Core Insights - VivoPower International PLC has executed an exclusive heads of agreement to acquire a 40MW+ data center in Norway powered by 100% renewable hydroelectric energy [1] - The facility will serve as a strategic foundation for VivoPower's Power-to-X strategy under Caret Digital, with plans to transition it into a Sovereign AI Hub [1] - The transaction is expected to close in January 2026, pending shareholder approval [1] Acquisition Details - The data center has an operational capacity of over 40MW, with an additional 40MW earmarked for potential approval in 2026 [1] - The facility benefits from low-cost hydropower access at below $0.035/kWh and a 50-year land lease [1] - The transition aims to support Large Language Model training and inference for clients seeking carbon-neutral compute [1] Financial Aspects - Convertible preference shares will have a conversion price of $6.80 and a PIK coupon of 6% per annum, contingent on shareholder approval [1] - The transaction is set to close in January 2026, aligning with VivoPower's strategic goals [1] Company Overview - VivoPower, founded in 2014 and listed on Nasdaq since 2016, operates in multiple regions including the UK, Australia, North America, Europe, the Middle East, and Southeast Asia [1] - The company has three business units: Tembo, Caret Digital, and Vivo Federation, focusing on electric solutions, power-to-x applications, and digital asset management respectively [1] - VivoPower is positioning itself to leverage its differentiated platform in power, mobility, compute, and digital infrastructure for Sovereign AI computing [1]

Group 1 - Zhipu AI, a Chinese artificial intelligence firm, initiated a share sale to raise HK$4.35 billion (US$560 million), aiming to become the first large language model (LLM) developer listed in Hong Kong [1][2] - The company set its offer price at HK$116.20 for over 37 million shares, with 10% allocated to retail investors, and plans to debut on January 8 [2] - Zhipu expects net proceeds of HK$4.17 billion from its IPO, with a post-listing market valuation estimated at HK$51.16 billion [3] Group 2 - The IPO activity in December has seen a surge of Chinese tech firms, including those in AI and semiconductors, accelerating their listings in Hong Kong [6] - Zhipu's retail bookbuilding could attract over 400,000 retail investors due to strong investment sentiment for tech shares, although first-day performance may differ from recent high-profile debuts [5] - Shanghai Biren Technology, another tech firm, attracted HK$459.68 billion in margin financing for its retail tranche, indicating strong demand in the market [7]

Core Insights - TCW Concentrated Large Cap Growth Fund reported a return of +4.11% in Q3 2025, underperforming the Russell 1000 Growth Index which returned +10.51% [1] Company Overview - Gartner, Inc. (NYSE:IT) is a research and advisory company established in 1979, operating through research, conferences, and consulting segments [2] - As of December 24, 2025, Gartner's stock closed at $251.18 per share, with a market capitalization of $19.023 billion [2] Financial Performance - Gartner reported revenue of $1.5 billion in Q3 2025, reflecting a year-over-year increase of 3% as reported and 1% on a foreign exchange neutral basis [4] Investment Analysis - Gartner's shares dropped following disappointing quarterly results, despite exceeding consensus estimates; growth excluding U.S. Federal business decelerated, and management lowered forward guidance [3] - Forward guidance now anticipates Contract Value (CV) growth to decelerate from mid-single-digit to low single-digit growth [3] - Approximately 35% to 40% of Gartner's research contract value is in tariff-impacted industries, which are implementing cost-cutting measures and experiencing delayed sales cycles [3] - The rise of AI is disrupting many end markets, impacting Gartner's Business Model Advantage (BMA) and potentially shrinking its Total Addressable Market (TAM) [3] - Due to these factors, the fund decided to completely exit its position in Gartner [3] Hedge Fund Interest - Gartner, Inc. was held by 42 hedge fund portfolios at the end of Q3 2025, a decrease from 45 in the previous quarter [4] - The company is not listed among the 30 Most Popular Stocks Among Hedge Funds [4]

Core Weave - CoreWeave is a next-generation neocloud company specializing in large language model (LLM) training and AI inference, with a close relationship with Nvidia for access to high-end GPUs [3] - The company is aggressively increasing capital expenditures, planning to more than double them next year, to meet soaring demand for AI services [4] - CoreWeave has reportedly turned away business worth an estimated $40 billion to $50 billion from Microsoft due to high demand [4] - Citigroup indicates that CoreWeave's capacity is sold out for 2026, with discussions already underway for early 2027 bookings, suggesting potential hypergrowth [5] - Despite a strong performance post-IPO, CoreWeave's stock is still over 50% below its all-time high, indicating room for growth [5] Applied Digital - Applied Digital builds and manages specialized data centers designed for AI, focusing on handling intense heat and power requirements [6] - The company designs cooling systems and provides power, addressing a significant bottleneck in AI infrastructure development [7] - Applied Digital has transitioned from Bitcoin mining to providing data center expertise, attracting companies that need power access but lack building capabilities [7] - Both Applied Digital and CoreWeave experienced strong performances in 2025, with Applied Digital supporting neocloud providers through specialized infrastructure [8]

Core Insights - Andrej Karpathy, co-founder of OpenAI, predicts that 2025 will be a pivotal year for large language models (LLMs), highlighting six key paradigm shifts that will reshape the industry and reveal LLMs evolving into a new form of intelligence [1][3] Group 1: Paradigm Shifts - Shift One: Reinforcement Learning with Verified Rewards (RLVR) is set to transform the training paradigm for LLMs, moving from traditional pre-training to a new phase that emphasizes longer-term reinforcement learning [4][5] - Shift Two: The concept of "ghost intelligence" will lead to a better understanding of LLMs' unique performance characteristics, which exhibit a "zigzag" nature, being both highly knowledgeable and occasionally confused [7] - Shift Three: The rise of Cursor signifies a new application layer for LLMs, focusing on vertical applications that encapsulate and orchestrate LLM calls for specific industries [8] - Shift Four: Claude Code introduces a new paradigm for local AI agents, emphasizing the importance of running AI in private environments on user devices rather than solely in cloud settings [9] - Shift Five: The emergence of "Vibe Coding" will democratize programming, allowing individuals to create complex programs using natural language, thus lowering the barriers to entry for software development [10][11] - Shift Six: Google’s Gemini Nano Banana is recognized as a groundbreaking model that could signify a major shift in computing paradigms, moving from text-based interactions to more human-preferred formats like images and multimedia [12] Group 2: Industry Implications - The integration of RLVR into LLM training processes will lead to significant improvements in model capabilities, with most advancements expected to stem from the optimization of computational resources previously allocated for pre-training [5] - The "zigzag" performance of LLMs raises concerns about the reliability of benchmark tests, as these models may perform exceptionally well in certain contexts while struggling in others [7] - The development of specialized LLM applications like Cursor will create a competitive landscape where general-purpose LLMs and vertical applications coexist, potentially reshaping industry standards [8] - Local AI agents, as demonstrated by Claude Code, will prioritize user privacy and personalized experiences, marking a shift in how AI interacts with users [9] - The trend towards Vibe Coding will not only empower non-programmers but also enable professional developers to innovate more rapidly, fundamentally altering the software ecosystem [10][11] - The transition to multimodal interfaces, as exemplified by Nano Banana, will redefine user interactions with AI, moving towards immersive experiences that integrate various forms of media [12]

The Stock Exchange of Hong Kong Limited and the Securities and Futures Commission take no responsibility for the contents of this Post Hearing Information Pack, make no representation as to its accuracy or completeness and expressly disclaim any liability whatsoever for any loss howsoever arising from or in reliance upon the whole or any part of the contents of this Post Hearing Information Pack. This Post Hearing Information Pack is in draft form. The information contained in it is incomplete and is subjec ...

Core Insights - Cerence Inc. is set to showcase its innovations at CES 2026, focusing on advancements in its conversational AI platform, Cerence xUI™ [2][9] - The company aims to address challenges faced by automakers, such as consumer expectations for AI experiences and the need for software updates post-purchase [3][4] Group 1: Cerence xUI Platform - Cerence xUI is designed to be hybrid, modular, and technology-agnostic, allowing OEMs to integrate various AI models and data sources [4] - The platform supports continuous innovation by enabling fast deployment of new features and LLM capabilities to existing vehicles [4][5] - End users benefit from a more engaging experience with proactive, context-aware in-car assistants [5] Group 2: Multimodal Edge AI - Cerence's collaboration with SiMa.ai will be highlighted, showcasing the CaLLM™ Edge model running on efficient MLSoC hardware, enhancing performance and reducing latency [6] - This partnership aims to deliver fast, low-power interactions without relying on cloud connectivity, improving communication between the vehicle and driver [6] Group 3: New AI Agents - Cerence will introduce two new agents at CES: an ownership companion agent for vehicle maintenance and a dealer assist agent for dealership automation [8] - The mobile work agent, developed with Microsoft, will provide voice-first access to Microsoft 365 applications, enhancing productivity for drivers [9] Group 4: Audio AI Innovations - The company will showcase its Audio AI portfolio, which includes advanced capabilities for speech enhancement and noise reduction, ensuring clear audio performance in vehicles [11] Group 5: Partner Ecosystem - Cerence's presence at CES reflects its strong partner ecosystem, which includes collaborations with companies like TCL and MediaTek, emphasizing the modularity and innovation of its platform [12]

Core Insights - VEON Ltd. announces the development of Ukraine's national large language model (LLM) in collaboration with Kyivstar and the WINWIN AI Center of Excellence, utilizing Google Gemma as the foundational model [1][2][3] Group 1: Project Overview - The Ukrainian LLM aims to encompass various Ukrainian dialects, terminology, and historical context while ensuring sensitive national data is securely processed within Ukraine [2] - Google was chosen for this initiative to strengthen technological ties between Ukraine and the United States, particularly following Kyivstar's Nasdaq listing in August 2025 [3] - The project is expected to enhance digital services across public and private sectors in Ukraine, with applications in areas such as education, finance, and healthcare [5] Group 2: Technical Development - Kyivstar will lead the operational development of the LLM, focusing on training the model with unique Ukrainian data to minimize linguistic and ethical risks [4] - The initiative will first optimize Google Gemma for the Ukrainian language, refining its tokenizer and training it on curated datasets [6] - Dedicated benchmarks will guide the model's fine-tuning and adaptation for specific applications [6] Group 3: Strategic Importance - This initiative is part of VEON's broader strategy to address the AI language gap in its markets, following similar projects in Kazakhstan and Pakistan [7] - The investment in the Ukrainian LLM is part of a larger commitment by Kyivstar and VEON to invest USD 1 billion in Ukraine from 2023 to 2027, focusing on infrastructure and technological development [8]

KYIV, Ukraine, Dec. 01, 2025 (GLOBE NEWSWIRE) -- Kyivstar (Nasdaq: KYIV; KYIVW), Ukraine’s leading digital operator, and the WINWIN AI Center of Excellence under the Ministry of Digital Transformation of Ukraine have selected Google’s Gemma as the base model for training the large language model (LLM). Gemma, Google’s next-generation open AI model, has been proven effective in both international and domestic projects. Kyivstar is the Ukrainian Government’s strategic partner and operational lead for developi ...

Group 1 - The era of scaling is over, and the focus has shifted to research, emphasizing the importance of model generalization over mere computational power [4][8][34] - Emotional value functions are expected to play a crucial role in future AI developments, enhancing the efficiency of reinforcement learning [10][14][18] - The generalization ability of current models is still significantly inferior to that of humans, raising fundamental questions about AI's learning capabilities [13][19][25] Group 2 - The current models exhibit a "zigzag" capability, performing well in evaluations but struggling with real-world applications, indicating a disconnect between training and practical performance [27][30] - Companies that continue to pursue a scaling strategy may generate substantial revenue but could face challenges in achieving profitability due to intense competition [34][35] - The deployment of AI on a large scale could potentially lead to rapid economic growth, although the exact pace of this growth remains uncertain [35] Group 3 - Good research taste is essential, requiring a multi-faceted approach to identify beauty and simplicity in AI development [36][38] - The ultimate goal for AI development should be to create systems that genuinely care for and perceive life, rather than merely focusing on self-evolving AI [39][43] - The timeline for achieving superintelligence is projected to be within the next 5 to 20 years, contingent on advancements in understanding reliable generalization [44][46] Group 4 - SSI's current focus is on research, with plans to gradually deploy AI while ensuring that the first products released are meaningful and impactful [50][56] - SSI differentiates itself through a unique technical approach, aiming to create AI that is aligned with human values and capable of meaningful interaction [58]