🎥 A quick hello from our Director of Enablement, Jainarine (Kevin) Kissoon ✌🏾 — welcoming you to our booth at #NVIDIAGTC! We’re gearing up for an afternoon of sharp insights and great booth demos. Come ready to swap ideas, meet the builders behind real AI outcomes, and see how data intelligence turns pipelines into results. 🤝 Planning your week? Book time with our team: bit.ly/4uc55aT See you soon at the AI Data Summit later today! 🙌 #NVIDIAGTC ...

Core Viewpoint - JOYY Inc. is set to release its fourth quarter and full year 2025 financial results on March 10, 2026, after the U.S. market closes, followed by an earnings conference call [1] Group 1: Financial Results Announcement - The financial results will be announced after the U.S. market closes on March 10, 2026 [1] - An earnings conference call is scheduled for 9:00 PM U.S. Eastern Time on the same day [1] - Participants can register online in advance to receive dial-in numbers and a unique PIN [1][2] Group 2: Company Overview - JOYY Inc. is a leading global technology company focused on enriching lives through technology [3] - The company has a diversified product portfolio that includes live streaming, short-form videos, instant messaging, and emerging initiatives like advertising and smart commerce SaaS [3] - JOYY is headquartered in Singapore and operates globally, empowering creators, merchants, and enterprises [3] - The company's American Depositary Shares (ADSs) have been listed on NASDAQ since November 2012 [3]

How are GPUs being constrained in average environments today. And really the big challenge is data and actually we sometimes call artificial intelligence data intelligence at DDN because it's really about how we turn data as a source code into applications you can run which are intelligent and provide intelligence to the to the customers. [music] And when we're building those models and when we're running those models and even when we're preparing the data [music] to build those models, these are all GPU op ...

Core Insights - ArisGlobal has launched XDI, a Data Intelligence Cortex aimed at transforming regulated life sciences data into continuous, explainable, decision-grade intelligence across the product life-cycle [1] Group 1: Product Features - XDI addresses the challenge of managing fragmented data across disparate systems, enabling organizations to generate consistent, explainable decisions [1] - The solution connects signals across domains, applies contextual learning, and delivers insights at decision-making points, allowing organizations to anticipate risks and opportunities [1] - XDI does not require data consolidation into a single platform, instead bringing intelligence to the data wherever it resides [1] Group 2: Operational Benefits - XDI's offerings include: - Regulatory operational intelligence, which can reduce compliance effort by 70-80% and quality control (QC) efforts by up to 75% through continuous checks [1] - Benefit-risk intelligence, enabling over 30% faster signal detection and up to 40% noise reduction in signal workflows, compressing cycle time from four to six weeks down to four days [1] - Pharmacovigilance operational intelligence, shifting operations from reactive to proactive, with similar reductions in compliance effort and QC [1] Group 3: Strategic Vision - The launch of XDI aligns with ArisGlobal's vision of evolving from an AI-first company to a data intelligence technology company in life sciences [1] - The focus for life sciences organizations in 2026 is on operationalizing AI at scale and leveraging cross-domain data intelligence [1] - XDI is built on the "Trust by Design" framework, integrating AI governance and ensuring regulatory defensibility across the AI lifecycle [1]

Core Insights - EXL has been granted 10 new U.S. patents in the past year, enhancing its capabilities in data and AI solutions across various industries including insurance, healthcare, retail, utilities, and financial services [1][2] - The innovations focus on making data AI-ready, automating workflows, and improving customer engagement, thereby strengthening EXL's position as a leader in the data and AI sector [1][2] Patent Innovations - EXLdata.ai, launched in October 2025, is an agentic AI-native suite designed to unify complex data ecosystems and accelerate enterprise-wide adoption [2] - EXLerate.ai integrates EXL and third-party AI agents into business operations, with patented solutions for multimodal data ingestion, knowledge graph creation, and unstructured data extraction [3][4] - Key patents include: - U.S. Patent No. 12,260,342 for multimodal table extraction and semantic search [3] - U.S. Patent No. 12,481,215 for advanced knowledge retrieval techniques [3] - U.S. Patent No. 12,253,832 for context-based entity recognition [3] - U.S. Patent No. 12,468,696 for enhancing regulatory reporting accuracy and transparency [4] AI and Data Solutions - EXL Transaction Insights™ utilizes AI to assess personal financial risk by mining deep consumer financial insights [3] - EXL Cognitive Image Analytics™ reduces network traffic for event predictions based on cognitive image analysis [4] - The EXL Insurance LLM™ is the first industry-specific large language model aimed at improving claim adjudication outcomes, achieving 20-30% higher accuracy in claims and underwriting tasks compared to general-purpose models [4][5] Company Overview - EXL is a global data and AI company founded in 1999, headquartered in New York, with approximately 63,000 employees across six continents [6] - The company focuses on transforming business models and driving better outcomes through data and AI solutions in various sectors including insurance, healthcare, and financial services [6]

Core Insights - The transition from the IT era to the DI (Data Intelligence) era is marked by the need for data centers to evolve from mere storage facilities to AI-driven factories, emphasizing the importance of data being "computed" rather than just stored [1] - XSKY has launched its comprehensive AI data solution, AIMesh, which highlights the significance of proprietary data as a unique competitive advantage in the AI era, advocating for a "data evergreen" strategy to protect this core asset [1] Group 1: AIMesh Strategy - XSKY aims to build a stable data foundation to counteract the rapid depreciation of computing power and technological uncertainties, committing to absolute neutrality and hardware-software decoupling [2] - AIMesh provides unified and standardized data services regardless of the GPU or model algorithm used, granting enterprises maximum freedom in future computing power battles [2] Group 2: Technical Innovations - AIMesh addresses three major barriers to AI efficiency: the IO wall, gravity wall, and memory wall, through innovative architecture [3] - The MeshFS technology overcomes the IO wall by enhancing data supply speed, achieving a sequential write bandwidth that exceeds competitors by 50% [3] - MeshSpace tackles the gravity wall by expanding storage capabilities to "single bucket EB" level, allowing seamless data flow in hybrid cloud environments [3] - MeshFusion addresses the memory wall by utilizing local NVMe SSDs to create L3-level persistent memory, achieving near-infinite context windows at a cost of only 1% [3] Group 3: Industry Collaboration - The launch of AIMesh is supported by industry giants like Intel, which recognizes its alignment with current industry pain points and is collaborating on advanced research [4] - Companies like Minimax are validating the stability of XSKY's architecture in practical applications, particularly appreciating MeshSpace's ability to resolve hybrid cloud data silos [4] - XSKY is positioning itself to help enterprises build a "data evergreen" AI infrastructure, ensuring their competitiveness in the intelligent era [4]

Core Insights - MySize, Inc. is evaluating new opportunities to monetize its portfolio of aggregated and anonymized data intelligence assets in a responsible manner [1] Data Intelligence Insights - MySize's platforms have generated large-scale, privacy-compliant insights related to apparel fit trends, sizing mismatches, and product-level performance across brands and retailers, derived exclusively from anonymized and aggregated data [2] - The company is developing a secure Data Intelligence Framework to provide brands, manufacturers, and industry partners with access to insights that support demand planning, inventory optimization, customer trends, product design, and sustainability initiatives [3] Business Model Exploration - MySize is assessing usage-based digital access models, such as data credits, allowing enterprise customers to consume insights in a controlled, transparent, and scalable manner, built with a privacy-first approach and in compliance with data protection regulations like GDPR and CCPA [4] - The initiative remains in an exploratory phase, with no assurance regarding the timing, scope, or potential financial impact of future commercialization [5]

Core Insights - Databricks has successfully raised over $4 billion in a Series L funding round, achieving a valuation of $134 billion, which is a 34% increase from its previous valuation of $100 billion just three months ago [1] - The company is focusing on developing products that cater to the AI revolution, including a database for AI agents, an AI agent platform, and applications for building and deploying data and AI solutions [2] Funding and Valuation - This funding round marks Databricks' third major venture fundraising effort within a year, reflecting strong investor confidence in the company's ability to leverage data for AI applications [4] - The company was valued at $60 billion around the same time last year, indicating significant growth in investor belief regarding its potential [4] Revenue Growth - Databricks reported a run-rate revenue exceeding $4.8 billion, which represents a 55% increase from the previous year, with over $1 billion of that revenue coming from AI products [4] Product Development - The company is heavily investing in its AI agent database, Lakebase, which is based on the open-source Postgres database, and aims to support corporate developers in their projects [3] - Databricks' AI agent platform, Agent Bricks, is designed to assist businesses in building and deploying AI agents that utilize their data [3] Strategic Partnerships - Databricks has secured significant deals worth hundreds of millions with AI labs such as Anthropic and OpenAI to integrate their models into its enterprise products [3] Job Creation and Expansion - The new funding will be utilized to create thousands of new jobs across Asia, Europe, and Latin America, as well as to recruit more AI researchers [6] Investor Participation - The funding round was led by notable firms including Insight Partners, Fidelity, and J.P. Morgan Asset Management, with participation from several other prominent investors [7]

AI token factories collapse without data intelligence. DDN can help. Here's the business problem.Most AI token factories fail not because of GPUs, but because data becomes a bottleneck. Token cost skyrocket. Power goes through the roof.Time to revenue stalls. And here's the NCP reality for cloud. Profitability isn't about selling GPU hours.It's about lowering token cost. DDN does that across training, inference, and rack at the system level, helping NCPs attract more customers. GPUs create power.DDN turns t ...

How are GPUs being constrained in average environments today. And really the big challenge is data and actually we sometimes call artificial intelligence data intelligence at DDN because it's really about how we turn data as a source code into applications you can run which are intelligent and provide intelligence to the to the customers. And when we're building those models and when we're running those models and even when we're preparing the data to build those models, these are all GPU operations that ar ...