fighting styles, WIRED quiz, brawler personality, combat skills, self-assessment, fighting arenas, personality quiz, test your skills, aggression in fighting ## Introduction Are you tired of pretending to be someone you're not? It’s time to face the brutal truth: not everyone can be a champion fighter, and even fewer can claim to know their true fighting style. The world of combat is rife...

Enterprise artificial intelligence investment is unprecedented, with IDC projecting global spending on AI and GenAI to double to $631 billion by 2028. Yet beneath the impressive budget allocations and boardroom enthusiasm lies a troubling reality: most organisations struggle to translate their AI ambitions into operational success.The sobering statistics behind AI’s promiseModelOp’s 2025 AI Governance Benchmark Report, based on input from 100 senior AI and data leaders at Fortune 500 enterprises, reveals a disconnect between aspiration and execution.While more than 80% of enterprises have 51 or more generative AI projects in proposal phases, only 18% have successfully deployed more than 20 models into production.The execution gap represents one of the most significant challenges facing enterprise AI today. Most generative AI projects still require 6 to 18 months to go live – if they reach production at all.The result is delayed returns on investment, frustrated stakeholders, and diminished confidence in AI initiatives in the enterprise.The cause: Structural, not technical barriersThe biggest obstacles preventing AI scalability aren’t technical limitations – they’re structural inefficiencies plaguing enterprise operations. The ModelOp benchmark report identifies several problems that create what experts call a “time-to-market quagmire.”Fragmented systems plague implementation. 58% of organisations cite fragmented systems as the top obstacle to adopting governance platforms. Fragmentation creates silos where different departments use incompatible tools and processes, making it nearly impossible to maintain consistent oversight in AI initiatives.Manual processes dominate despite digital transformation. 55% of enterprises still rely on manual processes – including spreadsheets and email – to manage AI use case intake. The reliance on antiquated methods creates bottlenecks, increases the likelihood of errors, and makes it difficult to scale AI operations.Lack of standardisation hampers progress. Only 23% of organisations implement standardised intake, development, and model management processes. Without these elements, each AI project becomes a unique challenge requiring custom solutions and extensive coordination by multiple teams.Enterprise-level oversight remains rare Just 14% of companies perform AI assurance at the enterprise level, increasing the risk of duplicated efforts and inconsistent oversight. The lack of centralised governance means organisations often discover they’re solving the same problems multiple times in different departments.The governance revolution: From obstacle to acceleratorA change is taking place in how enterprises view AI governance. Rather than seeing it as a compliance burden that slows innovation, forward-thinking organisations recognise governance as an important enabler of scale and speed.Leadership alignment signals strategic shift. The ModelOp benchmark data reveals a change in organisational structure: 46% of companies now assign accountability for AI governance to a Chief Innovation Officer – more than four times the number who place accountability under Legal or Compliance. This strategic repositioning reflects a new understanding that governance isn’t solely about risk management, but can enable innovation.Investment follows strategic priority. A financial commitment to AI governance underscores its importance. According to the report, 36% of enterprises have budgeted at least $1 million annually for AI governance software, while 54% have allocated resources specifically for AI Portfolio Intelligence to track value and ROI.What high-performing organisations do differentlyThe enterprises that successfully bridge the ‘execution gap’ share several characteristics in their approach to AI implementation:Standardised processes from day one. Leading organisations implement standardised intake, development, and model review processes in AI initiatives. Consistency eliminates the need to reinvent workflows for each project and ensures that all stakeholders understand their responsibilities.Centralised documentation and inventory. Rather than allowing AI assets to proliferate in disconnected systems, successful enterprises maintain centralised inventories that provide visibility into every model’s status, performance, and compliance posture.Automated governance checkpoints. High-performing organisations embed automated governance checkpoints throughout the AI lifecycle, helping ensure compliance requirements and risk assessments are addressed systematically rather than as afterthoughts.End-to-end traceability. Leading enterprises maintain complete traceability of their AI models, including data sources, training methods, validation results, and performance metrics.Measurable impact of structured governanceThe benefits of implementing comprehensive AI governance extend beyond compliance. Organisations that adopt lifecycle automation platforms reportedly see dramatic improvements in operational efficiency and business outcomes.A financial services firm profiled in the ModelOp report experienced a halving of time to production and an 80% reduction in issue resolution time after implementing automated governance processes. Such improvements translate directly into faster time-to-value and increased confidence among business stakeholders.Enterprises with robust governance frameworks report the ability to many times more models simultaneously while maintaining oversight and control. This scalability lets organisations pursue AI initiatives in multiple business units without overwhelming their operational capabilities.The path forward: From stuck to scaledThe message from industry leaders that the gap between AI ambition and execution is solvable, but it requires a shift in approach. Rather than treating governance as a necessary evil, enterprises should realise it enables AI innovation at scale.Immediate action items for AI leadersOrganisations looking to escape the ‘time-to-market quagmire’ should prioritise the following:Audit current state: Conduct an assessment of existing AI initiatives, identifying fragmented processes and manual bottlenecksStandardise workflows: Implement consistent processes for AI use case intake, development, and deployment in all business unitsInvest in integration: Deploy platforms to unify disparate tools and systems under a single governance frameworkEstablish enterprise oversight: Create centralised visibility into all AI initiatives with real-time monitoring and reporting abilitiesThe competitive advantage of getting it rightOrganisations that can solve the execution challenge will be able to bring AI solutions to market faster, scale more efficiently, and maintain the trust of stakeholders and regulators.Enterprises that continue with fragmented processes and manual workflows will find themselves disadvantaged compared to their more organised competitors. Operational excellence isn’t about efficiency but survival.The data shows enterprise AI investment will continue to grow. Therefore, the question isn’t whether organisations will invest in AI, but whether they’ll develop the operational abilities necessary to realise return on investment. The opportunity to lead in the AI-driven economy has never been greater for those willing to embrace governance as an enabler not an obstacle.(Image source: Unsplash)

The commission, valued at up to £46,000 (including VAT), will see the appointed architect work closely with ateb’s internal teams to deliver a 30-unit housing development, supporting the group’s mission to create better living solutions for the people and communities of West Wales. The two-year contract, running from July 2025 to July 2027, will require the architect to oversee all stages of design, from feasibility through to tender, in line with Welsh Government technical scrutiny and local authority planning requirements. The project is part of ateb’s ongoing commitment to respond to local housing need, regenerate communities, and provide a variety of affordable tenures, including social rent, rent to buy, and shared ownership.Advertisement According to the brief: ‘The ateb Group (where ateb means answer or solution In Welsh) is a unique set o companies that collectively has the shared purpose of 'Creating better living solutions for the people and communities of West Wales. ‘ateb currently has around 3,100 homes predominantly in Pembrokeshire, that we rent on either a social or intermediate rental basis.  ateb works closely with its Local Authority and other partners to develop around 150 new homes every year, to meet affordable housing need through a range of tenures such as, for rent, rent to buy or shared ownership.’ Tavernspite is a small village of around 350 inhabitants located 9.7km southeast of Narberth in Pembrokeshire. Ateb, based in nearby Haverfordwest, is a not-for-profit housing association managing around 3,100 homes across the county. The group’s social purpose is supported by its subsidiaries: Mill Bay Homes, which develops homes for sale to reinvest profits into affordable housing, and West Wales Care and Repair, which supports older and vulnerable residents to remain independent in their homes. Bids will be assessed 60 per cent on quality and 40 per cent on price, with a strong emphasis on experience in the housing association sector and collaborative working with internal client teams.Advertisement Applicants must hold professional indemnity insurance of at least £2 million and be prepared to attend in-person evaluation presentations as part of the assessment process. Competition details Project title Provision of Architect Services for Tavernspite Development Client Contract value Tbc First round deadline Midday, 3 July 2025 Restrictions The contract particularly welcomes submissions from small and medium-sized enterprises (SMEs) and voluntary, community, and social enterprises (VCSEs) More information https://www.find-tender.service.gov.uk/Notice/031815-2025

The government has axed a scheme for upgrading energy efficiency in public sector buildings. The Public Sector Decarbonisation Scheme (PSDS) delivered more than £2.5bn in its first three phases for measures such as heat pumps, solar panels, insulation and double glazing, with further funding of nearly £1bn recently announced. But the Department for Energy Security and Net Zero (DESNZ) has told Building Design that the scheme has been dropped after the spending review, leaving uncertainty about how upgrades will be funded when the current phase expires in 2028. Source: UK Government/FlickrEd Miliband’s Department for Energy Security and Net Zero is responsible for the scheme The department said it would set out plans for the period after 2028 in due course. In a post on LinkedIn, Dave Welkin, director of sustainability at Gleeds, said he had waited for the release of the spending review with a “sense of trepidation” and was unable to find mention of public sector decarbonisation when Treasury documents were released. “I hoped because it was already committed in the Budget that its omission wasn’t ominous,” he wrote. Yesterday, he was told by Salix Finance, the non-departmental public body that delivers funding for the scheme, that it was no longer being funded. It comes after the withdrawal of funding for the Low Carbon Skills Fund (LCSF) in May. According to the government’s website, PSDS and LCSF were intended to support the reduction of emissions from public sector buildings by 75% by 2037, compared to a 2017 baseline. “Neither LCSF or PSDS were perfect by any means, but they did provide a vital source of funding for local authorities, hospitals, schools and many other public sector organisations to save energy, carbon and money,” Welkin said. “PSDS has helped replace failed heating systems in schools, keeping students warm. It’s replaced roofs on hospitals, helping patients recover from illness. It’s replaced windows in our prisons, improving security and stopping drugs getting behind bars.” However, responding to Welkin’s post, Steve Connolly, chief executive at Arriba Technologies, a low carbon heating and cooling firm, said that the scheme was being “mismanaged” with a small number of professional services firms “scooping up disproportionately large grants for their clients”. The fourth phase of the scheme was confirmed last September, with allocations confirmed only last month. This latest phase, which covers the financial years between 2025/26 and 2027/28, saw the distribution of £940m across the country. A DESNZ spokesperson said: “Our settlement is about investing in Britain’s renewal to create energy security, sprint to clean power by 2030, encourage investment, create jobs and bring down bills for good. “We will deliver £1bn in current allocations of the Public Sector Decarbonisation Scheme until 2028 and, through Great British Energy, have invested in new rooftop solar power and renewable schemes to lower energy bills for schools and hospitals across the UK. “We want to build on this progress by incentivising the public sector to decarbonise, so they can reap the benefits in lower bills and emissions, sharing best practice across government and exploring the use of repayable finance, where appropriate.” A government assessment of phase 3a and 3b projects identified a number of issues with the scheme, including delays and cost inflation, with more than a tenth being abandoned subsequent to grants being offered. Stakeholders interviewed for the report also identified “difficulties in obtaining skilled contractors and equipment”, especially air source heat pumps. The first come first served approach to awarding funding was also said to be “encouraging applicants to opt for more straightforward projects” and “potentially undermining the achievement of PSDS objective by restricting the opportunity for larger [and] more complex measures which may have delivered greater carbon reduction benefits”. But the consensus among stakeholders and industry representatives interviewed for the report was that the scheme was “currently key to sustaining the existing UK heat pump market” and that it was “seen as vital in enabling many public sector organisations to invest in heat decarbonisation”.

Insights How to Create a Successful Leadership Development Program At Harvard Business Impact, we partner with organizations to craft tailored learning experiences for leaders across all levels. Though each collaboration is unique, there is a proven process for designing and developing impactful learning initiatives. Leverage our checklist to help your organization develop a leadership development program that delivers results. View the infographic Leadership DevelopmentStrategic Alignment Share this resource Share on LinkedIn Share on Facebook Share on X Share on WhatsApp Email this Page Connect with us Change isn’t easy, but we can help. Together we’ll create informed and inspired leaders ready to shape the future of your business. Contact us Latest Insights Strategic Alignment Harvard Business Publishing Unveils Harvard Business Impact as New Brand for Corporate Learning and Education Units Harvard Business Publishing announced the launch of Harvard Business Impact, a new brand identity for… Read more: Harvard Business Publishing Unveils Harvard Business Impact as New Brand for Corporate Learning and Education Units News Digital Intelligence Succeeding in the Digital Age: Why AI-First Leadership Is Essential While AI makes powerful operational efficiencies possible, it cannot yet replace the creativity, adaptability, and… Read more: Succeeding in the Digital Age: Why AI-First Leadership Is Essential Perspectives Digital Intelligence 4 Keys to AI-First Leadership: The New Imperative for Digital Transformation AI has become a defining force in reshaping industries and determining competitive advantage. To support… Read more: 4 Keys to AI-First Leadership: The New Imperative for Digital Transformation Infographic Talent Management Leadership Fitness Behavioral Assessment In our study, “Leadership Fitness: Developing the Capacity to See and Lead Differently Amid Complexity,”… Read more: Leadership Fitness Behavioral Assessment Job Aid The post How to Create a Successful Leadership Development Program appeared first on Harvard Business Impact.

Reading Time: 9 minutes In the ever-evolving landscape of customer engagement, staying ahead of the curve is not just advantageous, it’s essential. That’s why, for Chapter 7 of “The Customer Engagement Book: Adapt or Die,” we sat down with Mirela Cialai, a seasoned expert in CRM and Martech strategies at brands like Equinox. Mirela brings a wealth of knowledge in aligning technology roadmaps with business goals, shifting organizational focuses from acquisition to retention, and leveraging hyper-personalization to drive success. In this interview, Mirela dives deep into building robust customer engagement technology roadmaps. She unveils the “PAPER” framework—Plan, Audit, Prioritize, Execute, Refine—a simple yet effective strategy for marketers. You’ll gain insights into identifying gaps in your Martech stack, ensuring data accuracy, and prioritizing initiatives that deliver the greatest impact and ROI. Whether you’re navigating data silos, striving for cross-functional alignment, or aiming for seamless tech integration, Mirela’s expertise provides practical solutions and actionable takeaways.   Mirela Cialai Q&A Interview 1. How do you define the vision for a customer engagement platform roadmap in alignment with the broader business goals? Can you share any examples of successful visions from your experience? Defining the vision for the roadmap in alignment with the broader business goals involves creating a strategic framework that connects the team’s objectives with the organization’s overarching mission or primary objectives. This could be revenue growth, customer retention, market expansion, or operational efficiency. We then break down these goals into actionable areas where the team can contribute, such as improving engagement, increasing lifetime value, or driving acquisition. We articulate how the team will support business goals by defining the KPIs that link CRM outcomes — the team’s outcomes — to business goals. In a previous role, the CRM team I was leading faced significant challenges due to the lack of attribution capabilities and a reliance on surface-level metrics such as open rates and click-through rates to measure performance. This approach made it difficult to quantify the impact of our efforts on broader business objectives such as revenue growth. Recognizing this gap, I worked on defining a vision for the CRM team to address these shortcomings. Our vision was to drive measurable growth through enhanced data accuracy and improved attribution capabilities, which allowed us to deliver targeted, data-driven, and personalized customer experiences. To bring this vision to life, I developed a roadmap that focused on first improving data accuracy, building our attribution capabilities, and delivering personalization at scale. By aligning the vision with these strategic priorities, we were able to demonstrate the tangible impact of our efforts on the key business goals. 2. What steps did you take to ensure data accuracy? The data team was very diligent in ensuring that our data warehouse had accurate data. So taking that as the source of truth, we started cleaning the data in all the other platforms that were integrated with our data warehouse — our CRM platform, our attribution analytics platform, etc. That’s where we started, looking at all the different integrations and ensuring that the data flows were correct and that we had all the right flows in place. And also validating and cleaning our email database — that helped, having more accurate data. 3. How do you recommend shifting organizational focus from acquisition to retention within a customer engagement strategy? Shifting an organization’s focus from acquisition to retention requires a cultural and strategic shift, emphasizing the immense value that existing customers bring to long-term growth and profitability. I would start by quantifying the value of retention, showcasing how retaining customers is significantly more cost-effective than acquiring new ones. Research consistently shows that increasing retention rates by just 5% can boost profits by at least 25 to 95%. This data helps make a compelling case to stakeholders about the importance of prioritizing retention. Next, I would link retention to core business goals by demonstrating how enhancing customer lifetime value and loyalty can directly drive revenue growth. This involves shifting the organization’s focus to retention-specific metrics such as churn rate, repeat purchase rate, and customer LTV. These metrics provide actionable insights into customer behaviors and highlight the financial impact of retention initiatives, ensuring alignment with the broader company objectives. By framing retention as a driver of sustainable growth, the organization can see it not as a competing priority, but as a complementary strategy to acquisition, ultimately leading to a more balanced and effective customer engagement strategy. 4. What are the key steps in analyzing a brand’s current Martech stack capabilities to identify gaps and opportunities for improvement? Developing a clear understanding of the Martech stack’s current state and ensuring it aligns with a brand’s strategic needs and future goals requires a structured and strategic approach. The process begins with defining what success looks like in terms of technology capabilities such as scalability, integration, automation, and data accessibility, and linking these capabilities directly to the brand’s broader business objectives. I start by doing an inventory of all tools currently in use, including their purpose, owner, and key functionalities, assessing if these tools are being used to their full potential or if there are features that remain unused, and reviewing how well tools integrate with one another and with our core systems, the data warehouse. Also, comparing the capabilities of each tool and results against industry standards and competitor practices and looking for missing functionalities such as personalization, omnichannel orchestration, or advanced analytics, and identifying overlapping tools that could be consolidated to save costs and streamline workflows. Finally, review the costs of the current tools against their impact on business outcomes and identify technologies that could reduce costs, increase efficiency, or deliver higher ROI through enhanced capabilities. Establish a regular review cycle for the Martech stack to ensure it evolves alongside the business and the technological landscape. 5. How do you evaluate whether a company’s tech stack can support innovative customer-focused campaigns, and what red flags should marketers look out for? I recommend taking a structured approach and first ensure there is seamless integration across all tools to support a unified customer view and data sharing across the different channels. Determine if the stack can handle increasing data volumes, larger audiences, and additional channels as the campaigns grow, and check if it supports dynamic content, behavior-based triggers, and advanced segmentation and can process and act on data in real time through emerging technologies like AI/ML predictive analytics to enable marketers to launch responsive and timely campaigns. Most importantly, we need to ensure that the stack offers robust reporting tools that provide actionable insights, allowing teams to track performance and optimize campaigns. Some of the red flags are: data silos where customer data is fragmented across platforms and not easily accessible or integrated, inability to process or respond to customer behavior in real time, a reliance on manual intervention for tasks like segmentation, data extraction, campaign deployment, and poor scalability. If the stack struggles with growing data volumes or expanding to new channels, it won’t support the company’s evolving needs. 6. What role do hyper-personalization and timely communication play in a successful customer engagement strategy? How do you ensure they’re built into the technology roadmap? Hyper-personalization and timely communication are essential components of a successful customer engagement strategy because they create meaningful, relevant, and impactful experiences that deepen the relationship with customers, enhance loyalty, and drive business outcomes. Hyper-personalization leverages data to deliver tailored content that resonates with each individual based on their preferences, behavior, or past interactions, and timely communication ensures these personalized interactions occur at the most relevant moments, which ultimately increases their impact. Customers are more likely to engage with messages that feel relevant and align with their needs, and real-time triggers such as cart abandonment or post-purchase upsells capitalize on moments when customers are most likely to convert. By embedding these capabilities into the roadmap through data integration, AI-driven insights, automation, and continuous optimization, we can deliver impactful, relevant, and timely experiences that foster deeper customer relationships and drive long-term success. 7. What’s your approach to breaking down the customer engagement technology roadmap into manageable phases? How do you prioritize the initiatives? To create a manageable roadmap, we need to divide it into distinct phases, starting with building the foundation by addressing data cleanup, system integrations, and establishing metrics, which lays the groundwork for success. Next, we can focus on early wins and quick impact by launching behavior-based campaigns, automating workflows, and improving personalization to drive immediate value. Then we can move to optimization and expansion, incorporating predictive analytics, cross-channel orchestration, and refined attribution models to enhance our capabilities. Finally, prioritize innovation and scalability, leveraging AI/ML for hyper-personalization, scaling campaigns to new markets, and ensuring the system is equipped for future growth. By starting with foundational projects, delivering quick wins, and building towards scalable innovation, we can drive measurable outcomes while maintaining our agility to adapt to evolving needs. In terms of prioritizing initiatives effectively, I would focus on projects that deliver the greatest impact on business goals, on customer experience and ROI, while we consider feasibility, urgency, and resource availability. In the past, I’ve used frameworks like Impact Effort Matrix to identify the high-impact, low-effort initiatives and ensure that the most critical projects are addressed first. 8. How do you ensure cross-functional alignment around this roadmap? What processes have worked best for you? Ensuring cross-functional alignment requires clear communication, collaborative planning, and shared accountability. We need to establish a shared understanding of the roadmap’s purpose and how it ties to the company’s overall goals by clearly articulating the “why” behind the roadmap and how each team can contribute to its success. To foster buy-in and ensure the roadmap reflects diverse perspectives and needs, we need to involve all stakeholders early on during the roadmap development and clearly outline each team’s role in executing the roadmap to ensure accountability across the different teams. To keep teams informed and aligned, we use meetings such as roadmap kickoff sessions and regular check-ins to share updates, address challenges collaboratively, and celebrate milestones together. 9. If you were to outline a simple framework for marketers to follow when building a customer engagement technology roadmap, what would it look like? A simple framework for marketers to follow when building the roadmap can be summarized in five clear steps: Plan, Audit, Prioritize, Execute, and Refine. In one word: PAPER. Here’s how it breaks down. Plan: We lay the groundwork for the roadmap by defining the CRM strategy and aligning it with the business goals. Audit: We evaluate the current state of our CRM capabilities. We conduct a comprehensive assessment of our tools, our data, the processes, and team workflows to identify any potential gaps. Prioritize: initiatives based on impact, feasibility, and ROI potential. Execute: by implementing the roadmap in manageable phases. Refine: by continuously improving CRM performance and refining the roadmap. So the PAPER framework — Plan, Audit, Prioritize, Execute, and Refine — provides a structured, iterative approach allowing marketers to create a scalable and impactful customer engagement strategy. 10. What are the most common challenges marketers face in creating or executing a customer engagement strategy, and how can they address these effectively? The most critical is when the customer data is siloed across different tools and platforms, making it very difficult to get a unified view of the customer. This limits the ability to deliver personalized and consistent experiences. The solution is to invest in tools that can centralize data from all touchpoints and ensure seamless integration between different platforms to create a single source of truth. Another challenge is the lack of clear metrics and ROI measurement and the inability to connect engagement efforts to tangible business outcomes, making it very hard to justify investment or optimize strategies. The solution for that is to define clear KPIs at the outset and use attribution models to link customer interactions to revenue and other key outcomes. Overcoming internal silos is another challenge where there is misalignment between teams, which can lead to inconsistent messaging and delayed execution. A solution to this is to foster cross-functional collaboration through shared goals, regular communication, and joint planning sessions. Besides these, other challenges marketers can face are delivering personalization at scale, keeping up with changing customer expectations, resource and budget constraints, resistance to change, and others. While creating and executing a customer engagement strategy can be challenging, these obstacles can be addressed through strategic planning, leveraging the right tools, fostering collaboration, and staying adaptable to customer needs and industry trends. By tackling these challenges proactively, marketers can deliver impactful customer-centric strategies that drive long-term success. 11. What are the top takeaways or lessons that you’ve learned from building customer engagement technology roadmaps that others should keep in mind? I would say one of the most important takeaways is to ensure that the roadmap directly supports the company’s broader objectives. Whether the focus is on retention, customer lifetime value, or revenue growth, the roadmap must bridge the gap between high-level business goals and actionable initiatives. Another important lesson: The roadmap is only as effective as the data and systems it’s built upon. I’ve learned the importance of prioritizing foundational elements like data cleanup, integrations, and governance before tackling advanced initiatives like personalization or predictive analytics. Skipping this step can lead to inefficiencies or missed opportunities later on. A Customer Engagement Roadmap is a strategic tool that evolves alongside the business and its customers. So by aligning with business goals, building a solid foundation, focusing on impact, fostering collaboration, and remaining adaptable, you can create a roadmap that delivers measurable results and meaningful customer experiences.     This interview Q&A was hosted with Mirela Cialai, Director of CRM & MarTech at Equinox, for Chapter 7 of The Customer Engagement Book: Adapt or Die. Download the PDF or request a physical copy of the book here. The post Mirela Cialai Q&A: Customer Engagement Book Interview appeared first on MoEngage.

A dangerous strain of bird flu is spreading in US livestockMediaMedium/Alamy Since Donald Trump assumed office in January, the leading US public health agency has pulled back preparations for a potential bird flu pandemic. But as it steps back, another government agency is stepping up. While the US Department of Health and Human Services (HHS) previously held regular briefings on its efforts to prevent a wider outbreak of a deadly bird flu virus called H5N1 in people, it largely stopped once Trump took office. It has also cancelled funding for a vaccine that would have targeted the virus. In contrast, the US Department of Agriculture (USDA) has escalated its fight against H5N1’s spread in poultry flocks and dairy herds, including by funding the development of livestock vaccines. This particular virus – a strain of avian influenza called H5N1 – poses a significant threat to humans, having killed about half of the roughly 1000 people worldwide who tested positive for it since 2003. While the pathogen spreads rapidly in birds, it is poorly adapted to infecting humans and isn’t known to transmit between people. But that could change if it acquires mutations that allow it to spread more easily among mammals – a risk that increases with each mammalian infection. The possibility of H5N1 evolving to become more dangerous to people has grown significantly since March 2024, when the virus jumped from migratory birds to dairy cows in Texas. More than 1,070 herds across 17 states have been affected since then. H5N1 also infects poultry, placing the virus in closer proximity to people. Since 2022, nearly 175 million domestic birds have been culled in the US due to H5N1, and almost all of the 71 people who have tested positive for it had direct contact with livestock. Get the most essential health and fitness news in your inbox every Saturday. Sign up to newsletter “We need to take this seriously because when [H5N1] constantly is spreading, it’s constantly spilling over into humans,” says Seema Lakdawala at Emory University in Georgia. The virus has already killed a person in the US and a child in Mexico this year. Still, cases have declined under Trump. The last recorded human case was in February, and the number of affected poultry flocks fell 95 per cent between then and June. Outbreaks in dairy herds have also stabilised. It isn’t clear what is behind the decline. Lakdawala believes it is partly due to a lull in bird migration, which reduces opportunities for the virus to spread from wild birds to livestock. It may also reflect efforts by the USDA to contain outbreaks on farms. In February, the USDA unveiled a $1 billion plan for tackling H5N1, including strengthening farmers’ defences against the virus, such as through free biosecurity assessments. Of the 150 facilities that have undergone assessment, only one has experienced an H5N1 outbreak. Under Trump, the USDA also continued its National Milk Testing Strategy, which mandates farms provide raw milk samples for influenza testing. If a farm is positive for H5N1, it must allow the USDA to monitor livestock and implement measures to contain the virus. The USDA launched the programme in December and has since ramped up participation to 45 states. “The National Milk Testing Strategy is a fantastic system,” says Erin Sorrell at Johns Hopkins University in Maryland. Along with the USDA’s efforts to improve biosecurity measures on farms, milk testing is crucial for containing the outbreak, says Sorrell. But while the USDA has bolstered its efforts against H5N1, the HHS doesn’t appear to have followed suit. In fact, the recent drop in human cases may reflect decreased surveillance due to workforce cuts, says Sorrell. In April, the HHS laid off about 10,000 employees, including 90 per cent of staff at the National Institute for Occupational Safety and Health, an office that helps investigate H5N1 outbreaks in farm workers. “There is an old saying that if you don’t test for something, you can’t find it,” says Sorrell. Yet a spokesperson for the US Centers for Disease Control and Prevention (CDC) says its guidance and surveillance efforts have not changed. “State and local health departments continue to monitor for illness in persons exposed to sick animals,” they told New Scientist. “CDC remains committed to rapidly communicating information as needed about H5N1.” The USDA and HHS also diverge on vaccination. While the USDA has allocated $100 million toward developing vaccines and other solutions for preventing H5N1’s spread in livestock, the HHS cancelled $776 million in contracts for influenza vaccine development. The contracts – terminated on 28 May – were with the pharmaceutical company Moderna to develop vaccines targeting flu subtypes, including H5N1, that could cause future pandemics. The news came the same day Moderna reported nearly 98 per cent of the roughly 300 participants who received two doses of the H5 vaccine in a clinical trial had antibody levels believed to be protective against the virus. The US has about five million H5N1 vaccine doses stockpiled, but these are made using eggs and cultured cells, which take longer to produce than mRNA-based vaccines like Moderna’s. The Moderna vaccine would have modernised the stockpile and enabled the government to rapidly produce vaccines in the event of a pandemic, says Sorrell. “It seems like a very effective platform and would have positioned the US and others to be on good footing if and when we needed a vaccine for our general public,” she says. The HHS cancelled the contracts due to concerns about mRNA vaccines, which Robert F Kennedy Jr – the country’s highest-ranking public health official – has previously cast doubt on. “The reality is that mRNA technology remains under-tested, and we are not going to spend taxpayer dollars repeating the mistakes of the last administration,” said HHS communications director Andrew Nixon in a statement to New Scientist. However, mRNA technology isn’t new. It has been in development for more than half a century and numerous clinical trials have shown mRNA vaccines are safe. While they do carry the risk of side effects – the majority of which are mild – this is true of almost every medical treatment. In a press release, Moderna said it would explore alternative funding paths for the programme. “My stance is that we should not be looking to take anything off the table, and that includes any type of vaccine regimen,” says Lakdawala. “Vaccines are the most effective way to counter an infectious disease,” says Sorrell. “And so having that in your arsenal and ready to go just give you more options.” Topics:

The recent wave of cyber attacks targeting UK retailers has been a moment of reckoning for the entire retail industry. As someone who went through supporting one of the largest retail breaches in history, this news hits close to home. The National Cyber Security Centre’s (NCSC) call to strengthen IT support protocols reinforces a hard truth: cybersecurity is no longer just a technical/operational issue. It’s a business issue that directly affects revenue, customer trust, and brand reputation. Retailers today are navigating an increasingly complex threat landscape, while also managing a vast user base that needs to stay informed and secure. The recent attacks don’t represent a failure, but an opportunity - an inflection point to invest in stronger visibility, continuous monitoring and a culture of shared responsibility that meets the realities of modern retail. We know that the cyber groups responsible for the recent retail hacks used sophisticated social engineering techniques, such as impersonating employees to deceive IT help desks into resetting passwords and providing information, thereby gaining unauthorised access to internal systems. Employees are increasingly a target, and retailers employ some of the largest, most diverse workforces, making them an even bigger risk with countless touchpoints for breaches. In these organisations, a cybersecurity-first culture is vital to combatting threats. Cybersecurity-first culture includes employees that are aware of these types of attacks and understand how to report them if they are contacted. In order to establish a cybersecurity-first culture, employees must be empowered to recognise and respond to threats, not just avoid them. This can be done through simulation training and threat assessments - showcasing real life examples of threats and brainstorming possible solutions to control and prevent further and future damage. This allows security teams to focus on strategy instead of constant firefighting, while leadership support - through budget, tools, and tone - reinforces its importance at every level. In addition to support workers, vendors also pose a significant attack path for bad actors. According to data from Elastic Path, 42% of retailers admit that legacy technology could be leaving them exposed to cyber risks. And with the accelerating pace of innovation, modern cyber threats are not only more complex, but often enter through unexpected avenues, like third-party vendors. Research from Vanta shows 46% of organisations say that a vendor of theirs has experienced a data breach since they started working together. The M&S breach is a case in point, with it being reported that attackers exploited a vulnerability in a contractor’s systems, not the retailer’s own. This underscores that visibility must extend beyond your perimeter to encompass the entire digital supply chain, in real time. Threats don’t wait for your quarterly review or annual audit. If you're only checking your controls or vendor status once a year, you're already behind. This means real-time visibility is now foundational to cyber defence. We need to know when something changes the moment it happens. This can be done through continuous monitoring, both for the technical controls and the relationships that introduce risk into your environment. We also need to rethink the way we resource and prioritise that visibility. Manual processes don’t scale with the complexity of modern infrastructure. Automation and tooling can help surface the right signals from the noise - whether it’s misconfigurations, access drift, or suspicious vendor behavior. The best case scenario is that security measures are embedded into all digital architecture, utilising a few security ‘must haves’ such as secure coding, continuous monitoring, and regular testing and improvement. Retailers who want to get proactive and about breaches following the events of the last few weeks can follow this action plan to get started: First, awareness - have your security leadership send a message out to managers of help desks and support teams to make sure they are aware of the recent attacks on retailers, and are in a position to inform teams of what to look out for. Then, investigate - pinpoint the attack path used on other retailers to make sure you have a full understanding of the risk to your organisation. After that, assess - conduct a threat assessment to identify what could go wrong, or how this attack path could be used in your organisation. The final step is to identify - figure out the highest risk gaps in your organisation, and the remediation steps to address each one. Strong cybersecurity doesn’t come from quick fixes - it takes time, leadership buy-in, and a shift in mindset across the organisation. My advice to security teams is simple: speak in outcomes. Frame cyber risk as business risk, because that’s what it is. The retailers that have fallen victim to recent attacks are facing huge financial losses, which makes this not just an IT issue - it’s a boardroom issue. Customers are paying attention. They want to trust the brands they buy from, and that trust is built on transparency and preparation. The recent retail attacks aren’t a reason to panic - they’re a reason to reset, evaluate current state risks, and fully understand the potential impacts of what is happening elsewhere. This is the moment to invest in your infrastructure, empower your teams, and embed security into your operations. The organisations that do this now won’t just be safer - they’ll be more competitive, more resilient, and better positioned for whatever comes next. Jadee Hanson is the Chief Information Security Officer at Vanta Read more about cyber security in retail Content Goes Here Harrods becomes latest UK retailer to fall victim to cyber attack Retail cyber crime spree a ‘wake-up call’, says NCSC CEO Retail cyber attacks hit food distributor Peter Green Chilled

The Inefficiency of Static Chain-of-Thought Reasoning in LRMs Recent LRMs achieve top performance by using detailed CoT reasoning to solve complex tasks. However, many simple tasks they handle could be solved by smaller models with fewer tokens, making such elaborate reasoning unnecessary. This echoes human thinking, where we use fast, intuitive responses for easy problems and slower, analytical thinking for complex ones. While LRMs mimic slow, logical reasoning, they generate significantly longer outputs, thereby increasing computational cost. Current methods for reducing reasoning steps lack flexibility, limiting models to a single fixed reasoning style. There is a growing need for adaptive reasoning that adjusts effort according to task difficulty.  Limitations of Existing Training-Based and Training-Free Approaches Recent research on improving reasoning efficiency in LRMs can be categorized into two main areas: training-based and training-free methods. Training strategies often use reinforcement learning or fine-tuning to limit token usage or adjust reasoning depth, but they tend to follow fixed patterns without flexibility. Training-free approaches utilize prompt engineering or pattern detection to shorten outputs during inference; however, they also lack adaptability. More recent work focuses on variable-length reasoning, where models adjust reasoning depth based on task complexity. Others study “overthinking,” where models over-reason unnecessarily. However, few methods enable dynamic switching between quick and thorough reasoning—something this paper addresses directly.  Introducing OThink-R1: Dynamic Fast/Slow Reasoning Framework Researchers from Zhejiang University and OPPO have developed OThink-R1, a new approach that enables LRMs to switch between fast and slow thinking smartly, much like humans do. By analyzing reasoning patterns, they identified which steps are essential and which are redundant. With help from another model acting as a judge, they trained LRMs to adapt their reasoning style based on task complexity. Their method reduces unnecessary reasoning by over 23% without losing accuracy. Using a loss function and fine-tuned datasets, OThink-R1 outperforms previous models in both efficiency and performance on various math and question-answering tasks.  System Architecture: Reasoning Pruning and Dual-Reference Optimization The OThink-R1 framework helps LRMs dynamically switch between fast and slow thinking. First, it identifies when LRMs include unnecessary reasoning, like overexplaining or double-checking, versus when detailed steps are truly essential. Using this, it builds a curated training dataset by pruning redundant reasoning and retaining valuable logic. Then, during fine-tuning, a special loss function balances both reasoning styles. This dual-reference loss compares the model’s outputs with both fast and slow thinking variants, encouraging flexibility. As a result, OThink-R1 can adaptively choose the most efficient reasoning path for each problem while preserving accuracy and logical depth.  Empirical Evaluation and Comparative Performance The OThink-R1 model was tested on simpler QA and math tasks to evaluate its ability to switch between fast and slow reasoning. Using datasets like OpenBookQA, CommonsenseQA, ASDIV, and GSM8K, the model demonstrated strong performance, generating fewer tokens while maintaining or improving accuracy. Compared to baselines such as NoThinking and DualFormer, OThink-R1 demonstrated a better balance between efficiency and effectiveness. Ablation studies confirmed the importance of pruning, KL constraints, and LLM-Judge in achieving optimal results. A case study illustrated that unnecessary reasoning can lead to overthinking and reduced accuracy, highlighting OThink-R1’s strength in adaptive reasoning.  Conclusion: Towards Scalable and Efficient Hybrid Reasoning Systems In conclusion, OThink-R1 is a large reasoning model that adaptively switches between fast and slow thinking modes to improve both efficiency and performance. It addresses the issue of unnecessarily complex reasoning in large models by analyzing and classifying reasoning steps as either essential or redundant. By pruning the redundant ones while maintaining logical accuracy, OThink-R1 reduces unnecessary computation. It also introduces a dual-reference KL-divergence loss to strengthen hybrid reasoning. Tested on math and QA tasks, it cuts down reasoning redundancy by 23% without sacrificing accuracy, showing promise for building more adaptive, scalable, and efficient AI reasoning systems in the future.  Check out the Paper and GitHub Page. All credit for this research goes to the researchers of this project. Also, feel free to follow us on Twitter and don’t forget to join our 100k+ ML SubReddit and Subscribe to our Newsletter. Sana HassanSana Hassan, a consulting intern at Marktechpost and dual-degree student at IIT Madras, is passionate about applying technology and AI to address real-world challenges. With a keen interest in solving practical problems, he brings a fresh perspective to the intersection of AI and real-life solutions.Sana Hassanhttps://www.marktechpost.com/author/sana-hassan/Building AI-Powered Applications Using the Plan → Files → Code Workflow in TinyDevSana Hassanhttps://www.marktechpost.com/author/sana-hassan/MemOS: A Memory-Centric Operating System for Evolving and Adaptive Large Language ModelsSana Hassanhttps://www.marktechpost.com/author/sana-hassan/Google AI Unveils a Hybrid AI-Physics Model for Accurate Regional Climate Risk Forecasts with Better Uncertainty AssessmentSana Hassanhttps://www.marktechpost.com/author/sana-hassan/Run Multiple AI Coding Agents in Parallel with Container-Use from Dagger

Insights Learning to Lead in the Digital Age: The AI Readiness Reflection As the race to integrate generative AI accelerates, organizations face a dual challenge: fostering tech-savviness across teams while developing next-generation leadership competencies. These are critical to ensuring that “everyone” in the organization is prepared for continuous adaptation and change. This AI Readiness Reflection is designed to help you assess where your leaders stand today and identify the optimal path to build the digital knowledge, mindset, skills, and leadership capabilities required to thrive in the future. Take the assessment now to discover how your current practices align with AI maturity—and gain actionable insights tailored to your organization’s readiness level. To download the full report, tell us a bit about yourself. 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