- Excerpt from "The Dawn of Everything"
If, as many are suggesting, our species’ future now hinges on our capacity to create something different (say, a system in which wealth cannot be freely transformed into power, or where some people are not told their needs are unimportant, or that their lives have no intrinsic worth), then what ultimately matters is whether we can rediscover the freedoms that make us human in the first place. As long ago as 1936, the prehistorian V. Gordon Childe wrote a book called Man Makes Himself. Apart from the sexist language, this is the spirit we wish to invoke. We are projects of collective self-creation. What if we approached human history that way? What if we treat people, from the beginning, as imaginative, intelligent, playful creatures who deserve to be understood as such? What if, instead of telling a story about how our species fell from some idyllic state of equality, we ask how we came to be trapped in such tight conceptual shackles that we can no longer even imagine the possibility of reinventing ourselves?
- ChatGPT is bullshit - Michael Townsen Hicks, James Humphries, Joe Slater
Investors, policymakers, and members of the general public make decisions on how to treat these machines and how to react to them based not on a deep technical understanding of how they work, but on the often metaphorical way in which their abilities and function are communicated. Calling their mistakes ‘hallucinations’ isn’t harmless: it lends itself to the confusion that the machines are in some way misperceiving but are nonetheless trying to convey something that they believe or have perceived. This, as we’ve argued, is the wrong metaphor. The machines are not trying to communicate something they believe or perceive. Their inaccuracy is not due to misperception or hallucination. As we have pointed out, they are not trying to convey information at all. They are bullshitting.
Calling chatbot inaccuracies ‘hallucinations’ feeds in to overblown hype about their abilities among technology cheerleaders, and could lead to unnecessary consternation among the general public. It also suggests solutions to the inaccuracy problems which might not work, and could lead to misguided efforts at AI alignment amongst specialists. It can also lead to the wrong attitude towards the machine when it gets things right: the inaccuracies show that it is bullshitting, even when it’s right. Calling these inaccuracies ‘bullshit’ rather than ‘hallucinations’ isn’t just more accurate (as we’ve argued); it’s good science and technology communication in an area that sorely needs it.
- The GenAI Divide - State of AI in Business 2025 (via archive.org) - MIT NANDA
Despite $30–40 billion in enterprise investment into GenAI, this report uncovers a surprising result in that 95% of organizations are getting zero return. The outcomes are so starkly divided across both buyers (enterprises, mid-market, SMBs) and builders (startups, vendors, consultancies) that we call it the GenAI Divide. Just 5% of integrated AI pilots are extracting millions in value, while the vast majority remain stuck with no measurable P&L impact. This divide does not seem to be driven by model quality or regulation, but seems to be determined by approach.
Tools like ChatGPT and Copilot are widely adopted. Over 80 percent of organizations have explored or piloted them, and nearly 40 percent report deployment. But these tools primarily enhance individual productivity, not P&L performance. Meanwhile, enterprisegrade systems, custom or vendor-sold, are being quietly rejected. Sixty percent of organizations evaluated such tools, but only 20 percent reached pilot stage and just 5 percent reached production. Most fail due to brittle workflows, lack of contextual learning, and misalignment with day-to-day operations.
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The core barrier to scaling is not infrastructure, regulation, or talent. It is learning. Most GenAI systems do not retain feedback, adapt to context, or improve over time.
- The Many Flavors of Ignore Files - Andrew Nesbit
Every tool wants to be git until it has to implement git’s edge cases.
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Excerpt from "The Dawn of Everything"
Nonetheless, on those occasions when people do reflect on the lessons of prehistory, they almost invariably come back to questions of this kind. We are all familiar with the Christian answer: people once lived in a state of innocence, yet were tainted by original sin. We desired to be godlike and have been punished for it; now we live in a fallen state while hoping for future redemption. Today, the popular version of this story is typically some updated variation on Jean-Jacques Rousseau’s Discourse on the Origin and the Foundation of Inequality Among Mankind, which he wrote in 1754. Once upon a time, the story goes, we were hunter-gatherers, living in a prolonged state of childlike innocence, in tiny bands. These bands were egalitarian; they could be for the very reason that they were so small. It was only after the ‘Agricultural Revolution’, and then still more the rise of cities, that this happy condition came to an end, ushering in ‘civilization’ and ‘the state’ – which also meant the appearance of written literature, science and philosophy, but at the same time, almost everything bad in human life: patriarchy, standing armies, mass executions and annoying bureaucrats demanding that we spend much of our lives filling in forms.
Of course, this is a very crude simplification, but it really does seem to be the foundational story that rises to the surface whenever anyone, from industrial psychologists to revolutionary theorists, says something like ‘but of course human beings spent most of their evolutionary history living in groups of ten or twenty people,’ or ‘agriculture was perhaps humanity’s worst mistake.’ And as we’ll see, many popular writers make the argument quite explicitly. The problem is that anyone seeking an alternative to this rather depressing view of history will quickly find that the only one on offer is actually even worse: if not Rousseau, then Thomas Hobbes.
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As the reader can probably detect from our tone, we don’t much like the choice between these two alternatives. Our objections can be classified into three broad categories. As accounts of the general course of human history, they:
- simply aren’t true;
- have dire political implications;
- make the past needlessly dull.
This book is an attempt to begin to tell another, more hopeful and more interesting story; one which, at the same time, takes better account of what the last few decades of research have taught us. Partly, this is a matter of bringing together evidence that has accumulated in archaeology, anthropology and kindred disciplines; evidence that points towards a completely new account of how human societies developed over roughly the last 30,000 years. Almost all of this research goes against the familiar narrative, but too often the most remarkable discoveries remain confined to the work of specialists, or have to be teased out by reading between the lines of scientific publications.
- How Vibe Coding is Killing Open Source - Maya Posch
- Vibe Coding Kills Open Source - Miklós Koren, Gábor Békés, Julian Hinz, Aaron Lohmann
- The open source design stack - Scott Riley
- Disassembling a Cortex-M raw binary file with Ghidra - Niall Cooling
- Understanding the C runtime memory model - Niall Cooling
- Introduction to Janet RPC - Joe Creager