RT Custom Content from WSJ (@WSJCustom)Paid Program with @Google: As AI transforms the nature of work, companies must cultivate a workforce that is flexible, and open to change. Google’s Fabien Curto Millet explains.https://t.co/5puTuPnZFq https://t.co/34BFe1OCCD ...

I'm about to take Google Maps's new Gemini feature for a test drive so I can get hands-free navigation assistance and information on my route and destination. Let's check it out. This is all things mobile.So, this latest Gemini integration with Google Maps is essentially your assistant. So, say you're driving, you just thought of something you have to do or a message that you have to send. You don't have to touch your phone.You just say, "Hey, Google." And it'll do what you need to do. I took the new featur ...

Disney Picks a Side in the OpenAI-Google Rivalry https://t.co/1mwLyAuSUs ...

Core Insights - The Humanoids Summit, a leading event in the humanoid robotics sector, took place in Silicon Valley on December 11-12, 2025, attracting nearly 2,000 professionals from major tech companies and robotics developers [1][3] Group 1: Event Overview - The summit featured prominent developers such as Agility Robotics, Apptronik, Boston Dynamics, and Sanctuary, along with representatives from the "Big Seven" tech companies including Meta, Amazon, NVIDIA, and Google [1] - Apex Sensing, a wholly-owned subsidiary of Fola New Materials, was the only flexible sensor supplier at the summit, leveraging the opportunity to engage with numerous potential clients in North America [1] Group 2: Company Developments - Apex Sensing's flexible sensors provide tactile perception similar to human skin, which is crucial for achieving high precision and dexterity in robotic hands [3] - The company successfully established high-quality potential client connections and identified future strategic cooperation projects, gaining valuable market feedback during the summit [3]

Summary of Key Points from the Webinar on AI Data Center Memory Demand Industry Overview - The discussion centers around the U.S. IT Hardware industry, specifically focusing on AI data centers and their memory requirements [1][12]. - The webinar featured Gunjan Shah, a former Senior Cloud Engineer at Google, who provided insights into memory demand for AI workloads [1][12]. Core Insights Memory Demand in AI - Training AI models requires significantly more memory than inference, with medium-sized models consuming approximately 1TB of memory during training compared to much lower demands during inference [2][15]. - The rapid adoption of AI has led to a sharp increase in memory demand and prices, particularly for components like HBM (High Bandwidth Memory) and DRAM [3][21]. - Innovations in model architectures and memory technologies are expected to help manage memory demand sustainably in the long term [3][18]. Shift from HDDs to SSDs - Due to HDD shortages, many hyperscalers are transitioning to SSDs, which are 5 to 10 times more expensive but offer superior performance and lower operational costs [4][38]. - SSDs provide benefits such as reduced power consumption and minimal cooling requirements, contributing to a lower total cost of ownership (TCO) [4][40]. Emerging Memory Technologies - High Bandwidth Flash (HBF) is an emerging technology that aims to provide fast, non-volatile memory, potentially lowering energy consumption and cooling costs for AI inference workloads [5][18]. Investment Implications - Companies such as Seagate Technology (STX), Western Digital (WDC), SanDisk (SNDK), Samsung, SK Hynix, and Micron have been rated with specific price targets based on their performance in the memory market [7][8][9][10][11]. - STX is rated Outperform with a price target of $370, while WDC is rated Market-Perform with a target of $170 [8][9]. Additional Insights Memory Usage Breakdown - The memory footprint for training is heavily reliant on model weights, activations, and gradients, while inference requires only temporary tensors and KV caches [15][16]. - The demand for storage during training is significantly higher, with requirements ranging from terabytes to petabytes depending on the model size [24][25]. Market Dynamics - The demand for memory is outpacing supply, leading to increased prices for HBM, DRAM, and SSDs [21][29]. - Hyperscalers are signing multi-year purchase agreements and vertically integrating into chip design to secure memory supplies [29][36]. Comparison of AI Models - Gemini 3.0 is currently outperforming ChatGPT 5.0 in various benchmarks, attributed to its optimized training and architecture [33][34]. - The U.S. is leading in AI model development compared to China, with significant differences in performance and resource availability [35][36]. Cost Considerations - Despite the higher initial costs of SSDs, their lower operational costs and performance benefits make them more economical for performance-critical tasks over time [40][42]. - The TCO for SSDs is favorable due to lower power consumption, reduced cooling needs, and higher reliability compared to HDDs [40][42]. Conclusion - The AI data center memory landscape is evolving rapidly, driven by increasing model sizes and the need for efficient memory solutions. The shift from HDDs to SSDs and the emergence of new memory technologies are key trends to watch in this sector.

New AI-powered tools from Google, Adobe, Apple and others can improve group shots and fun selfies https://t.co/SySjyLsegi ...

We would be in a tough spot for a while if Enthropic went away because all our apps wouldn't work. That would suck. But if Chat GBD went away tomorrow, we'd be fine in a couple days.We'd lose a little memory. We'd have to rebuild it in Google. But we use Google every day.It would not be the end of the world. ...

Product Updates - Gemini Live will have improved conversational manners, addressing the issue of cutting users off mid-sentence [1] - The update will first roll out on Android, followed by iOS in the new year [1] - Users will be able to mute their microphone while Gemini is speaking to prevent accidental interruptions [1] User Experience Enhancement - The goal is to create smoother and more natural conversations on the Gemini App [1]

Core Insights - Armis, a privately-held Israeli cybersecurity company, is in discussions for a potential sale to US-based ServiceNow for up to $7 billion, with an announcement expected soon [1] - ServiceNow is a leading platform for enterprise management and automation, boasting a market capitalization of nearly $180 billion [2] - Armis has recently surpassed an annual revenue of $300 million, growing by $100 million in less than a year, indicating strong demand for its cybersecurity solutions [3] Company Overview - Armis focuses on securing critical assets for large organizations, including airports and oil and gas infrastructure, and has expanded its offerings to address cyber vulnerabilities [5] - The company was previously controlled by Insight Partners, which acquired it in 2020 for $1.1 billion, making them significant beneficiaries of the potential sale [4] - Armis's founders have a history in cybersecurity, having previously worked at Adallom, which was acquired by Microsoft for $320 million in 2025 [5] Investment and Future Plans - The company is considering an IPO, targeting a flotation in late 2026 or early 2027 [3] - Other notable investors in Armis include Goldman Sachs, Google's Capital G, and Brookfield Asset Management, indicating strong backing from prominent financial entities [4]

New AI-powered tools from Google, Adobe, Apple and others can improve group shots and fun selfies https://t.co/DoPvQCozi9 ...