Yamaha Motor: Consolidated Business Results Summary - First Half of Fiscal Year Ending December 31, 2025 -
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Revenues for the period were 1,277.8 billion yen (a decrease of 70.6 billion yen or 5.2% compared with the same period of the previous fiscal year), operating income was 84.1 billion yen (a decrease of 70.0 billion yen or 45.4%), and net income attributable to owners of parent was 53.1 billion (a decrease of 59.8 billion yen or 52.9%).
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For the first half-year consolidated accounting period, the U.S. dollar traded at 148 yen (an increase of 4 yen from the same period of the previous fiscal year) and the euro at 162 yen (an increase of 3 yen).
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Declining unit sales in motorcycles, personal watercraft, and golf cars led to lower revenues. For operating income, the decrease in unit sales and higher R&D expenses in the core motorcycle and Marine Product businesses, as well as an increase in labor costs and other SG&A expenses brought revenue down.
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Forecast of Consolidated Business Results
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Regarding the consolidated business results for the first half of the fiscal year ending December 31, 2025, the Company's motorcycle business experienced a temporary suspension of production and shipments in Vietnam in the first quarter and India recorded lower unit sales in the first half of the year. Also, in the Marine Products business, demand in the major market of the U.S. was lower than predicted. As a result, both revenue and operating income fell below expectations.
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As for the Company's forecast of consolidated business results for the full fiscal year, further declines in revenues and profits are projected not only due to the lower sales factors outlined above but also due to the impact on demand from higher automobile taxes in Indonesia and increased costs brought on by additional tariffs by the U.S. Taking all these factors into account as well as the risk of a partial reversal of deferred tax assets, the Company has made the following downward revisions to its revenue and incomes forecast for fiscal 2025:
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The Province
39 minutes ago
- The Province
Speeding motorist driving at 320 km/h on Germany's Autobahn fined more than $1,000
Published Aug 06, 2025 • Last updated 3 hours ago • 1 minute read In this May 15, 2013 file photo a traffic sign indicating a speed limit of 120 km/h is pictured at the highway A59 close to Troisdorf, Germany. Photo by Oliver Berg / AP BERLIN — A motorist was clocked driving at more than 320 km/h on the Autobahn west of Berlin, a record high at more than 199 km/h above the speed limit, German police said. This advertisement has not loaded yet, but your article continues below. THIS CONTENT IS RESERVED FOR SUBSCRIBERS ONLY Subscribe now to read the latest news in your city and across Canada. Exclusive articles by top sports columnists Patrick Johnston, Ben Kuzma, J.J. Abrams and others. Plus, Canucks Report, Sports and Headline News newsletters and events. Unlimited online access to The Province and 15 news sites with one account. The Province ePaper, an electronic replica of the print edition to view on any device, share and comment on. Daily puzzles and comics, including the New York Times Crossword. Support local journalism. SUBSCRIBE TO UNLOCK MORE ARTICLES Subscribe now to read the latest news in your city and across Canada. Exclusive articles by top sports columnists Patrick Johnston, Ben Kuzma, J.J. Abrams and others. Plus, Canucks Report, Sports and Headline News newsletters and events. Unlimited online access to The Province and 15 news sites with one account. The Province ePaper, an electronic replica of the print edition to view on any device, share and comment on. Daily puzzles and comics, including the New York Times Crossword. Support local journalism. REGISTER / SIGN IN TO UNLOCK MORE ARTICLES Create an account or sign in to continue with your reading experience. Access articles from across Canada with one account. Share your thoughts and join the conversation in the comments. Enjoy additional articles per month. Get email updates from your favourite authors. THIS ARTICLE IS FREE TO READ REGISTER TO UNLOCK. Create an account or sign in to continue with your reading experience. Access articles from across Canada with one account Share your thoughts and join the conversation in the comments Enjoy additional articles per month Get email updates from your favourite authors The speedster, who was not identified, was caught while racing along the A2 highway near Burg on July 28. The driver was handed a fine of 900 euros (US$1,043), stripped of two points from his driver's license and banned from driving for three months, the Magdeburg police office said Tuesday. A roadside radar stand, known as an 'Enforcement Trailer,' caught the motorist in a routine check. A reading from its display showed 'the highest record speed' of 321 km/h, police said. Germany's famed Autobahn motorways have captured fascination and interest around the world for their lack of speeding limits. German authorities and driving clubs have argued over the years about whether the policy should continue. Limitless speeds aren't universal on the Autobahn, though, as parts of the motorway are subject to speed limits. The section of the motorway where the record-breaking driver was caught has a limit of 120 km/h. Vancouver Whitecaps News Sports Local News Celebrity
Globe and Mail
an hour ago
- Globe and Mail
Deepfake AI Market Latest Trends, Future Outlook, Size, Share, Applications, Advance Technology And Forecast
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Generative Adversarial Networks (GANs) and diffusion models, which enable hyper-realistic deepfake generation; the growing creator economy and social media's demand for creative content, which leads to wider adoption; and the concerning increase in deepfake frauds and misinformation, which feeds the urgent need for reliable detection solutions across industries, are the main factors driving the deepfake AI market. Download PDF Brochure@ The deepfake AI market is witnessing accelerated growth due to the rising adoption of multimodal detection systems that combine audio-visual signals with metadata analysis to enhance detection precision. As synthetic media becomes more layered, with deepfakes now blending facial animations, voice mimicry, and scene manipulation, enterprises are investing in tools that analyze cross-modal inconsistencies rather than relying on isolated visual cues. These advanced solutions are being embedded across high-stakes environments such as banking authentication flows, online proctoring, and digital onboarding platforms where real-time decisioning and high accuracy are critical. Multimodal detection also supports operational scalability by reducing false positives and improving model confidence, enabling enterprises to automate content trust decisions at volume. Regulatory scrutiny is further driving adoption, especially in sectors such as finance, government, and telecommunications, where content authenticity and user verification have become compliance priorities. With AI foundation models and transformer architectures now capable of jointly processing audio, video, and contextual metadata, the deepfake detection landscape is evolving into a strategic layer of enterprise risk management. Generative adversarial networks remain the backbone technology of deepfake AI development and detection, registering the largest share by market value in 2025 Among all core technologies underpinning the deepfake AI market, Generative Adversarial Networks (GANs) represent the largest and most commercially entrenched segment. Their bidirectional framework—comprising generator and discriminator models—forms the foundational mechanism for crafting synthetic media and serves as the analytical basis for detecting forgeries with increasing accuracy. GANs have matured from research prototypes to enterprise-grade engines that power a wide spectrum of deepfake capabilities, including face swapping, expression control, voice imitation, and image realism scoring. On the detection side, their adversarial structure is being reverse-engineered to identify digital fingerprints, compression artifacts, and inconsistencies in texture, lighting, or pixel alignment. GANs are also embedded in real-time media forensics and security pipelines, especially across sectors such as law enforcement and social platforms, where they aid in decoding malicious manipulation. The widespread availability of pre-trained GAN libraries and cloud-based tools is fueling enterprise adoption and reducing time-to-deployment for deepfake-centric solutions. Their continued evolution into variants like StyleGAN and conditional GANs is enabling more granular control and detection precision, positioning them as the dominant technology category in both deepfake generation and defense. BFSI is expected to be the fastest-growing vertical during the forecast period, fueled by a spike in synthetic fraud threats and regulatory pressure By vertical, the BFSI sector is expected to register the fastest growth in the deepfake AI market during the forecast period, driven by rising concerns around digital identity fraud, social engineering attacks, and synthetic KYC submissions. As financial institutions digitalize onboarding and service workflows, they are deploying advanced deepfake detection systems to validate customer identity during eKYC, video banking, and loan verification processes. Liveness detection and micro-expression analysis are increasingly being used to distinguish real users from AI-generated imposters, with regulatory mandates further accelerating deployment. Fraud analytics platforms are integrating deepfake-specific classifiers to monitor voice spoofing in call centers, manipulated transaction videos, and altered screenshots submitted in claims. Additionally, private banks and insurance providers are leveraging synthetic media analysis tools to prevent reputational and compliance risks linked to fake communications or phishing campaigns. Strategic partnerships with detection vendors and biometric verification startups are also rising, particularly in North America and Asia Pacific. With regulators in several jurisdictions issuing early-stage guidelines on synthetic identity detection, the BFSI segment is rapidly becoming the proving ground for enterprise-grade, compliant deepfake AI solutions. Asia Pacific to witness the fastest growth in the deepfake AI market, accelerated by a surge in synthetic media abuse and high-volume digital onboarding across financial institutions Asia Pacific is witnessing the fastest growth in the deepfake AI market, fueled by rapid digital transformation, a booming social media user base, and mounting cybersecurity threats. Countries such as China, India, South Korea, and Japan are experiencing a surge in manipulated media cases, ranging from identity fraud to misinformation campaigns, which are prompting governments and enterprises to invest in detection and liveness verification technologies. Financial institutions across the region are embedding deepfake identification tools within eKYC and fraud prevention systems, especially in emerging markets with high digital onboarding volumes. Regulatory bodies have also begun tightening guidelines on content authenticity and AI usage, encouraging the adoption of compliant AI governance and media authentication layers. The region's large pool of AI research talent, combined with public-private collaborations, is accelerating the development of multimodal detection models customized for regional languages and facial features. Additionally, Asia Pacific's growing investments in metaverse infrastructure and synthetic media production are creating parallel demand for quality control tools. Enterprises in sectors such as BFSI, government, and media are now embedding deepfake detection capabilities at the infrastructure level, positioning Asia Pacific as the most dynamic growth hub for deepfake AI during the forecast period. Request Sample Pages@ Unique Features in the Deepfake AI Market Generative Adversarial Networks (GANs) remain the backbone of deepfake generation, responsible for creating highly realistic synthetic media by pitting generator and discriminator models against each other. These systems capture subtle facial expressions, voice patterns, and micro‑motions. Meanwhile, transformer-based architectures—rapidly growing in adoption—are key in boosting realism, temporal coherence, and multimodal integration in deepfake outputs Platforms like Synthesia and Colossyan offer scalable generation of AI avatars that support dozens of languages, enabling video production without cameras or actors. Reid Hoffman's "deepfake twin" experiment shows how these tools can clone one's voice and extend it into multiple languages—used, for example, to deliver speeches in Hindi, Chinese, Japanese, and more Deepfake maturity now includes real-time and even autonomous generation, where AI-driven agents interact live across platforms. Check Point Research notes these can be used in scams like CEO fraud in live video calls, with losses exceeding tens of millions in recent incidents The detection segment has grown sophisticated: solutions like Vastav AI (India‑based), Intel FakeCatcher, BioID, Veritone, etc., offer forensic-level detection, metadata inspection, confidence scoring, and heatmaps to identify deepfakes in real time. These tools are increasingly offered on cloud platforms for scalable enterprise deployment Major Highlights of the Deepfake AI Market The deepfake AI market is witnessing explosive growth, driven by advancements in generative AI, computer vision, and natural language processing. Its use spans across entertainment, marketing, education, healthcare, and increasingly, malicious domains like misinformation and cyber fraud. The expansion of use cases—from Hollywood-grade face swapping to AI-generated avatars—underscores the growing versatility and commercial interest in the space. One of the most pressing highlights is the surge in cybercrime facilitated by deepfakes, particularly impersonation scams, political manipulation, and financial fraud. Real-time deepfake voice or video manipulation has been used in high-profile scams, including impersonation of CEOs during video calls to extract money or data. As technology becomes more accessible, threats to businesses and governments are becoming more sophisticated and harder to detect. To counteract misuse, the demand for deepfake detection technologies has surged. Tools from companies like Intel, Sensity AI, Deepware, and Vastav AI are being adopted by media platforms, financial institutions, and law enforcement. These tools use AI to identify manipulated content through metadata, facial distortions, lip sync mismatches, and contextual anomalies—ushering in a new age of content authentication. Despite the risks, the deepfake AI market is also evolving positively, with ethical applications growing in fields like education, accessibility, marketing, and film production. For instance, AI avatars are being used for personalized learning, digital actors for low-budget film production, and language dubbing across global markets. These uses are helping to legitimize and monetize the technology in regulated ways. Inquire Before Buying@ Top Companies in the Deepfake AI Market The major players in the deepfake AI market include Datambit (UK), Microsoft (US), AWS (US), Google (US), Intel (US), Veritone (US), Cogito Tech (US), Primeau Forensics (US), iProov (UK), Kairos (US), ValidSoft (US), MyHeritage (Israel), HyperVerge (US), BioID (Germany), DuckDuckGoose AI (Netherlands), Pindrop (US), Truepic (US), Synthesia (UK), (US), Deepware (Turkey), iDenfy (US), Q-Integrity (Switzerland), D-ID (Israel), Resemble AI (US), Sensity AI (Netherlands), Reality Defender (US), Attestiv (US), WeVerify (Germany), (US), Kroop AI (India), Respeecher (Ukraine), DeepSwap (US), Reface (Ukraine), (UK), Oz Forensics (UAE), Perfios (US), Illuminarty (US), Deepfake Detector (UK), buster (France), AutheticID (US), Jumio (US), and Paravision (US). Microsoft Microsoft has become one of the key players in the deepfake AI market through a broader strategy of embedding advanced AI ethics, trust, and safety measures across its expansive product ecosystem. Recognizing the threat posed by synthetic media to digital trust, Microsoft has developed and integrated technologies such as the Microsoft Video Authenticator, which can analyze photos and videos to provide a confidence score about whether the media is artificially manipulated. Additionally, Microsoft's strategic acquisition of startups and partnerships with academic institutions have strengthened its detection capabilities. A notable move was its collaboration with the AI Foundation to advance responsible content creation and fight deepfake misuse. By embedding deepfake detection and authenticity verification tools within its Azure AI and Microsoft 365 suites, Microsoft empowers enterprises, media outlets, and government agencies to protect against misinformation. The company has also backed initiatives like Project Origin and the Coalition for Content Provenance and Authenticity (C2PA) to promote industry-wide standards for digital media provenance. These strategic choices align with Microsoft's trust-first brand positioning, giving it an edge in addressing regulatory concerns and building customer confidence. Moreover, Microsoft invests heavily in educating its enterprise customers on synthetic media threats, positioning itself not just as a tech provider but as a key thought leader shaping policy discussions on deepfakes. This multi-faceted approach has helped Microsoft strengthen its share in the deepfake AI market while reinforcing its commitment to digital security and ethical AI innovation. Google Google has emerged as one of the most influential technology players tackling the challenges posed by deepfakes through a mix of pioneering research, robust product integration, and strategic ecosystem collaboration. Google's decision to publicly release one of the largest deepfake datasets, the DeepFake Detection Dataset, gave the global research community a valuable resource to train and benchmark detection models. This open-source approach demonstrates Google's commitment to transparency and collective progress in combating synthetic media threats. On the product side, Google has embedded detection capabilities within its YouTube platform to counter manipulated videos and misinformation campaigns, investing heavily in machine learning models that flag fake content at scale. Google has also been a driving force behind open standards for digital media authenticity through partnerships with the Content Authenticity Initiative (CAI) and the Coalition for Content Provenance and Authenticity (C2PA), aligning its strategy with industry leaders like Adobe and Twitter. Beyond detection, Google's AI research teams at DeepMind contribute foundational research on generative adversarial networks (GANs) and countermeasures, ensuring it stays at the forefront of both generation and detection advancements. By combining its technical expertise, vast computing infrastructure, and global reach, Google is uniquely positioned to address deepfake risks across platforms and devices. This proactive, research-driven approach enhances its reputation as a trusted steward of information integrity, bolstering its competitive advantage in the rapidly evolving deepfake AI market. Datambit Datambit is a UK-based AI company recognized for its innovative contributions to multimedia forensics and synthetic media detection. In the Deepfake AI market, Datambit focuses on developing advanced detection systems that leverage computer vision and machine learning to identify manipulated video and audio content. Their solutions are increasingly adopted by media companies, legal entities, and cybersecurity firms to combat misinformation, protect brand integrity, and enhance content authenticity in a rapidly evolving digital landscape. Amazon Web Services (AWS) Amazon Web Services (AWS) plays a pivotal role in the Deepfake AI market by offering scalable cloud infrastructure and machine learning tools that enable the development and deployment of deepfake generation and detection technologies. Through services like Amazon Rekognition and SageMaker, AWS supports researchers, developers, and enterprises in creating synthetic media as well as detecting manipulated content. AWS also emphasizes ethical AI use, providing resources and policies aimed at mitigating the misuse of generative models. Intel Corporation Intel is a key player in the Deepfake AI space, driving innovation through its hardware acceleration technologies and AI research. The company collaborates with academic and industry partners to develop tools for deepfake detection, including the FakeCatcher—a real-time deepfake detection platform that identifies synthetic content by analyzing subtle biological signals in videos. Intel's commitment to responsible AI development and content authenticity positions it as a trusted leader in countering the spread of manipulated media across industries.
Globe and Mail
an hour ago
- Globe and Mail
Strategic Growth in the Global X-Ray Detectors Market (2025-2030)
"Originally a part of Varian Imaging, Varex Imaging Corporation has expanded to become a world leader in producing and selling medical imaging devices, catering to industries like cargo screening and border security." key players operating in the global X-ray detectors market are Varex Imaging (US), Canon (Japan), Thales Group (France), Analogic Corporation (US), Agfa-Gevaert Group (Belgium), Carestream Health (US) The global X-ray detectors market is on a trajectory of sustained growth, projected to expand from US$3.4 billion in 2025 to US$4.4 billion by 2030, advancing at a CAGR of 5.5%. As digital transformation accelerates across healthcare, defense, and industrial sectors, X-ray detector technologies have become a key enabler of high-stakes decision-making, operational efficiency, and national security. For C-level executives and senior decision-makers, this evolution represents more than a technological upgrade—it's a strategic opportunity for ROI, innovation, and competitive advantage. Download PDF Brochure: Healthcare, Defense, and Beyond: Why the X-Ray Detectors Market Is Booming X-ray detectors are no longer limited to diagnostic imaging in hospitals. They are transforming border security, aerospace inspections, homeland defense, and precision medicine, thanks to major advances in flat-panel technologies, backscatter X-rays, and photon-counting detectors. Here's why this market matters for enterprise leaders: Security and Defense Digitization: Airports, seaports, and critical checkpoints are integrating advanced X-ray imaging to combat emerging threats. High-resolution, real-time detection of concealed weapons, explosives, and contraband is now critical for national and global security. Medical Imaging Modernization: As healthcare systems digitize globally, the shift from analog to flat-panel digital radiography ensures higher throughput, faster diagnostics, and improved patient safety—delivering both clinical value and operational cost savings. Industrial Inspection & Automation: Rugged and handheld detectors are increasingly used for non-destructive testing (NDT) in aerospace, oil & gas, and manufacturing—ensuring safety, compliance, and uptime in mission-critical systems. Market Leaders & Strategic Differentiators Varex Imaging (US): Diversification and Deep Sector Expertise Varex Imaging exemplifies the market's transition from traditional radiology to multisector innovation. With strong capabilities across medical, industrial, and security imaging, Varex's inorganic growth strategy—driven by acquisitions and global expansion—makes it a versatile partner for OEMs and system integrators. Their investment in AI-enabled imaging and advanced detector materials positions them as a formidable player in custom and scalable detector design. Thales Group (France): Security and Medical Fusion Through its Trixell division, Thales provides state-of-the-art flat-panel detectors for OEMs across radiography, fluoroscopy, and cardiovascular applications. The company's legacy in defense and secure communications complements its healthcare imaging operations—making it uniquely positioned to lead in dual-use imaging systems for civilian and military applications. Canon Inc. (Japan): Ecosystem Strength in Healthcare Canon leverages its expansive global network and R&D capabilities across digital radiography, CT, and MRI systems. The firm's seamless integration of X-ray detectors within a broader portfolio of diagnostic tools enables healthcare institutions to modernize imaging infrastructure holistically—reducing downtime, radiation exposure, and diagnostic uncertainty. Request Sample Pages : Technology Spotlight: Flat-Panel Detectors Drive Value Flat-panel detectors (FPDs), particularly those using cesium iodide (CsI), dominate the technology landscape due to: Superior Image Resolution: Ideal for early detection of chronic conditions like cancer or cardiovascular disease. Reduced Radiation Dosage: Enhances patient safety and supports regulatory compliance. Faster Image Acquisition: Improves clinical workflow and diagnostic throughput. With hospitals and imaging centers under pressure to improve diagnostic accuracy while managing costs, FPDs represent a high-ROI investment with proven clinical and operational benefits. Geographic Growth Hotspots: Strategic Markets to Watch North America remains the most mature market, driven by advanced infrastructure, strong reimbursement systems, and early adoption of AI-enhanced imaging. Asia Pacific is rapidly expanding due to increased healthcare spending, government initiatives in rural diagnostics, and a rising middle class demanding high-quality imaging. Europe continues to innovate through public-private partnerships, particularly in preventive care and cancer diagnostics. Global players are expected to deepen regional partnerships and invest in localized production to navigate shifting trade regulations and accelerate time to market. Investment Outlook: ROI and Strategic Benefits For C-suite leaders, the X-ray detectors market offers: Long-term ROI: Upgrading to advanced detectors can result in 10–20% operational efficiency gains, reduced maintenance costs, and improved service turnaround times. Innovation Advantage: Early investment in photon-counting or AI-integrated detectors can differentiate offerings in competitive bids or tenders. Sustainability Impact: Digital detectors reduce chemical waste (vs. film-based systems), support greener operations, and align with ESG mandates. Future Outlook: AI, Photon Counting, and Space Applications Looking forward, the X-ray detector market is being reshaped by: Photon-Counting Detectors: Emerging as a disruptive force with unparalleled resolution and low-dose imaging for precision diagnostics. AI & Predictive Imaging: Integration with artificial intelligence enhances image interpretation, triage, and workflow automation—enabling faster, more accurate decisions. Space & Deep Tech Applications: X-ray systems are being explored for use in satellite inspections, asteroid mining, and extraterrestrial exploration, unlocking new industrial frontiers. Key Takeaways for Decision-Makers Strategic Priority Value Proposition Modernize Imaging Infrastructure Enhance speed, accuracy, and ROI Align with National Security Demands Adopt advanced X-ray tech for defense & border safety Leverage ESG & Sustainability Transition to greener, digital imaging systems Capitalize on Global Expansion Target high-growth regions and partner with OEMs Invest in R&D and Innovation Future-proof your portfolio through emerging tech Ready to Lead the Next Wave of Imaging Innovation? The X-ray detectors market presents an intersection of innovation, resilience, and growth. Enterprises that invest now in next-generation detector technologies will be better equipped to meet rising demand, navigate regulatory shifts, and deliver exceptional value to customers. For more information, Inquire Now!
