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At some point between 2013 and 2015, I argue that we entered the Exponential Age. It is a new period of human affairs catalysed by accelerating technologies in four broad domains: computing, energy, biology and manufacturing.
Azheem Azhar, 7 September 2021
We are walking into a nexus of network adoption effects, at scale of which humanity has never seen before, of numerous technologies.
Raoul Pal in discussion with Nathaniel White 25 April 2023
Being a Large Language Model neural net, ChatGPT cannot by itself do non-trivial computations nor be relied upon to produce correct data. Recent months, however, have seen ChatGPT being linked with Wolfram|Alpha and the Wolfram Language to give it a powerful computational capability. In his blog post ChatGPT Gets Its “Wolfram Superpowers”!, Stephen Wolfram uses some examples to explain the current scope of this combined capability and to hint at the revolutionary power of its future potential.
Steve Blank’s blog post Playing With Fire – ChatGPT looks at that combined capability from another perspective. He highlights that not only is ChatGPT good at what is was designed to do but that it is demonstrating emergent behaviours (things it was not designed to do) which were not seen in its smaller-scale predecessors. He points out, also, that ChatGPT is beginning to interact with a variety of other applications through an application programming interface. These applications can be used by ChatGPT to enhace its own capabilities. Conversely, the applications can harness ChatGPT’s capabilities for their separate, third-party purposes. These increasingly complex systems will display emergent properties, ie properties that the individual parts of the system do not have on their own but which emerge when the parts interact as a whole. Some of the emergent properties will occur by design, but it is inevitable that there will be some which cannot be predicted.
We are still some way from artificial general intelligence, but that is the direction of travel and we should be concerned that the continued development of this technology is driven by for-profit companies, venture capitalists and autocratic governments without any means of control.
ChatGPT can respond to a question presented to it in natural language and is proving to be good at producing a human-like answer. But the answer is not always correct, and this is especially the case when the question involves quantitative data. In this respect ChatGPT is similar to most humans: we find it easy to write an essay but struggle to include correct facts and figures about the subject where these require us to do complicated calculations. Give us a pocket calculator, however, and we can do very much better. Is there a pocket calculator that ChatGPT could use?
Stephen Wolfram believes there is. In Wolfram|Alpha as the Way to Bring Computational Knowledge Superpowers to ChatGPT, he explains that Wolfram|Alpha is able to accept questions in natural language which it then converts into “precise, symbolic computational language [the Wolfram Language] on which it can apply its computational knowledge power” and then produce an answer in natural language. In other words, because ChatGPT communicates using natural language it is in principle able to use Wolfram|Alpha as its pocket calculator.
A possible next step, which Stephen Wolfram says has already started, is for ChatGPT to learn how to use Wolfram Language directly in the same way that humans do. This could enable ChatGPT to produce computational essays which bring together three elements: text to describe context and motivation; computer input in Wolfram Language for a precise specification of what is being talked about; and computer output for facts and results, often in graphical form. A key point here is that the Wolfram Language enables each piece of computer input to be short, not more than a line or two, and to be understandable both by the computer and by a human reading the essay.
Thomas Rid is Professor of Strategic Studies at and a founding director of the Alperovitch Institute for Cybersecurity Studies at Johns Hopkins University School of Advanced International Studies, Washington DC. Recently, he spent five days as a student in a class studying Malware Analysis and Reverse Engineering. The chat.openai.com/chat/-tab was open on most student machines at all times during the course, and they used it in real time to enhance their learning. Formerly “a hardened skeptic of the artificial intelligence hype“, Professor Rid is now convinced that it will transform higher education.
The class saw that ChatGPT had limitations. “To scale it in the classroom we need to better understand its strengths and weaknesses …. It will hallucinate. It will make mistakes. It will perform more poorly the closer you move to the edge of human knowledge. It appears to be weak on some technical questions.” But Rid wrote that “[by] Saturday evening it felt like we had a new superpower“. Rather than talk about plagiarism and cheating, he urges us to engage in a more inspiring conversation: how can artificial intelligence enable the most creative, ambitious and brilliant students – helped by educators – to “push out the edge of human knowledge through cutting-edge research faster and in new ways“?
In his podcast A Skeptical Take on the A.I. Revolution Ezra Klein talks with Gary Marcus, emeritus professor of psychology and neural science at New York University. Marcus argues that although ChatGPT seems to produce impressive results, in fact it generates a pastiche of true and false information which it is unable to distinguish between. So, is it not to be trusted?
Some commentators such as New York Times tech columnist Kevin Roose are suggesting that ChatGPT could have value as a “teaching aid …. [which] could unlock student creativity, offer personalized tutoring, and better prepare students to work alongside A.I. systems as adults”. James Pethokoukis takes it further, seeing an upside in “the ability of such language models to aid academic research as a sort of “super research assistant” .
That aspect of ChatGPT is the subject of new research from finance professors Michael Dowling (Dublin City University) and Brian Lucie (Trinity College Dublin). In their paper ChatGPT for (Finance) Research: The Bananarama Conjecture, Dowling and Lucie report how ChatGPT’s output can be made impressively good by using domain experts to guide what it does. That opens up the possibility of using ChatGPT as an e-ResearchAssistant and of it becoming an everyday tool for researchers. It also, of course, opens up debate about authorship and copyright of papers co-authored with ChatGPT.
Being electrical engineers by background, we in Anapoly are keen supporters of the work Plymouth Energy Community is doing and we have been shareholders in PEC for some years. Although they are not PEC initiatives, our colleague Ray Holland is closely involved with community solar farms in the South Hams.
PEC is looking for rooftop sites to install solar PV:
https://plymouthenergycommunity.com/business/energy-installation
Anapoly’s office is in Skardon Place – a cul de sac off North Hill. In addition to our office there are 15 homes in Skardon Place, and there is a strong community spirit. It occurs to us that it might be possible to set up a community scheme to take up the offer of free renewable energy installation. I have contacted them to explore the possibility.
A persuasively argued essay by Scott Ludlum about the global struggle for our digital rights, published May 2019 in Griffith Review 64: The New Disruptors . Scott is a former Australian politician representing the Australian Greens. He served as a senator from Western Australia from 2008 to 2017, and as co-deputy leader of his party from 2015 to 2017. He is currently a columnist for The Guardian.
Wikipedia describes Sam Harris as “an American neuroscientist, philosopher, author, critic of religion, blogger, public intellectual, and podcast host“. In his Making Sense podcasts he converses with a wide range of people whose experiences, thinking and analysis of what is happening in the world today have much to offer us.
A recent conversation with Renée DiResta explored the methods used by Russia to influence society in the United States. She gives a very clear explanation of how these are made possible by the way social media have developed and discusses the main lines of attack, which are to increase the polarisation that already exists in society and to amplify conspiracy thinking.
Two conversations by Kara Swisher, recently published on her podcast recode decode, offer thought provoking insights to surveillance capitalism and what we can do to counter it.
One is with Roger McNamee, venture capitalist, erstwhile mentor to Mark Zuckerberg and early investor in Facebook. He is now speaking out against the social media platform and has written a book with the title Zucked: waking up to the Facebook catastrophe.
The other conversation is with Nuala O’Connor, CEO of the Center for Democracy and Technology, around the question ‘Can big tech be fixed?’ Her organisation is headquartered in Washington, with an international presence in Brussels; it supports laws, corporate policies and technology tools to protect the privacy of internet users, and advocates for stronger legal controls on government surveillance.
On her website, the Harvard professor Shoshana Zubhoff says: “I’ve dedicated this part of my life to understanding and conceptualising the transition to an information civilization“. Her latest book is ‘The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power’ . It draws together four themes to argue that we have allowed the global technology companies – notably Google and Facebook – to become dangerously out of control. Her themes are the historical emergence of psychological individuality, the conditions for human development, the digital revolution and the evolution of capitalism. In Start the Week on 4 February, Andrew Marr explored these ideas with her.
Continue reading “Surveillance capitalism”