Generative AI and the Importance of Original Thought
Alex Papli Alex Papli

Generative AI and the Importance of Original Thought

Explore the limitations of generative AI and the crucial role of original thought in today’s fast-changing business landscape, emphasizing the integration of humanities and STEM education for fostering creativity and ethical innovation.

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MYOB Report: Data & AI Innovation in the ANZ Mid-Market
Alex Papli Alex Papli

MYOB Report: Data & AI Innovation in the ANZ Mid-Market

Discover how mid-market businesses in Australia and New Zealand are harnessing the power of data and AI to fuel growth and innovation. Our comprehensive review of the November MYOB Mid Market report reveals optimism and a keen investment focus in cutting-edge technologies. Learn practical recommendations to boost productivity, enhance user experience, and automate processes with generative AI and modular solutions. Stay ahead with actionable insights on uplifting data estates, leveraging AI-enhanced workflows, and transforming customer interactions.

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Five great AI use cases I’ve seen
Alex Papli Alex Papli

Five great AI use cases I’ve seen

Generative AI is creating a buzz with its diverse applications beyond traditional chatbots, offering significant benefits across various business operations. Here are 5 interesting use cases I wanted to share with you.

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My take on Mckinsey’s Generative AI report
Alex Papli Alex Papli

My take on Mckinsey’s Generative AI report

Explore the economic potential of generative AI identified in by McKinsey's latest report. Learn how generative AI could add $2.6 trillion to $4.4 trillion to the global economy and reshape industries like banking and marketing. Discover the importance of skills in managing unstructured data and human-AI collaboration, plus key strategies for organizations to harness AI effectively. Join the conversation on navigating this transformative frontier!

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Time Series Analysis: Does TimeGEN-1 challenge the traditional ML approach?
Alex Papli Alex Papli

Time Series Analysis: Does TimeGEN-1 challenge the traditional ML approach?

I explore TimeGPT, a groundbreaking large language model (LLM) designed specifically for time series analysis. Developed by Nixtia, TimeGPT aims to simplify forecasting and anomaly detection, leveraging over 100 billion data points from diverse fields like finance and healthcare. Its key features include zero-shot inference, allowing users to generate predictions on unseen datasets without additional training, and the option for fine-tuning on specific datasets for enhanced accuracy.

TimeGPT's user-friendly design, accessible via a Python SDK or REST API, enables rapid predictions, achieving impressive speeds while outperforming traditional models like ARIMA and XGBoost in accuracy. Although I'm not entirely convinced it can replace well-trained machine learning solutions, TimeGPT presents a promising option for hypothesis validation and low-risk use cases, offering a maintenance-free approach to time series forecasting. Dive into the article to discover how this innovative tool could reshape the landscape of time series analysis!

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AI for good: 3 uplifting videos to brighten your day
Alex Papli Alex Papli

AI for good: 3 uplifting videos to brighten your day

Watch three uplifting videos that showcase the positive impact of AI on people's lives:

1. The Met & OpenAI: Witness how AI breathes life into history by allowing visitors to interact with 1930s socialite Natalie Potter through a custom ChatGPT experience.

2. EdChat: Discover an AI tool from the South Australian Department of Education that personalizes learning for students and reduces teacher workloads.

3. Jugalbandi Chatbot: See how Microsoft’s chatbot bridges linguistic gaps in rural India, providing access to vital government information and services.

These examples highlight the transformative potential of AI for good. Dive into the full article to learn more!

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Finding a good partner to build your next generative AI project
Alex Papli Alex Papli

Finding a good partner to build your next generative AI project

When selecting a vendor for a generative AI project, it's crucial to focus on key areas and ask targeted questions to ensure the firm aligns with your business goals and possesses the necessary skills. Important considerations include balancing data science with app development skills, understanding the development stages, and ensuring effective prompt training and testing. Additionally, evaluating model cost and performance, solution architecture, and the decision between low code and full code solutions are essential, along with strategies for improving and testing chatbots, updating search indexes, and managing permissions.

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Microsoft Fabric for Small Business: Do You Need It?
Alex Papli Alex Papli

Microsoft Fabric for Small Business: Do You Need It?

Is Microsoft Fabric Right for Your Small Business? Explore how Microsoft Fabric can simplify data management and analytics for small businesses by integrating tools like Power BI and Azure. Learn about its key features, benefits, and how it compares to traditional setups to see if it's the right fit for your company's needs.

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Focus on search: Set your Generative AI projects up for success
Alex Papli Alex Papli

Focus on search: Set your Generative AI projects up for success

Discover how to optimize your AI application by implementing a robust search mechanism that ensures the retrieval of the most relevant information. This guide covers the four key stages of building an effective search pipeline, explores various indexing and search strategies, and provides best practices for enhancing search quality and performance.

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