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Analyticsindiamag
17h
491
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LTIMindtree, IBM Setup Watsonx Center of Excellence for GenAI in India
- LTIMindtree and IBM are collaborating to establish a global, joint Generative AI Center of Excellence (CoE) in India.
- The CoE will combine the power of IBM Watson AI and data platform with LTIMindtree's engineering skills.
- The collaboration aims to accelerate clients' generative AI adoption and offer a comprehensive suite of services.
- The CoE will focus on building point solutions to expand the scope of generative AI applications for clients' digital initiatives.
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Analyticsindiamag
18h
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Can Ruby Survive as the ‘Human-First’ Programming Language?
- Ruby, a general-purpose programming language, and Rails, a framework for creating websites, apps, and systems recently released version 7.1.3.2, which addresses several security issues.
- Despite declining popularity, the Ruby community remains committed to improving the language and framework.
- Ruby's 'human-first' approach and emphasis on simplicity make it well-suited for developers in the AI era.
- By focusing on integrating AI to enhance the developer experience, Ruby can carve out a unique niche in the AI era.
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Medium
18h
236
New Research on Large Language Models part7
- Large language models (LLMs) have the capability to reproduce various rhetorical styles and generate text expressing a wide range of sentiments.
- The low-cost availability of LLMs makes them powerful tools for manipulation and control, leading to underestimated societal harms.
- The rapid and unregulated adoption of LLMs has led to the pollution and uniformization of information environments.
- Emerging research areas such as real-time design of choice architectures, computational models of human agents and populations, and reinforcement learning combined with LLMs enable the development of systems for individual, social, and political control.
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Analyticsindiamag
18h
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AGI is a Rorschach Test for People to Project Their Technology Anxieties
- There’s a lot of murmur around AGI, but we’re still not sure when we will achieve it.
- Kevin Scott, CTO of Microsoft, called AGI kind of a Rorschach test for people to project their anxieties.
- OpenAI CEO Sam Altman believes that AGI is a poorly formed question and talks about the importance of iterative deployment.
- All major tech companies are in the pursuit of AGI, but the developer community seems to be disappointed by OpenAI for making tall claims.
- Soket AI Labs has become the first Indian startup to build solutions towards ethical AGI.
- When asked about the AGI timeline, Altman said that people want to know when their lives will change due to it.
- Altman believes that every year for the next many years, there will be dramatically more capable systems.
- However, he doesn't know how to give a precise timeline of when we get to that milestone people care about.
- OpenAI COO Brad Lightcap says generative AI, as it is today, will be 'laughably bad' within a year.
- Many experts have different opinions about AGI – some believe it will be here in 2029 while some say never.
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Medium
18h
70
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Odyssey Continues…
- The journey started with a quest to improve programming skills, but deviated due to other commitments.
- The focus of the week was on data science and web development, with more emphasis on web development.
- Explored key terms in data science and understood the roles of a data scientist and data analyst.
- Discovered the Odin Project for web development and found it liberating and satisfying to complete sections.
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Medium
18h
151
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Building Intelligent Applications with Spring AI
- In the current era of digital advancements, intelligent applications with AI techniques have become crucial for enterprises to maintain their competitiveness. Spring Framework has introduced Spring AI to equip developers with necessary tools and abstractions for integrating AI capabilities into Spring applications.
- Spring AI offers different extensions and components such as integrating AI models, document processing, and data transformation. Developers need to set up their project using Spring Initializr.
- Natural Language Processing (NLP) is an AI field that focuses on the interaction between computers and human languages, and Spring AI offers different tools for NLP tasks such as Text Tokenization, Named Entity Recognition (NER), and Sentiment Analysis.
- Image recognition is a foundational component of computer vision and developers can seamlessly integrate image recognition features into their Spring applications using different methods. The methods include image classification and object detection.
- The article emphasizes incorporating strong security measures, ensuring scalability, implementing comprehensive error handling mechanisms, and monitoring while building AI applications with Spring AI.
- Developers can simplify the process of integrating AI into Spring applications by utilizing Spring AI, thus emphasizing the Spring Framework's adaptability and scalability.
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Towards Data Science
18h
303
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The struggle of Artificially Imitated Intelligence in specialist domains
- Artificially Imitated Intelligence (LLMs) appears to be struggling in specialized domains like finance, medicine, and law due to its limited ability to reason.
- Ontology is a knowledge representation of the domain that could help LLMs overcome its weaknesses and add semantic understanding about how things work.
- Ontologies can ensure complete audit trails, consistency, and objective interpretations in specialist areas like banking regulations, asset and liabilities management with minimal effort.
- LLMs are already making an impact on customer service chats and reducing human costs but is still prone to hallucination.
- Moreover, LLMs can leverage knowledge graphs to achieve better results in Retrieval-Augmented Generation (RAG).
- Ontologies and Knowledge Graphs are game-changers for real intelligence and for future specialist AIs that reduce hallucinations.
- An example of a simple ontology created with the CogniPy library shows how structure, data, and logic can be united with minimal effort.
- The example was able to evaluate rules, make deductions, and explain with complete audit trails.
- Ontologies could benefit businesses for enforcing a common dictionary, understanding the rules, reducing effort on interpretation, and adding more knowledge to specialist fields.
- A proof of concept that unites structure, data, and logic in a smart data structure, both human and machine-readable, could claim the title of AI.
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Towards Data Science
19h
355
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What Is a Latent Space?
- Understanding the latent space is crucial to understanding generative AI.
- The latent space is a mathematical space from which we generate synthetic objects.
- Examples of the latent space include compressed representations of patient data and representations of images.
- Generative models can identify a low-dimensional set of features in large datasets.
- The latent space can be used to explore other dimensions, such as hair length and smile.
- Text material can also be analyzed through the latent space by encoding words and phrases.
- The AI model learns the latent space, performs operations within it, and then reconstructs the data.
- The latent space highlights essential properties for the current task being performed by the AI model.
- The latent space is a critical concept to understand the function of generative AI.
- It allows the creation of synthetic objects by using compressed numerical representations of the original objects.
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Medium
19h
96
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Navigating the Basics of Software Engineering: A Beginner’s Guide
- Software engineering is essential in our digital world, supporting the development of various applications.
- The software development lifecycle (SDLC) encompasses multiple phases such as requirements gathering, design, implementation, testing, deployment, and maintenance.
- Mastery of programming languages, tools like IDEs and version control systems, and project management platforms is crucial in software engineering.
- Effective communication, teamwork, continual learning, and engagement with the software engineering community are vital for professional growth.
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Medium
19h
300
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Training Llama-3 with Bengali Data: A GPU-Optimized Approach using Unsloth
- Llama-3, a language model, was trained on a Bengali dataset using Unsloth for optimizing GPU usage.
- Bengali, being the seventh most spoken language, lacks high-quality NLP resources.
- The training process involved using the Bengali dataset, formatting prompts, and optimizing GPU usage with Unsloth.
- The results showed that Llama-3 can accurately understand and generate Bengali text, contributing to Bengali NLP development.
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Medium
20h
348
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Capitalizing on Efficiency — Shifting Investment from Data Platforms to Generative AI Initiatives…
- Organizations are increasingly looking towards generative artificial intelligence (AI) as the next frontier for innovation and advantage.
- Optimizing existing data platforms is an impactful strategy to facilitate this transition.
- Optimizing and streamlining existing data platforms boosts efficiency and also liberates capital that can be redirected towards pioneering AI projects.
- Streamlining operations, minimizing waste and ensuring that data platforms operate at peak efficiency is crucial to unleashing the full potential of generative AI.
- Minimizing waste involves critical assessment and overhaul of existing data management practices, including cumbersome ETL/ELT, and data engineering processes.
- Companies that optimized their ETL/ELT processes saw a reduction in data processing costs by up to 30%, freeing up resources for other initiatives.
- The focus should be on breaking through complexity by democratizing data access through a single language and providing elements to future-proof the architecture for new capabilities.
- Two key changes to the traditional approach are shifting capital from data management to AI innovation and adopting an agile stepwise approach.
- By optimizing data platforms and adopting decentralized models, organizations can move capital towards cutting-edge generative AI initiatives, transforming their data from a static asset into a dynamic catalyst for innovation.
- Investing in AI is the way to gain a competitive edge and future proof the company, it's not just about having a big idea but also efficiently allocating resources to count.
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Analyticsindiamag
20h
556
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Microsoft Acquires 48 Acres of Lands in Hyderabad for Building Data Centres
- Microsoft has acquired 48 acres of land in Hyderabad, India for building data centres.
- The land was purchased from Sai Balaji Developers and is located approximately 40 km away from Hyderabad's main city.
- Microsoft plans to develop one of the largest data centres in the country as part of its expansion strategy.
- This acquisition complements Microsoft's existing data centre regions in Pune, Mumbai, and Chennai.
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Towards Data Science
20h
129
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Apache Hadoop and Apache Spark for Big Data Analysis
- The article explains the installation of Hadoop Distributed File System, Apache Spark and PySpark on a macOS using Homebrew.
- The author uses the Steam Reviews Dataset 2021 with 21.7 million rows and 23 columns for demonstrating the use of HDFS and analysis of Big Data.
- The author uses PySpark library to access, clean and analyze the dataset to find demography, sentiment analysis and game recommendation.
- The article uses the PySpark show() function to briefly go through the dataset and proceeds to remove the reviews column in the dataset. The column had multiple languages making any sentiment analysis difficult.
- The dataset had 23 variable names presented in a format not acceptable as a Python identifier. The date and time attributes were also in a different data type and had to be changed accordingly.
- The dataset is split into different PySpark data frames to analyze the data from different perspectives.
- The article focuses on understanding review and recommendation patterns for different games. It further shows how to determine popular languages used for review and languages used by reviewers of popular games and to use this trend to determine the demographic influence and sentiments of the players to be used for recommending new games in the future.
- The article details the implementation of the Alternating Least Squares (ALS) machine-learning algorithm from the Spark ML Library to recommend games based on player’s behavior.
- The implemented algorithm identified the game selection pattern for players who play each available game on the Steam App.
- In conclusion, the article successfully implements the installation of Hadoop Distributed File System, Apache Spark and PySpark on a macOS and demonstrates how to analyze a Big Data using PySpark. The Steam Reviews Dataset 2021 is used for demonstrating the use of HDFS and analysis of Big Data.
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Analyticsindiamag
20h
278
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Leading the Way: DuxData’s Data Leadership & Strategy Course Prepares Data Pros for the AI Era
- DuxData is a course designed to equip data professionals with the necessary leadership, strategy, and communication skills to navigate the complexities of modern data science and AI integration within organisations.
- DuxData’s curriculum is designed to enhance practical application through real-world scenarios and case studies.
- The curriculum of DuxData covers topics including intrapreneurial data science, measuring the value of data science initiatives and Stakeholder Analysis & Change Management among others.
- DuxData offers lifetime access to all future topics, resources, and digital downloads/templates to its learners.
- DuxData empowers data professionals to bring meaningful changes within their organisations by focusing on leadership, strategy, and communication skills.
- The curriculum is accompanied by video lectures and digital download templates that can be applied directly to real-world business settings.
- DuxData guides data professionals through the integration of data science into the broader business context and serves as a roadmap for success in the field.
- The course founder believes that the fundamental goal of a data scientist is to be valuable and generate insights and efficiencies for the business.
- DuxData equips data scientists with the foresight that AI or ML may not be the appropriate solution to a problem.
- DuxData’s promo code LAUNCH30 offers a 30% discount until June 24th.
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16 Likes
Medium
20h
208
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Gradient Ascent: My Journey Through AI’s Diverse Landscapes
- This series, 'Gradient Ascent: My Journey Through AI’s Diverse Landscapes' is a map for navigating the terrain of artificial intelligence.
- The author, with a background in tech companies like Microsoft, Google Cloud, and Snowflake, aims to demystify AI and make it accessible for everyone.
- The series is described as a reality show where a business veteran dives into the technical aspects of AI to transform business acumen into AI fluency.
- The author invites readers to engage, critique, suggest, and contribute, making AI integration more intelligent and less artificial.
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