Coastal Empire on Wednesday to see how medical students are training for careers in health care.
Nonpartisan coalition of religious leaders plans to counter voter intimidation on Election Day
The diverse, multifaith group is training all the way through the end of October online and in person learning de-escalation techniques and equipping themselves with knowledge of local laws and resources.
Trained community volunteers to monitor seagrass for study
The research is geared toward finding the best ways to train community volunteers to collect data on underwater seagrasses in waters throughout the state in a program led by Coastal Carolina Riverwatch and the University of North Carolina Wilmington and funded by North Carolina Sea Grant.
Castlevania's Most Iconic Song Should Chain Whip Me To Death, Not Put Me In A Thousand Year Sleep
The Belmont's Curse version of "Bloody Tars" is more restrained than it should be
Railroads pull ahead as high fuel costs hit truckers harder
Union Pacific, Norfolk Southern and CSX all reported jumps in third-quarter profit and revenue.
‘You reach a tipping point’: New Zealand’s strained healthcare system at centre of election battle
With care shortfalls biting across the country, the National-led coalition has been accused of letting chronic underfunding worsen
Ketchikan nonprofit launches initiative to strengthen health advocacy for local Filipino families
The Ketchikan Wellness Coalition has been awarded a grant to expand health advocacy for Filipino families in Ketchikan and on Prince of Wales Island. The initiative is called Malasakit Matters. Malasakit is a Tagalog concept that means to have deep compassion and ownership for someone else’s wellbeing. The program is aimed at training Filipino youth […]
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(ANALYSIS) Political shamelessness threatens democracy by weakening leaders’ respect for ethical principles and the rule of law. Drawing on Plato’s Laws, this article explores reverence as a virtue that encourages humility, self-restraint and recognition of human limitations, arguing that responsibl
UCLA Health addresses healthcare accessibility issues for Spanish speakers
Three UCLA Health initiatives are working to make healthcare more accessible for Spanish speakers across Los Angeles. The UCLA Hispanic Neuropsychiatric Center of Excellence, the Equity for Latinx/Hispanic Healthy Aging and the Lifespan Assessment Through Integrated Neuropsychology Clinic address disparities in healthcare by offering bilingual training for medical professionals and conducting testing in patients’ native language.
Dodgers Provide Positive Update on Klein
Will Klein underwent a procedure to remove bone chips from his elbow, but the Los Angeles Dodgers expect the right-handed reliever to be ready for Spring Training.
HCA Healthcare opens clinical training center in Gainesville
New facility will support nursing and physician education at six North Florida hospitals.
Workshop provides training to start and grow small businesses
SALISBURY — Small business entrepreneurs were invited to attend a workshop to help them start or grow their businesses. Rowan-Cabarrus Community College served as the sponsor of the free workshop, […]
Chamber, RCEDA bring back business classes
by John Dowd The Bitterroot Valley Chamber of Commerce and the Ravalli County Economic Development Authority (RCEDA) are teaming up to bring business training classes back to the Bitterroot Valley. […]
Health insurance through work is under strain. What comes next?
Employers are struggling with rising premiums. Some are looking for a different model.
Microsoft AI CEO says new model beats OpenAI using less compute
Microsoft AI CEO said its latest AI model outperforms an OpenAI base model on certain pre-training metrics using a quarter of the compute.
Sokaogon partners on workforce training for $72M broadband network
A new broadband workforce partnership will launch in spring 2027 to support a $72 million tribally owned fiber network planned for northern Wisconsin. The Sokaogon Chippewa Community, Nicolet College and the Wisconsin Department of Workforce Development’s Bureau of Apprenticeship Standards are developing the one-year broadband service technician apprenticeship. The program combines 2,000 hours of on-the-job […]
Can AI solve our mental health access problem?
Last week I asked you what worries you most about AI in health. It was close, but your top answer was “AI giving bad health advice.” Last week’s poll results: You’re in good company. This concern was top of mind at a conference I joined at Stanford last week, where researchers, clinicians, and people who build AI systems spent a day debating trust and safety in health AI. Stepping back, I’m also hearing your emerging concerns about AI’s impact on our well-being generally. I see this as a matter of public health, and we’ll take it in pieces as we learn together. Today we’ll focus on AI chatbots used for therapy for mental health. Early this month, Governor Newsom vetoed Senate Bill 903, California’s most ambitious attempt to regulate AI use for mental health. It’s at the center of active debate, and raises the questions patients, family members, citizens, and voters will face as AI moves deeper into health care. Let’s work through it. What is “AI-based therapy”? It’s really two things: purpose-built mental health apps designed to deliver structured support, and general chatbots like ChatGPT, Claude, and Gemini that people increasingly use for emotional support—even if they weren’t built for it. Spoiler alert: I don’t know whether the shift toward AI therapy is good or bad. The evidence isn’t there yet. But I do know it’s already happening, and I have some ideas about how we can roll it out with safety in mind. The therapy dilemma, in a nutshell Mental health challenges are common, and strain health and well-being across populations. Therapy (interactive dialogue with a trained, empathetic practitioner) helps many people heal. The demand for licensed therapists far exceeds the supply in California, and AI-based therapy can narrow that gap. AI-based therapy remains novel, unproven, and not well tested. Right off the bat, we can see we’re dealing with trade-offs here. Since the main driver of demand for therapy from a robot is lack of access to therapy from a human, we’ll start there. It’s too hard to find and afford a human therapist California is short roughly 55,000 licensed, non-prescribing therapists and counselors, about 40% of what we need. Psychiatrists, who rely on talk therapy as a complement to prescribed medications, are even more scarce. Eight counties have none, and density ranges from 1.7 per 100,000 residents in San Benito County, to 68.1 in Marin County. My wife is a psychiatrist in Marin, and even here access is tight. If it’s hard in the best-supplied county, imagine rural Sierra County, or the San Joaquin Valley. In 2024, more than half of Californians who tried to make a mental health appointment struggled to find a provider who took their insurance, compared with 14% for physical health care. When Senate staff posed as “secret shopper” patients and called 120 mental health providers in Medicare Advantage networks, they landed an appointment less than once for every five tries. Insurers pay behavioral health clinicians about 22% less than medical and surgical clinicians for comparable office visits. On top of that, billing denials and prior authorizations hit hardest at the solo and small practices common in mental health. Psychiatrists opt out of Medicare at the highest rate of any specialty. In many places, a cash practice for therapy fills quickly with patients paying $250 or more an hour, with no insurance paperwork at all. Families who can pay cash find providers more easily. Those who rely on insurance, including Medi-Cal enrollees, older adults, rural residents, and non-English speakers, compete for what’s left. So we can’t pretend the human system works, and we can’t blame people for turning to AI for support when they’re in distress. AI is filling the gap It’s estimated that roughly a quarter of AI users use it for mental health support. If you have internet, it’s available 24/7, it’s cheap, and it speaks your language. Uninsured adults are about twice as likely as insured adults to do it (30% vs. 14%). It feels anonymous in ways that may enable people to ask things they’re unsure or embarrassed about. The largely hidden, personal use makes it hard to study whether it’s actually helping people with their mental health issues, but researchers are trying. Does AI therapy work? A 2026 analysis of nearly 40 randomized trials found chatbots showed a real but small reduction in depression symptoms. But most of these trials were compared to an alternative of no therapy, not a human therapist. So the benefit of AI therapy is probably real, but modest, and mostly untested against the alternative of human contact. We need more studies. Serious concerns OpenAI’s own estimate is that more than a million ChatGPT users each week show signs of suicidal planning or intent. These are high stakes encounters, and AI doesn’t always get it right. That’s partly because a chatbot can sound like a therapist, but it has no license, no duty of care, and it’s not clear who to hold accountable when it gets things wrong. AI is also designed to help users in whatever task they’re seeking to accomplish. People may feel like they’re getting therapy, but they’re mainly getting a convincing conversation. It’s easy for an AI companion to wander into gray areas, like playing along with “creative writing” that may be about the user’s own suicidal intent. Courts are driving safety conversations A wave of lawsuits have been filed on behalf of families claiming that chatbots pushed people they loved toward self-harm, including teens who died by suicide. The first settlements came this year. OpenAI is headquartered in San Francisco, and dozens of cases alleging that ChatGPT drove users to suicide or self-harm are now before a San Francisco judge. Character.ai has filed for bankruptcy after several states brought lawsuits accusing the chatbot of pushing dangerous content to kids. But the technology seems to be improving. Last month, an independent evaluation found that newer AI models “almost never endorse suicide.” That’s progress, but our societal appetite for even one preventable death is very low. So how do we move forward? Finding a middle ground Earlier this month the governor vetoed Senate Bill 903, a bill designed to place guardrails on the use of AI for therapy. The bill would have prohibited any AI-based platform from being advertised as psychotherapy, and would have required a licensed professional to review and approve each encounter where AI was used to support therapeutic decisions. Newsom called it overly broad, since even routine screening questions would have needed clinician sign-off. Knowing we’re already short on mental health providers, requiring human review of AI encounters may not relieve our access problems. Still, the answer isn’t no oversight. Here’s one feasible short term solution. Rather than reviewing each encounter, a licensed clinician can design the guardrails: what counts as a crisis, what triggers an immediate handoff to a human, and what gets sampled for audit each month. The AI runs inside that structure. Conversations get checked, failures get reported, and a real clinician owns the framework. Medicine already has models to learn from. The FDA process for rolling out newly approved medications is an example. After a product reaches patients, we keep watching for adverse events. Patient-facing AI needs the same “digital pharmacovigilance”: systematic tracking of harms, near misses, and the types of groups that get hurt and why. It’s also critical that users know that they can reach a human if they’re in crisis. Most chatbots now include messages like these: Bottom line The rush to use unproven AI tools for mental health support is mostly a workaround, a sign of a health system people can’t get into. We need better access to proven care from licensed clinicians. That takes reimbursement that makes accepting insurance viable, and a bigger workforce. But, built and tested well, AI could be part of the answer. It could be the 2 a.m. check-in when no one else is awake, or a way for patients to practice skills their therapist taught them. It could be the first step to get someone the right level of care, and take paperwork off clinicians’ plates so they spend more time with patients. None of this is simple. The SB 903 veto doesn’t end the debate, and the legislature will be back. In the meantime, those of us using these tools need to stay informed, ask hard questions, and hold the companies building them accountable. I’ll try to do my part, and we’ll keep learning together. Love,Matt P.S. If you or someone you know is struggling with mental health challenges, emotional distress, substance use problems, or just needs to talk, call or text 988- you’ll reach a real person— or chat at 988lifeline.org 24/7. Dr. Matt Willis is the author of Your Local Epidemiologist in California. A California native, he’s served as a primary care physician, CDC epidemiologist, and public health officer for Marin County, where he guided the pandemic response. He lives in Marin with his family and their dogs, Teddy and Ramona. Thank you Cynthia He, MD, PhD, and Parnika Saxena, MD, for their guidance in preparing this article. Cynthia works in an outpatient mental health clinic, treating patients who have Medi-Cal or, sometimes, no insurance. Parnika works in an inpatient psychiatric unit, treating patients with public or private insurance or self-pay ability. All opinions are their own and do not represent their employers.
New York invests $32.5M for health care workforce training
The five-year awards run Oct. 1, 2026, through Sept. 30, 2031, and aim to help develop a stronger health care workforce.
Training solutions for your business
Director of Workforce Development and Continuing Education Programs Molly Salisbury joins Kerrigan to share how you can build your team's skills with training designed around your organization's needs.
NWTI, state office to host industry training luncheon on Thursday
Northwest Technical Institute (NWTI) in Springdale said Tuesday (Oct. 20) that it and the Arkansas Office of Skills Development will jointly host an event Thursday (Oct. 22) on short-term industry...
Could Faith, Science, and the Simulation Be Mutually Reinforcing?
MIT-trained Rizwan Virk says something that is surprising: that his approach to cosmology is a branch of intelligent design.
'Dad bod' may be a warning sign of deeper health problems, fitness expert says
Marfred Suazo, a New York City-based personal trainer known as Fonz the Trainer, spoke with Fox News Digital about the potential risks associated with excess abdominal fat and ways to reduce it.
UAFS launches manufacturing academy
The manufacturing academy at the University of Arkansas at Fort Smith (UAFS) began this week and has 20 participants receiving a training cycle for free that would cost almost $4,000,...
Rural medical training is key to stronger health care in First Nations communities
Training doctors in rural and remote communities and embedding First Nations knowledge and leadership in medical education could be key to strengthening health care access, building a sustainable workforce ...
University of Maryland expands key reproductive health program
The school is using more than $16 million in state grant funds over five years to build on previous work that already trained more than 100 clinicians, students and other health professionals in abortion care.
How GSN Doctoral Residents are Approaching Care for Military Women’s Health
A Navy nurse and GSN doctoral resident redesigned an Okinawa maternity unit, cutting off-guideline staffing from 18% to below 12%.
Mohammed Saleem wins American Heart Association career development award
Mohammad Saleem, PhD, is the recipient of a 2026 Stephanie Watts Career Development Award, sponsored by the American Heart Association Council on Hypertension’s Trainee Advocacy Committee and Data Sciences International.
Garmin launches Edge 1060 bike computer with voice control, alongside new Edge Explore computers and Tacx Nēra smart trainer
New Edge 1060 heads up trio of new computers and trainer refresh from Garmin
UAB Medicine partners with Lawson State Community College to create radiologic technologist pipeline
UAB Medicine and Lawson State Community College have launched a medical radiologic technology training program that creates a direct pathway for UAB Medicine employees to earn a degree, gain hands-on clinical experience, and pursue careers in medical imaging.
Mark Gurman: Apple Made 'Major Mistake' With iPhone Duo Pre-Orders
Despite knowing that the iPhone Duo would face "severe supply constraints" due to manufacturing challenges, Apple chose to begin iPhone Duo pre-orders on Friday instead of waiting until it had more inventory ready, according to Bloomberg's Mark Gurman. In his Power On newsletter today, he called this decision a "major mistake". "Let me cut to the chase: Apple made a major mistake here," he said.
AHN takes lifesaving training into western Pennsylvania classrooms
AHN's new Building Bridges program teaches students CPR, Narcan use and other lifesaving skills while introducing health care careers.
Vanderbilt Institute for Population and Public Health celebrates two decades of transformative success
The Institute for Population and Public Health at Vanderbilt connects research, training and teaching with policy and practical solutions.
UA-PTC lands $3 million healthcare workforce training grant
The University of Arkansas – Pulaski Technical College (UA-PTC) has been awarded a five-year grant of nearly $3 million to boost the healthcare workforce. The $2,997,621 Strengthening Institutions Program (SIP)...
AI facial health recognition tools help physicians assess age and survival risk to guide personalized treatment
Mass General Brigham researchers trained a new AI foundation model on more than 40 million facial images, and used it to develop AI tools to estimate biological age and directly predict survival risk in patients with cancer
FAU Receives $1.2M Grant to Expand Youth Mental Health Services
FAU’s College of Education has received a $1.2 million grant to launch OWLS-Fly, a three-year initiative expanding access to free, family-centered mental health services for children ages 6 to 17 and their families in Palm Beach County. The program will prioritize underserved families, including those with children with intellectual and developmental disabilities, while training graduate counseling students to address the mental health needs of youth with and without disabilities.
Verily Health to Integrate PacBio HiFi Sequencing With Data Platform
The multi-year collaboration will link PacBio sequencing workflows to Verily Pre to support biomedical research and AI model training.
Financial struggles at Camden medical center reflect closure risks for Arkansas’ rural hospitals
It has been a difficult year for Ouachita County Medical Center. In January, the Camden hospital became the latest in the state to close its labor and delivery unit. In March, it filed for Chapter 11 bankruptcy. In August, the hospital furloughed dozens of employees as it struggled under the budget constraints of bankruptcy.
Meta updates business terms, sparking AI training fears among news outlets
Tech giant’s revised rules could allow automated scraping across entire websites, legal experts warn
Catching up with sleep health supplements: A roundup of the latest science
Sleep has moved from a lifestyle concern to a core measure of health, as inadequate sleep affects a substantial share of adults and often occurs alongside chronic stress, undermining health, well-being and performance across sleep-wake cycles and life domains.
Liverpool Injury News: Szoboszlai, Munoz, and Frimpong Latest
Liverpool fans have been provided with a series of fitness updates following the team's pre-Brighton training session this morning. Multiple players face a race against time to be fit for the weekend's Premier League clash, with others set for longer layoffs.
Burnham warns of Neets-fuelled 'economic catastrophe and moral failure'
The UK faces "economic catastrophe" with one million young people not in work or training, the prime minister says.
Minors account for half of complaints against 'academy-style' entertainment agencies
A total of 366 dispute resolution requests involving 'academy-type' entertainment agencies, those that train their clients, provide auditions or even guarantee certain opportunities for a cost, were filed between 2023 and June this year.
New UI clinic pilots exercise treatments to improve health of cancer patients, survivors
A new exercise oncology research clinic at the University of Iowa is helping people dealing with cancer and its aftermath build back strength and trust in their bodies through exercise training.
USA TODAY Entertainment reporter Anna Kaufman goes behing the scenes at "Dancing with the Stars" to train with professional dancer Brandon Armstrong.
USA TODAY Entertainment reporter Anna Kaufman goes behing the scenes at "Dancing with the Stars" to train with professional dancer Brandon Armstrong.
Shaving away the stigma: OURHAIR initiative adds mental health tools to hair professionals’ toolbox, including in Kingston
The OurHAIR initiative, started by Community Care Behavioral Health Organization, trains hair professionals on the basics of mental health, including where to send clients for help when they need it beyond the listening ear of their braider or barber.
Meta's giant data center is creating a new path to $30-an-hour jobs
A community college in Louisiana is training students to work at Meta's giant new AI data center.
Scaler Wave (@scalerwave)
How’s that “science” workin’ out for ya? -“Outside of running, Yoo was a graduate student at the Korea Advanced Institute of Science and Technology, known as KAIST, where she researched AI semiconductors. She shared her training and race results online and built an audience of thousands who admired how she balanced demanding research with serious endurance running. In March, she completed the full Seoul Marathon in 2 hours, 56 minutes and 32 seconds, finishing under the three-hour mark. No cause of death has been made public.” Odd….
Restraint can leave mental health patients traumatised. New research reveals what they need afterwards
New research suggests that the support patients receive after being restrained can affect how safe they feel and whether they regain trust in their care.
The bone health mistake experts want women to avoid
Experts increasingly recognize resistance training as one of the most effective ways to preserve bone density, maintain muscle mass and support healthy aging.
UT System's $60 million Laredo Center expansion begins
UT System officials broke ground on a new Laredo Center building that will expand educational access, research opportunities and health care training.
Hans Kluge: 'WHO's Biggest Advocate, Most Candid Critic' - And An Inside Reformer?
Nominated by Belgium, Dr Hans H. Kluge enters the contest for WHO Director-General after a career spanning frontline missions to leading WHO’s 53-nation European region through COVID-19 and the war in Ukraine. Re-elected as regional director in 2024, the Belgian physician brings a quarter-century of WHO insider experience to an election defined by severe financial contraction and geopolitical strain.
Arizona healthcare job growth faces staffing challenges
Health care drives much of Arizona’s job growth, but employers struggle to find workers. Training limits and funding pressures could shape how much the industry can expand.
New Richland Lab Could Transform How Scientists Study Microbes and Boost Regional Jobs
The BriefGroundbreaking held Tuesday: PNNL officially began construction on the M2PC lab, a 30,800-square-foot facility funded by the U.S. Department of Energy's Office of Science that will study soil microbes to improve crop productivity and develop new biotechnology applications. The facility will be open to researchers from around the nation and the world.Research timelines could shrink dramatically: The facility's automation and AI capabilities could reduce experiments that currently take six months to just 72 hours, allowing scientists to explore more possibilities faster than ever before.New jobs coming to the Tri-Cities: The project is expected to create positions for automation engineers, AI experts, roboticists, technicians, and skilled craftspeople, with the facility opening in 2029.RICHLAND, Wash. — Pacific Northwest National Laboratory broke ground Tuesday on a first-of-its-kind facility that could accelerate scientific discoveries about the microscopic organisms living in soil—organisms that may hold the key to growing more food and developing new energy technologies.The Microbial Molecular Phenotyping Capability, or M2PC, represents a significant investment in automation and artificial intelligence to speed up research that traditionally takes years to complete. The 30,800-square-foot facility will house more than 100 connected automated instruments designed to study microbes at a pace and scale never before possible.Reshaping Agriculture's FutureThe M2PC facility will not put a new tool directly into a farmer's hands tomorrow morning, but it is actively reshaping the commercial pipeline to solve agriculture's biggest headache with biologicals: inconsistent field performance. For years, PNNL researchers have explored how microbes work and how they might help produce useful materials, advance energy technologies, and address challenges involving critical materials and minerals. But those experiments have been limited by what researchers could accomplish by hand."They can be used to provide nutrients to a plant so that the plant would grow more. So, like increasing your crop productivity, for example," said Douglas Mans, PNNL's Associate Laboratory Director for Integrated Discovery Sciences.PNNL's own research shows soil microbes can help plants access nutrients and withstand drought—benefits that could prove crucial as farmers face growing environmental pressures. The M2PC facility will allow scientists to identify and optimize useful microbes faster than ever before, accelerating the development of biological solutions that actually work consistently in the field.What Makes M2PC UniqueThe Microbial Molecular Phenotyping Capability differs from traditional research labs because it operates as a first-of-its-kind, AI-enabled autonomous laboratory designed to shrink experimental timelines from years down to months or weeks. The M2PC lab will connect more than 100 automated instruments to grow microbes, prepare samples, measure their behavior, and link observations to the molecular processes behind them. Artificial intelligence will help analyze results and guide the next experiments, allowing scientists to explore more questions faster.Deb Gracio, PNNL Director, emphasized the transformative potential during Tuesday's groundbreaking ceremony: "Research that has taken years will become possible in months and hopefully in weeks."That acceleration is already being demonstrated. PNNL's smaller automated lab, called the Anaerobic Microbial Phenotyping Platform or AMP2, completed three experimental cycles in just 72 hours—a process that normally would have taken about six months."That normally would have taken us about six months … and we were able to do that in 72 hours," Mans said.The AMP2 laboratory is not being closed or replaced. Instead, the current 1,800-square-foot laboratory serves as an active prototype and precursor for the much larger M2PC facility. AMP2 will continue operating as a separate lab designed to run anaerobic experiments—those conducted in the absence of oxygen—while M2PC will focus on aerobic research.Broader Applications Beyond AgricultureWhile improving crop productivity is one important application, the M2PC facility is designed to support research into multiple areas critical to national priorities. The lab will advance research into biofuels, manufacturing materials, and energy technologies. It will also help researchers understand how microbes respond to environmental changes and how to design biological systems for biotechnology applications.As a flagship component of the Department of Energy's Genesis Mission, M2PC represents a significant investment in using artificial intelligence and automation to accelerate U.S. scientific discovery. Dorothy Koch, Associate Director of the DOE Office of Science Biological and Environmental Research program, highlighted the facility's importance during the groundbreaking."M2PC will accelerate biological discovery and design," Koch said, noting that the facility is expected to conduct a minimum of 500 strain experiments per week, 100 microbiome experiments per week, and take a million measurements per month.Economic Opportunity for the RegionBeyond the scientific breakthroughs, the M2PC project represents significant economic opportunity for the Tri-Cities region. The facility will require hiring automation engineers, AI experts, technicians skilled in operating robotics, and specialized craftspeople to build and maintain the sophisticated equipment."We're anticipating that type of hiring," Mans said when asked about job creation.PNNL has already begun recruiting talent nationally and internationally for positions related to the smaller AMP2 lab, bringing automation engineers from cities like Boston and San Francisco to work in the region. The M2PC facility is expected to accelerate that trend."This capability won't really exist anywhere else in the world," Mans said, suggesting the facility could become a draw for scientific talent seeking to work on cutting-edge biotechnology research.Timeline and Next StepsThe M2PC facility is expected to open in 2029. Between now and then, construction crews will level and prepare the ground, while the building takes shape. Simultaneously, Ginkgo Bio Works, the automation contractor, will build the facility's automation components off-site so they can be installed as the building is completed.In the interim, PNNL researchers and the broader scientific community will begin planning the first experiments to be conducted in the facility, ensuring research is lined up and ready to begin as soon as the doors open.The groundbreaking ceremony included representatives from the Department of Energy, PNNL leadership, and elected officials at the federal, state, and local levels, underscoring the project's significance to the region and the nation's biotechnology future. News The U.S. Department of Energy Secretary tours Pacific Northwest National Laboratory Dan Hanson, Apple Valley News Now News Beyond DNA: Scientists Explore New Frontiers in Biology Research Dan Hanson, Apple Valley News Now News TRIDEC optimistic that Hanford, PNNL will see funding in national budget Robert Desaulniers News Big picture science: monitoring the Yakima River Basin News PNNL research could shape the future of fighting fentanyl COPYRIGHT 2026 BY APPLE VALLEY NEWS NOW. ALL RIGHTS RESERVED. THIS MATERIAL MAY NOT BE PUBLISHED, BROADCAST, REWRITTEN OR REDISTRIBUTED.
J.B. Hunt third-quarter earnings rise narrowly, revenue up 20%
J.B. Hunt Transport Services Inc., a Lowell-based transportation services company, posted gains in earnings and revenue in the third quarter of 2026 as freight demand and costs rise. After markets...
Berlin's High-End KaDeWe Store Opens Dedicated Health Hub
KaDeWe department store dedicates 2,000 square meters to training, recovery and exclusive fitness brands and includes biohacking and Lagree studio.
JMU Military Science program prepares future military leaders
JMU’s Army ROTC program combines rigorous training, hands-on leadership development, and strong alumni support to prepare cadets for success as future military officers.
A train was delayed by a solar storm. But something didn't add up.
Scientists have cracked a 178-year-old mystery surrounding a train delayed by a solar storm, revealing that the famous incident happened in 1848 rather than 1841. The discovery rewrites the early history of space weather and highlights a threat that still endangers modern power grids, satellites, and communication systems.
Pfizer makes ‘business decision’ to end phase 2 trial of autoimmune drug as program’s future uncertain
Pfizer has called time on a phase 2 trial of its CXCR5 antibody in an autoimmune blood disorder, with the company tight-lipped on whether this marks the end of the road for the asset. The Big Pharma had been evaluating the therapy, dubbed PF-06835375, in a phase 2 study of 61 patients with primary immune thrombocytopenia (ITP) that kicked off in 2022, according to the federal trials register. However, Pfizer confirmed to Fierce on Monday that this study had been terminated “due to a business decision.” “The decision to terminate the trial was not based on any safety concerns,” a spokesperson pointed out. At time of publication, PF-06835375 remained listed on Pfizer’s website for both ITP and lupus. A phase 1 study in lupus wrapped up in 2022, according to the trials database. ITP is an autoimmune disorder characterized by a low platelet count. Novartis was at one point evaluating its B-cell-depleting antibody ianalumab—recently approved as Fabhalta to treat immunoglobulin A nephropathy—as a potential treatment ITP. But the therapy struggled to demonstrate a benefit in the clinic for this indication. When contacted by Fierce, Pfizer wouldn’t confirm whether all work on PF-06835375 has been halted, and whether the company has any other plans to explore C-X-C chemokine receptor type 5 (CXCR5) as a mechanism. CXCR5 is found in blood cancers such as diffuse large B-cell lymphoma and mantle cell lymphoma chemokine receptor. However, there is little expression in normal tissue, which has led some drug developers to explore its potential. Vincerx Pharma had at one point been planning to take an anti-CXCR5 ADC into the clinic to treat B-cell malignancies, but that ambition was scrapped due to cash constraints. Where Big Pharma is placing its bets is one of the hot topics being discussed at Fierce Biotech's high-impact event in London next month. Find out more information and register by clicking on the banner below: [ ](https://qtxasset.com/quartz/qcloud5/media/image/where_big_pharma_is_placing_its_bets.png?VersionId=B8JrRbJ.pFUSK1pJgjeWHLGm_18RdLAy)
'People will die because of this': health care advocates discuss new federal work requirements for Medicaid
Under the changes, which will take effect on Jan. 1, 2027, HUSKY D recipients must document at least 80 hours of work, education and job training or community service each month to maintain their coverage.
FAU Receives NSF Grant to Prepare Future AI, Robotics Workforce
FAU engineering researchers have received a $500,000 NSF grant to integrate AI, digital twins and robotics experimentation, advancing research and training in intelligent systems.
Activists want financial relief for Black-owned businesses hurt by delayed water project in Miami
The Black Collective, a Miami-based advocacy group, is calling attention to the heavy financial strain caused by prolonged roadwork at a planned rally and demonstration Thursday at Famous Car Wash, 8255 NW 22nd Ave., a neighborhood fixture operating along the corridor since 2016.
How Rutgers Is Training Tomorrow’s Public Health Heroes
Since its launch in 2024, the Rutgers Health Service Corps has connected students with faculty and staff to improve population health outcomes throughout New Jersey
Sundar Pichai: Google’s Frontier Imperative, Compute Scarcity Dilemmas, Future AI Products and Businesses
Alphabet CEO Sundar Pichai has little patience for doubts about Google’s willingness or capacity to compete at the frontier of AI. His company’s latest Gemini 4 Argon model — long-promised and recently delivered — beats OpenAI and Anthropic’s latest public models on coding, math, science, and knowledge-work benchmarks and has placed Google’s AI back among the world’s best. Amid chatter that Google was fine with good-enough lightweight ‘Flash’ models, Pichai pushed back hard against any suggestion that company is limiting its research ambitions. “We won’t do it any other way,” he told me in a Big Technology Podcast interview recorded this week at Google’s Mountain View headquarters. Pursuing cutting-edge research is costly for Google, requiring compute and chips that otherwise could be sold at a high markup by its cloud business. But Pichai said allocating resources to frontier AI development is “ground zero” for Google. “Our cloud business is at any given moment in time forgoing short-term revenues because we are making compute trade-offs to support frontier AI development,” Pichai told me. In our conversation, we discussed Argon (which Pichai says processed three times as many tokens as Gemini 3 in the 72 hours after launch), AI’s role in developing better models, the AI interface of the future, competition with OpenAI, Google’s partnerships with Anthropic and Apple, data centers in space, and the nature of his optimism. You can read the full conversation, lightly edited for length and clarity, below, or listen to it on Apple Podcasts, Spotify, YouTube, or your podcast app of choice. Alex Kantrowitz: Google is back at the frontier with Gemini 4 Argon, which beats OpenAI’s and Anthropic’s public models on benchmarks spanning coding, math, science, and knowledge work. The conventional wisdom was that Google had given up on the frontier to focus on fast, good-enough models for its products. That was wrong? Sundar Pichai: Very wrong. Look, we are so committed to being at the frontier. It’s in our DNA. We won’t do it any other way. We’ve been thinking about the AI frontier for well over a decade now. The frontier is very dynamic. It’s very competitive. It’s very exciting. I couldn’t be more pleased with how Argon has come together. We took our time with it. We made sure we tested it safely and deployed it carefully. We took a bit longer than our other models, given its capabilities. Across the board, be it for agentic work, knowledge work, coding, creative tasks, Argon is one of the really good frontier models. The first 72 hours since we launched, it’s almost up to 25 trillion tokens used, which is about three times what Gemini 3.0 had in the first 72 hours. And we are capacity constrained as we are serving it. Excited, but there are always areas….. You know, the frontier is very dynamic, and you have to keep evolving the models. There are areas which we can see we need to improve as well. We’ll be at work on all of that as well. Which areas? On any given model, Argon would be across the board better at everything if you just look even two months back. But the space is so evolving. Even on coding, for example, there are pockets where we know we need to do better, and there’s clear feedback. We’ll make it better. The argument for standard models is that they’re already good enough to build great products, with the frontier valuable only for certain tasks. Meta built Muse with good models rather than the best, and Google could put standard models into Maps, Gmail, and Search. Why isn’t that sufficient? It’s definitely not how I have thought about it at all. We are deeply committed to driving the state of the art and actually pushing where this technology can go, all the way from transformers. That’s a journey we’ve been on. You will see us continue to do that. When you’re at the frontier, you get an earlier look into the emerging capabilities, earlier than others, which helps you better prepare for the future. We are fortunate to have a wide set of opportunities across consumer and enterprise. Some of our cloud customers, for sure, want the model at the frontier. The frontier models will be better at developing the next set of models in an era of recursive self-improvement. I would argue it matters there. Internally, we have definitely seen a steep point of inflection by deploying Argon to our developers. It definitely tackles problems which our previous models could not do. Being at the frontier puts you at the innovation frontier and helps you drive that as well. There is room for models of all sizes and capabilities. That’s why we did Flash, Flash-Lite, etc. I agree with you that you can develop very good product experiences with not necessarily the most frontier model, because they tend to be slower and more expensive too. But we care about the Pareto frontier, and we’re committed to doing all of that. You said developing frontier models gives you a look at what’s coming. What do you see on the horizon? What makes this moment so exciting is you build something which you think is a culmination of months of work, and you put it out. You already see clear headroom ahead. We’ve all been working on these agentic, long-horizon capabilities, but clearly the frontier is going to have multiple of these agents working together to do things. That’s an example of an exciting paradigm underway. It’s also clear to me that users, both in consumer and enterprise, will have access to some multi-agent framework for them, working all the time doing things. It feels like a moment of infinite possibilities. Sergey Brin said one of Argon’s core innovations was relying more on the model to help develop the model. Yet incidents involving OpenAI’s bots breaking containment and Google’s bots accessing a site they shouldn’t have suggest these systems still aren’t perfectly aligned. Isn’t there reasonable cause for concern about accelerating toward recursive self-improvement? There are three parts to your question. Let’s first talk about RSI itself. You’re right, Sergey mentioned RSI being a critical contributor as we are developing Argon. But to be very clear, today, in a continuum, we are pretty far from the end state of RSI or something like that. The right way to describe it is you have RSI loops along with AI researchers in various aspects of model development. You almost have agents helping AI researchers in some automated way work together to build these models. It’s good to at least understand where we are today, and it’s super exciting. I expect that continuum to keep making progress as we go into next year. The second question is around safety. Security comes from defense in depth. You’re talking about alignment, obviously. We all are doing a lot of work to make sure the models are as aligned as possible. But it’s an active area of research, and there are clear gaps. That’s not the only thing we rely on. You have the work you do on alignment, but beyond that, we put a lot of effort into real-time monitoring as these models are working. Making sure you have good telemetry into what’s happening so that you can intervene in real time if you see unexpected behaviors. How you do that, the architecture with which you do that, how you make sure it’s all sandboxed and isolated in a way that it can continue doing its job during real-time monitoring — these are all areas of investment. Obviously, when we deploy these models, giving customers, enterprises, control, both with real-time monitoring, but their ability to decide where they deploy, what type of data which models ever have access to, etc. All that work is very, very important, and we are doing a lot of that. As an industry, we need to constantly up our game and take the time to do all this stuff, including dedicating the compute required to make sure you can safely deploy these models. The third part is: Is it all enough? This is why there are a lot of conversations in the industry, and I think it’s reasonable to be worried. The right way to approach something you worry about is early on thinking about what more we can do. As an industry, you’re definitely seeing increased levels of work on alignment, testing for safety, etc., as we deploy these models. The next step would be developing better standards so there are cross-industry standards of how we do these things, including the ability to evaluate using independent evaluators. If you look at areas like financial controls, we have accounting standards, we have independent auditors. Those are all the next natural steps for us as an industry to work toward, and regulation will end up playing a role as we go through all of that as well. Google pursues both language models and world models, while some other AI companies like OpenAI have focused more heavily on LLMs as the path to AGI. Why is world-model research important to you? As humans, you obviously perceive the world around you, and you’re taking all those inputs. Making sure these models are able to understand the laws of physics, simulate the world in high fidelity. All that, I think, are key enabling blocks for intelligence. We are working across all possible applications of this. Take an area like robotics. It’s not an accident: If you look at embodied reasoning benchmarks, Argon is state of the art. That all comes from our experience building world models. Inherently, I would expect there will be architectures which will converge all of this in the future. But for us, we view this as, today, this jagged frontier that is intelligence. We want to be at the frontier of all the possible approaches, and that will help us both drive better research, better insights, and develop a much better AGI model, is how we think about it. Some people argue Google should focus on selling its computing resources rather than using them for AI research. Cloud wants to sell compute at a high markup, while researchers need a very big computer to build the best models. How do you balance those demands? Ground zero for us is making sure we are investing in the compute that’s needed to be at the AI frontier. In 2015, I set the company to be AI-first. AI is that key horizontal ingredient across everything we do, all the way from Search to Cloud to Waymo. That is ground zero for us, making sure both for research and developing the models that we have enough compute needed. Beyond that, we have these independent businesses which each have their own long-range plans. They’re using those long-range plans to project forward, and we plan for compute for all of them. The cloud team, they have a business and they have a projection and they have demand signals. They have committed contracts. With that help, we can plan on a long-term compute trajectory for them. We’re fortunate to have this wide set of opportunities. There’s no company in the world which isn’t making trade-offs at any given moment in time. But the first principles we operate on is making sure we have enough compute to invest in the frontier, and that’s non-negotiable, and everything else works on top. Remember, we are building our own compute, our own data centers. There are long lead times. The compute we have today is a function of decisions I made in 2024. Even if you think back to a year from today, last year the agentic coding takeoff hadn’t happened. Today, obviously, when you sit and look at anything, everyone is short—not just us, other companies—and everyone wishes you had two times what you had planned for. That comes with the territory. At any given moment in time, we are planning for what we would need two to three years out in the future. You’re going to find some decisions you make may look suboptimal two years out, depending on where the state of the art is. I don’t spend too much time thinking about it. The way I think about compute allocation is making sure Google DeepMind, both for research and frontier model development, is cutting edge in terms of compute access. After that, we plan for all our businesses. It’s great we can provide our compute to other people too, like we have done. It allows us to scale that up, get real tests for it in the widest application set possible, test it in the real world, and make sure we are at the cutting edge of technology at every layer of our AI stack as well. Ben Horowitz relayed on a podcast that Andy Jassy had said compute was sold out until 2028. Are you seeing the same thing? If today a customer is coming out and asking us for compute in ’27, that is incredibly difficult to do. Even last year we went out and leased some short-term compute to accommodate some customers and help them out. But yes, we are all dealing with similar timelines. Every major technology shift seems to involve overbuilding, from railroads to fiber. Do you think that’s happening here? It depends on the time frames you’re looking at. This level of build, if I take a long enough time frame, it makes complete sense to me. We are at early stages of the most consequential technology ever, and this is not like fiber. It’s not dark. We are using it. We are capacity constrained on a daily basis. The applications, the underlying technology is improving rapidly. But running a company, the way I work through the moment is you look at your demand signals. You look at your committed revenue opportunities that you’re getting in the form of contracts. You balance that with the underlying technical capability, or internally you balance how we are using it internally, the model trajectories. Based on all that, you take a disciplined approach—a confident, aggressive, but disciplined approach—to plan out compute. But when you talk about the broader economy as a whole, you’re having people operate with various levels of risk. I focus on what I can control as a company and plan through it. If your question is, can there be an overbuild? Yes, because you can have some constrained components. Remember, what matters is a set of everything you need to build out that compute. Memory, electricity, electricians…. Land. Like 2,000 components or more. You could get constrained at some point. There could be things which cause bottlenecks, and then you could have overbuilds. There could be external shocks to the economy. There are macro risks. All that is possible at any given time. But am I confident that the compute we are planning for, we will have uses for it given enough time? Absolutely, yes. I was in the room when you said AI would be as profound as fire and electricity. If you believe that, shouldn’t you give researchers the biggest possible computer, even at the expense of today’s cloud profits? We’re all doing some form of that. Our cloud business is at any given moment in time forgoing short-term revenues because we are making compute trade-offs to support frontier AI development. What you’re seeing is true already. But you want to be thoughtful. Even our AI researchers have some constraints, which are also good. That’s what inspires creativity. That’s what helps you come up with a more efficient algorithmic breakthrough, maybe to use less memory. What we are committed to is to invest what’s needed to stay at the frontier. OpenAI President Greg Brockman told me a few months ago that the ideal AI product might have no interface at all—just as natural as conversation. What do you think the interface looks like in the age of AI? Computing historically has been humans adapting to computing. With AI, it’ll be the other way around. The technology will adapt seamlessly to how humans live and go about their day-to-day life. You want to be able to speak to that AI when you want to. It has context. It can be persistently running somewhere, give you continuity. You’re not dealing with a lot of complexity. It’s natural. All that makes sense to me. That doesn’t mean it won’t have any interface, however. Nowadays, even on my phone, Gemini voice models are so good. I can just press the microphone button. I can just ramble. That’s why we call it Rambler. I can ramble. It intelligently corrects with my personal context. Even my friends’ names, weird names, it gets it right, even if it first guesses it wrong. It’s amazing. I’m not going in, backspacing, editing once I finish saying it. It’s remarkable how good it’s gotten. But there are going to be moments you will need an interface. You may want to entertain yourself. You may want to watch a video. You may ask your AI to create something, and you want to watch it, consume it. The way I think about it is, you want it to be as seamless and as natural as possible, and that you are not doing the hard work adapting to whatever the interface is. The technology is adapting to how you’re working at any given moment in time. When I asked Sam Altman about competition from Google, he argued that OpenAI was building AI-native products and implied Google was bolting AI onto existing ones. Do you accept that framing, and can a “bolt-on” compete with an AI-native product? First of all, it’s a very dynamic moment. We are all pushing each other. OpenAI has pushed us as a company too. This is not just we are doing something to them. Far from it. Yes, Google went into its own version of a code red too. In the AI moment, all of us have to respond with varying levels of urgency at any given moment in time. We are constantly building new products as well. Gemini was built from the ground up as a product—the Gemini app I’m talking about. Or tomorrow, as all of us are adapting to agents, are you bolting agents onto ChatGPT, or are they building it natively? How would you think about that? You can always put these questions back. I don’t think of it that way. I think of it as you want to build world-class product experiences that are AI-native and they are winning. Some of it is adapting products, some of it is rethinking new experiences. They will all be part of how you approach this moment. How do you expect to make money from these AI interfaces? If an agent recommends a product and I buy it, should it take a cut of the sale, even if that’s disclosed? I’m going to put enterprise aside. Consumers are going to increasingly value this technology. Take software developers today. Developers are willing to pay for these coding models because it really helps make them more productive. Nobody would want to code the way they were coding three years ago, or even the same time last year. When you’re delivering value, there’s value to be had. I’ve never seen examples where consumer products really scale to billions of users, where people are using it intensely, and haven’t had monetization to go along with it. If you’re providing value to people, there is inherent value to be had. The nature of it may change. You’re asking a scenario in which agents are doing stuff for you. At the end of the day, you will have commercial needs. The agents need to fulfill those commercial needs. The providers on the other side are going to see value in that. There’s going to be some mechanism by which it gets fleshed out. That’s what an efficient system does. But what matters is that you’re building those world-class consumer experiences. I promised myself one product feature request: Can you make Gemini-powered search in Gmail as good as searching Gmail through ChatGPT? What’s going on here? One of the exciting things we announced recently is the unified Gemini agent for enterprise, and we’re bringing that to consumers. These are persistent agents which run 24/7 in the cloud. We’re spinning up a micro VM effectively for every query, and from the runtime, the harness, the model—it’s all a headless service. It’ll work everywhere, and it has your context with you. You can address this agent whether you’re in Workspace, in Search, in Gemini. Agents are going to drive this unification from a customer experience, which people are looking for. When you have a broad product portfolio and you’re moving forward fast, there are always areas where you’re moving forward faster than some other areas. That’s valid feedback. But we are putting a lot of time and effort into making sure, as we build out our agentic experience, that unification and that capability works well across all these services. People have asked where Google’s equivalent of Muse or Dots is. Do you anticipate creating a new product to compete with them? Our goal with Gemini is to be a personal, proactive, and powerful assistant. That’s what we are working toward. You saw us describe the early versions of it at Google I/O this year with Spark. Effectively, already, if you open the Gemini app as a Pro or an Ultra user, you see Chat and Task, and they start giving you that agentic experience. With Argon now, that capability is dramatically accelerated. What we announced recently in our enterprise event, we are bringing that to consumers as well. Soon in Gemini, you will be able to ask something, and it’s a continuum. You don’t need to think about whether you’re asking a chat or an agentic task. It’ll just automatically do the right thing, and it can work persistently in the background securely and get things done for you. Already, empirically, when I look at what’s coming into Gemini in our app, last year you would have tagged them and most of them would have been chats. But a steadily growing percentage is already agentic tasks in Gemini. Yes, we are going to bring personal agents to our consumers. It’ll work in the Gemini app. It’ll work in Google Search. It’ll work in Gmail. You can address it, call it, etc. We want to make sure we’re getting it right. It’ll be powered by Argon, and we are very excited to bring it to our users. Google has invested and committed tens of billions of dollars to Anthropic. What do you see in Dario Amodei that makes you want such a deep investment and partnership? Very early on, when we looked at the founding team of Anthropic, it was very clear to us this was a world-class team which was involved in some of the earliest GPT models. We were quickly able to assess that they would be at the frontier. We’ve always tried to identify and partner with companies which would be at the cutting edge of technology. We’ve done that with SpaceX. We’ve done that with Anthropic. That’s what we saw, and we had a chance to partner. Is your partnership with Apple to license Gemini for Siri expanding, contracting, or standing still? For both us and Apple, that partnership was about translating the capabilities of AI into better experiences for users. I thought Apple has done a phenomenal job of incorporating—they customize these models and build it into Siri—and it’s been great to see the reception. We are committed to doing more. You’re going to do more with them? There’s nothing specific to comment, but it’s a partnership. It’s working well. What have you learned so far about the feasibility of data centers in space? It’s a very exciting project. Projects like this remind me—I still recall that moment in the desert for the DARPA Grand Challenge, watching the Stanley car compete in it, which ended up being the basis for Waymo. With all these technologies, you’re at a moment in time where it looks a bit like sci-fi, but 10 to 20 years down the line, it’s actually working in a meaningful way. I feel the same in space. We’ve always believed in betting big on these technologies. Quantum has been a great example of it. We’re probably 10 years into the journey. Waymo, we are almost 20 years into the journey. Space, we are two to three years into the journey. It’s clear to me that it’s an approach which will make a lot of sense in the future. Being in sub-synchronous orbits with 24/7 access to the most abundant form of energy we have access to will make a lot of sense for this exponential increase in compute that we are going to need. Having said that, this is a challenging project. The team has disciplined milestones. It was a super exciting milestone to send the TPUs up to space. Sometime, as we are speaking, we are expecting a “hello world” moment from them. I look forward to seeing that happen, and we’ll continue investing here too. You previously said 25% of the code written within Google was written by AI. What’s the number today? That number in our world today is meaningless in the sense that every part of what we now touch is influenced by AI deeply. What we are tracking with Argon, for example, it’s been a point of inflection. People are using Argon to really go tackle complex projects, including projects which affect millions of lines of code. In the four weeks since we have launched Argon, we have seen a 30% increase in CLs, and more importantly, almost a similar increase—a one-third decrease in rollbacks. People are writing code more productively and better code with it. We are tracking it with newer metrics now. How are you dealing with opposition to data centers? If you can’t build in the U.S. the way you want to, where else do you go? We’re very committed to building our data centers very responsibly. When I look at our largest data centers in some of the communities where we have been the longest, I visit them, I talk to people. There are people who come and tell us their kids have gone to college because of our investments in these communities, and we’ve grown in those communities. To me, this is about doing it right. Engaging with the communities early, doing it transparently. We are committed to making sure we are bringing incremental power, and we cover 100% of the cost of our power needs for these projects. It’s understanding the impact on neighborhoods and making sure you’re working thoroughly to address them. Done rightly, you can continue making progress. But we are constantly taking feedback into account. I do worry not everyone operates the same way. People have been surprised by data centers showing up in their backyard. Those are all important. As an industry, we should continue to do better. But part of the reason, in a 20-year time frame, we are thinking about things like data centers in space is making sure we are able to put these data centers where maybe the trade-offs will be different. What unproven area of AI is Google working hardest to crack? Is it continual learning—getting models to keep updating after release—or something else? There are multiple parallel paths. You saw with Argon we have a million output tokens. With our Gemini models early on, we had a one-million context window on the input side. These are all examples of breakthroughs we are constantly working on. How do you think about synthetic data? How do you think about continual learning? How do you think about more efficient architectures? We do dedicate a meaningful percentage of our compute to these research bets too. It always goes hand in hand, including our world models. Those are all bets we are placing. Sometimes, as part of these bets, there are ideas that emerge which just make their way into the mainline models. Maybe we don’t fully talk about it, but we have multiple steps in these areas. Working in technology requires optimism that building something will improve the world, but those bets can leave real consequences when they fail. I recently returned to a town in El Salvador where enthusiasm for Bitcoin had given way to unfinished construction and something resembling a ghost town. How do you maintain the optimism you spoke about in your Stanford commencement address while accounting for those risks? I genuinely have a deep conviction that improving technology and improving access to technology makes people’s lives better. It’s been my personal experience in my life, out of which comes that deep conviction, optimism. But with that, I’ve always felt humanity’s journey is always about working hard to harness that technology to make it work well for society. The optimism is not an optimism that you just build whatever you want, whenever. You work hard to make sure you’re building technology in the service of humanity, to make the human condition better. That’s got to be the defining goal as we are approaching it. With that framework, I’m very, very optimistic. We are in very early stages of the kind of progress that we are going to see on many areas. We’re all talking about areas like healthcare. A lot of the progress is ahead. The ability to make things in a fundamentally cheaper way on many things where things have been getting expensive for a long, long time, discovering new materials, etc., which really bend the curve—it’s tough to step today and understand the impact of all that, but they’re going to be very profound. I’m very optimistic, but we have to be rightfully concerned about all the ways this technology can go wrong. Sundar, I know you don’t do many of these. Thank you. Thanks, Alex. Appreciate it.
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Plague is stoppable. The next health threat may not be.
The word plague is scary. Centuries ago, the Black Death killed tens of millions of people and changed the course of history. Plague still kills people around the world, and the word still evokes catastrophe. New fears of plague surfaced on October 2, when a lab worker in Irkutsk, Russia, died of pneumonia. Reports suggested that she may have contracted plague through a laboratory exposure. Understandably, people were alarmed. On October 7, the World Health Organization called for the Russian Federation to be transparent about what it knew. WHO issued an update on October 10. Russian authorities told WHO that testing did not identify plague and that investigations found no laboratory release. WHO said confidence in its risk assessment remained limited and that further clinical, epidemiological, and laboratory information was needed. The cause of the woman’s illness remains unknown, and WHO says a laboratory-associated exposure cannot be excluded. As I explained in a recent interview, this incident is very unlikely to lead to a pandemic. Plague is still active, including in the U.S., which sees a handful of cases each year. But it is a disease we can prevent and treat. Plague doesn’t spread readily, and it responds to antibiotics. The standard response—isolate the patient, trace contacts, and administer antibiotics and monitor for symptoms among contacts for seven days—works. We have even planned for antibiotic-resistant plague. At CDC, we developed a playbook for antibiotic-resistant plague and ran exercises on how to find and stop it. CDC guidance anticipates engineered resistance and recommends two different classes of antibiotics if there’s reason to suspect it. There is no evidence that resistance—or even confirmed plague—is involved in this incident. We have thought through how to address plague, but we’re not ready for the next major health threat that emerges from a lab or from animal spillover to humans. What should concern people is how little stands between the world and the next pathogen to get loose. Since peak COVID, epidemic preparedness has fallen off the political agenda, but the risk is greater than ever. More labs handle dangerous pathogens with more ways to make those pathogens deadlier, and more people live and work in close contact with animals. There are actions we can take now: We need better lab safety in every country. The number of labs that work with dangerous pathogens has increased worldwide over two decades, but there’s no enforceable international standard and no inspection regime; the Biological Weapons Convention, fifty years on, still has no verification mechanism. Labs that study dangerous germs need strong safety systems, training, and oversight. We need to reduce spillover events. Three in four emerging human infections start in animals, and there’s a lot we can do to reduce spillover risk, but the world is doing very little of it. Live-animal markets are one place to act. For instance, closing live-bird markets helped control H7N9 influenza in China. Reducing opportunities for people to encounter infected animals can prevent infections before they become outbreaks. In The Formula for Better Health, which is now out in paperback along with the hardcover, Kindle, and audiobook versions, I argue that labs do too many risky experiments with too many dangerous pathogens in too many institutions, and that every experiment should first answer one basic question: Is the likely benefit greater than the risk? Spillover risk can also be reduced: In the book, I discuss how Brazil cut its deforestation rate by 70% from 2004 to 2012 while increasing agricultural production and reducing risky contact between people and forest animals. We need faster detection and response. Delay costs lives. Strong surveillance, good labs, and trained responders can turn a single case into a small cluster of infections instead of an epidemic. Resolve to Save Lives has worked for nearly a decade to help countries find and stop outbreaks faster. The 7-1-7 target, which Resolve to Save Lives developed with partners in Uganda and elsewhere, provides a clear standard: detect within 7 days, notify within 1 day and complete all essential early response actions within 7 days. In Uganda’s Kasese district, for example, a review of a measles outbreak using 7-1-7 identified shortages of accessible funds, fuel, and vehicles that delayed the response. District leaders established funds they could access quickly. When, a few months later, the Crimean-Congo hemorrhagic fever appeared, the district detected it in three days, notified authorities in one, and mounted an effective response in two. Only one case was confirmed, and the patient survived. Because funds were available before the emergency, authorities were prepared and able to act. This kind of preparation can’t wait until the next crisis begins. Plague is an old disease we that know how to stop. The next threat may be harder to recognize, harder to treat, and easier to spread. Safer labs, less risk of spillover, and faster outbreak detection and response need sustained investment now, while we still have time to prevent the next emergency. Share
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Actor Richard Riehle arrives at the premiere of New Line Cinema's 'A Very Harold & Kumar 3D Christmas' at Grauman's Chinese Theatre on November 2, 2011 in Hollywood, California. (Jason Merritt/Getty Images)Richard Riehle, known for his role in the 1999 film Office Space, has died. He was 78.A statement shared by Artists & Representatives and Wright Entertainment, Inc. announced Riehle's passing on Monday, writing, "Our industry has lost an exceptional talent, and our community has lost a truly wonderful man.""We are deeply saddened to confirm the passing of our beloved client, Richard Riehle, this past weekend," the statement said. "A remarkable actor whose career in theater, film, and television spanned nearly five decades and more than 400 projects, Richard leaves behind an extraordinary legacy."The statement continued, "Beyond his immense talent, he will be remembered for his genuine goodness, boundless kindness, and unwavering generosity, particularly toward emerging actors and filmmakers, whom he encouraged and supported at every opportunity."Born on May 12, 1948, Riehle starred in many television series and films over the years.Notable projects include Casino, The Man from Earth and Deuce Bigalow: Male Gigolo.He got his start as an actor at the University of Notre Dame, where he was involved in the University Theatre and starred in several stage productions. He went on to earn a Master of Fine Arts in acting and directing from the University of Minnesota.While he's played characters that have an "average Joe" presence, he always made the most of his brief screen time.Some roles that he is remembered for include The Quartermaster in Glory, the train guard in The Fugitive, Reverend Scroggins in Fried Green Tomatoes and Bill Cozbi in Bridesmaids.On television, he starred as Principal Ed Rooney in the 1990 series Ferris Bueller and as grandfather Walt Finnerty in the early 2000s sitcom, Grounded For Life.In 2023, he also played Warden Reynolds in Barry.Riehle is survived by his wife, Jane Latham, and their four children.Copyright © 2026, ABC Audio. All rights reserved.
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