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Google's Gemini Omni turns images, audio, and text into video — and that's just the start
Google's Gemini Omni is a new multimodal model that reasons across text, images, audio, and video to generate and edit videos through simple conversation — starting with Omni Flash.
Google's AI Studio now lets anyone build Android apps in minutes
Google unveiled new web-based AI tools that can generate native Android apps in minutes, as the company expands its push into AI-powered software development.
Google's Gemini Omni Can Generate 'Anything From Any Input,' Starting With Video
Google didn't forget AI creators in its latest round of Gemini announcements.
As an aspiring science communicator, I learned a lot from an “eco artist”
Globally renowned, Xavier Cortada creates artwork to generate awareness about climate challenges. He inspired students during a campus visit, among them one who hopes to advocate for the environment.
A key science publishing platform is cracking down on AI slop
The pre-print website arXiv has announced that researchers who put their names to papers which included errors clearly generated by artificial intelligence (AI) will face a year-long ban and ongoing restrictions.
LA mayor's race: AI videos supporting Spencer Pratt shake up political playbook
AI-generated videos depicting L.A. mayoral candidate Spencer Pratt as a superhero and his rival Karen Bass as a villain are gaining traction online.
Amazon Alexa Plus Now Produces AI-Generated Podcast Episodes
The podcast industry suddenly has a big new player: Amazon's Alexa+ AI-powered voice assistant, which can now create extended 'podcasts' on any topic.
New MatterChat Model Helps AI to ‘See’ the Language of Science
From writing emails to generating computer code, much of the artificial intelligence prevalent in our daily lives has succeeded by mastering one domain: text. However, this leaves a major blind spot in the physical sciences, where models depend on the high-resolution, three-dimensional data of the physical world, like the intricate lattice of atoms in a crystal. Delivering on the promise of using AI for science requires teaching these data-driven text models to seamlessly “talk to” physics-based models. Now, a new AI framework from Lawrence Berkeley National Laboratory (Berkeley Lab), called MatterChat, solves this problem by creating a specialized “bridge.” It connects the conversational power of a Large Language Model (LLM) with a physics-based AI that models “interatomic potentials”: the complex physical forces between atoms. The resulting system already significantly outperforms general-purpose AI tools like GPT-4 at predicting material properties, and the team hopes it can accelerate scientific discovery by serving as a robust research partner that provides grounded insights and generates step-by-step instructions for synthesizing novel materials. A paper describing this work was recently published in Nature Machine Intelligence. “Traditional simulations can provide the physical rigor required for materials science, yet their computational cost remains prohibitive for high-throughput screening. Conversely, while LLMs excel at rapid knowledge synthesis, they inherently lack the ‘structural vision’ to interpret materials directly from their underlying atomic coordinates,” said Yingheng Tang, a postdoctoral researcher in Berkeley Lab’s Applied Math and Computational Research Division (AMCR) and lead author on the paper. “MatterChat was built to solve this dilemma, empowering LLMs with a structural ‘vision’ that allows researchers to leverage their full potential for solving complex, real-world materials challenges.” Empowering language models to solve complex challenges in materials science To build MatterChat, the Berkeley Lab team drew inspiration from technologies like Vision Question Answering (VQA) and Text-to-Image (T2I) generation. In these tasks, AI must translate high-level text concepts into visual images, or vice versa. Doing so requires developers to build tools that “bridge” two fundamentally different forms of data. The researchers adapted this concept to the physical sciences. With MatterChat, they created a “bridge model” that successfully connects an LLM’s general knowledge with the deep understanding of the atomic-scale world encoded in scientific interatomic potentials. Until now, researchers using LLMs to solve materials problems usually had to feed them raw data files as if they were just strings of text. It’s like asking an AI to understand a complex 3D engine based only on a parts list: the LLM can read the names, but it can’t “see” how the atoms fit together in space. MatterChat solves this by training a specialized AI bridge model, pre-trained on millions of crystal structures and an LLM, to align the LLM’s representation of the world with the interatomic potential’s representation of the world. The bridge model can translate physical insights into a format the LLM can actually understand. By giving the LLM these “scientific eyes”— a scientific “inductive bias” in the terminology of AI — the Berkeley Lab team has transformed it into a robust research tool capable of providing grounded scientific insights into complex materials challenges, such as predicting thermal stability or analyzing electronic band gaps. “We think of atoms as living in a physical space, but from a machine learning perspective, they are just vectors living in some very non-trivially structured manifold in a high-dimensional Euclidean space; and, of course, the same is true for the sentences and paragraphs that we use to express our ideas about those atoms,” said co-author Michael Mahoney, Berkeley Lab’s Scientific Data Division (SDD) AI Initiative Research Lead. “The bridge model basically gets those two structures to ‘talk with’ each other.” As a proof-of-concept of this general approach, the team trained their bridge model on a dataset curated by pairing nearly 143,000 stable atomic structures from the Materials Project with their corresponding physical properties. This training data was automatically assembled using the Materials Project’s API and deliberately enriched with properties fundamental to microelectronics design — like formation energy and bandgap — allowing MatterChat to learn the complex patterns connecting a material’s atomic blueprint to its functional performance. To validate their model, the researchers benchmarked MatterChat against a suite of other AI systems, from general-purpose LLMs to other specialized scientific AI methods. The results show that MatterChat consistently outperformed its competitors across a range of tasks. The model was more accurate in classifying material types and demonstrated superior precision in predicting numerical properties. For example, it excelled at predicting a material’s bandgap, a property critical for designing new electronics from high-capacity energy storage to next-generation computer chips. “Our design is significantly more efficient because we don’t have to build a massive AI model from the ground up,” said co-author Zhi (Jackie) Yao, a research scientist in Berkeley Lab’s AMCR. “Instead, we take two powerful, pre-trained models — a structural encoder for materials physics and an open-source LLM — and use them off-the-shelf. The only component we actually train is the lightweight ‘bridge model’ that translates between them. It’s the difference between building an entire car factory and simply designing a smart adapter that connects a world-class engine to a world-class navigation system. This approach is not only computationally efficient, but also makes the system modular, so we can easily upgrade components or adapt the bridge for other scientific domains in the future.” Crucially, this modular design highlights exactly how institutions like Berkeley Lab and the Department of Energy are carving out a highly valuable niche in the booming AI landscape. Rather than competing with Silicon Valley tech giants to build ever-larger language models from scratch, the lab is focusing on the specialized connective tissue that makes commercial AI useful for hardcore science. Because the bridge model approach underlying MatterChat is forward-compatible, it is perfectly positioned to leverage these parallel tracks of innovation. As Mahoney pointed out, “We expect that industry will continue to develop improved LLMs, and we expect domain scientists and facilities will continue to generate new data. An important part of scientific machine learning is not simply to solve problems on today’s data, but instead to develop general methods that will be forward-compatible with orders of magnitude more data, whether from scientific domains or from LLMs.” According to Yao, the MatterChat project, which was initially developed and enhanced with funding from a Berkeley Lab Laboratory Directed Research & Development (LDRD) Program, will now expand its capabilities. In a collaboration with Fermilab, MatterChat is already contributing to a U.S. Department of Energy Genesis Mission project — called Accelerating eXtreme Environment Specs-to-Silicon (AXESS) — that aims to speed up the development of next-generation, high-speed, radiation-hardened detectors for challenging particle physics experiments by using advanced 3D integrated circuits (chiplets) and AI-driven data analysis. In addition to the LDRD support, the team also credits supercomputing resources at the National Energy Research Scientific Computing Center (NERSC), located at Berkeley Lab, with MatterChat’s success. “We are incredibly grateful to NERSC; this research simply would not have happened without access to the Perlmutter supercomputer through their AI for Science program,” said Tang. Wenbin Xu, a NERSC postdoctoral fellow at the time, was also a major co-author of the work, as was Benjamin Erichson, a research scientist in Berkeley Lab’s SDD, highlighting the benefits of AMCR-SDD collaboration on AI for science. ### Lawrence Berkeley National Laboratory (Berkeley Lab) is committed to groundbreaking research focused on discovery science and solutions for abundant and reliable energy supplies. The lab’s expertise spans materials, chemistry, physics, biology, earth and environmental science, mathematics, and computing. Researchers from around the world rely on the lab’s world-class scientific facilities for their own pioneering research. Founded in 1931 on the belief that the biggest problems are best addressed by teams, Berkeley Lab and its scientists have been recognized with 17 Nobel Prizes. Berkeley Lab is a multiprogram national laboratory managed by the University of California for the U.S. Department of Energy’s Office of Science. DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.
Final Fantasy creator Hironobu Sakaguchi praises AI-generated FF6 remake teaser, is promptly told "please stop" by SaGa's Akitoshi Kawazu
Hironobu Sakaguchi, the father of Final Fantasy, praised an AI-generated teaser for a hypothetical FF6 remake, but SaGa creator Akitoshi Kawazu disagrees.
Nature is good for business – and we now have numbers to show it
A New Zealand-focused analysis finds businesses in areas with healthier ecosystems tend to generate higher sales and profits, revealing an overlooked green benefit.
Researchers built a switch 1,000 times faster than today's AI chips, and it barely generates any heat
The research, which was published in Science earlier this week, builds on another study published in Nature in January 2025. It demonstrates a new way to flip...
Quantum ghost imaging works using only sunlight in stunning new experiment
Scientists have achieved something that once sounded almost impossible: using ordinary sunlight to create quantum-linked photon pairs, a phenomenon normally dependent on precise laboratory lasers. By building a sun-tracking system that funnels sunlight through optical fiber into a special crystal, researchers generated strongly correlated photons capable of performing “ghost imaging,” where images are reconstructed indirectly through quantum correlations. Remarkably, the sunlight-powered setup produced image quality close to that of a traditional laser system, even recreating detailed images like a “ghost face.”
‘Never-ending’ AI slop strains corporate hacking reward schemes
‘Bug bounty’ programmes have seen a jump in spurious AI-generated submissions
Lawmakers considering raising taxes on sports betting operators
People familiar with state budget negotiations told WRAL that lawmakers have discussed increasing the tax rate paid by sports betting operators to generate more money for the state.
NYU's Joshua Tucker on the politics of training AI
Joshua Tucker, New York University Center for Social Media & Politics co-director, joins 'Squawk Box' to discuss details of the university's new research showing that AI chatbots generate more government-friendly responses when prompted in languages tied to countries with tighter media controls, the intersection of politics and AI, and more.
AI research papers are getting better, and it’s a big problem for scientists
Journal editors and peer reviewers are being flooded with AI-generated papers that are almost impossible to detect.
AI-generated pro-Spencer Pratt mayoral campaign videos point to a new political reality
The reality TV alum’s bid for higher office gained viral traction after videos, which Pratt said were “fan-made,” circulated across social media.
Hantavirus Is Scary. Your Daily Habits Are More Dangerous.
Why rare diseases like hantavirus generate fear while heart disease, loneliness, obesity, and poor sleep quietly cause far greater harm.
Evaluating the Business Case for AI in Patent Practice
Legal organizations that treat AI as a capital allocation, workflow design, and practice-management discipline will be positioned to generate real advantage.
Adam Schiff Accuses CFTC Chair Mike Selig Of 'Duplicitous' Behavior Over Sports Prediction Markets
Sen. Adam Schiff (D-Calif.) on Tuesday accused CFTC Chair Mike Selig of contradictory statements on the contentious issue of sports betting in prediction markets. Schiff Says Prediction Markets Violate State Sovereignty In his Brookings interview with Aaron Klein, Schiff described prediction markets as “pretty indistinguishable” from gaming and sports betting. Schiff argued that these platforms bypass state-level consumer protections and generate no public revenue. “It really seems to violate st
The Top New Features in Google’s Android 17—and Gemini Intelligence—Coming This Summer
You’ll soon be able to generate your own widgets or ask Gemini to finish a booking in Chrome on Android.
Scientists make old blood stem cells young again in major anti-aging breakthrough
As blood stem cells age, their lysosomes become overactive and damaged, triggering inflammation and weakening the body’s ability to regenerate healthy blood and immune cells. By calming this cellular “overdrive,” researchers restored the stem cells’ youthful function, dramatically boosting their ability to regenerate and produce balanced blood cells.
How mixed-use stadium districts — for work, play and football — became college sports’ latest craze
As schools look under every rock for money in the revenue-sharing era, trying to generate money from the area around the stadium is a trend.
Thinking Machines wants to build an AI that actually listens while it talks
Right now, every AI model you've ever used works the same way. You talk, it listens. It responds, you listen. Thinking Machines is trying to change that by building a model that processes your input and generates a response at the same time, so it's more like a phone call than a text chain.
Deepfake “doctors” are a problem—here are 7 keys to stopping them
There’s a need for clear, enforceable protections against unauthorized AI generated deepfakes that threaten patient safety. Learn more with the AMA.
Basketball gets more money, while tennis and other small college sports worry over their future
Among them are the disbanding of tennis teams at Arkansas, new efforts to generate revenue in the Big 12 and at Duke and the ongoing issues surrounding the industry's new
Investing In Climate Health Could Generate High Returns, Study Finds
Every $1 invested in climate health solutions could yield up to $68 in benefits for low and middle-income countries, according to a new analysis.
OpenClaw and Claude can put your AI-generated podcasts in Spotify
Your own personal AI podcast feed.
Sphere Entertainment generated $386.4M in Q1 revenues, up 38% YoY – driven by The Wizard of Oz and concert
‘Today’s results demonstrate our continued success proving out Sphere’s business model,’ said Executive Chairman and CEO James L.
Sports tourism generates $150 million annually for Panama City Beach
Dozens gathered at Publix Sports Park to celebrate Tourism Appreciation Day as the facility continues to serve as a major draw for visitors.
AI political ad stirs controversy ahead of California debates
An AI-generated political ad depicting reality star and L.A. mayoral candidate Spencer Pratt is being celebrated by some, but also raises ethical questions. All of it as candidates prepare for key California debates just weeks before the primary. NBC News' Dana Griffin reports
Astrocade: $56 Million Raised To Build AI-Powered Interactive Entertainment Platform
Astrocade announced $56 million in new funding to expand its AI-powered interactive entertainment platform that enables users to create and play games generated with artificial intelligence. The funding included a Series B round led by Sequoia Capital and a Series A round led by Sea, with participation from Google’s AI Futures Fund, NVIDIA, LG Technology Ventures, Dentsu Ventures, Conviction Embed, Chaac Ventures, Rogue VC, and additional investors.
A Landslide in Alaska Set Off a Tsunami. There May Be More to Come.
Scientists say as glaciers retreat in a warming climate, landslide-generated tsunamis are likely to become more frequent.
Ironmouse claims Neverness to Everness lied to her about AI use and cancels sponsorship
VTuber Ironmouse has called out Neverness to Everness after the game was hit with accusations of using AI-generated content.
Stanford researchers develop AI scientists for therapeutic discovery
The multi-agent system generated SARS-CoV-2-binding proteins in days.
Xperia 1 VIII listed on Amazon: Release date, specs, colors, sky-high price revealed; WH1000XM6 headphones with pre-orders
A massive leak on Amazon UK and Germany has revealed the Sony Xperia 1 VIII ahead of schedule. The listings detail a June 26 release date, new colors, 6.5-inch 120Hz OLED display, a new telephoto lens, and a launch bundle. With prices starting at £1,728, Sony's next flagship faces scrutiny over a significant price hike compared to the Xperia 1 VII.
AI lets chemists design molecules by simply describing them
Creating complex molecules usually requires years of experience and countless decisions, but a new AI system is changing that. Synthegy lets chemists guide synthesis and reaction planning using simple language, while powerful algorithms generate and evaluate possible solutions. The AI doesn’t just compute—it reasons, scoring pathways and explaining which ones make the most sense.
Thymus renaissance poised to boost health and longevity
Nature Biotechnology - Evidence linking thymic function with health and longevity is piling up, and a cluster of biotechnology companies is trying to regenerate the thymus directly or recapitulate...
Indianapolis to host national NRA conventions in 2029, 2031
Each of the events is expected to draw more than 70,000 visitors and generate $26.4 million for the city's economy.
Don’t trust AI for help with citations, science-fair judges warn
Fake, AI-generated citations have begun disqualifying major science-fair projects. Such ‘ghost’ references even haunt research journals.
Global Health & WASH: May 2026 Funding Opportunities (14 new opportunities!)
The May update for Global Health & WASH brings new calls that cluster around three distinct shifts: LMIC research leadership moving from funder encouragement into a hard eligibility constraint, pharmaceutical and corporate-linked funders running structurally independent education and use-inspired research portfolios at substantial scale, and AI adoption shifting decisively from speculative tool to operational capability across health and WASH systems alike. In LMIC Research Leadership as Eligibility, Not Encouragement, Wellcome anchors the dominant signal of the month with three separate major calls that all require or strongly center LMIC leadership in their basic eligibility architecture. Wellcome’s ESIC Hubs (£1.5-£1.9M per hub over 3-5 years) explicitly requires an LMIC-based lead applicant, treating Global South leadership as a design constraint rather than a participation goal. Wellcome’s Infectious Disease Clinical Trial Development Award funds transdisciplinary teams whose lead must be a mid-career or established researcher based at an organization in Africa, South Asia, or Southeast Asia. Wellcome’s larger Infectious Disease Clinical Trial Award (£1M-£8M for optimizing licensed interventions) requires the administering organization to be in eligible LMIC regions and at least 50% of applicants based there. Around Wellcome, the same pattern shows up at smaller scale and across funders: CHINNOVA channels $1M into West and Central African research institutions for climate-health work; IBRO’s Neuroscience Training Grants explicitly tier ceilings by region of residence with Africa receiving the highest amount ($5,000); IHME’s GBD Emerging Researcher Award reserves at least one of its two annual awards for an LMIC researcher; Sidaction’s HIV Cure call funds research teams across France, the Netherlands, and eligible African countries with a minimum two-country collaboration requirement. Taken together, these calls signal a meaningful shift in how research equity is being operationalized — not as encouragement language at the bottom of a call, but as a structural feature of who can lead, where the work must be administered, and what proportion of the team must be regionally rooted. In Pharma-Funded Independent Medical Education and Use-Inspired Research, the lineup this month is unusually deep. Pfizer alone runs four parallel calls under independent education and quality improvement frameworks: a Migraine and Women’s Health RFP (200K x 2-year, $500K pool), Migraine IME ($200K, $1M pool), JAK Inhibitor evidence-based education ($100K), and Maternal Vaccination HCP Education in Saudi Arabia ($75K), plus a separate Pediatric Pneumococcal Surveillance research call in Saudi Arabia ($400K per project). Novo Nordisk Foundation runs four parallel calls of its own at substantial scale: Infectious Diseases Catalyst Grants (DKK 60M pool, up to DKK 7M collaborative), Non-Diabetic Endocrinology Collaborative Grants (DKK 53M pool, DKK 5-10M per project), Pioneer Innovator Grant Health (DKK 1.1M), and Distinguished Innovator Grant Health (DKK 6.8M). LEO Foundation deploys DKK 2-4M per project for dermatology research excellence. Pfizer’s framing across calls deliberately separates the funding from product promotion, emphasizing measurable practice-relevant change and structural distance between scientific outputs and commercial activity. Novo Nordisk’s “use-inspired” hard filter pushes researchers toward a credible translation pathway from mechanism to deployable tool. The pattern: industry-aligned funders are running structurally independent portfolios at meaningful $ that fund implementation evidence, not promotion. In AI as Operational Capability, Not Speculation, several calls this month explicitly treat AI adoption as a near-term operational question with real evidence and governance requirements, rather than a speculative trend to be watched. Wellcome’s ESIC Hubs frames AI as “the accelerator” for evidence synthesis, asking hubs to translate technical innovation into adoption-ready workflows that can match real-world policy timelines. UNICEF Venture Fund’s new Climate Tech for Children’s Health call funds for-profit startups deploying AI, machine learning, and blockchain in low-resource environments, with a strict requirement that solutions must already have a working prototype with promising pilot results. The Water Research Foundation has launched two simultaneous AI calls treating reproducibility, cybersecurity guardrails, and human-in-the-loop deployments as core design constraints rather than nice-to-haves: one on GenAI and Agentic AI in water utilities ($200K), one on alternatives to water shutoffs that explicitly screens for implementation economics evidence. Nordic Innovation’s quantum technology call (NOK 4.5M) extends the same logic into life science and healthcare, demanding consortium-stage projects mature enough to test with real users. TEF-Health offers €300K in subsidized testing infrastructure for European healthcare AI and robotics SMEs. The pattern: funders are converting AI pilots into playbooks, requiring transfer evidence and risk controls before AI can move from experimentation to sector-wide operational practice. For LMIC-based researchers in infectious disease or evidence synthesis, the three Wellcome calls together represent the deepest concentration of LMIC-led research capital in recent memory — pair the Infectious Disease Clinical Trial Development Award (£200K, deadline May 19) as a strategic pipeline feeder into the larger Infectious Disease Clinical Trial Award (£1-£8M, deadline June 2), since the development award functions explicitly as a track into the larger trial scheme. For Nordic researchers, the four Novo Nordisk Foundation calls plus LEO Foundation and Nordic Innovation Quantum represent ~$30M in regional research capital this cycle, all with deadlines clustered in May-August. For WASH practitioners, the three Water Research Foundation calls together (each up to $200K) are a cluster worth reading across — one on AI deployment, one on shutoff alternatives, one rewarding applied innovation — and the strongest applicants will articulate how their work bridges utility operations to policy-relevant evidence. For US-based clinical researchers and educators, the four Pfizer calls plus the APF Portfolio’s 80+ programs form an unusually accessible recurring pipeline; APF’s prohibition on indirect costs is a meaningful structural feature for early-career applicants whose institutions might otherwise absorb significant overhead. Snapshot of New Opportunities Total Estimated Funding Pool: $100 Million+ USD The grants are organized into three categories: Open Calls: Current grant and opportunities with a deadline. Grants are listed by closing date. 39 open opportunities- 14 new! Rolling Applications: current grant and opportunities with rolling applications (but it’s still best to submit as early as possible). 14 rolling opportunities- 1 new opportunity! Long term planning: Grants that have closed their current rounds, but are expected to open new windows. 4 long term opportunities! A quick tip for returning readers: if you want to jump straight to the newest additions, use CTRL F to search for “New!” and navigate quickly to the latest funding opportunities This post is for paid subscribers. This helps support the time and effort it takes to curate and organize these opportunities. Subscribe To keep this accessible to everyone who needs it, we’re happy to offer pay what you can rates. You can find more details here. Open Calls: Migraine Competitive Grant Program: Migraine and Women’s Health (Quality Improvement and/or Research RFP), Pfizer.*Closing soon!* Pfizer, in collaboration with the American Headache Society, is seeking independent quality improvement and research projects that close persistent gaps in migraine care for women across the United States. The funding logic centers on measurable, practice-relevant change: proposals should generate actionable evidence, tools, or system improvements that can be shared and used widely, not just within a single site. Priority areas span menstrual migraine and screening in women’s health settings, the role of hormonal fluctuations across the lifespan, sex-specific risk factors, comorbidities and quality-of-life burden, and disparities in outcomes by race, ethnicity, and socioeconomic status. The call is structured as a two-step competitive process with an initial Letter of Intent, with the strongest concepts expected to translate scientific insight into implementable improvements in diagnosis, management, and equity. Geographies: United States. Who can apply: U.S.-based organizations (not individuals), including professional schools, healthcare institutions, professional organizations, and other entities focused on healthcare improvement. Funding amount: Up to USD $200,000 total over 2 years; total pool USD $500,000. Targeted Sectors / SDGs: Health; Focus areas: migraine, women’s health, quality improvement, clinical research, menstrual migraine, health disparities. Deadline: LOI: May 5, 2026; Full proposal (by invitation): August 28, 2026. Learn more and apply here. This RFP rewards “shareable impact”: the most competitive submissions will pair rigorous methods with a clear plan for system uptake and dissemination beyond the originating institution. ReSSARC: Strengthening the Health Sector and Food Security in the Central African Republic (AID 013381/01/0) Call for Proposals, Italian Agency for Development Cooperation (AICS). *Closing soon!* AICS is seeking a limited set of high-capacity humanitarian partners to deliver an integrated package that stabilizes essential health services while reducing acute malnutrition and strengthening food security resilience in priority areas of the Central African Republic. The funder’s logic is explicitly nexus-based: proposals should meet urgent, life-saving needs while reinforcing local systems, coordination mechanisms, and community-level capacity so results persist beyond the emergency window. AICS emphasizes inclusion and protection outcomes, expecting gender-sensitive design and explicit measures for groups facing compounded vulnerability, including women, children under five, internally displaced people, and people with disabilities. The call also signals a localization pathway, encouraging stronger collaboration with national NGOs and balanced partnerships, alongside clear coordination with existing cluster and humanitarian actors to minimize duplication and improve coverage. Geographies: Central African Republic (Bangui, Ombella-Mpoko, Ouham, Ouham-Pende, Lim-Pende, Lobaye). Who can apply: Non-profit organizations registered with AICS, plus eligible non-profits without an office in Italy that have a pre-existing collaboration agreement with an AICS-listed organization. Funding amount: Total pool EUR €1,800,000; max EUR €800,000 (single applicant) or EUR €1,000,000 (ATS). Targeted Sectors / SDGs: Health; Focus areas: malnutrition prevention and treatment, maternal and child health, community health services, food security and resilience, localization partnerships Deadline: May 5, 2026. Learn more and apply here. This call is structured to reward partners who can link frontline service delivery to system durability and localization, not just short-term coverage gains. Contracts for Innovation in drug and alcohol addiction healthcare, Innovate UK. *Closing soon!* Innovate UK, on behalf of the Office for Life Sciences Addiction Healthcare Goals program, is procuring R&D to accelerate innovations that can improve treatment outcomes, strengthen recovery, and reduce harm and deaths linked to drug and alcohol addiction. The competition is positioned as a market-facing readiness push: selected projects are expected to advance solutions toward later-stage validation, generate evidence of user acceptability and UK market fit, and map credible routes through regulatory and certification requirements. Innovate UK signals a preference for innovations that can be field-tested in relevant UK settings and progressed to TRL 6 or 7, with practical plans for commercialization after contract completion. This structure favors applicants that can execute most work in-house, co-develop with service providers and people with lived experience, and translate technical progress into deployable tools for addiction healthcare delivery. Geographies: United Kingdom. Who can apply: Single organizations of any size (including EU, EEA, or international) leading delivery, with most work and key deliverables carried out in the UK; subcontractors for specialist skills only. Funding amount: GBP £200,000–1.5 million per project (inclusive of VAT); Total pool: GBP £20 million (across two strands). Targeted Sectors / SDGs: Health; Focus areas: Mental Health, Health Systems Strengthening, Research & Development, Technology Access. Deadline: May 6, 2026 (11:00am). Learn more and apply here. This call uses procurement to pull near-market addiction innovations toward operational proof and adoption pathways in UK services.
Is it true that … your lungs regenerate when you quit smoking?
Our lungs have evolved to heal from damage, but for some cigarettes will cause changes beyond the body’s ability to fix them
Former Congressman Barney Frank reflects on his life, entering hospice, and the future of the Democratic Party
Pirro on press dinner suspect: ‘It is definitively his bullet’ in vest of Secret Service officer
Tillis: If the case against Comey is based on a picture in the sand, it ‘makes no sense to me.’
Science 4 Everyone: Why do data centers need water?
Why do data centers generate so much heat? Storm Team4 meteorologist Ryan Miller explains its water use and what it has to do with droughts.
Democratic Michigan Senate candidate Mallory McMorrow explains deleted tweets following CNN report
More Than a Third of All New Podcasts Are AI-Generated
Synthetic podcasts just keep coming.
How A.I. Is Transforming China’s Entertainment Industry
A.I.-generated microdramas have taken off. Celebrities have threatened legal action against the use of their likeness, while actors say jobs have dried up.
‘The reality, for better or worse’: Columbia comp sci students and faculty grapple with AI’s disruption of the field
‘The reality, for better or worse’: Columbia comp sci students and faculty grapple with AI’s disruption of the field ‘The reality, for better or worse’: Columbia comp sci students and faculty grapple with AI’s disruption of the field A field that once seemed like a direct path to stable, lucrative work is becoming less certain under AI, students and faculty told Spectator. By Ria Vasishtha and Arjun Menon May 3, 2026 Shanying Liu / Deputy Illustrations Editor Asia Genawi, SEAS ’29, first encountered artificial intelligence during her sophomore year at her high school in Indiana. Back in 2023, policies on AI varied widely—even within the same district—and some schools had no guidance at all. As Genawi began to see the effects of AI trickle into her classroom, she turned to guidance from her home state’s Department of Education, which she said she found “outdated and inaccessible.” Genawi spent the rest of her high school career dedicated to the issue, including writing a 15-page memo exploring varying AI policies across Indiana schools, which she sent to every Indiana state senator and representative whose contact information she was able to find. She later helped draft a bill that would have required public high schools to establish and share their own AI policies with students in an accessible format. But with so many other bills already awaiting referral, hers never made it to committee. When Genawi arrived at Columbia to study computer science, she found that the gaps she had spent years trying to address in Indiana had followed her there. Many students and professors were also grappling with what AI meant for the field. Across Columbia’s undergraduate schools, computer science has become the most popular major—accounting for around 11 percent of degrees awarded in Columbia College, 32 percent in the School of Engineering and Applied Science, and 12 percent in the School of General Studies in 2024. While the number of computer science majors in SEAS grew from 166 to 173 during the 2024-25 academic year, the total number across the three schools fell around 4.5 percent from 393 to 375, driven by declines at Columbia College and General Studies. At Barnard, it has grown to become the second most popular major as of 2025, up from third the year prior. The number of degrees awarded have grown fivefold since 2016. Faculty members and students in the department told Spectator that the surge in the major’s popularity has been driven in large part by its apparent promise of a secure, well-paid career path. However, they noted that the recent rise of generative AI has compromised the sense of stability that once defined the field, even as interest in technical skills among students persists. According to data from the Federal Reserve Bank of New York in 2024, out of 74 majors tracked, computer science had the fifth highest unemployment rate among majors at 7 percent, while computer engineering had the second highest at 7.8 percent. “Anecdotally, people are moving away from CS as a major,” Daniel Bauer, a senior lecturer in the computer science department, said. “They’re still taking some of our classes, right, because they think they need that, but they’re instead majoring in other things.” Bauer described a field that had shifted from what he called a “nerdy outlier discipline” to one that “everyone needs,” a sign that technical skills have become a baseline expectation across industries with the emergence of AI. “A lot of people thought, ‘Oh, it’s a guaranteed path to a stable income. You get a six-figure job right out of your undergrad,’” Bauer said. Now, companies may see AI as a way to reduce demand for entry-level programmers, especially in what he calls “code monkey jobs,” roles where a large number of employees are “just writing out code nine-to-five.” Chris Murphy, a senior lecturer in the computer science department, described the current moment as the convergence of two forces: the downturn of the job market and generative AI coming onto the scene. “Things kind of started to really pick up in 2014, 16,” he said, recalling the years after the weaker 2010 market. Murphy added that this was also a period where “students were getting more experience outside of class than they were inside of class” through internships, jobs, and side projects. Murphy suggested that the earlier momentum helped make computer science feel like both an academic program and a reliable pathway into work. That feeling is harder to sustain now as the industry reconfigures, which is a shift that students are seeing firsthand. Rebecca Yu, SEAS ’27, said that during a recent internship in Big Tech, she saw that “every single tech company was racing to integrate” large language models. She added that her manager said her intern class was the first to complete their assigned projects, which she attributed to the increased efficiency that comes with AI. Frank Liu, SEAS ’29, said that with AI lowering the barrier to coding, companies now expect everyone to write code. “A lot of companies outright say if you’re not using coding in your job, you might get fired for not being productive enough,” Liu said. Yu similarly expressed that students increasingly have to accept AI being a part of industry workflow, adding that many also “make use of it to maximize their productivity.” Richard Li, CC ’28, described a “franticness” among his peers as the pace of change accelerates. He explained how “some new tool” is released regularly, noting that tools rise and fall in prominence within weeks. He has come to believe that he doesn’t need to “match that speed all the time” and keep up with every development. Li has learned that AI tools allow him to “take a breath” and “get back into the loop much easier than before” when he needs to. While some companies specifically target Columbia when hiring, sending representatives to campus career fairs and recruiting large numbers from Columbia, a computer science degree cannot be treated as a static credential, Yu described. “You can’t just get your degree and stop learning after that. You have to always be learning,” Yu said. “That is something you basically have to expect for your job.” AI has not only affected students’ decisions to major in computer science, but also reshaped how the subject is taught. Across departments, faculty members no longer treat work done outside the classroom as a reliable measure of understanding, shifting instead toward in-person exams, quizzes, and attendance checks. While homework once made up as much as 60 to 70 percent of a student’s grade in computer science classes, Murphy said that breakdown has since flipped, with exams and quizzes now accounting for the majority. “The assumption—especially among pessimists—is that they’re using it to do their homework,” Murphy said. “They take the homework assignment. They put it into generative AI. Out comes the solution. Submit solution. The end.” Murphy said that faculty members ranged in their responses from fully prohibiting AI use to actively teaching students how to effectively work with AI. He said he shifted his approach this year after his teaching assistants called his belief that students weren’t using the technology “naïve,” and now permits students to use AI on assignments. His surveys of students in his introductory classes have told a more complicated story than the one so-called pessimists offer: Around 60 to 70 percent of students who reported using AI said they used it to have concepts explained to them, to clarify assignment instructions, to generate test cases, or to create practice questions. “Those are all ways that you might have had a tutor in the past to do that, and now you have this AI essentially as your tutor,” he said. Bauer has taken a different approach, teaching students how to use AI productively without sacrificing the core principles of the discipline. “People who are trained to actually use AI tools productively, while being in charge of designing the overall project, will be very much in demand in the next couple of years,” he said. Over the past year, a working group of computer science faculty has been redesigning the introductory and intermediate programming sequence to integrate generative AI as both a subject and a tool, representatives from SEAS wrote in a statement to Spectator. The effort is “coordinated” across the department, “not course-by-course,” with a systematic assessment of how AI integration is affecting student outcomes underway to shape the next round of changes. The goal, the department explained, is for students to be able to “read, verify, and reason about code, whether they or a model wrote it.” Tony Dear, senior lecturer in the computer science department, is piloting individualized AI feedback in a discrete mathematics course, while a machine learning course is also testing a Socratic AI dialogue system designed to “guide inquiry rather than supply answers,” the statement reads. Beyond individual courses, SEAS funded seven cross-departmental faculty projects in generative AI this past academic year, spanning biomedical engineering, chemical engineering, industrial engineering, and computer science, according to the statement. This phenomenon extends beyond the computer science department. SEAS’ new AI minor, which it announced in November 2025, reflects the University’s attempt to adapt. The minor is specifically designed for noncomputer science majors and aims to provide “essential AI knowledge” while emphasizing practical and responsible use across disciplines, according to the SEAS website. At the center of the minor is AI in Context, a course taught by a team of faculty from the departments of computer science, applied mathematics, philosophy, music, literature, and the Writing Center, the representatives told Spectator. Bauer described it as targeted at students who want to bring AI into fields like economics or biology, rather than as a path into software engineering itself. At the graduate level, SEAS announced a new Master of Science in artificial intelligence in February, with the inaugural cohort starting in the fall. While recognizing how AI has helped them navigate coursework, students also described its rise as isolating, even among members of the Application Development Initiative, one of Columbia’s largest computer science clubs. “As people start to ask AI for questions that they would normally ask students and members, it starts to isolate people” Li said. Alexa Kafka, BC ’27, echoed Li’s sentiment, pointing out that computer science has always been a collaborative discipline with code reviews and pull requests, even as AI makes independent work easier. Despite this, Kafka noted that she hasn’t been to office hours “in at least a year.” Bauer added that faculty are exploring long-term solutions to the assessment problem. “One of the things that we’re trying to do at the department or school level is to maybe move towards computerized testing facilities,” Bauer said, referring to ideas in the department to revitalize computer labs as an alternative to pen-and-paper exams. “We have to accept that this is the reality, for better or worse.” But more exams, students say, does not mean better learning, nor does it reflect how computer science is actually done. “Code is so variable and can be approached in so many directions, there’s never just going to be one correct answer. There can be multiple optimal solutions,” Kafka said. Students also expressed concern that the shift toward exam-heavy grading pulls focus away from the applied, project-based work that better reflects both discipline and industry expectations. ADI has tried to respond more quickly than the curriculum can. Through a vibe coding workshop this past semester, club members said they wanted to help students understand not just that AI exists, but how to use it deliberately. “Vibe coding” refers to the practice of prompting AI to write code for a task or project, and has become widespread enough that ADI felt the gap in formal instruction was worth addressing, according to Sophia Huang, BC ’29. The workshop introduced students to the concept of context engineering, which Shaina Sahu, SEAS ’27, described as not just writing a prompt, but optimizing “the rest of the relevant information that you would feed into the model.” Without that, students said that AI-generated code can fail at scale or introduce difficult-to-detect bugs. Genawi said the shift toward AI has changed what it means to be good at computer science. “I think the shift has kind of gone towards what can you create and what can you do, instead of, what do you know,” she said. Indeed, during ADI DevFest, its annual hackathon, Li said more teams are trying to complete their projects than in years past. While sign-ups have historically outpaced submissions, Li said this is beginning to change because teams “have a tool that completes the vision for them.” While many students see AI as an equalizer that lowers the barrier to entry for coding and technical work, Murphy said it also creates new equity concerns inside the classroom around who can afford stronger tools and who already knows how to use them. “The equity issues I worry about are students who have access to paid versions of things versus free versions of things,” he said. Although popular AI models like ChatGPT and Claude have free versions available, both have paid models that can reach over $100 per month, which output different qualities of code. Murphy also pointed to differences in prior exposure to AI literacy itself. “Students who go to high schools or K-12 education, where they’re taught AI literacy, prompt engineering, context engineering, they understand how to do this, as opposed to students who go to schools who don’t teach that,” he said. “Then they come in, and then they’re somehow expected to know how to use these tools.” For Genawi, those disparities begin long before students arrive on campus. “It’s very interesting to consider how lucky you were geographically,” she said. “To be born where you were is influencing your ability to get access to these spaces.” Students like Yu, though broadly apprehensive about the future of computer science, are not without hope. “I’m optimistic, because I think if you’re truly passionate about CS, there will definitely be a place in the field to do something you want to do,” she said. Senior Staff Writer Ria Vasishtha can be contacted at ria.vasishtha@columbiaspectator.com. Follow Spectator on X @ColumbiaSpec. Staff Writer Arjun Menon can be contacted at arjun.menon@columbiaspectator.com. Follow Spectator on X @ColumbiaSpec. Want to keep up with breaking news? Subscribe to our email newsletter and like Spectator on Facebook. Produced with Spectate by Emily Ta
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Punk Politics/Camp Costume is a fashion exhibition curated by (some of my) brilliant Parsons students!
I have the most amazing students. I teach Fashion Journalism at Parsons, as part of its MA Fashion Studies degree, though I have students of all different disciplines throughout the New School in my class — from fine-art photographers to investigative journalists to textile designers. And I learn about all sorts of fascinating things from them, like that designers are adding faux sweat stains to their garments now (part of a trend piece about “anatomy core”) and that real “French girl style” is actually about being “cunti cunta” (aka loud, rude, too much, liberated). So when I found out that some of my students were curating a fashion exhibition opening tonight(!!!), I just knew that it would be brilliant too. Wearable Art is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe It’s called Punk Politics/Camp Costuming1, and it’s up through May 10 at La Sudestada, the wonderful gallery and concept store in Greenpoint, Brooklyn. I asked the exhibit’s lead curator, Ella Birney (a talented costume and knitwear designer from Belfast who also happens to be in my class), all about it. This conversation has been edited for length and clarity. Tell me about the idea of this exhibition and how it came about. Ella Birney: For our Fashion Curation class, we had to pitch [exhibition] proposals to our professor, Jessica [Glasscock], and I really wanted to continue on the themes that I was exploring in my BA when I was studying in London a couple of years ago. My BA was very punk-inspired and very political. Everything I do, as you know from my writing, always has a slight Irish, political twist to it2. So in my BA project, it was looking at knitwear as a conveyor for exploring political identity in somewhere like Ireland, where identity is such a point of contention. And looking at the images that I generated from that project, there was something so camp about the whole thing. Like, it’s so playful and in bad taste to do a political message — like a knitted Union Jack — out of mohair. There’s something very camp about that. So that’s where it kind of became punk politics/camp costuming — looking at how from the 1970s to now there’s been protest through costume and clothing. What was your BA in? It was fashion textiles, knitwear. Very craft heavy, which — craft is never taken seriously either. That’s also a kind of spin [on the punk/camp thing]. The Union Jack knit that you made is included in the show — what is camp about knitting a Union Jack out of mohair? The whole ethos of camp is kind of bad taste, doing things that are tongue in cheek and a bit wink, wink, nudge, nudge. Like, this is a bit silly. Everything I do is like, this is a bit silly. Like, being from the North of Ireland, everything you do is political. So it’s like, everything is going to be looked at in a certain lens anyway, so we may as well lean into it. So the Union Jack was because I come from a mixed marriage — Protestant-Catholic. And in the North of Ireland, that’s still a big deal. And even though I’m a Catholic and brought up in a very like Catholic Nationalist family, there [were] Union Jacks [the symbol of the United Kingdom] on my street. So I was like, then I’m gonna make your Union Jack out of knitwear. And then that kind of all linked back to the punk movement that Vivian Westwood forefronted in the late 70s, [with her stores] Let It Rock and Seditionaries. How did you source your items? Once we decided on this exhibition idea, everyone in the class was put to [think about] what do you think can fit into punk politics/camp costuming and finding designers that fit that brief. Me and my co-curators, Dulcinea Flores and Allison Gramando, made a brief to send out — with a mood board and color stories, stuff like that — and then everyone kind of got to work emailing people. We reached out to other Parsons grads. Even through Instagram stories we’ve been able to reach so many people who were like, Yeah, of course, I’ll write something for this, or Please — let me submit stuff. It actually was quite easy sourcing things. … The Parsons thing gets you quite far. What were some great pieces you got? There’s a Brooklyn-based, nonbinary artist called Buzz Slutsky. I can’t even remember how I found them, but I came across this crazy, shoe thing — they had made all these different shoes out of papier-mâché, and the story behind them is so fantastic, so interesting. They were just so obliging, like, Of course, you can have these for a few weeks. I was really happy about that. And then we have art from a collective here called Art Comes First. And they lent loads of really amazing pieces that just tied everything together. You have your Union Jack knit in the show too. Any other pieces that you made? There’s three of my BA mohair knits. There’s the Union Jack. There’s a mohair with the word “No” — which is based on an old political campaign in Ireland that was “Ulster says no to sodomy.” And then there’s another one that is red, white and blue, like the Union Jack, but has the word “Catholic” on it and lots of holy medals. I’m so happy I got to include those. How many pieces are in the show? Between 49 and 52, something like that. A load of clothing and accessories, shoes. There’s a Brooklyn-based Irish photographer who’s given us photos. There’s also a shopping cart that is an art piece by Art Comes First that has gold knuckle dusters as the handles. There’s also lots of T-shirts, original pins from the 70s and 80s that were from people’s dads. I also brought my record player, and all of [co-curator] Allison’s dad’s original albums so everyone could play records. Oh my gosh! Yeah, it’s cool. Anything else you would like to add? If we get to do an exhibition, why would we not make it political in this day and age? I hope that people come. There’s a lot of history, because it starts back in the 70s. It’s not like chronological or anything, but there are historical objects. I hope people come out of it thinking, out of all the really horrendous decades of the 70s and 80s and 90s, all these amazing subcultures happened. There are horrible political times, but there’s art that comes out of it that lasts. Punk Politics/Camp Costume is on view May 1-10 at La Sudestada, 67 West St. Suite 513, Greenpoint, Brooklyn. RSVP for the opening Friday May 1 6pm-8pm here. There’s also a button-making and patch-making workshop and artist talk May 9. Follow the show’s Instagram page @punkxcamp.parsons. Special shout out to all the students who put on this show: Ella Birney (lead curator), Dulcinea Flores (curator), Allison Gramando (curator), Pierre Sanon (lead exhibition designer), Eliana Daneshvari (exhibition designer), Reilly Lowell (editor), Jess Gayo (researcher/writer), Joyce Gayo (researcher/writer), Maria Magdalena Ugarte Montero (researcher/writer), Cassidy Colarik (exhibition press officer), Shelby Shovein (educator), Sarah Mahnke-Baum (educator), Trinidy Coleman (graphic designer), and Leonie Soravia (project manager). Jessica Glasscock was the faculty advisor. 1 The website is definitely worth checking out. 2 This is true!
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Advancing epidemic and pandemic preparedness through research readiness: SEAR Unity Studies Network Sites chart the way forward in 2026
On 25 March 2026, WHO Regional Office for the South‑East Asia Region (SEARO) convened the first meeting of the SEAR Chapter of the Unity Studies Network Meeting in 2026 to take stock of progress and plan next steps for strengthening epidemic and pandemic preparedness across the Region. The meeting focused on reviewing the ongoing adaptation of selected, standard Unity Study methodologies, sharing field implementation experiences from 2025, and identifying key priorities to guide collaborative work in 2026.Held virtually, the meeting brought together representatives from six Unity Studies network sites across five countries (Bangladesh, India, Nepal, Sri Lanka, and Thailand) as well as participants from all three levels of WHO.The meeting took place against the backdrop of ongoing regional efforts in South‑East Asia to strengthen early investigations and studies for epidemic and pandemic preparedness, with a focus on pandemic influenza and other emerging respiratory pathogens with epidemic and pandemic potential. In this context, and as part of preparedness for the rapid generation of evidence, the WHO Health Emergencies Programme in SEAR (WHE/SEAR) encourages Unity Studies sites to adapt prioritized, standardized Unity Study protocols to their national contexts. This approach supports the generation of timely and reliable evidence to inform public health decision‑making during epidemics and pandemics.These efforts are supported through a combination of experience sharing, participation in the global Unity Studies network webinars, capacity‑building of the national public health workforce, and regional collaboration that promotes inter‑country, inter‑agency, and inter‑ministerial action. In parallel, sites are encouraged to explore diversified funding sources to help sustain research preparedness over the long term.Discussions highlighted the importance of WHO’s catalytic financial support through the Pandemic Influenza Preparedness (PIP) Partnership Contributions (PIP‑PC). When combined with national and institutional resources, this support enables countries and sites to maintain continuity of activities at a core level and remain prepared to respond rapidly and effectively to future epidemics and pandemics.Regional and Global Updates: Opening the session, Dr Pushpa Ranjan Wijesinghe, Programme Area Manager, Pandemic and Epidemic Management (PEM) Unit, WHO Health Emergencies Programme, highlighted the progress made in operationalizing the Unity Studies Network across the Region and acknowledged the collaborative efforts of WHO at all three levels, together with country unity studies sites. He emphasized the availability of limited but catalytic funding through the Pandemic Influenza Preparedness (PIP) Partnership Contribution (PIP‑PC) workplan at SEARO to sustain network activities in 2026, while encouraging sites to leverage additional funding sources to expand implementation.Representing SEARO, Dr Ashok Basnet, consultant, Pandemic Influenza Preparedness reported that, at the regional level, the Unity Studies Network currently includes six sites across five countries: Bangladesh, India, Nepal, Sri Lanka, and Thailand. He noted that in 2025, catalytic funding supported protocol adaptation, training, and pilot implementation. In addition, a regional Unity Studies symposium held during the Global Public Health Summit in Sri Lanka strengthened and advocated collaboration between the Unity Studies site, national decision‑making forum, relevant technical units of the ministry of health, WHO and other partners.The symposium also highlighted the role of early investigations and studies as a key component of a multi‑source surveillance system needed at country level to generate a broad range of evidence. It underscored the critical role of country Unity Studies sites and similar research entities in generating evidence to support public health decision‑making during epidemics and pandemics.Participants of the WHO GISRS Unity Studies Sites Network- SEAR Chapter Meeting 2026 (Photo credit- PEM/WHE/SEARO). SEARO also updated participants on ongoing efforts to develop a regional Unity Studies webpage and to promote participation in global knowledge‑sharing platforms, including webinars and the WHO Community of Practice. Priorities for 2026 include supporting the implementation of Unity protocols, strengthening collaboration and experience sharing across sites, documenting and publishing findings, integrating Unity Studies activities as a component of multi-source national surveillance systems, and building workforce capacity.Dr Nickle Boddington of the Global Influenza Programme (GIP) at WHO Headquarters, which coordinates the Unity Studies Network globally, provided updates on global Unity Studies activities, noting that the network has expanded to 16 sites worldwide. New and updated protocols, including rapid clinical severity assessment tools and standardized data platforms, are being developed to support implementation. The global Community of Practice has also been launched to facilitate technical exchange, and continued support will be provided to sites for protocol adaptation, ethical approvals, and readiness for early investigation during outbreaks. Updates from Unity Studies sites in SEAR in 2025Unity Studies sites shared progress and experiences in implementing protocols across diverse country contexts. Sites initiated activities in 2025 using catalytic funding from SEARO, complemented by the mobilization of internal national resources. The Institute of Epidemiology, Disease Control and Research (IEDCR), Bangladesh, reported the adoption and piloting of investigation protocols on non‑seasonal influenza and emerging respiratory diseases during recent avian influenza outbreaks, demonstrating a multi‑source funding approach involving government, WHO and One Health partners.The Hamdard Institute of Medical Sciences and Research (HIMSR), New Delhi, India, highlighted the piloting of household transmission investigation studies, the expansion of the national Unity Studies network, and the contribution of study findings to global evidence through published outputs. The All-India Institute of Medical Sciences (AIIMS), New Delhi, India, shared experiences from large‑scale seroprevalence studies conducted during the COVID‑19 pandemic, recent efforts to strengthen national Unity network sites through training activities, and plans to initiate multi‑centre studies on respiratory viruses.Similarly, Prince of Songkla University, Thailand, highlighted its experience in developing integrated surveillance and diagnostic protocols for multiple respiratory pathogens, enhancing readiness for targeted investigations of emerging threats. The University of Sri Jayewardenepura, Sri Lanka, reported ongoing engagement with the Ministry of Health and exploration of additional funding sources to initiate studies. Meanwhile, the National Public Health Laboratory, Nepal, provided updates on continued coordination with national stakeholders to initiate implementation, despite delays related to the country context.Across sites, shared experiences underscored the importance of protocol adaptation, multisectoral collaboration, and sustainable funding to operationalize Unity Studies and generate evidence for public health action.Discussions and Way ForwardThe meeting reinforced key priorities for 2026, including strengthening unity studies protocol implementation, enhancing collaboration, knowledge sharing, integrating research as a component of national multi-source surveillance systems, and ensuring that generated evidence informs public health decision‑making. Participants also emphasized the importance of documentation, visibility, and leveraging multiple funding sources, and agreed on the following action points.Unity Studies Sites and WHO Country Offices:Advance adoption and implementation of at least one Unity protocol, continuing activities initiated in 2025 with catalytic funding, supplemented with other sources of funding where feasible.Document site-specific experiences, outcomes, and lessons learned; participate in regional and global knowledge-sharing platforms including WHO webinars and the Community of Practice.Work closely with ministries of health to establish unified national platforms for translating generated evidence into national public health decision-making. WHO Country Offices may facilitate technical support and complementary, synergistic funding opportunities where feasible. WHO Regional OfficeCoordinate with WHO Country Offices to support implementation of core unity studies activities by network sites through catalytic funding and provide technical guidance and virtual engagement opportunities throughout 2026.Facilitate the participation of all Unity Studies sites in the regional meeting on Unity Studies implementation in October 2026, to be held back‑to‑back with the Annual SEAR Regional PIP‑PC Meeting; develop and host a SEAR Unity Studies website; and mobilize support from academic institutions within the SEAR Unity Studies Network to support the development of regional manuscripts that showcase Unity Studies activities to scientific audiences and promote knowledge‑sharing.Explore complementary funding opportunities and partnerships to sustain and expand network activities across the Region.WHO HeadquartersProvide global technical guidance, updated protocols, and toolkits to support the implementation of Unity Studies in SEAR.Facilitate engagement of SEAR sites in global webinars, the Community of Practice, and opportunities to showcase their work.Support joint publications, inclusion of SEAR experiences in global outputs, and identification of additional funding and collaborative opportunities to strengthen Unity Studies activities.
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