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Analyticsindiamag
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Microsoft Launches Phi-4 multimodal and Phi-4-mini, Matches OpenAI’s GPT-4o
- Microsoft has launched Phi-4-multimodal and Phi-4-mini, small language models (SLMs).
- Phi-4-multimodal integrates speech, vision, and text processing, enabling natural and context-aware interactions.
- The Phi-4 multimodal model surpasses Google Gemini and is comparable to OpenAI’s GPT-4o.
- Phi-4-mini is a text-based model suitable for reasoning, coding, and long-context tasks.
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Analyticsindiamag
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How Databricks Powers Domino’s to Deliver 1.5 Million Pizzas Daily
- Domino's leverages Databricks' Mosaic AI tools to enhance customer insights and streamline operations.
- Databricks' vector search enables rapid retrieval of customer feedback for sentiment analysis and theme identification.
- Model serving endpoints in Databricks facilitate sentiment analysis and feedback classification with optimized performance.
- Domino's plans to expand AI-powered insights to other platforms and integrate additional social media channels for feedback analysis.
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VentureBeat
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Microsoft’s new Phi-4 AI models pack big performance in small packages
- Microsoft has introduced a new class of highly efficient AI models, Phi-4, that require less computing power than existing systems.
- The Phi-4 models, Phi-4-Multimodal and Phi-4-Mini, outperform similarly sized competitors and match or exceed the performance of models twice their size.
- Phi-4-Multimodal can process text, images, and speech simultaneously, offering advanced AI capabilities for developers.
- The models aim to run on standard hardware or at the 'edge' to reduce costs, latency, and maintain data privacy for enterprises.
- Phi-4-Multimodal uses a 'mixture of LoRAs' technique to handle various inputs without performance degradation.
- The model excels in speech recognition, vision tasks, language understanding, and math and coding tasks.
- Capacity, an AI Answer Engine, has leveraged the Phi models to enhance efficiency and accuracy, reporting cost savings and better results.
- Phi-4 challenges the idea that bigger AI models are always better, emphasizing efficiency over scale for real-world applications.
- Phi-4 models are designed to operate on standard devices and at the edge of networks, making AI more accessible and widely adoptable.
- Masaya Nishimaki of Headwaters Co., Ltd., highlights the performance of Edge AI in environments with unstable network connections or strict confidentiality requirements.
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Medium
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Zip to Jpg Converter ( Fast & Free)
- Converting ZIP to JPG solves problems of instant sharing, editing flexibility, and storage efficiency.
- Manual conversion can be done using built-in software, but it becomes tedious for larger batches.
- Top 5 ZIP to JPG converters: Zamzar, WinZip, CloudConvert, 7-Zip, FileZigZag.
- JPGs use lossy compression. Choose maximum quality and use PNG for text-heavy images to minimize quality loss.
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Towards Data Science
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The Dangers of Deceptive Data–Confusing Charts and Misleading Headlines
- Misleading with data is a common tactic empowered by various tools like high-speed internet, social media, and AI.
- To protect oneself from being misled, understanding deceptive data practices is crucial.
- Different visual representations like bars and circles can impact how data is perceived visually.
- Using accurate visual cues in data visualization is essential for clear communication and interpretation.
- A key flaw in data visualization is often the absence of a clear title to provide context.
- Visuals, especially in social media, must stand alone and be easy to interpret without additional context.
- Political headlines can easily mislead with data, leading to misconceptions and false narratives.
- Employing 3D charts distorts data interpretation, making it misleading and unreliable.
- Understanding deceptive techniques in data presentation is essential to avoid being deceived.
- Data science offers valuable insights, but accurate interpretation is crucial amidst widespread data sharing.
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Dev
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Big O Notation Explained: How to Analyze Your Algorithm’s Speed
- Time complexity is a tool for algorithm analysis that helps you calculate roughly how fast your algorithm is. It measures the number of operations in an algorithm.
- Big O notation, denoted as O(f(n)), is used to represent time complexity.
- Constant factors and lower-order terms are ignored in time complexity calculations.
- Examples of different time complexities, such as O(1), O(n), O(nm), O(n^2), O(log n), and O(sqrt(n)), are provided.
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VentureBeat
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Hugging Face launches FastRTC to simplify real-time AI voice and video apps
- Hugging Face launches FastRTC, an open-source Python library that simplifies building real-time audio and video AI applications.
- FastRTC automates complex parts of real-time communication and allows developers to create basic applications with just a few lines of code.
- The library bridges the gap between AI models and real-time communication, enabling faster implementation of voice-first and video-enhanced AI experiences.
- FastRTC opens up possibilities for smaller companies and independent developers to access capabilities that were previously reserved for specialized teams.
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VentureBeat
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ElevenLabs’ new speech-to-text model Scribe is here with highest accuracy rate so far (96.7% for English)
- ElevenLabs has launched Scribe v1, a speech-to-text model with the highest accuracy rate so far, achieving 96.7% accuracy for English.
- Scribe outperforms Google's Gemini 2.0 Flash, OpenAI's Whisper v3, and Deepgram Nova-3 in accurately converting spoken speech into text.
- The model delivers state-of-the-art transcription accuracy in 99 languages and can distinguish and isolate up to 32 different speakers in the same audio file.
- Scribe is available now through the ElevenLabs website and API, with pricing set at $0.40 per hour of input audio.
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Medium
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How a Simple AI Bot Helped Me Earn Daily Income
- The 100% Done-for-You AI Bot System is a simple solution to earn extra income with minimal effort.
- It automates various tasks and streamlines processes to generate income even while you sleep.
- Users have reported earning $300 in the first few weeks and $2,000 in the first month.
- The program is user-friendly, comes with customer support, and is suitable for individuals and businesses alike.
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Medium
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Burning Cash on AI Won’t Magically Make Your Business Win
- AI cannot magically fix inefficiencies in a business process.
- AI amplifies existing flaws and inefficiencies, making them fail faster and more expensively.
- Automating a flawed process with AI leads to incorrect predictions, stock shortages, over-ordering, and financial losses.
- AI should be the final optimization layer, not a shortcut. Fix the underlying issues before implementing AI.
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Medium
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Training a CNN to Detect Pneumonia: Here’s What I Learned
- The author shares their experience of training a Convolutional Neural Network (CNN) for detecting pneumonia.
- Key skills learned include handling class imbalance in the training set, using validation and test sets, image resizing, pixel normalization, and data augmentation.
- The author explains the importance of avoiding photometric transformations in pneumonia detection and the use of ReLU activation function.
- Metrics used for evaluation include accuracy, precision, recall, and loss tracking. The author invites discussion on optimizing CNN performance.
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Towards Data Science
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LLaDA: The Diffusion Model That Could Redefine Language Generation
- LLaDA introduces a novel approach to Language Generation by using a 'diffusion-based' process, moving away from traditional autoregression.
- LLaDA operates without the use of RLHF, which is common in current large language models (LLMs).
- Current LLMs, based on the Transformer architecture, predict text tokens one at a time using masked self-attention.
- LLaDA aims to address limitations of current LLMs, such as computational expense, lack of global reasoning, and reliance on vast training data.
- Rather than predicting subsequent tokens, LLaDA focuses on a diffusion-based generation process during pre-training.
- The 'remasking' concept in LLaDA allows for a more controlled and refined text generation process compared to autoregressive models.
- LLaDA combines diffusion with autoregressive generation in semi-autoregressive diffusion, offering a hybrid approach for language generation.
- Inspired by image diffusion models, LLaDA progressively unmasks tokens to generate coherent language, akin to 'denoising' in image generation.
- LLaDA shows promise in improving efficiency, reasoning, and context understanding in language models, with potential for diverse applications.
- The flexibility of LLaDA in adjusting parameters makes it suitable for various tasks, indicating a shift towards more natural and efficient language models.
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Analyticsindiamag
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Amazon’s New Alexa+ Knows What You Want Before You Do
- Amazon has announced Alexa+, a next-generation personal assistant powered by Anthropic Claude, which will be available for free to Prime members.
- Alexa+ is more conversational, smarter, personalised, and helps you get things done.
- It can understand and respond naturally to users, take action on behalf of users, and control smart home devices, book reservations, manage music libraries, order groceries, and track ticket sales.
- Alexa+ introduces agentic capabilities, allowing it to complete tasks independently and remember user preferences for more personalized recommendations and actions.
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TechBullion
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Revolutionizing Data Science: How Paras Doshi is Transforming Decision Science and AI
- Paras Doshi is a visionary leader revolutionizing data science, AI, and data engineering, with significant impacts at Opendoor and Amazon.
- At Opendoor, Doshi spearheaded transformations in decision-making, marketing science, pricing optimization, and analytics platforms.
- He led the revitalization of Opendoor's Marketing Science team, optimizing over $100M of spend and introducing the Physics of Marketing model.
- Doshi scaled the Pricing Decision Science team and contributed to Opendoor's India strategy, enhancing global data capabilities.
- During his tenure at Amazon, Doshi drove cost savings, efficiency gains, and >$1 billion in revenue through data-driven innovations.
- He is recognized for his impactful blog, industry mentorship, and thought leadership in AI, analytics, and engineering.
- As a judge at elite AI hackathons and active member of prestigious networks, Doshi contributes to shaping the future of AI and data ethics.
- Doshi's mentorship programs have guided over 20 data professionals, emphasizing structured thinking and leadership skills.
- His expertise in decision science, AI-driven analytics, and data transformation positions him as a sought-after leader in the industry.
- Paras Doshi's work exemplifies the power of data-driven transformation, setting the standard for excellence in analytics and decision science.
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Medium
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EFI Theory: Is Energy Learning Through Us?
- Energy is constantly seeking balance and learning from its own disruptions.
- Babies absorb energy before birth, making the womb the first energy transfer station.
- Water, electricity, and energy are interconnected and form the foundation of creation.
- Humans may be a means by which energy experiences itself and expands.
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