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Towards Data Science
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This Is How LLMs Break Down the Language
- LLMs, comprised of transformer neural networks and giant mathematical expressions, process input sequences through embedding layers converting tokens into numerical representations.
- During training, the neural network's billions of parameters are iteratively updated to align its predictions with patterns observed in the training set.
- The transformer architecture, introduced in 2017, serves as the foundation for LLMs and is specialized for sequence processing.
- Nano-GPT, with approximately 85,584 parameters, uses token sequences as inputs that undergo transformations to predict the next token in the sequence.
- Training a language model like ChatGPT involves stages like pretraining with a large dataset, such as FineWeb, to teach the model the flow of text.
- Tokenization, the process of converting raw text into symbols, is essential in LLMs and uses techniques like Byte-Pair Encoding to compress sequence length.
- Byte Pair Encoding involves identifying frequent symbol pairs to shorten sequences and expand the symbol set, with GPT-4 having a vocabulary size of around 100,000.
- Tools like Tiktokenizer allow for interactive exploration of tokenization models like GPT-4 base model, aiding in understanding how tokens correspond to text.
- State-of-the-art transformer-based LLMs rely on efficient tokenization strategies like Byte-Pair Encoding to process text inputs and enhance model performance.
- A well-designed tokenization approach is essential for improving the efficiency and overall performance of language models in processing and generating text.
- Understanding tokenization can provide insights into how LLMs interpret and generate text, contributing to advancements in model efficiency and effectiveness.
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Analyticsindiamag
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How Longevity India is Riding the AI Health Revolution
- AI and systems biology are transforming diagnostics in India, creating a healthcare model focused on prevention rather than cure.
- AI-driven models analyze molecular pathways, genetic markers, and large-scale health data to predict diseases before symptoms appear.
- India is uniquely positioned to build a next-gen AI-driven health system without legacy constraints.
- Initiatives in India, such as Biopeak, are utilizing AI for early disease detection and conscious medicine standards.
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Medium
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Wiccan Love Spells That Work: How to Harnessing Positive Energy for Love
- Wiccan love spells are rituals rooted in the principles of Wicca, emphasizing harmony, balance, and personal growth.
- These spells utilize natural elements like herbs, candles, and crystals to attract or nurture love.
- Three simple Wiccan love spells are provided: building self-worth, attracting a compatible partner, and promoting healing in a relationship.
- It is important to align with the Wiccan Rede and follow ethical guidelines when performing love spells.
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Medium
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DatasphereAI: Illuminating your data universe
- DatasphereAI is a startup aimed at simplifying data interaction and visualization through AI, created by an experienced professional in the Data/AI field.
- The application is currently in the prototype stage and offers features like automatic data visualization, natural language interaction, and AI-powered data exploration.
- Users can generate dashboards by uploading data files, interact with visualized data through a chat feature, and explore datasets with AI-generated visualizations based on questions.
- DatasphereAI extracts metadata from various data sources for efficient information retrieval, enabling users to search through extracted information using filters and create dashboards for specific categories.
- The application also allows users to define attributes for specific data categories, interact with their data using AI agents, and execute complex tasks via natural language commands.
- Users can visualize information, ask questions, and analyze data using AI agents in a conversational manner, enabling a deep exploration of data sources.
- Datasphere AI is at an early stage and seeks collaborators and supporters to further develop and enhance its capabilities in revolutionizing data interaction and understanding.
- The application aims to simplify complex data tasks and invites interested parties to explore its features for potential business benefits.
- The blog post hints at future technical insights into Datasphere AI, promising continued innovation and advancements in the data universe.
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Medium
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Preparing for the Future: Essential Data Science Skills for 2025
- Data science is evolving rapidly, with increasing demands from companies for a broad range of skills beyond just technical expertise.
- To remain competitive in 2025 and beyond, data scientists must continuously learn and adapt to new techniques and advancements in AI, machine learning, and cloud computing.
- NLP and Generative AI are revolutionizing various industries, offering new opportunities for data scientists.
- To deliver impactful results, data scientists need to align model outcomes with business objectives, collaborating with stakeholders and considering trade-offs.
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Medium
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Comprehensive Breakdown of Agentic AI vs Traditional AI: Future Trends, Ethics & Real-World Impact
- Agentic AI and Traditional AI are two giants in the field of artificial intelligence.
- Agentic AI is capable of autonomous decision-making and adapting to unpredictable situations.
- Traditional AI, on the other hand, follows set instructions and executes tasks flawlessly.
- Agentic AI represents a future trend in AI technology, while Traditional AI has a more limited role.
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Medium
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Understanding Digital Images: A Deep Dive into Pixels, Color Spaces, and Python Representation
- A pixel (short for 'picture element') is the smallest unit of a digital image.
- An image is made up of thousands or millions of pixels, each carrying a specific color value.
- Color spaces, such as RGB and HSV, define how colors are represented in an image.
- Understanding pixels and color spaces is crucial in fields such as AI, computer vision, and digital design.
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Analyticsindiamag
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Pega India as the Powerhouse Miniature
- Pega India, part of Pegasystems, focuses on building core skills like transition risk and sustainability.
- The company nurtures talent and encourages employees to take on global roles.
- Pega India has around 1,900 employees primarily based in Hyderabad and Bengaluru.
- The team collaborates across functions, reflecting the global Pega culture.
- Pega Cloud plays a significant role in the company's growth, aiding clients in application deployment on cloud infrastructure.
- Pega India excels in core product engineering with achievements like Constellation technology.
- The company has strong expertise in AI, investing in adaptive, predictive models, and NLP over the years.
- Pega integrates with leading AI models but focuses on governance, security, scalability, and resilience.
- Pega India hires talent from universities and conducts lateral hiring for specialised roles.
- The company values mentorship, with 40% of individual contributors having more than 10 years of experience.
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Analyticsindiamag
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Quest Global Acquires US-Based VLSI Design Firm Alpha-Numero Technology Solutions
- Quest Global has acquired Alpha-Numero Technology Solutions, a US-based VLSI design firm.
- The acquisition aims to strengthen Quest Global's capabilities in semiconductors and expand its mission and safety-critical engineering solutions.
- Alpha-Numero is known for its expertise in avionic design and verification, specializing in safety-critical avionics systems and complex electronics hardware.
- The company also works on the design and verification of FPGA or ASIC or system on a chip (SoC) used in automotive systems and consumer electronics.
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Analyticsindiamag
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Fractal CEO Reflects on the ‘Worst Mistake of His Life’ After 25 Years
- Srikanth Velamakanni, co-founder and group CEO of Fractal, reflects on the 'worst mistake of his life' in turning down a $750,000 investment from HCLTech co-founders due to board control conditions.
- Fractal's founding team rejected the termsheet valuing the company at $3 million, and subsequently faced financial struggles after the dot-com bust.
- Velamakanni emphasizes the importance of not letting ego drive decisions, respecting investors' trust, and addressing their concerns.
- Fractal, India's first AI unicorn, is planning to raise $500 million through an IPO at a valuation of at least $3.5 billion.
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Educba
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Benefits of AI Chatbots in Customer Service
- AI chatbots provide faster responses, eliminating long wait times for customers.
- AI chatbots offer consistent and reliable support, ensuring a better customer experience.
- AI chatbots personalize customer interactions by remembering past interactions and tailoring responses accordingly.
- AI chatbots can act as lead generators by engaging potential customers in real-time, aiding in sales.
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Medium
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DeepSeek’s Emergence: Assessing Its Impact on Nvidia’s Market Position
- DeepSeek, founded by Liang Wenfeng, has developed advanced AI models at a fraction of the cost of competitors.
- The emergence of DeepSeek led to a 17% drop in Nvidia's stock, reflecting concerns about competition from cost-effective AI solutions.
- Analysts suggest that DeepSeek's advancements could benefit Nvidia by increasing the demand for GPUs as AI applications expand.
- Nvidia remains resilient, reporting a 78% YoY revenue increase in Q4 2025 and adapting to industry shifts.
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Analyticsindiamag
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Manus is a Wrapper of Anthropic’s Claude, and It’s Okay
- Manus, a Chinese startup, has developed a 'general purpose AI agent' that can autonomously plan, execute tasks, and deliver results in real time.
- Praised for its capabilities, Manus can complete professional work quickly, showcased features like data analysis, creating itineraries, and received positive feedback on its user experience.
- Manus utilizes a human-in-the-loop approach, where human work is required for various permissions and approvals, and was evaluated in the GAIA benchmark, outperforming OpenAI's Deep Research.
- Despite being a wrapper of Anthropic's Claude Sonnet model, Manus has been appreciated for its well-designed interface and agentic capabilities.
- Some users critiqued Manus for issues like taking excessive time on tasks, getting stuck on web searches, and being invite-only.
- However, professionals like Aidan McLaughlin from OpenAI commend Manus for its value creation, emphasizing capabilities over architecture.
- The development of an open-source alternative for Manus called 'OpenManus' on GitHub has sparked anticipation, indicating that Manus' capabilities can be replicated.
- Criticism also arose regarding Manus' underlying models, potential slowdown due to using multiple models, and its invite-only distribution strategy.
- The evolution of Manus prompts questions about when other major players in the AI ecosystem will release more accessible versions of similar capabilities.
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Analyticsindiamag
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Google DeepMind’s Thinking Models: What to Expect
- Google DeepMind has been making significant strides in developing ‘thinking models’—a new class of AI models that can reason, plan, and solve complex problems more effectively than previous models.
- Google DeepMind's thinking models have shown advancements in performance on tasks such as math, coding, and multimodal reasoning.
- The company has released experimental versions of the Gemini Flash Thinking model and plans to integrate it with Google Search and Maps.
- Google DeepMind is actively gathering feedback from developers and working towards a general availability (GA) release of the thinking models.
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Analyticsindiamag
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Foxconn Unveils FoxBrain—Chinese AI Model Poised for Open Source Release
- Hon Hai Research Institute, a research centre by Hon Hai Technology Group (Foxconn), launched a traditional Chinese large language model (LLM) code-named FoxBrain.
- FoxBrain is set to become an important engine for Foxconn’s three major platforms: Smart Manufacturing, Smart EV, and Smart City.
- The model, initially developed for internal systems, will be open-sourced and shared publicly in the future.
- FoxBrain was trained efficiently using a training strategy that optimized the process, resulting in a local AI model with powerful reasoning capabilities.
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