Tl;dr: GenAI uses water unsustainably. And there was a Tuesday in last week.
https://dl.acm.org/doi/epdf/10.1145/3724499
(However, note obviously AI-generated front-page picture, sigh.)
Tl;dr: GenAI uses water unsustainably. And there was a Tuesday in last week.
https://dl.acm.org/doi/epdf/10.1145/3724499
(However, note obviously AI-generated front-page picture, sigh.)
friends don’t let friends use spicy autocarrot to generate #passwords… 💁♀️
Your AI-generated password isn't random, it just looks that way
“AI security company Irregular looked at Claude, ChatGPT, and Gemini, and found all three #GenAI tools put forward seemingly strong passwords that were, in fact, easily guessable.”
…
“Irregular found that all three AI #chatbots produced passwords with common patterns, and if hackers understood them, they could use that knowledge to inform their brute-force strategies.”
…
“Knowing the patterns also reveals how many times #LLMs are used to create passwords in open source projects. The researchers showed that by searching common character sequences across #GitHub and the wider web, queries return test code, setup instructions, technical documentation, and more.”
https://www.theregister.com/2026/02/18/generating_passwords_with_llms/
#PSA #Authors #Writing #GenAI #Meta #Anthropic #AnthropicClassAction
Deadline to join the class action against Meta/Anthropic: Friday August 15, 2025.
"Submitting your information here does not make you a member of the Class. But, if you are a member of the class, submitting your information will help us direct formal notice of the class action at the appropriate time."
https://www.lieffcabraser.com/anthropic-author-contact/
Gift link to The Atlantic database search tool:
https://www.theatlantic.com/technology/archive/2025/03/search-libgen-data-set/682094/?gift=uvbqc-y7RgcozRTSY7kANHrt8LyDF9nPyN5h5Dmp4rE
Please share widely!
This misguided trend has resulted, in our opinion, in an unfortunate state of affairs: an insistence on building NLP systems using ‘large language models’ (LLM) that require massive computing power in a futile attempt at trying to approximate the infinite object we call natural language by trying to memorize massive amounts of data. In our opinion this pseudo-scientific method is not only a waste of time and resources, but it is corrupting a generation of young scientists by luring them into thinking that language is just data – a path that will only lead to disappointments and, worse yet, to hampering any real progress in natural language understanding (NLU). Instead, we argue that it is time to re-think our approach to NLU work since we are convinced that the ‘big data’ approach to NLU is not only psychologically, cognitively, and even computationally implausible, but, and as we will show here, this blind data-driven approach to NLU is also theoretically and technically flawed.
TFW an author whose books you really like is releasing four or five titles a year, and you then go to check their publication history to reassure yourself they've been doing this since the early 2010s (they're just prolific, not likely they're using GenAI). Then you get angry you have to do this now.
Page Against the Machine: On the Poetics of AI Refusal
Pip Thornton documents and debates some of the outputs of ‘Writing the Wrongs of AI’, a project which explored creative ways to demonstrate the power that human words, poetics and writing might have in resisting the influence of artificial intelligence in the literary sphere and beyond.
The true power of #genAI is not technological, but rhetorical: almost all conversations about it are about what executives are saying it will do "one day" or "soon" rather than what we actually see (and of course no mention of business model which doesn't exist).
We are told to simultaneously believe AI is so "early days" as to excuse any lack of real usefulness, and that it is so established - even "too big to fail" - that we are not permitted to imagine a future without it.
Anthony Horowitz admits he uses the plagiarism regurgitron:
Writing vs AI slop:
"AI slop is... vomited into existence...something they read, not something the wrote. And to a writer those are not the same."
"The Wikimedia Foundation, the nonprofit organization that hosts Wikipedia, says that it’s seeing a significant decline in human traffic to the online encyclopedia because more people are getting the information that’s on Wikipedia via generative AI chatbots that were trained on its articles and search engines that summarize them without actually clicking through to the site."
Generative AI keeps on ruining everything.
#AI #genai #LLM #wikipedia #internet #tech #news
https://www.404media.co/wikipedia-says-ai-is-causing-a-dangerous-decline-in-human-visitors/
The AI industry wants us to believe AI superintelligence is the real threat from generative AI.
But that narrative was crafted to distract from the many ways genAI is being used to tear our societies apart, as we saw this week when a deepfake video rocked the Irish election. It must be reined in.
https://disconnect.blog/generative-ai-is-a-societal-disaster/
“Universities that encourage students to use #ChatGPT? I’m stunned to hear something like that.”
Luc Steels – the “godfather of #AI research in Belgium” –is one of the Belgian signatories of a recent open letter to “stop the uncritical adoption of AI technologies in academia”, initiated by @olivia and @Iris.
I spoke with Steels, computational linguist Katrien Beuls, and computer scientist @wim_v12e, and others, about their resistance against #genAI in academia.
The #GenAI bubble gets entertainingly weird: https://newsletterhunt.com/emails/276581
JesusGPT…
Former CEO of Intel Building Special AI to Bring About Second Coming of Christ
https://futurism.com/artificial-intelligence/former-ceo-intel-ai-christ
#religion #AI #ArtificialIntelligence #LLM #LLMs #MachineLearning #tech #technology #BigTech #GenAI #generativeAI #AISlop #Meta #Google #OpenAI #ChatGPT
I never stopped using evolutionary computation. I'm even weirder and use coevolutionary algorithms. Unlike EC, the latter have a bad reputation as being difficult to apply, but if you know what you're doing (e.g. by reading my publications 😉) they're quite powerful in certain application areas. I've successfully applied them to designing resilient physical systems, discovering novel game-playing strategies, and driving online tutoring systems, among other areas. They can inform more conventional multi-objective optimization.
Many challenging problems are not easily "vectorized" or "numericized", but might have straightforward representations in discrete data structures. Combinatorial optimization problems can fall under this umbrella. Techniques that work directly with those representations can be orders of magnitude faster/smaller/cheaper than techniques requiring another layer of representation (natural language for LLMs, vectors of real values for neural networks). Sure, given enough time and resources clever people can work out a good numerical re-representation that allows a deep neural network to solve a problem, or prompt engineer an LLM. But why whack at your problem with a hammer when you have a precision instrument?
AI is intellectual Viagra
This is an excellent video. This is the message. Perhaps we need to refine it more. Find ways to communicate it more clearly. But this is the correct take on LLMs, so-called-AI and the proliferation of these tools to the general public. #LLM #llms #ai #genAI #video #slop #slopocalypse #enshittification