Skip to main content

About this Blog, why?

 Introduction and Welcome

I began writing this blog on the April 8th, 2003. I say that, but it's inaccurate. What I did, in fact was start a series of 'prompts' in ChatGPT via the Edge Browser to generate text, also  in Dall-E image creator to formulate the graphics. I only began my own content the day after, here. The examples of Tools I've used and Speculations about how certain tasks will change is far from exclusive. For instance I will not comment on the medical implications of AI, though fascinating (as GPT4 has passed medical exams - without taking a hypocritic oath) but instead confine myself to tasks I have had to undertake in my recent work career.

So welcome, this is a simple blog that aims to document the next 6 months of some of the AI occurrences, tools, news and opinions to document:
  1. Will the legislators respond to the call for a 6 month halt to a ChatGPT5 occur?
  2. Given the unprecedented speed of development, just 4 months ago ChatGPT could only muster a 40% pass rate at a bar exam and now it is passing at a 90% rate, what will happen in this next crucial time period.
There was a time, at the beginning of the 1980's and throughout the 1990's where I could, with a fair amount of accuracy, predict the development of IT, as it was then known, out to an 18 month or so period into the future. This gap became increasingly smaller circa 1997. I have still retained an interest, primarily as a user and low level developer of communication technologies. I write simple code for websites, CRM's and DAMs and customise them to suit a purpose. I began with code for typesetting in the late 1970's. 

All of this may seem that my views are perhaps archaic, the fact is that if people haven't studied what's happened last week, their views too are soon to be archaic. Where it once took 6 -18 months for major breakthroughs in technological applications to occur, it is now weeks, and very soon it will be counted in days, such is the transformative growth we are witnessing. 

So, I aim to complete this blog in October. I have no idea how much time I can spend upon it yet, but I do hope that the content I begin with will provide some utility.

Update June 2024.

I have started the blog once more, to cover some of the more interesting tools, perhaps describe my own experiences in setting up Open Source tools (like Llama in a Rag environment) and to use as a sounding out board as I've gone about AI policy developments. What I realised during the initial burst of blog writing is that if the tech evangelists are right - despite my many doubts - and we are seeing a transformative technology, then our governance responses are vital. This is the area I have a considerable amount of experience in, therefore this is the area I'm directing my energies. 

Just a quick note: I'm continuing to use the (appalling) AI generated 'art' for the articles, they are a part of the aesthetic. Even if the tech improves I want these bad images, reminds me of my early days with 8 bit graphics.

Comments

Post a Comment

Popular posts from this blog

The Whispers in the Machine: Why Prompt Injection Remains a Persistent Threat to LLMs

 Large Language Models (LLMs) are rapidly transforming how we interact with technology, offering incredible potential for tasks ranging from content creation to complex analysis. However, as these powerful tools become more integrated into our lives, so too do the novel security challenges they present. Among these, prompt injection attacks stand out as a particularly persistent and evolving threat. These attacks, as one recent paper (Safety at Scale: A Comprehensive Survey of Large Model Safety https://arxiv.org/abs/2502.05206) highlights, involve subtly manipulating LLMs to deviate from their intended purpose, and the methods are becoming increasingly sophisticated. At its core, a prompt injection attack involves embedding a malicious instruction within an otherwise normal request, tricking the LLM into producing unintended – and potentially harmful – outputs. Think of it as slipping a secret, contradictory instruction into a seemingly harmless conversation. What makes prompt inj...
Post a Comment
Read more

Can We Build a Safe Superintelligence? Safe Superintelligence Inc. Raises Intriguing Questions

  Safe Superintelligence Inc . (SSI) has burst onto the scene with a bold mission: to create the world's first safe superintelligence (SSI). Their (Ilya Sutskever, Daniel Gross, Daniel Levy) ambition is undeniable, but before we all sign up to join their "cracked team," let's delve deeper into the potential issues with their approach. One of the most critical questions is defining "safe" superintelligence. What values would guide this powerful AI? How can we ensure it aligns with the complex and often contradictory desires of humanity?  After all, "safe" for one person might mean environmental protection, while another might prioritise economic growth, even if it harms the environment.  Finding universal values that a superintelligence could adhere to is a significant hurdle that SSI hasn't fully addressed. Another potential pitfall lies in SSI's desire to rapidly advance capabilities while prioritising safety.  Imagine a Formula One car wi...
Post a Comment
Read more

The Hidden Environmental Cost of AI: Data Centres' Surging Energy and Water Consumption

 In recent years, artificial intelligence (AI) has become an integral part of our daily lives, powering everything from smart assistants to complex data analysis. However, as AI technologies continue to advance and proliferate, a concerning trend has emerged: the rapidly increasing energy and water consumption of data centres that support these systems. The Power Hunger of AI According to the International Energy Agency (IEA), global data centre electricity demand is projected to more than double between 2022 and 2026, largely due to the growth of AI. In 2022, data centres consumed approximately 460 terawatt-hours (TWh) globally, and this figure is expected to exceed 1,000 TWh by 2026. To put this into perspective, that's equivalent to the entire electricity consumption of Japan. The energy intensity of AI-related queries is particularly striking. While a typical Google search uses about 0.3 watt-hours (Wh), a query using ChatGPT requires around 2.9 Wh - nearly ten times more en...
Post a Comment
Read more