All posts tagged: Embedding

The late Ian Watson’s sci-fi The Embedding is intriguing – but dated

The late Ian Watson’s sci-fi The Embedding is intriguing – but dated

Published by skeptic

The Embedding is a first-contact novel that centres on linguistics Ignatiev/Getty Images The EmbeddingIan Watson, Gollancz The acclaimed British science-fiction writer Ian Watson, author of more than two dozen novels, died this April. His fame may have faded over the decades, but his debut novel The Embedding was greeted with acclaim when it was published in 1973. The Spectator declared it “the most spectacular thing in science fiction since the outstanding Solaris by Stanisław Lem”. Watson’s later work, both sci-fi and fantasy, included novels relating to Warhammer 40,000 games and a stint developing the script of A.I. Artificial Intelligence with Stanley Kubrick. To my embarrassment as a reviewer of sci-fi, I had never heard of Watson until his death and I decided to put that right, starting with his debut, which remains the best-known of his novels. The Embedding is a first-contact story that centres on linguistics. Chris is running an experiment on children in a British research institute. The idea is to see what happens to children if they are brought up speaking an …

how to use RAG and an embedding model to stop wasting context

how to use RAG and an embedding model to stop wasting context

Published by skeptic

Local LLMs are fantastic, and they keep getting better at a staggering pace. I have non-negotiable reasons for preferring a local setup over relying on cloud giants like Claude or ChatGPT. Because of that, I’ve been relentlessly trying to integrate local models into my actual, day-to-day workflow. But as anyone who has tried will tell you, the DIY route comes with distinct caveats and drawbacks. The absolutely biggest hurdle is the context window. To get better responses from an LLM, we need to give it more context. But context is expensive. And as soon as the context window starts to fill up, the model starts to deteriorate in both speed and quality. So what are we supposed to do? The problem, I realized, was not the LLM itself. The problem was that I was using the LLM for a job it was never meant to do. And the fix was a tiny model I had completely ignored. LLMs and the problem of context It really is expensive Raghav Sethi/MakeUseOf Half of our experience with a …

Closing the data security maturity gap: Embedding protection into enterprise workflows

Closing the data security maturity gap: Embedding protection into enterprise workflows

Published by skeptic

Presented by Capital One Data security remains one of the least mature domains in enterprise cybersecurity. According to IBM, 35% of breaches in 2025 involved unmanaged data source or “shadow data.” This reveals a systemic lack of basic data awareness. It’s not because of a lack of tooling or investment. It’s because many organizations still struggle with the most fundamental questions: What data do we have? Where does it live? How does it move? And who is responsible for it? In an increasingly complex ecosystem of data sources, cloud platforms, SaaS applications, APIs, and AI models, those questions are only becoming more difficult to answer. Closing the maturity gap in data security demands a cultural shift where security is no longer treated as an afterthought. Instead, protection is embedded throughout the full data lifecycle, grounded in a robust inventory, clear classification, and scalable mechanisms that translate policy into automated guardrails. Visibility as the foundation The most persistent barrier to data security maturity is basic visibility. Organizations often focus on how much data they hold, but …

Google’s Gemini Embedding 2 arrives with native multimodal support to cut costs and speed up your enterprise data stack

Google’s Gemini Embedding 2 arrives with native multimodal support to cut costs and speed up your enterprise data stack

Published by skeptic

Yesterday amid a flurry of enterprise AI product updates, Google announced arguably its most significant one for enterprise customers: the public preview availability of Gemini Embedding 2, its new embeddings model — a significant evolution in how machines represent and retrieve information across different media types. While previous embedding models were largely restricted to text, this new model natively integrates text, images, video, audio, and documents into a single numerical space — reducing latency by as much as 70% for some customers and reducing total cost for enterprises who use AI models powered by their own data to complete business tasks. VentureBeat collaborator Sam Witteveen, co-founder of AI and ML training company Red Dragon AI, received early access to Gemini Embedding 2 and published a video of his impressions on YouTube. Watch it below: Who needs and uses an embedding model? For those who have encountered the term “embeddings” in AI discussions but find it abstract, a useful analogy is that of a universal library. In a traditional library, books are organized by metadata: author, …

Embedding human-centred values into robotics

Embedding human-centred values into robotics

Published by skeptic

Dr Farshad Badie, Dean of the Faculty of Computer Science and Informatics, Berlin School of Business and Innovation, explores how AI and robotics can incorporate human-centred values to complement our experiences. When I think about the rapid advances in artificial intelligence (AI) and robotics, I am both excited and cautious. In my opinion, these technologies (and, in fact, systems) have significant potential to reshape all industries and improve our daily lives. But along with such a promise comes a challenge: How do we ensure these systems serve us in ways that are truly meaningful? How can we design robots that not only perform tasks but also respect and reflect human beings’ (as well as societies’) values, feelings, and diverse cultural contexts? Why human-centred values matter in robotics I see responsible AI development in robotics as being grounded in human-centric principles, including empathy, inclusivity, cultural awareness, and design driven by a clear purpose, integrated at every step. Actually, it’s not enough to create robots that are technically functional or efficient. The designed robots need to be …