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How to Use AI for Predictive Analytics and Smarter Decision Making

AI for predictive analytics represents a cutting-edge approach to forecasting future trends and making data-driven decisions with precision. By integrating AI, you can uncover deep insights, identify emerging opportunities, and mitigate potential risks in real-time. In this article, you’ll...

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Practical ETL Strategies to Refine AI Models and Decision Making

Extract, Transform, and Load, or ETL, is a crucial data management process, especially in the AI and machine learning space. It’s like a data-moving team that takes information from various sources, cleans it up, and organizes it neatly in one place. This process is vital for businesses and...

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The AI Weekly Breakthrough Newsletter Edition #5 - April 9, 2024. Midjourney depiction of a robot in chains.

Many-Shot Jailbreaking, More AI Agents, Contemplating Paid Search …

The AI Weekly Breakthrough | Issue 5 | April 9, 2024 Welcome to The AI Weekly Breakthrough, a roundup of the news, technologies, and companies changing the way we work and live. More Agents Is All You Need A study using a simple sampling-and-voting method showed that LLM performance scales with...

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Building Smarter AI with Data Augmentation

Data augmentation is a pivotal technique in the realm of Natural Language Processing (NLP). It’s used to expand and diversify training datasets, thereby enhancing the performance and robustness of AI models. This technique is crucial for AI practitioners, data scientists, and technologists who aim...

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Masterclass in AI: Leveraging Foundation Models for Success

Foundation models are a cornerstone in how we approach, develop, and implement AI technologies. These models, with their ability to learn from vast datasets and adapt to a multitude of tasks, represent a significant leap in AI’s evolution. Whether you’re an IT professional looking to deepen...

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Decipher Ambiguity in NLPs for Sharper AI Intelligence

Navigating the multifaceted nature of human language is a unique challenge for machines. Ambiguous words, phrases, sentences, and contexts make language models struggle to understand and interpret human language with nuance and precision. Addressing ambiguity, therefore, is crucial for modern...

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Augmented Shelf AI Newsletter Edition Midjourney depiction of Robot reading a newspaper

Street Fighting LLMs, AI’s Spending Dilemma, Stargate 2028 …

Augmented Shelf | Issue 4 | April 3, 2024 Welcome to Augmented Shelf, a wrap-up of the week’s AI news, trends and research that are forging the future of work. Street Fighting LLMs Ready for a digital brawl like no other? In a groundbreaking experiment, cutting-edge Language Models (LLMs)...

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Why Recurrent Neural Networks (RNNs) Dominate Sequential Data Analysis

Recurrent Neural Networks (RNNs) are a class of artificial neural networks uniquely designed to handle sequential data. At its core, an RNN is like having a memory that captures information from what it has previously seen. This makes it exceptionally suited for tasks where the order and context...

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Contemplative AI, (In)Stability AI, AI Antibodies, and More

Augmented Shelf | Issue 3 | March 26, 2024 Welcome to Augmented Shelf, a wrap-up of the week’s AI news, trends and research that are forging the future of work. Enterprises Quintuple-Down on GenAI in 2024 New research from a16z punctuates the enterprise sector’s growing bet on...

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Data Mesh or Data Fabric? Choosing the Right Data Architecture

Data mesh and data fabric are two architectural paradigms that are shaping the future of data management and analytics. At their core, both aim to address the complexities of handling vast and diverse data in modern organizations, but they approach the challenge from different angles. In this...

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Evil Geniuses Attack, The LLM Forgettery, Character Consistency and More

Augmented Shelf | Issue 2 | March 19, 2024 Welcome to Augmented Shelf, a wrap-up of the week’s AI news, trends and research that are forging the future of work. Evil Geniuses Vs. ChatDev To evaluate the vulnerability of LLM-based agents, researchers at Tsinghua University in Beijing, China, have...

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Forget LLM Memory – Why LLMs Need Adaptive Forgetting

Large Language Models (LLMs) rely on extensive memory to store and manipulate vast datasets, a key factor that allows them to learn from past inputs and improve their linguistic abilities over time. But what if, alongside remembering, LLMs could also benefit from adaptive forgetting? The notion of...

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