Alan Morrison

San Jose

Contributor at Data Science Central

Technology Editor, Researcher and Writer at Freelance

Data tech strategy advisor and writer.

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Articles

How do AI chatbots compare to human educators?

4 weeks ago | datasciencecentral.com | Zachary Amos |Manoj Kumar |Alan Morrison |Dan Wilson

AI chatbots seem to grow more advanced with each passing month. The idea of a computer handling ordinary tasks sounds great, but how do AI chatbots compare to human educators? Understanding the strengths and weaknesses of people versus machines in education allows administrators to make more informed decisions about when to invest in equipment and what areas today’s teachers excel in that robots likely never will.
Re-rankers maximize vector database retrieval results

1 month ago | datasciencecentral.com | Jelani Harper |Dan Wilson |Alan Morrison

There’s a really good reason almost every credible vector database—or enterprise application of this technology—incorporates re-ranking models, or re-rankers. It’s not just because these deep neural networks score vector retrieval engines’ results so they’re more useful for search and Retrieval Augmentation Generation (RAG). Quite simply, it’s because for most vector database use cases, no one has actually fine-tuned the embedding model on an organization’s specific, or proprietary, data.
Contemporary applications of ChatGPT

1 month ago | datasciencecentral.com | Jelani Harper |Bill Schmarzo |Alan Morrison

Not so long ago, ChatGPT almost single-handedly broadened the adoption rates and general awareness of LLMs. Shortly thereafter, everyone from enterprise users to consumers were clamoring to avail themselves of its capacity to answer questions and generate human-like textual responses about virtually any subject.
Best practices for vector database implementations: Mastering chunking strategy

2 months ago | datasciencecentral.com | Jelani Harper |Dan Wilson |Alan Morrison

Although numerous vendors gloss over this fact, there’s much more to reaping the enterprise benefits of generative AI than implementing a vector database. Organizations must also select a model for generating their vector embeddings; shrewd users will take the time to fine-tune or train that model.
Python vs R for data science: Which should you choose?

2 months ago | datasciencecentral.com | Scott Thompson |Bill Schmarzo |Alan Morrison

Welcome to another comparison article where you will understand the features, intricacies, pros, and cons of two different stacks of the information technology industry. Today’s comparison blog is especially for data scientists who spend their day and night with datasets, insights, trends, and analysis of many other factors. From a long list of skills that data scientists and analysts must master, one is the programming language.
Transformational Power of Marginal Propensity to Reuse Undermined by Siren of One-off AI Projects

2 months ago | datasciencecentral.com | Bill Schmarzo |Alan Morrison |J. Rusnak

In the world of physical assets, the more something is used, the more it depreciates—it wears out, loses value, and eventually needs to be replaced. But in the digital economy, the opposite is true. Welcome to the Marginal Propensity to Reuse (MPR).
Data strategy for sustainable ESG compliance

2 months ago | datasciencecentral.com | Rob Turner |Bill Schmarzo |Alan Morrison

Image: pexelsBusinesses face mounting pressure to meet ESG, i.e. Environmental, Social, and Governance expectations. Compliance is no longer optional. It shapes reputations, investor trust, and long-term growth. How do data strategies fit in? They provide a backbone for tracking progress while ensuring companies align with legal and ethical benchmarks. This article unpacks how data analytics drives actionable insights.
How long until quantum computing is a real data security risk?

Jan 24, 2025 | datasciencecentral.com | Zachary Amos |Julian Durand |Alan Morrison

Quantum computing could do a lot of good for the world, but it also raises serious security concerns. Any technology that powerful could cause significant damage if cybercriminals get ahold of it, so cybersecurity professionals must prepare for a post-quantum future. But how much time do they have? The United Nations has labeled 2025 the Year of Quantum Science and Technology, reflecting the growing importance of understanding this field.
Using AI to Solve the Deepest Math Conjectures

Jan 22, 2025 | datasciencecentral.com | Vincent Granville |John Lee |Alan Morrison

Tools such as OpenAI can on occasion give the impression that they are able to prove theorems and even generalize them. Whether this is a sign of real (artificial) intelligence or simply combining facts retrieved from technical papers and put things together without advanced logic, is irrelevant. A correct proof is a correct proof, no matter how the author – a human or a bot – came to it. My experience is that tools like OpenAI make subtle mistakes, sometimes hard to detect.
Big AI: Cloud infrastructure dependence and the industrialization of AI

Jan 21, 2025 | datasciencecentral.com | John Lee |Alan Morrison |Zachary Amos

The ‘cloud AI wars’ at major technology companies are intensifying (Goldman, 2022). Industry leaders say AI is transforming society. AI’s foundational and transformative nature is emphasised by Bill Gates (2023) and Alphabet’s Sundar Pichai (2023). Amazon, Microsoft, and Google are allegedly driving this transformation. Cloud computing has created the socio-technical infrastructure for expansive growth and platform capitalism, enabling their ‘hyper-scalability’ (Narayan, 2022).