Plutonic Rainbows

DeepSeek, a rising player in AI development, has unveiled a groundbreaking model that is shaking up Silicon Valley. The technology, which reportedly offers unparalleled capabilities in data synthesis and predictive analytics, has left competitors both impressed and unnerved. Its potential to reshape industries such as finance, healthcare, and defence has prompted admiration for its ingenuity but also concerns about ethical implications and regulatory oversight. Executives across the tech world are grappling with the model’s impact, particularly as its proprietary nature raises questions about transparency and the monopolisation of AI advancements.

While DeepSeek’s innovation is lauded as a step forward for AI, it has also triggered debates about fair competition and accountability. Critics warn that the model’s dominance could stifle smaller players and concentrate power in fewer hands. This announcement comes amid growing calls for AI governance to prevent misuse and ensure responsible development. As the industry scrambles to catch up, DeepSeek’s disruptive unveiling is a reminder of the double-edged sword of rapid technological progress.

DeepSeek, a Chinese start-up, has developed a free large language model called R1 that matches the performance of leading AI models such as those from OpenAI. Its rapid growth and immediate popularity, alongside a low development cost of around $5.6 million, has unsettled both investors and major US tech firms. DeepSeek’s innovative training methods and the programme’s open-source nature are especially significant given the US ban on exporting powerful computer chips to China.

Markets have reacted by selling off shares in large US technology companies that have been investing heavily in data centres to train and deploy AI. Investors are now questioning whether expensive cloud computing and vast hardware reserves are truly necessary, given DeepSeek’s demonstration of a more cost-efficient approach. Tech leaders like Microsoft’s Satya Nadella have acknowledged the impact of DeepSeek’s model and are urging serious consideration of China’s progress in AI research.

DeepSeek’s decision to release R1 as open source has been lauded as a “profound gift” but also raises concerns over potential misuse by malicious parties. Some Western developers may be wary of Chinese censorship controls embedded within the code, while others see this move as evidence of China’s resilience in circumventing US chip restrictions. Influential figures like Marc Andreessen have likened the development to a “Sputnik moment,” prompting calls for greater US investment and strategic planning to maintain a competitive edge in the global AI race.

I haven’t watched this Brian De Palma film in years. Blow Out opened to scant audience interest upon its release, despite earning predominantly positive notices from critics. Travolta and Allen’s lead performances, De Palma’s direction, and the film’s visual style were praised as its strongest points. However, it ultimately fared poorly at the box office, largely due to negative word of mouth surrounding its bleak ending.

For the past few months, I simply haven’t been able to get this fragrance out of my mind, so I was delighted when a small sample finally arrived from the States. I’d been eagerly awaiting its arrival, especially as this brand has only released a handful of products over the last ten years.

On my first try, I detect a hint of liquorice, which is really quite lovely. I’ll need to explore it further, though I’m not yet certain about its longevity or strength.

Update (26 January 2025): I have tried this fragrance again today and must note that it smells remarkably similar to Dior’s New Look. This new impression comes from a more detailed testing session, where its distinctive floral nuances and elegant sillage echoed the Dior creation’s signature blend.

My new book arrived today: Prompt Engineering for Generative AI, a new publication focusing on the application of large language models (LLMs) and diffusion models. I do think O’Reilly books are overpriced, but they do offer publications on very specialised topics.

I added some React animations to an app I am working on. It looks completely different to how I was originally using it. Last year, I was basically sending all my json requests via the terminal.

I also added a simple React animation to this site. The title should now sweep into view.

I couldn’t get out to exercise today because it was raining on and off, so I spent many hours working on prompting templates for Flux. I finally managed to send my fleece off for repairs. It’s still a brilliant piece of winter clothing, so letting a few rusty zips stop me from using it seemed rather wasteful.

Inspired by Walpole Bay; seaweed, white flowers and salt water collected on 25th March 2014, (sunny day).

Reminiscent of an uninhabited bay; man-made structures that bridge land and sea and a crisp fragrance of salt, sweet pea and musk.

In the next five years, the landscape of AI-related jobs will evolve significantly as artificial intelligence becomes more deeply integrated into industries. Traditional roles in IT and data science will increasingly focus on AI-specific tasks, such as training, fine-tuning, and managing machine learning models. Positions like AI Ethics Officers and AI Compliance Specialists will emerge to address ethical concerns and ensure regulatory compliance in AI development and deployment. Additionally, roles such as Prompt Engineers will become more prominent, focusing on crafting precise instructions to guide generative AI systems. As businesses strive to leverage AI responsibly and effectively, demand for professionals skilled in interdisciplinary collaboration—bridging AI technology with areas like healthcare, finance, and education—will grow.

Creative and design roles will also transform as AI takes on more of the heavy lifting in content creation. Positions like AI-Assisted Creators or AI Content Curators will focus on guiding and enhancing AI-generated outputs rather than starting from scratch. Similarly, technical roles like AI Maintenance Specialists will focus on troubleshooting and optimising AI systems in real-time. New jobs like Synthetic Data Engineers will become crucial for generating high-quality data to train AI systems while maintaining privacy. Overall, there will be a significant shift towards roles that combine technical expertise with creativity, critical thinking, and ethical considerations to ensure AI is deployed to its fullest potential while mitigating risks.

Recent breakthroughs in AI have not only increased demand for AI products, they've also lowered the barriers to entry for those who want to build AI products. The model-as-a-service approach has transformed AI from an esoteric discipline into a powerful development tool that anyone can use. Everyone, including those with minimal or no prior AI experience, can now leverage AI models to build applications. In this book, author Chip Huyen discusses AI engineering: the process of building applications with readily available foundation models.

The book starts with an overview of AI engineering, explaining how it differs from traditional ML engineering and discussing the new AI stack. The more AI is used, the more opportunities there are for catastrophic failures, and therefore, the more important evaluation becomes. This book discusses different approaches to evaluating open-ended models, including the rapidly growing AI-as-a-judge approach.

AI application developers will discover how to navigate the AI landscape, including models, datasets, evaluation benchmarks, and the seemingly infinite number of use cases and application patterns. You'll learn a framework for developing an AI application, starting with simple techniques and progressing toward more sophisticated methods, and discover how to efficiently deploy these applications.