Alibaba reported its financial results for the quarter and six months ending September 30, 2025, revealing strong momentum in its AI and cloud businesses but significant pressure on profitability as the company enters an aggressive investment cycle.

CEO Eddie Wu said the company is doubling down on “long-term strategic value” across AI technologies, cloud infrastructure, and a unified consumption platform integrating e-commerce with daily life services. Cloud Intelligence Group remained the standout performer—revenue jumped 34% year-over-year, driven by surging enterprise demand for AI tools. AI-related products posted triple-digit growth for the ninth straight quarter.

In its consumption business, Alibaba continued scaling quick commerce, improving unit economics and pushing rapid growth in monthly active users on Taobao. CFO Toby Xu noted that Alibaba has deployed roughly RMB120 billion in capex over the past four quarters to strengthen AI and cloud infrastructure, while cautioning that profitability will fluctuate in the near term.

Quarterly Performance: Revenue Up, Profit Down

Alibaba posted quarterly revenue of RMB247.8 billion, up 5% year-over-year, or 15% on a like-for-like basis excluding divested units Sun Art and Intime.
But income from operations fell 85% to RMB5.4 billion, weighed down by a 78% drop in adjusted EBITA due to heavy investment in quick commerce, user experience enhancements, and technology development.

Net income attributable to shareholders came in at RMB21.0 billion, down 53% from the prior year as operating income contracted sharply.
Free cash flow flipped to an outflow of RMB21.8 billion, compared to a RMB13.7 billion inflow last year, reflecting major spending on cloud infrastructure and commerce expansion. Alibaba ended the quarter with RMB573.9 billion in cash and liquid investments.

Six-Month Results: Modest Revenue Growth, Margin Pressure Continues

For the six-month period, revenue rose 3% to RMB495.4 billion, or 12% on a like-for-like basis. Income from operations dropped 43% to RMB40.4 billion, with adjusted EBITA declining 44% year-over-year.

Net income held up comparatively better, slipping 7% to RMB63.0 billion, supported by mark-to-market gains on equity investments, lower impairments, and gains from the disposal of Trendyol’s local consumer services unit.

However, free cash flow again swung into negative territory, with an outflow of RMB40.7 billion, driven by elevated capex for cloud expansion and quick commerce initiatives.

Alibaba emphasized that while its AI + Cloud and consumption businesses are delivering strong growth, it expects continued volatility in profitability as it reinvests heavily in future-focused infrastructure and next-generation services.

The World Legends Padel Tour (WLPT) is dialing up its digital game. The fast-growing international padel circuit, known for its roster of former global football icons, has partnered with Miami-based Streann Media to deliver a fully modernized streaming and content experience for the 2025 Miami Finals.

The season-ending event, set for November 29–30 at the Ultra Padel Club, anchors a global tour that spans London, Paris, Rome, Madrid, Amsterdam, Istanbul, and New York. Miami now serves as the finale—and the most digitally connected moment in WLPT’s calendar.

And with the lineup the WLPT brings, attention won’t be hard to find. Fans can expect appearances from legends such as Francesco Totti, Christian Vieri, Fernando Llorente, Vincent Candela, Luca Toni, Andriy Shevchenko, Diego Perotti, Germán Denis, Tommaso Locatelli, and Marco Materazzi. The tour continues to merge elite athletic culture with global football heritage, giving padel an entertainment boost few emerging sports can claim.

AI, Streaming, and Real-Time Production Take Center Stage

Under the new partnership, Streann Media will manage every digital touchpoint of the Miami Finals. This includes multi-camera production for matches and the awards gala, live venue feeds, and a full-scale social media content operation. The event will stream on a newly launched WLPT channel hosted on StreannStudio.ai, Streann’s AI-powered video platform aimed at creators, brands, and sports communities.

The platform functions as a complete digital hub. It blends live studio controls, on-demand hosting, highlight clipping, and channel programming—giving WLPT a central place to distribute everything from top-tier match coverage to behind-the-scenes footage. Fans worldwide will be able to watch live broadcasts, replays, interviews, and AI-generated short clips designed for discovery across social platforms.

Social coverage itself will lean heavily on automation. Streann’s SocialCap.ai tool will be used to generate captions, post copy, and short-form edits in real time. WLPT expects to deliver continuous updates across its channels throughout the Finals weekend, optimizing visibility and engagement.

Why This Partnership Matters for Sports Tech

Padel’s global footprint has been accelerating faster than many traditional sports, and leagues are racing to modernize how they reach fans. WLPT’s move signals a broader trend: mid-sized sports properties embracing AI-driven media infrastructures to compete with major leagues.

By centralizing video workflows and layering in AI-assisted content creation, WLPT is positioning itself as one of the most digitally progressive global sports circuits. For Streann Media, the partnership becomes a showcase of its rapidly expanding AI capabilities at the intersection of sports and entertainment.

Alessandro Moggi, President of the World Legends Padel Tour, emphasized the importance of digital transformation. He noted that Streann’s platforms will allow WLPT to deliver a more elevated, cohesive experience across all channels. Streann CEO Giovanni “Gio” Punzo framed the collaboration as part of a larger convergence of sports, technology, and global entertainment—one that makes AI-driven workflows essential to fan engagement.

A More Connected Finals—and a Template for the Future

The 2025 Miami Finals will be the most digitally integrated stop in WLPT’s history. With AI-assisted editing, centralized streaming, and a production system built for real-time distribution, the event aims to reach fans faster and more effectively—across continents and platforms.

If successful, this model could serve as the tour’s blueprint for future stops and potentially influence how other rising sports circuits approach media modernization.

WLPT isn’t just playing padel. It’s playing the digital game—and with Streann Media in the mix, it plans to win that one too.

Datatonic has appointed Stephen Charko as Head of Sales, Americas, marking a pivotal move as enterprise adoption of AI accelerates. The ten-time Google Cloud Partner of the Year is deepening its North American footprint, and Charko is now tasked with scaling the firm’s AI, data, and analytics business across major verticals including telecom, media, retail, agencies, and financial services.

Based in Toronto, Charko joins Datatonic with a track record of building and commercializing high-impact analytics programs. At KPMG Canada, he more than doubled the Deal Advisory Analytics practice, posting 50%+ year-over-year growth. His earlier leadership roles at Gartner and Telemetry further solidify his experience in driving measurable business outcomes for enterprise clients.

“As we enter a new chapter of growth in the Americas, Stephen’s leadership will be key to uniting our sales vision across the AI continuum and doubling down on delivering measurable business value,” said Cyril Marques, Managing Director, Americas.

A Timely Hire as AI Maturity Reaches an Inflection Point

Charko’s appointment arrives as enterprises move from AI experimentation to full-scale deployment — and struggle to prove tangible ROI. Gartner forecasts that 30% of generative AI projects will be abandoned by end of 2025, often due to unclear business value and the lack of a scalable operational framework.

“Datatonic held the definitive position,” Charko said. “They don’t just build solutions; they engineer business advantage. With Google Cloud’s ecosystem, Datatonic helps clients move from AI experimentation to enterprise-wide profitability.”

Delivering AI That Moves the Needle

Datatonic has quickly become a go-to partner for companies with complex, high-volume data environments. The firm is already powering AI initiatives across media, financial services, retail, and entertainment, working with customers such as United Football League, Wizards of the Coast, and streaming leader Cineverse.

Under Charko, Datatonic will focus on scaling production-ready AI solutions that deliver measurable impact, such as:

• Cloud Modernization: Its Gemini-powered Migration Accelerator has reduced dashboard load times by 80% and cut time-to-data by 75% for enterprise clients.

• Operational Efficiency: AI-driven invoice processing has reduced per-invoice processing costs by up to 70%.

• Data Transformation: Standardizing and enriching fragmented data pipelines to fuel analytics and AI workloads.

• Media Search Optimization: Improving discovery speeds by 90% and reducing churn by 15% for streaming platforms.

• Real-Time Fraud Detection: Deploying models that operate at >90% accuracy with <6% false positives, protecting an estimated $100M in annual transactions.

Expanding Datatonic’s Americas Footprint

Datatonic’s rapid growth is powered by its award-winning engineering teams and deep alignment with Google Cloud. The company is known for delivering enterprise-grade AI systems that don’t stop at prototypes — they go live, scale, and deliver results.

Charko’s appointment signals a clear strategy: accelerate commercial growth, strengthen enterprise partnerships, and position Datatonic as the partner of choice for organizations seeking AI with real ROI.

Clarivate has rolled out a new weapon for IP and R&D teams: Derwent Patent Monitor, an AI-driven platform designed to cut through the tangle of patent reviews. In an industry where speed determines competitive advantage, the new tool aims to streamline how organizations assess patentability, evaluate Freedom to Operate (FTO), and navigate opposition or assertion threats.

The launch comes at a time when innovation cycles grow shorter and patent portfolios expand in every direction. Teams often find themselves slowed by fractured workflows, siloed communication, and basic tools not built for the complexity of modern IP strategy. Clarivate is positioning Derwent Patent Monitor as a direct answer to that problem.

Shandon Quinn, Vice President of Patent Intelligence at Clarivate, captures the state of play well: patent teams want deeper alignment with R&D, but legacy systems undermine that partnership. Derwent Patent Monitor attempts to solve the disconnect by combining structured collaboration tools, proprietary data, and machine intelligence to flag high-risk patents quickly and with greater accuracy.

At the center of the platform is AI-powered threat analysis, which performs first-pass reviews to highlight the most critical risks tied to a patent or competitor filing. Instead of digging through dense legal documents or waiting on back-and-forth email threads, IP professionals can surface red flags instantly and pivot faster on FTO or filing decisions. For companies navigating crowded markets or aggressive competitors, that acceleration can be a strategic edge.

Derwent Patent Monitor leans heavily on Clarivate’s most valuable asset: the Derwent World Patents Index (DWPI). The database includes more than 67 million invention summaries, manually curated by over 850 subject-matter experts. This is not generic scraped data—DWPI’s structured, normalized summaries provide clearer views into claims and technical innovations, giving users higher-quality signals for decision-making.

The tool also emphasizes collaboration, a longstanding friction point in IP management. Instead of jumping between disjointed emails, spreadsheets, and outdated repositories, teams can work within a project-based review system that supports real-time feedback. This structure keeps R&D, legal, and IP aligned as they assess high-value patents or identify infringement risks. For companies with distributed teams or fast-moving product cycles, this unified workflow could be the difference between a missed deadline and a defensible position.

Derwent Patent Monitor enters a competitive market of AI-enhanced IP solutions, but few platforms offer the combination of proprietary data depth and workflow design aimed at eliminating fragmentation. As global patent filings rise and enforcement actions intensify, tools that reduce review bottlenecks will become less optional and more foundational.

Clarivate’s latest launch signals that IP professionals are shifting from manual, document-heavy processes toward intelligence-first systems. And with industry leaders seeking stronger cross-functional cooperation, Derwent Patent Monitor may arrive at precisely the right moment.

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Blizzard Skis is stepping into new territory with the Canvas Collection, a freeski lineup that treats the mountain as a creative medium rather than a playground built only for performance. The first release, the Canvas 108, drops on December 15 and marks a distinct shift for the long-standing brand. Instead of relying solely on engineering, Blizzard blended art, athlete input, and iterative design in a way that feels fresh for the category.

The company spent two years and cycled through more than 160 prototypes to bring Canvas to life. That level of testing signals a clear goal: build skis that reflect how modern freeride athletes move, express themselves, and shape their lines. The result is a collection that leans into individuality without sacrificing technical control.

Art Meets Engineering

Creativity sits at the center of the Canvas identity. The topsheet artwork, crafted by Japanese-Australian printmaker Penelope Misa, sets the tone. Her monotype style uses one-of-one prints that mirror the idea of a skier carving a unique line into untouched snow. Both forms require a single, irreversible gesture—no two turns or prints look the same.

Misa sees skiing and monotypes as parallel processes. Both rely on instinct. Both reflect personal expression. And both celebrate what happens when movement becomes art. That perspective shapes the visual identity of the Canvas Collection and adds cultural depth to a product usually driven solely by specs.

Developed by Skiers Who Live in the Mountains

Blizzard also let its athletes lead. Instead of creating a signature ski for one rider, the brand built a collaborative model shaped by its entire freeride roster. Skiers including Connery Lundin, Piper Kunst, Kaz Sosnkowski, and Zeb Schreiber pushed prototypes across continents, then shared direct feedback that influenced everything from flex patterns to pop profiles.

Their input gave the skis a distinct feel. The Canvas 108 balances looseness with accuracy. It can charge on demand, yet it still feels playful when a skier wants to pivot, smear, or float. Lundin explains the shift well. According to him, Blizzard allowed the team to build something different, and that freedom led them toward a design that finally feels like true self-expression.

This approach signals a broader industry trend. As brands compete for younger skiers who value style as much as stability, athlete-driven product design becomes more important. Blizzard’s decision to hand the steering wheel to its team aligns with that shift. It also positions Canvas as a next-gen product line rather than a traditional update.

Built for a New Type of Freeskiing

The first model, the Canvas 108, targets skiers who prefer to draw their own lines instead of following established tracks. It delivers a responsive feel underfoot and a lively, energetic ride. Blizzard built it for skiers who want to mix creativity with capability.

Rick Sorenson, Blizzard’s Content Marketing and Team Manager, says the collection required full creative freedom. The team experimented relentlessly, embraced failure, and rebuilt until the skis matched the vision. He frames the final product as the result of genuine collaboration between artists, athletes, and engineers.

That perspective will likely resonate with a younger demographic. Many skiers want gear that feels personal, expressive, and less locked into the traditional freeride formulas. Canvas aims directly at that crowd.

Expanding the Lineup Through 2026

The Canvas 108 is only the beginning. Two additional models—Canvas 100 and Canvas 118—arrive in North America in fall 2026.

The Canvas 100 targets skiers who want agility across the mountain. It excels when riders want to butter, float, or improvise their way down varied terrain. The Canvas 118 pushes in a different direction. It’s built for deep-snow skiers who want power and freedom without compromise.

All three skis share a common construction philosophy. Each model uses a blend of poplar and paulownia wood cores, a powder rocker, and a thin titanal strip that runs tip to tail. That mix delivers float, energy, and predictable responsiveness. Blizzard wanted the skis to feel intuitive yet expressive, and the materials support that intention.

From shape to story, the Canvas Collection arrives as more than a ski launch. It is Blizzard’s attempt to redefine how freeski gear can merge art, athlete insight, and engineering. And as the industry pushes toward products built for identity as much as performance, Canvas could signal where the next generation of ski design is headed.

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AI is reshaping how developers learn, grow, and navigate their careers, and the latest Agoda AI Developer Report 2025 makes that shift impossible to ignore. The findings show a regional workforce leveling up at unprecedented speed, often without institutional support. Developers are teaching themselves AI faster than many companies can roll out structured training, accelerating innovation while widening gaps in access and preparedness.

The report, based on responses from developers across Southeast Asia and India, captures a clear trend: AI is now the center of career strategy. Eighty-seven percent of developers have changed their learning priorities because of AI, and 62% believe it will create more opportunities than it replaces. Yet most of this growth is happening independently. Seventy-two percent are self-taught, while only 28% receive employer-backed training.

This divide reflects a broader issue. Organizations are struggling to keep pace with the fast-moving expectations of AI-driven work. As companies ramp up internal education, many developers have already built their own pathways—leaning heavily on open-source communities, online platforms, and peer-driven experimentation.

Peer Learning Is Winning Where Formal Training Lags

With traditional programs unable to scale quickly, developers are turning to decentralized learning. More than 52% now rely on online communities or open-source projects as their primary AI education hubs. This shift fuels a culture built on rapid experimentation, shared code, and distributed problem-solving.

However, momentum varies across the region. Access to formal training differs significantly by geography. Developers in Singapore are almost twice as likely to receive structured AI education compared to those in Vietnam. Senior engineers also report far higher confidence than juniors, revealing a 25-point experience gap that mentorship and structured training could address.

These disparities hint at a future where AI skills become a differentiator not only between companies but across entire economies.

AI Skills Are Becoming a Baseline Requirement

The speed of AI adoption also brings new pressures. Forty-four percent of developers worry they may fall behind, given how quickly tools evolve. Meanwhile, 58% believe AI proficiency has already become a standard hiring requirement.

As a result, the regional developer ecosystem is more ambitious, adaptable, and self-sufficient—but also under strain. Developers are moving fast, but without consistent guidance, the path becomes uneven.

Idan Zalzberg, Chief Technology Officer at Agoda, explains the dynamic clearly. Developers see AI as an accelerator, not a replacement. Yet they are upskilling faster than many organizations can react. Zalzberg emphasizes the need for companies to establish systems of trust and accountability if they want to harness this momentum effectively.

Agoda's Playbook: Build Trust, Enable Experimentation

Agoda is investing heavily in those systems. The company has created an internal ecosystem designed to support ongoing AI education and experimentation.

Its initiatives include:

• Internal AI hackathons that encourage hands-on exploration

• Regular tech talks and knowledge-sharing sessions to expand peer learning

• Tech Camp Day, a social impact program that has provided thousands of Thai students with essential tech skills

These efforts help strengthen both Agoda’s engineering teams and the broader tech communities where the company operates. The focus is on long-term capability building, not short-term skill spikes.

A Regional Snapshot of AI Adoption

The AI Developer Report 2025 also includes insight from leading regional companies such as Carousell, MoMo, Omise, and SCB 10x. Together, their input reveals a rapidly evolving ecosystem shaped by grassroots learning as much as enterprise adoption.

Developers across Southeast Asia and India are integrating AI into their work faster than ever. While this speed fuels innovation, it also exposes gaps between those with access to structured training and those without. If companies want to build resilient, future-ready tech teams, they will need to close those gaps.

For now, the message is clear: developers aren’t waiting for permission. They’re already building the AI future themselves.

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Pony.ai is pushing its Robotaxi ambitions into higher gear. The autonomous mobility company has expanded its partnership with Sunlight Mobility to adopt a fully asset-light model—an approach designed to scale faster, deploy more efficiently, and cut the capital demands that usually weigh down autonomous fleet operators.

The move builds on a collaboration first formed in mid-2024. With the new agreement, Sunlight Mobility will fund Pony.ai’s Gen-7 Robotaxi vehicles, with the first batch set to roll out in Guangzhou by the end of 2025. This marks a notable shift: instead of owning every car in its fleet, Pony.ai is leaning into a model where third parties finance the vehicles and lease Pony.ai’s Virtual Driver technology for commercial operations.

It’s a bet on scalability. And the market seems ready for it. More external partners are showing interest in funding autonomous fleets, a sign that confidence in the Robotaxi business model is rising—particularly in China’s highly competitive mobility sector.

Sunlight Mobility’s Scale Powering Pony.ai’s Strategy

Sunlight Mobility operates one of China’s largest digital mobility platforms, spanning more than 180 cities. It brings user demand, operational expertise, and dispatch intelligence—key ingredients that autonomous fleet operators often struggle to build quickly.

By integrating their platforms, Pony.ai and Sunlight Mobility will jointly manage autonomous vehicle supply and share economic upside. The result aims to be a more efficient, more responsive Robotaxi network that benefits both companies and, ideally, the passengers they serve.

This collaboration also strengthens Pony.ai’s long-term roadmap. A capital-light approach could help the company deploy fleets at a pace that would be difficult with traditional ownership models, especially as the autonomous mobility landscape matures into a race defined by speed, funding leverage, and regulatory readiness.

The broader implications reach beyond Pony.ai itself. As more mobility players adopt asset-light models, the economics of Robotaxi deployment could shift dramatically—lowering barriers for scale and making the technology more commercially viable in more cities.

For now, Pony.ai and Sunlight Mobility are setting their sights on expansion across China after the initial Guangzhou launch. If the partnership delivers on its promise, this could signal a new phase in the rollout of autonomous transportation: faster, leaner, and increasingly decentralized.

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R Systems has vaulted into the top tier of UiPath’s global partner ecosystem, securing Diamond Partner status and recognition as a UiPath Agentic Automation Fast Track Partner. The dual milestone positions the company among an elite group leading the charge in AI-powered enterprise automation.

The announcement reflects two parallel trends shaping the automation market: the rise of agentic AI and the growing value of partners who can operationalize it. While many enterprises are still experimenting with task-level automation, UiPath and its top partners are pushing into a world where AI agents, robots, models, and human expertise work together to automate entire business processes end-to-end.

Agentic Automation: Early Access, Early Advantage

The Fast Track designation is limited to UiPath partners trained directly in agentic automation capabilities—an emerging class of automation powered by autonomous AI agents that can sense, decide, and act across workflows. R Systems earned early access, identified customer-ready use cases, and contributed feedback to UiPath’s ongoing development efforts.

This places the company ahead of the pack in a space where enterprises are still figuring out how to apply agentic AI responsibly and at scale. The recognition underscores R Systems’ ability to design automation scenarios that combine robots, people, and AI models to deliver more adaptive workflows.

UiPath’s Regional Vice President for South Asia, Joey Chong, describes R Systems as instrumental to shaping the “agentic future” of the platform, highlighting its hands-on product work and commitment to co-innovation.

Diamond Partner Status Signals Deep Automation Strength

UiPath’s Diamond tier is its highest partner classification, signaling excellence in sales performance, solution delivery, and technical expertise. R Systems’ elevation to this level confirms its maturity in implementing UiPath’s automation stack—from discovery and orchestration to complex enterprise-scale deployments.

Its work with customers such as Shelf Drilling reinforces that reputation. The company has supported the oil and gas contractor’s automation roadmap since 2021, offering domain alignment, delivery precision, and forward-looking technology guidance. According to Shelf Drilling’s ERP Senior Manager, Adnan Sharafat, agentic AI is now opening even more opportunities for expansion.

Automation With Purpose—and ROI

R Systems is framing these recognitions as validation of its broader mission: using Agentic AI to enhance human productivity rather than replace it. The company continues to expand its capabilities through organic growth and strategic acquisitions, all aimed at building automation frameworks with measurable business impact.

Its approach reflects a larger industry shift. Enterprises are no longer satisfied with efficiency gains alone—they want automation that improves decision-making, elevates experiences, and delivers durable ROI. With UiPath putting more weight behind agentic intelligence, the partners who master it early are likely to shape how enterprises transition into the next era of work.

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