The core engineering behind @UnslothAI has always been impressive!Instead of relying on PyTorch's default autograd for backpropagation, Unsloth built their own backprop kernels from scratch in OpenAI's Triton language (a Python-based language for writing GPU kernels without needing to write raw CUDA C++).One of the reasons to do this is that the default autograd runs each operation as a separate GPU call, and each call reads and writes data back to global memory before the next one can start.Across dozens o ...

Investment Rating - The report does not explicitly state an investment rating for the healthcare technology sector Core Insights - Technology is significantly transforming healthcare, enhancing patient care through AI, AR, and VR, leading to improved drug development and medical outcomes [1] - The Dell Precision 7875 Tower, equipped with AMD Ryzen™ Threadripper™ PRO processors, meets the increasing demands of healthcare and life science firms for high-performance hardware [2] - The need for healthcare organizations to manage unprecedented data speeds and volumes is critical, particularly with higher resolution medical images [4] - Image quality and consistency are essential for accurate diagnoses, and the Dell Precision 7875 Tower provides the necessary power and expandability for diverse display and peripheral support [5] - Electronic Health Records (EHR) and Electronic Medical Records (EMR) enhance communication and coordination among healthcare providers, with the Dell Precision 7875 Tower ensuring fast access to patient data and robust security features [6] - Advances in technology have streamlined clinical research and medical training, creating a more affordable and effective research environment [8] - The Dell Precision 7875 Tower enables researchers to analyze large data sets efficiently, leveraging high core counts and professional graphics for detailed results [9] - Emerging technologies like VR, AR, AI, ML, and DL are facilitating more immersive collaboration in healthcare workflows [10] - The Dell Precision 7875 Tower supports demanding VR and AR applications, powered by AMD Ryzen™ Threadripper™ PRO processors, enabling the implementation of cognitive technology platforms [11]

If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs. https://t.co/cFg4mLOtU3Avi Chawla (@_avichawla):DeepSeek fixed one of AI's oldest problems.(using a 60-year-old algorithm)Here's the story:When deep learning took off around 2012-2013, researchers hit a wall. They couldn't just stack layers endlessly because gradients either exploded or vanished.So training deep https://t.co/1BHGBoWHVG ...

DeepSeek fixed one of AI's oldest problems.(using a 60-year-old algorithm)Here's the story:When deep learning took off around 2012-2013, researchers hit a wall. They couldn't just stack layers endlessly because gradients either exploded or vanished.So training deep networks was nearly impossible.ResNets solved this in 2016 with residual connections:output = input + what the layer learnedThat "+" creates a direct highway for information. This is why we can now train networks with hundreds of layers.Recently, ...

OUR world is dictated by systems far more complex than any one of us can see. A financial market, for example, is not just numbers on a screen. It is billions of individual decisions, buyers and sellers interacting with one another in ways that are anything but linear.A tiny policy change in one corner of the world can trigger a chain reaction across industries, economies, and entire continents. Climate, supply chains, social networks, the complex systems that shape our lives all share the same structure. T ...

Core Viewpoint - Sterling Capital Management launched the Sterling Capital Hedged Equity Premium Income ETF (SCEP), which combines artificial intelligence for idea generation and human intelligence for portfolio construction to provide a U.S. equity allocation while employing options strategies for income generation and market protection [1][3]. Fund Overview - The fund began trading on December 12 and currently manages $214.1 million in assets with a management fee of 0.65% [2]. - The ETF structure was chosen for its tax efficiency, intraday trading capability, and lower costs compared to traditional mutual funds [2]. Investment Strategy - SCEP aims to deliver tax-efficient monthly income, better risk-adjusted returns through AI-driven stock selection, and reduced downside risk via protective options trading [3]. - The fund's sub-adviser, Guardian Capital, has utilized AI in equity strategies since 2018 and manages over $4 billion in assets using similar investment processes [3]. AI Utilization - Guardian's AI models forecast key investment variables, including earnings growth and dividend growth, using machine learning and deep learning techniques [4]. - The AI narrows the investment universe to a shortlist of companies with a higher probability of durable earnings and dividend growth [5][6]. Portfolio Composition - The fund's top holdings include Alphabet Inc. (6.37%), Apple Inc. (6.09%), NVIDIA Corp. (5.77%), Microsoft Corp. (5.07%), and Amazon.com, Inc. (4.58%), identified for their strong balance sheets and growth potential [7]. - The fund maintains around 21% exposure to midcap stocks, which may provide better valuations compared to large-cap alternatives [11]. Options Strategy - SCEP employs a dynamic options overlay strategy, writing covered call options on up to 100% of its portfolio to boost income while buying protective put options to cushion against market declines [8][9]. - Protective puts are structured to guard against a 10% to 30% market decline, aiming to protect income-focused investors from large drawdowns [9][10]. Tax Efficiency - The fund's structure seeks to deliver more tax-efficient income by finding losses on individual securities and options to offset gains, potentially allowing for return of capital distributions [13]. - Return of capital distributions are generally not taxable in the year received, deferring taxes until the shares are sold, which may result in a higher capital gain [14][15].

Core Insights - The PGA Tour has enhanced its partnership with Amazon Web Services (AWS) to modernize operations and improve production capabilities using AWS AI infrastructure [1][4][7] Group 1: Partnership Development - The PGA Tour and AWS have been collaborating since 2021, with AWS serving as the official cloud provider and AI partner for the Tour [10] - The expanded partnership aims to transform how golf content is created, distributed, and experienced globally [4][7] Group 2: New Features and Enhancements - A "favorite players hub" will be introduced on the Tour's app and website, allowing fans to track their favorite players' stats and storylines [4] - Real-time shot-by-shot commentary will be provided throughout the season, along with enhanced graphics and statistics for the Tour's "World Feed" [5][7] Group 3: Vision and Future - The PGA Tour aims to connect fans with players, events, and content more effectively, leveraging AWS's vision for personalized sports experiences [7][8] - AWS's commitment to supporting golf is further reinforced by its partnership with the DP World Tour, which also named AWS as its official cloud provider in 2025 [10]

Core Insights - Geoffrey Hinton has officially become the second computer scientist in history to surpass 1 million citations on Google Scholar, following his collaborator Yoshua Bengio [1][3][4]. Academic Achievements - Hinton's most cited paper, "ImageNet classification with deep convolutional neural networks," has received 188,837 citations since its publication in 2012, marking a significant milestone in deep learning [3]. - He co-authored the influential paper "Deep learning," published in 2015, which has garnered over 107,646 citations, summarizing the development and applications of deep learning [23]. - Hinton's contributions include the development of backpropagation, Boltzmann machines, deep belief networks, dropout techniques, and t-SNE, among others, which have laid the groundwork for modern AI [11][14][15][21]. Personal Background - Geoffrey Hinton was born into an academic family in London, UK, and faced high expectations from a young age, which shaped his pursuit of academic excellence [5][9]. - His early curiosity about the world led him to explore various fields, including physics, philosophy, and psychology, before committing to artificial intelligence [9][10]. Career Milestones - Hinton moved to Canada in the 1980s, where he established a long-term academic career at the University of Toronto, contributing significantly to the AI field [10]. - He received the Turing Award in 2018 alongside Bengio and Yann LeCun, recognized as the "three giants of deep learning" [21]. Recent Developments - In 2023, Hinton left Google after a decade to freely discuss the risks associated with AI, expressing concerns about the potential dangers of advanced digital intelligence [27]. - In 2024, he was awarded the Nobel Prize in Physics alongside John Hopfield for their foundational discoveries in machine learning using artificial neural networks [25].

Core Insights - Gorilla Technology Group Inc. will participate in an investor webinar on January 28, 2026, to discuss its latest milestones and strategic objectives for 2026 [1][2]. Company Overview - Gorilla Technology Group Inc. is a global solution provider specializing in AI-driven Security Intelligence, Network Intelligence, Business Intelligence, and IoT technology, with over 24 years of operating history and 29 granted patents [3]. - The company is headquartered in London, U.K., and offers a wide range of solutions across various sectors, including Government & Public Services, Manufacturing, Telecom, Retail, Transportation & Logistics, Healthcare, and Education [4]. Financial Performance - Gorilla has a growing pipeline exceeding $7 billion, driven by strong demand for GPU-as-a-Service infrastructure, AI-powered smart cities, and mission-critical security platforms [3]. - Recent milestones include a $1.4 billion multi-year partnership to deploy AI-ready data centers in Southeast Asia and continued expansion of public safety programs in Asia and Latin America [3]. - The company reaffirmed its 2025 revenue guidance of $100-$110 million with EBITDA margins of 20-25% and expects 2026 revenue to range from $137 million to $200 million, reflecting increasing scale and sustained momentum [3].

Core Insights - Magnite and Cognitiv have announced a partnership to enhance real-time data integration, improving curation capabilities within Magnite's ClearLine solution, which allows media buyers to access premium video inventory more effectively [1][2] Company Overview - Magnite is the largest independent sell-side advertising company, providing technology for publishers to monetize content across various formats including CTV, online video, display, and audio [4] - Cognitiv is a leading advanced performance partner utilizing deep learning to predict consumer behavior and optimize advertising strategies [5] Industry Context - The media landscape is becoming increasingly fragmented across multiple channels such as streaming TV, audio, display, and mobile, necessitating advanced solutions for effective media curation [2] - The complexity of the programmatic ecosystem is driving demand for AI solutions that can enhance content signals and streamline workflows for buyers [3]