Core Insights - Snap's stock has experienced a significant decline of 88% from its peak value, primarily due to privacy changes by Apple that affected its advertising effectiveness [2][5] - The company is showing signs of recovery, with improvements in its advertising technology and a growing user base [6][10] Group 1: Stock Performance - Snap's stock reached an all-time high of $83 in September 2021, representing a 388% gain from its IPO price of $17 [1] - Following the peak, Snap's stock has lost 88% of its value, indicating substantial volatility [2] Group 2: Advertising Challenges - Apple's privacy changes in 2021 required app developers to obtain user consent for tracking, which negatively impacted Snap's ability to sell targeted ads [4][5] - Meta Platforms adapted quickly to these changes, while Snap was slower but has made significant progress with a new machine learning-powered advertising engine [6] Group 3: Revenue Trends - Snap's annual revenue grew by 64% in 2021 but fell to 12% in 2022 and less than 1% in 2023 [8] - In 2024, Snap achieved record revenue of $5.4 billion, reflecting a growth rate of 16% [9] Group 4: User Engagement - As of the end of Q1 2025, Snapchat had 460 million daily active users, a 9% increase year over year, indicating strong user engagement [10] - The platform has gained approximately 140 million more daily users since the end of 2021, enhancing its attractiveness to advertisers [12] Group 5: Valuation and Investment Potential - Snap's current price-to-sales ratio is 2.8, near its lowest level since going public in 2017, suggesting a potentially undervalued stock [13] - If Snap successfully addresses its advertising challenges, it could lead to increased investor confidence and higher valuations in the future [15]

Core Viewpoint - The open-source project ZLUDA, which enables non-NVIDIA chips to run CUDA, has been revived after facing near bankruptcy due to the withdrawal of AMD's support. A mysterious organization has stepped in to provide assistance, allowing the project to continue its development and support for large model workloads [1][2][12]. Historical Development - ZLUDA was initiated by Andrzej Janik, who previously worked at Intel, aiming to allow CUDA programs to run on non-NVIDIA platforms [4][5]. - Initially, ZLUDA was taken over by Intel as an internal project to run CUDA programs on Intel GPUs, but it was soon terminated [6][9]. - In 2022, ZLUDA received support from AMD but was again halted in February 2024 after NVIDIA released CUDA 11.6, which restricted reverse engineering on non-NVIDIA platforms [10][11][12]. Recent Developments - In October 2024, Janik announced that ZLUDA had received support from a mysterious organization, focusing on machine learning and aiming to restore the project to its previous state by Q3 2025 [13][15]. - The project has added a new full-time developer, Violet, who has made significant improvements, particularly in supporting large language model workloads [17]. Technical Progress - ZLUDA is working on enabling 32-bit PhysX support, with community contributors identifying and fixing errors that may also affect 64-bit CUDA functionality [19]. - A test project named llm.c is being developed to run the GPT-2 model using CUDA, marking ZLUDA's first attempt to handle both standard CUDA functions and specialized libraries like cuBLAS [20][22]. - The team has made progress in supporting 16 out of 44 required functions for the test program, indicating a step closer to full functionality [25]. Accuracy and Logging Improvements - ZLUDA aims to run standard CUDA programs on non-NVIDIA GPUs while matching NVIDIA hardware as closely as possible. Recent efforts have focused on improving accuracy by implementing PTX "scan" tests to ensure correct results across all inputs [26][28]. - The logging system has been significantly upgraded to track previously invisible activities and internal behaviors, which is crucial for running any CUDA-based software on ZLUDA [31][33]. Runtime Compiler Compatibility - ZLUDA has addressed issues related to the dynamic compilation of device code necessary for compatibility with modern GPU frameworks. Recent changes in the ROCm/HIP ecosystem have led to unexpected errors, but the ZLUDA team has resolved these problems [34][36][38].

Core Insights - Snowflake (SNOW) and Microsoft (MSFT) are significant players in the growing cloud data platform market, with Snowflake offering a scalable data warehouse and Microsoft providing a suite of data services on Azure [1][2] Market Overview - The global cloud data platform market was valued at $22.78 billion in 2025 and is projected to reach $104.50 billion by 2033, reflecting a CAGR of 24.3% [2] Microsoft (MSFT) Analysis - Microsoft Cloud revenue reached $42.4 billion in Q3 of fiscal 2025, up 20% year over year, with Azure and other cloud services growing 33% year over year [3] - Nearly 60% of Fortune 500 companies use PostgreSQL on Azure, and Cosmos DB showed steady growth supported by major customers [5] - Microsoft’s Fabric, a unified analytics solution, served over 21,000 paid customers, up 80% year over year, with OneLake seeing data volumes increase more than six times compared to the prior year [6][10] - Microsoft is well-positioned to lead in cloud data infrastructure due to strong enterprise demand and an integrated platform [7] Snowflake (SNOW) Analysis - In Q1 of fiscal 2026, Snowflake's product revenues rose 26% year over year to $996.8 million, with a net revenue retention rate of 124% [8] - Snowflake's platform supports a unified data experience across storage, processing, governance, and AI, with offerings like Snowpark and the Native App Framework [9][11] - Snowflake is enhancing its platform for modern analytics and AI workloads, with partnerships and features that improve cost efficiency and performance [10][11] Price Performance and Valuation - Year-to-date, SNOW shares have increased by 43.5%, while MSFT shares have appreciated by 18.3% [12] - Snowflake trades at 14.94X forward 12-month Price/Sales, compared to Microsoft's 11.7X, indicating a higher valuation for Snowflake [15] Earnings Estimates - The Zacks Consensus Estimate for SNOW's fiscal 2026 earnings is $1.06 per share, indicating a 27.71% increase year over year [18] - The Zacks Consensus Estimate for MSFT's 2025 earnings is $13.36 per share, indicating a 13.22% increase year over year [19] Investment Outlook - Microsoft is viewed as a more attractive investment due to its broader product ecosystem and strong growth driven by Azure, while Snowflake faces near-term valuation concerns and competition [20][21]

Investment Rating - The report maintains a positive outlook on global defense spending, indicating potential growth opportunities for defense contractors through the remainder of the decade [3][7][57]. Core Insights - The report highlights a significant shift in defense spending priorities under President Trump's administration, focusing on bolstering security in the Indo-Pacific and reducing reliance on European security [6][56]. - NATO member countries have set a new defense spending target of 5% of GDP by 2035, with core defense spending rising from 2% to 3.5% of GDP, which could enhance NATO's defense capabilities if achieved [4][22]. - The report emphasizes the increasing importance of technological advancements, particularly in artificial intelligence and unmanned systems, which are expected to drive future defense investments [49][81]. Summary by Sections Global Defense Spending - The U.S. defense budget is projected to increase significantly, with a flat discretionary budget and $119 billion in mandatory spending allocated for fiscal 2026 [10][72]. - The U.S. is currently spending 3.4% of GDP on defense, with a notable increase in defense spending across NATO countries due to geopolitical tensions [28][29]. European Defense - European defense spending has increased by approximately 40% over the past two years, with Germany accounting for a significant portion of this growth [39]. - The EU's ReArm Europe program aims to unlock additional funding for defense, potentially adding €160 billion annually over the next four years [37][40]. Indo-Pacific Defense - Countries in the Indo-Pacific region are enhancing their defense capabilities in response to threats from China and North Korea, with increased cooperation among Western and Eastern allies [9][18]. - The report notes that while some nations have maintained spending levels, others are increasing their budgets to deter regional conflicts [18]. Technological Advancements - The report discusses the role of AI and machine learning in modernizing defense efforts, with a focus on enhancing decision-making and operational capabilities [81]. - The U.S. is investing in autonomous systems and cyber capabilities to improve defense readiness and counter adversarial threats [81][83]. Procurement and Spending Trends - The report anticipates a shift in defense procurement priorities, with an emphasis on attritable systems and advanced technologies to enhance military effectiveness [74][90]. - The U.S. Department of Defense is expected to allocate significant funding towards shipbuilding and missile defense initiatives, reflecting a strategic focus on maritime threats [86][92].

CLEVELAND, July 7, 2025 /PRNewswire/ -- As part of its ongoing commitment to innovation and digital transformation, KeyBank (NYSE: KEY) today announced the launch of KeyTotal AR™, a fully unified solution for the invoice-to-cash process, powered by Versapay. Leveraging machine learning, the platform modernizes and automates accounts receivable (AR) operations for middle-market businesses. This latest enhancement reinforces KeyBank's commitment to delivering market-leading, technology-driven solutions to cli ...

Core Insights - Freight Technologies, Inc. (Fr8Tech) has secured Reckitt Benckiser de México as a client, highlighting its ability to attract globally recognized companies in the logistics sector [1][2][3] - The partnership with Reckitt Benckiser is seen as a validation of Fr8Tech's platform and its value proposition within the logistics ecosystem [3] - Fr8Tech is focused on expanding its technology and network to enhance cross-border and domestic shipping capabilities in the USMCA region [3] Company Overview - Fr8Tech offers a diverse portfolio of technology-driven solutions aimed at optimizing and automating supply chain processes, utilizing AI and machine learning [4] - The company's solutions include Fr8App for B2B cross-border shipping, Fr8Now for less-than-truckload shipping, Fr8Fleet for enterprise clients, Waavely for ocean freight management, and Fleet Rocket as a Transportation Management System [4] - Each product is interconnected within a unified platform to improve operational efficiency through features like live pricing, real-time tracking, and digital freight marketplace [4]

Project Overview - The project involves building a mini-ChatGPT application [1] - The application is powered by DeepSeek-R1 and operates 100% locally [1] Resource Sharing - The author shares tutorials and insights on DS (Data Science), ML (Machine Learning), LLMs (Large Language Models), and RAGs (Retrieval-Augmented Generation) daily [1] - The author encourages readers to reshare the content with their network if they find it insightful [1]

Core Insights - The article discusses the author's academic and professional background in Machine Learning, Economics, and Finance, highlighting expertise in Data Science and Machine Learning applications within the banking and finance sectors [1]. Group 1: Academic Background - The author holds a PhD in Machine Learning with a focus on Economics and Finance [1]. - The author has academic affiliations with IESE Business School, ESADE Business School, and the Barcelona Supercomputing Center [1]. Group 2: Professional Experience - The author has worked at Deloitte Financial Advisory, specializing in Data Science and Machine Learning applications for clients in banking, insurance, and finance [1]. - The author currently teaches Asset Pricing and Introduction to Corporate Finance at ESADE Business School at the MSc/BSc level [1]. Group 3: Research Focus and Interests - Current research focuses on Generative AI in sustainable finance [1]. - The author's interests include machine learning and generative AI applications in finance and economics, with proficiency in Python, R, and SQL [1].

Industry Overview - The technology services industry is mature, with demand for services in good shape, and revenues, income, and cash flows are expected to gradually return to pre-pandemic levels, enabling stable dividends for most players [1] - The global shift toward digitization is creating opportunities in markets such as 5G, blockchain, and AI, with companies adopting generative AI, machine learning, and data science to gain competitive advantages [4] - The business software industry is benefiting from strong demand for multi-cloud-enabled software solutions as companies transition from legacy platforms to modern cloud-based infrastructure [4] Company Highlights AppLovin Corp. (APP) - AppLovin is a software-based platform for mobile app developers, enhancing marketing and monetization of apps [6] - The introduction of AI-powered AXON 2.0 technology and strategic expansion in gaming studios have significantly boosted revenue growth [7] - AppLovin's expected revenue and earnings growth rates for the current year are 16% and 84.8%, respectively, with a Zacks Consensus Estimate for current-year earnings improving by 0.1% in the last seven days [8] - The average short-term price target for AppLovin shares indicates a potential increase of 37% from the last closing price of $341.64, with a maximum upside of 90.3% [8] Duolingo Inc. (DUOL) - Duolingo operates as a mobile learning platform offering courses in 40 different languages and provides a digital language proficiency assessment exam [10] - The company utilizes AI applications to personalize and automate the learning process, with tools like Birdbrain analyzing real-time user performance [11] - Duolingo's expected revenue and earnings growth rates for the current year are 33.5% and 54.3%, respectively, with the Zacks Consensus Estimate for current-year earnings improving by 2.1% over the last 60 days [12] - The average short-term price target for Duolingo shares indicates a potential increase of 24% from the last closing price of $391.86, with a maximum upside of 53.1% [12]

Market Overview - The global market for Data Annotation Tools was estimated at US$1.9 Billion in 2024 and is projected to reach US$6.2 Billion by 2030, growing at a CAGR of 22.2% from 2024 to 2030 [1][14]. Importance of Data Annotation Tools - Data annotation tools are essential for labeling and categorizing data to train AI and machine learning models, which is crucial for applications like computer vision, natural language processing, and speech recognition [2][3]. - High-quality, accurately labeled data is vital for the performance of AI models in critical applications such as autonomous driving and medical imaging [3]. Growing Demand Across Industries - The demand for data annotation tools is increasing as industries rely on AI and machine learning to enhance efficiency and customer experiences [4][6]. - In the automotive sector, these tools are necessary for training autonomous vehicles to recognize road signs and obstacles [4]. - In healthcare, annotated data aids in developing AI models for disease detection and treatment planning [5]. - Other sectors like e-commerce and finance utilize data annotation for personalization and fraud detection [6]. Market Segmentation and Growth - The report highlights significant growth in the Text segment, expected to reach US$2.1 Billion by 2030 with a CAGR of 19.6%, while the Image/Video segment is projected to grow at a 24.3% CAGR [13]. - The U.S. market is valued at $474.1 Million in 2024, with China forecasted to grow at an impressive 28.0% CAGR to reach $1.7 Billion by 2030 [13]. Strategic Insights - The report includes analysis of market dynamics, competitive intelligence, and the impact of global trade and economic shifts on the data annotation tools market [10][16]. - Key players in the market include Alegion, Amazon Mechanical Turk, Appen, and Clickworker, among others [16][19]. - The increasing focus on AI-powered solutions and the need for high-quality labeled data are driving the growth of the data annotation tools market [16].