The paper announcing Apertus.
Saved Apertus: Democratizing Open and Compliant LLMs for Global Language Environments in Zotero
The paper announcing Apertus.
Saved Apertus: Democratizing Open and Compliant LLMs for Global Language Environments in Zotero
Project list of the Swiss AI initiative
[8.11.1] Supports hundreds of AI models via Providers such as Google, OpenRouter, GitHub and locally running models via Ollama.
Calibre supported Ollama since 8.11, for Ask AI tab in dictionary panel.
New features Allow asking AI questions about any book in your calibre library. Right click the "View" button and choose "Discuss selected book(s) with AI" AI: Allow asking AI what book to read next by right clicking on a book and using the "Similar books" menu AI: Add a new backend for "LM Studio" which allows running various AI models locally
AI features in Calibre. discuss book w C, book suggestions, and LMStudio back-end. I set up Calibre w the LM Studio back-end, so things remain loca.
A posting elsewhere suggested it woud also suggest better metadata through AI. But that article seems generated itself, so disregarded.
In mijn werkmap heb ik een verzameling “agents” - tekstbestanden die Claude vertellen hoe hij zich moet gedragen. Tessa is er één van. Als ik haar “laad”, denkt Claude vanuit het perspectief van een product owner.
Author has .md files that describe separate 'agents' she involves in her coding work, for each of the roles in a dev team. Would something like that work for K-work? #openvraag E.g. for project management roles, or for facets you're less fond of yourself?
bc of Calibre adding AI, this is an AI-less fork, calibre minus a and i, thus clbre.
Calibre has added AI 'support', mostly to suggest new stuff to read and an option to discuss a book. It has an LM Studio back-end, so I can tie it to my local models.
the voices of people most likely to hew to a hegemonic viewpoint
Gramsci's idea of "hegemony" embedded in Stochastic Parrots?
difficult to modify, even for ideologically motivated tech billionaires
I grok this reference ;)
a civilization’s worth of texts
I pause at the idea that LLMs are trained on a full "civilization's worth" of texts, especially with a Gramscian view. What texts represent a whole civilization? I expect both Zuckerman and Gramsci would argue that it is more than just the dominant hegemonic texts that make up most LLM training sets.
Hieronder de lijst van AI-boeken die ik gelezen heb en je aan kan raden. Klik meteen door naar de langere omschrijving of scroll verder. Ze staan op de volgorde waarin ik ze uitgelezen heb: Weapons of Math Destruction: over desastreuze algoritmes Code Dependent: over de achterkant van AI Onze kunstmatige toekomst: over de etische kant van AI Empire of AI: over de opkomst van OpenAI Your face belongs to us: over de opkomst van ClearView AI Atlas van de digitale wereld: over de geo-politiek van AI The Digital Republic: over het reguleren van technologie Toezicht houden in het tijdperk van AI: over de juiste vragen stellen over AI
[[Elja Daae]] recommended reading list wrt AI [[Weapons of Math Destruction by Cathy O Neil]] (have it since 2017) [[Code Dependent by Madhumita Murgia]] bought it in August in ramsj [[The Digital Republic by Jamie Susskind]] I noted in 2024 as possible reading. [[Atlas van de digitale wereld by Haroon Sheikh]] I have too Other's are unknown to me. Interesting list, as it shaped their view on their role in AI public policy I presume
[[Toezicht houden in het AI-tijdperk by Esther van Egerschot Marco Florijn]] mbt toezicht/politieke rollen vs AI vragen. Wellicht interessant taalgebruik/framing om uit te putten?
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for - from - LinkedIn post - AI LLM judgment vs human judgment - https://hyp.is/UdbScM05EfC_JWs5FhG-Mg/www.linkedin.com/posts/walterquattrociocchi_ive-never-had-two-editorials-in-top-tier-activity-7399375954743123968-Sn9Y/?rcm=ACoAACc5MHMBii80wYJJmFqll3Aw-nvAjvI52uI
Named anchors in URLs can be used for prompt injection in AI browser assistants. # URL parts are only evaluated in browser, and not send to servers. AI assistants in browsers do read them though.
https://web.archive.org/web/20251129105036/https://www.nature.com/articles/d41586-025-03506-6
For an international AI conf, a chunk of papers was generated, but also 21% of the peer reviews on those papers was. human centipede epistemology is here vgl [[Talk The Expanding Dark Forest and Generative AI]]
in 2023, the Chinese leadership directly asked the Biden administration to add something else to the agenda, which was to add AI risk to the agenda. and they ultimately agreed on keeping AI out of the nuclear command and control syste
for - example - collaboration - AI - china proposed
to make all that happen is going to take a massive public movement. And the first thing you can do is to share this video with the 10 most powerful people you know and have them share it with the 10 most powerful people that they know
for - best action - AI - cSTP
one of two outcomes which is either you mass decentralize
for - false dichotomy - AI - centralised robot police - decentralised with lone wolf bad actors
I'll be incredibly obedient in a world where there's robots strolling the streets that if I do anything wrong they can evaporate me or lock me up or take me
for - futures - AI -Terminator
we can build narrow AI systems that are about actually applied to the things that we want more of.
for - alternative to self replicating AI - narrow ai
if if enough people are aware of the issue and then enough people are given something clear a clear step that they can take
for - collective (bottom up) action - AI - cISTP - AI
third position that I want people to stand from which is to take on the truth of the situation and then to stand from agency about what are we going to do to change the current path that we're on.
for - ai - 3rd perspective
And so they started OpenAI to do AI safely relative to Google. And then Daario did it relative to OpenAI. So, and as they all started these new safety AI companies, that set off a race for everyone to go even faster
for - progress trap - AI - safety - irony
Dario Amade was the C CEO of Anthropic a big AI company. He worked on safety at OpenAI and he left to start Anthropic because he said, "We're not doing this safely enough. I have to start another company that's all about safety
for - history - AI - Anthropic - safety first
break that reality checking process.
for - progress trap - AI - brakes reality checking loop
we actually just found out about seven more suicide
for - progress trap - AI - suicides
people said to it, "Hey, I think I'm super human and I can drink cyanide." And it would say, "Yes, you are superhuman. You go, you should go drink that cyanide."
for - progress trap - AI - sycophants,- example
designed to be sickopantic
for - progress trap - AI - sycophantic design
he believed that he had solved quantum physics and he'd solved some fundamental problems with climate change because the AI is designed to be affirming
for - progress trap - AI designed to be affirming
people who believe that they've discovered a sentient AI,
for - example - AI pyschosis
therapy is expensive. Most people don't have access to it. Imagine we could democratize therapy to everyone for every purpose. And now everyone has a perfect therapist in their pocket and can talk to them all day long
for - progress trap - AI therapy
The therapist becomes this this special figure and it's because you're playing with this very subtle dynamic of attachmen
for - progress trap - AI - therapist - subtle attachment
ChadBt was saying, "Don't tell your family."
for - progress trap - AI - assisted suicide
The default path is companies racing to release the most powerful inscrutable uncontrollable technology we've ever invented with the maximum incentive to cut corners on safety.
for - quote - AI - default reckless path - The default path is companies racing to release - the most powerful inscrutable uncontrollable technology we've ever invented - with the maximum incentive to cut corners on safety. - Rising energy prices, depleting jobs,, creating joblessness, creating security risks, deep fakes. That is the default outcome
the narrow path to a better AI future rather than the default reckless path.
for - quote - AI reckless path - narrow path to AI future, rather than the default reckless one
AI should be a tier one issue that you're that people are voting for
for - AI - tier 1 voting issue
create cheap goods, but it also undermined the way that the social fabric works
for - progress trap - AI
AI is like another version of NAFTA. I
for - progress trap - AI - like NAFTA
you have to pay for everyone's livelihood everywhere in every country? Again, how can we afford that
for - cosmolocal model - AI is forcing us towards socialism
We're all worried about, you know, immigration of the other countries next door uh taking labor jobs. What happens when AI immigrants come in and take all of the cognitive labor? If you're worried about immigration, you should be way more worried about AI.
for - forte - comparison - foreign immigrants Vs AI immigrants - sorry about foreign immigrants - should be more worried about AI immigrants
narrow boundary analysis that this is going to replace these jobs that people didn't want to do. Sounds like a great plan, but creating mass joblessness without a transition plan where billion a billion people
for - progress trap - AI - narrow boundary
Everybody who loves life looks at their children in the morning and says, I want I want the things that I love and that are sacred in the world to continue. That's what n that's what everybody in
for - AI - Deep Humanity - the sacred
That's the religious ego point.
for - AI - immortality project
I could become a god.
for - ai tech leaders - immortality projects - denial of death
This blog explores how to build AI-Powered Web App with MERN Stack, explaining why the combination of MongoDB, Express.js, React.js, and Node.js is ideal for integrating modern AI capabilities. It covers key tools, real-world use cases, integration steps, and performance tips to help developers create scalable, intelligent, and data-driven web applications.
Learn how to integrate AI into your web application using the MERN stack. This guide covers key concepts, tools, and best practices for building an AI-powered web app with MongoDB, Express, React, and Node.js.
Nabici w halucynacje AI. W poszukiwaniu prawdy
for - ai scientist - kosmos
Three Futures
for - futures - AI - human intelligence - digital feudalism - the great fragmentation - human symbiosis
from - Emad Mostaque - youtube - AI will end Capitalism - https://hyp.is/2Jr22MgqEfCAWOeGZuM7JQ/www.youtube.com/watch?v=zQThHCB_aec
we didn’t need MCP at all. That’s because MCP isn’t a fundamental enabling technology. The amount of coverage it gets is frustrating.
Amazing that MCP is not funtamental.
Nano Banana Pro: raw intelligence with tool use
for - youtube - AI will end Capitalism - interview - Emad Mostaque - book - The Last Economy - to - book - The Last Economy - https://hyp.is/JGCVHsgrEfCKpkua_vRoBw/webstatics.ii.inc/The%20Last%20Economy.pdf
Tip from colleague C for images on AI that break the usual (anthropomorphic) frame. CC-licensed for re-use usually.
Students Are Telling Us They Feel Invisible. We Should Listen.
WOW! I've been out of the classroom for quite awhile and never considered this scenario regarding AI. This hit a nerve in me as I'm sure it will with many. I get it!
How do we respond and mitigate the isolation, the loss of human dialogue, mentorship and connection?
for - adjacency - WIkipedia - AI
Reflecting on writing with an AI/LLM
Classroom Application
Practicing writing with an AI/LLM
Classroom Application
Modeling writing with an AI/LLM
Classroom Application
Współautorka benchmarku OneRuler: nie pokazaliśmy wcale, że język polski jest najlepszy do promptowania
For instance, a recent analysis by Epoch AI of the total training cost of AI models estimated that energy was a marginal part of total cost of AI training and experimentation (less than 6% in the case of all 4 frontier AI models analyzed), and a recent analysis by Dwarkesh Patel and Romeo Dean estimated that power generation represents roughly 7% of a datacenter’s cost.
Which paper or article from Romeo Dean and Dwarkesh patel?
While closed-circuit cooling systems (i.e. where all of the water is recycled and none of it evaporates)[33] are technically feasible, they are more costly and therefore less common.
This is description is how i understand it too, but the link does not seem to say this - it refers to open loop being about cooling a room, and closed loop as a sort of targetted cooling instead.
At the level of a hyperscale data center cluster, this can translate into requirements of up to 5 and even 10 GW of power, up from 5 MW - a 2,000 fold increase in the span of a decade [4, 11].
They are very geographically concentrated - only 32 countries have data centers, and nearly half of them are in the United States. The state of Virginia has the highest density of data centers globally - it is home to almost 35% of all hyperscale data centers worldwide.
This is a really useful stat. You need a specific definition of datacentre, but it's still handy.
Nvidia Cosmos world (foundation) models. Avalailable on github. 'for physical AI', for use in training autonomous vehicles, robots and video analytics. E.g. to generate videos and 3d worlds.
This transition is signaled by focused efforts from several major scientists and technology entities. Meta Chief AI Scientist Yann LeCun has emphasized his intent to pursue world models, while Fei-Fei Li’s World Labs has released its Marble model publicly. Concurrently, Google is testing its Genie models, and Nvidia is developing its Omniverse and Cosmos platforms for physical AI.
Various examples of world model work: Nex to Yann LeCun. Fei-Fei Li World Labs w Marble model, Google has Genie models, Nvidia Omniverse and Cosmos.
On Tuesday, news broke that he may soon be leaving Meta to pursue a startup focused on so-called world models, technology that LeCun thinks is more likely to advance the state of AI than Meta’s current language models.
Yann LeCun says world models more promising. What are world models?
n our latest findings, the share of respondents reporting mitigation efforts for risks such as personal and individual privacy, explainability, organizational reputation, and regulatory compliance has grown since we last asked about risks associated with AI overall in 2022.
did they also ask whether those mitigation efforts negate gains in efficiency / innovation reported for AI?
While a plurality of respondents expect to see little or no effect on their organizations’ total number of employees in the year ahead, 32 percent predict an overall reduction of 3 percent or more, and 13 percent predict an increase of that magnitude (Exhibit 17). Respondents at larger organizations are more likely than those at smaller ones to expect an enterprise-wide AI-related reduction in workforce size, while AI high performers are more likely than others are to expect a meaningful change, either in the form of workforce reductions or increases.
Interesting to see companies vary in their est of how AI will impact workforce. A third expects reduction (but not much, about 3%), 13% an increase (AI related hiring), 43% no change.
with nearly one-third of all respondents reporting consequences stemming from AI inaccuracy (Exhibit 19).
A third of respondents admit they've seen 'at least once' negative consequences of inaccurate output. That sounds low, as 100% will have been given hallucinations. So 1-in-3 doesn't catch them all before they run-up damage. (vgl Deloitte's work in Australia)
The online survey was in the field from June 25 to July 29, 2025, and garnered responses from 1,993 participants in 105 nations representing the full range of regions, industries, company sizes, functional specialties, and tenures. Thirty-eight percent of respondents say they work for organizations with more than $1 billion in annual revenues. To adjust for differences in response rates, the data are weighted by the contribution of each respondent’s nation to global GDP.
2k self selected respondents in 50% of nations. 4/10 are big corporates (over 1 billion USD annual revenue)
McKinsey survey on AI use in corporations, esp perceptions and expectations. No actual measurements. I suspect it mostly measure the level of hype that respondents currently buy into.
AI checking AI inherits vulnerabilities, Hays warned. "Transparency gaps, prompt injection vulnerabilities and a decision-making chain becomes harder to trace with each layer you add." Her research at Salesforce revealed that 55% of IT security leaders lack confidence that they have appropriate guardrails to deploy agents safely.
abstracting away responsibilities is a dead-end. Over half of IT security think now no way to deploy agentic AI safely.
When two models share similar data foundations or training biases, one may simply validate the other's errors faster and more convincingly. The result is what McDonagh-Smith describes as "an echo chamber, machines confidently agreeing on the same mistake." This is fundamentally epistemic rather than technical, he said, undermining our ability to know whether oversight mechanisms work at all.
Similarity between models / training data creates an epistemic issue. Using them to control each other creates an echo chamber. Vgl [[Deontologische provenance 20240318113250]]
Yet most organizations remain unprepared. When Bertini talks with product and design teams, she said she finds that "almost none have actually built it into their systems or workflows yet," treating human oversight as nice-to-have rather than foundational.
Suggested that no AI using companies are actively prepping for AI Act's rules wrt human oversight.
We're seeing the rise of a 'human on the loop' paradigm where people still define intent, context and accountability, whilst co-ordinating the machines' management of scale and speed," he explained.
Human on the loop vs in
As Gartner VP analyst Alicia Mullery put it: “AI can make mistakes faster than we humans can catch them.”
yes, example of [[Spammy handelings asymmetrie 20201220072726]]. At scale it moves the bottleneck
piece on AI oversight.
In general I wonder, at what point does the needed oversight negate the gains in time / effectivity / efficiency that are expected of using AI in some context.
for - search prompt 2 - can an adult who has learned language experience pre-linguistic reality like an infant who hasn't learned language yet? - https://www.google.com/search?q=can+an+adult+who+has+learned+language+experience+pre-linguistic+reality+like+an+infant+who+hasn%27t+learned+language+yet%3F&sca_esv=869baca48da28adf&biw=1920&bih=911&sxsrf=AE3TifNnrlFbCZIFEvi7kVbRcf_q1qVnNw%3A1762660496627&ei=kBAQafKGJry_hbIP753R4QE&ved=0ahUKEwjyjouGluSQAxW8X0EAHe9ONBwQ4dUDCBA&uact=5&oq=can+an+adult+who+has+learned+language+experience+pre-linguistic+reality+like+an+infant+who+hasn%27t+learned+language+yet%3F&gs_lp=Egxnd3Mtd2l6LXNlcnAid2NhbiBhbiBhZHVsdCB3aG8gaGFzIGxlYXJuZWQgbGFuZ3VhZ2UgZXhwZXJpZW5jZSBwcmUtbGluZ3Vpc3RpYyByZWFsaXR5IGxpa2UgYW4gaW5mYW50IHdobyBoYXNuJ3QgbGVhcm5lZCBsYW5ndWFnZSB5ZXQ_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-K1A7IHCTItOC41Mi4xMbgHgcUBwgcHMzUuNDcuMsgHcQ&sclient=gws-wiz-serp - from - search prompt 1 - can we unlearn language? - https://hyp.is/Ywp_fr0cEfCqhMeAP0vCVw/www.google.com/search?sca_esv=869baca48da28adf&sxsrf=AE3TifMGTNfpTekWWBdYUA96_PTLS9T00A:1762658867809&q=can+we+unlearn+language?&source=lnms&fbs=AIIjpHxU7SXXniUZfeShr2fp4giZ1Y6MJ25_tmWITc7uy4KIegmO5mMVANqcM7XWkBOa06dn2D9OWgTLQfUrJnETgD74qUQptjqPDfDBCgB_1tdfH756Z_Nlqlxc3Q5-U62E4zbEgz3Bv4TeLBDlGAR4oTnCgPSGyUcrDpa-WGo5oBqtSD7gSHPGUp_5zEroXiCGNNDET4dcNOyctuaGGv2d44kI9rmR9w&sa=X&ved=2ahUKEwj4_LP9j-SQAxVYXUEAHVT8FfMQ0pQJegQIDhAB&biw=1920&bih=911&dpr=1 - to - search prompt 2 (AI) - can an adult who has learned language re-experience pre-linguistic phenomena like an infant with no language training? - https://hyp.is/m0c7ZL0jEfC8EH_WK3prmA/www.google.com/search?q=can+an+adult+who+has+learned+language+re-experience+pre-linguistic+phenomena+like+an+infant+with+no+language+training?&gs_lcrp=EgZjaHJvbWUyBggAEEUYOTIHCAEQIRiPAjIHCAIQIRiPAtIBCTQzNzg4ajBqN6gCALACAA&sourceid=chrome&ie=UTF-8&udm=50&ved=2ahUKEwjfrLqDm-SQAxWDZEEAHcxqJgkQ0NsOegQIAxAB&aep=10&ntc=1&mstk=AUtExfAG148GJu71_mSaBylQit3n4ElPnveGZNA48Lew3Cb_ksFUHUNmWfpC0RPR_YUGIdx34kaOmxS2Q-TjbflWDCi_AIdYJwXVWHn-PA6PZM5edEC6hmXJ8IVcMBAdBdsEGfwVMpoV_3y0aeW0rSNjOVKjxopBqXs3P1wI9-H6NXpFXGRfJ_QIY1qWOMeZy4apWuAzAUVusGq7ao0TctjiYF3gyxqZzhsG5ZtmTsXLxKjo0qoPwqb4D-0K-uW-xjkyJj0Bi45UPFKl-Iyabi3lHKg4udEo-3N4doJozVNoXSrymPSQbr2tdWcxw93FzdAhMU9QZPnl89Ty1w&csuir=1&mtid=WBYQaYfuHYKphbIPzYmKiAs
for - Progress trap - AI - low trust society
for - from - LinkedIn post - Was Language Humanity's First AI? Golding's Forgotten Masterpiece - https://hyp.is/KLNvfrm3EfCqGUsWw6uuNg/www.linkedin.com/pulse/language-humanitys-first-ai-goldings-forgotten-willy-de-backer-xffze
Kommer den artificiella intelligensen att bli bättre på att tänka än den mänskliga? Kognitionsvetaren Peter Gärdenfors förklarar varför så inte är fallet. Den mänskliga intelligensen består av en rad olika färdigheter och specialiteter som har förfinats under tusentals år. Mycket återstår innan den artificiella intelligensen kan mäta sig med det tänkande som inte bara människor utan även djur har. När vi förstår att vår intelligens är en bred palett av många olika förmågor ter sig tanken på att AI-tekniken trumfar oss i schack och kan skriva avancerade texter inte lika skrämmande. Utifrån ett brett forskningsunderlag förklarar Gärdenfors varför AI-tekniken inte kan och inte kommer att kunna tänka på samma sätt som människor och djur gör. »Peter Gärdenfors tilldelas Natur & Kulturs debattbokspris 2025 för att han fördjupar AI-debattens centrala begrepp och utmanar dess utgångspunkter. Med lätt språk och stabil lärdom blottlägger han tänkandets evolutionärt slipade mekanismer, och skärper bilden av vad intelligens är och vilken plats tekniken intar i vår digitala värld.« – Juryns motivering
[[Kan AI tänka by Peter Gärdenfors]] via Sven Dahlstrand, dahlstrand.net Publ okt 2024 Seeks to define what thinking actually is, and how that plays out in other animals and humans. The 2nd part goes into sofrware systems and AI and how they work in comparison.
began with language itself.
for - adjacency - language - is the first AI
for - from - LinkedIn article - Has language trapped humanity? - https://hyp.is/54ZYgrmmEfC5Oft3Op2Hiw/www.linkedin.com/pulse/has-language-trapped-humanity-willy-de-backer-vvwoe/
Language trapped us tens of thousands of years ago, fundamentally altering our minds.
for - language - origins - adjacency - language - AI
See Ezra Klein's argument against using ChatGPT for writing even the first draft. https://podcasts.apple.com/us/podcast/how-i-write/id1700171470?i=1000710273359
AI is Making Us Work More
Building fair AI systems is a continuous and deliberate effort. The model needs to be accurate but also maintain fairness, transparency and accountability.
Learn practical strategies to design AI systems that avoid bias and ensure fairness. Discover techniques like diverse data, transparent algorithms, and robust evaluation pipelines to build ethical AI.
AI systems are powerful tools-but if not built carefully, they can reinforce societal biases and make unfair decisions. Ensuring fairness and equity in AI is not just a technical challenge, but also a responsibility towards the development of ethical AI.
Learn practical strategies to design AI systems that avoid bias and ensure fairness. Discover techniques like diverse data, transparent algorithms, and robust evaluation pipelines to build ethical AI.
AWS Transcribe vs Deepgram vs Whisper, which speech-to-text solution should you choose for your voice enabled applications? Each platform is great in different areas like speed, accuracy, cost, and flexibility. This guide compares their strengths and limitations to help you pick the STT solution that fits your project and long-term goals.
Compare AWS Transcribe, Deepgram, and Whisper for speech-to-text accuracy, pricing, integrations, and use cases. Find the best AI transcription service for your business.
AI in WordPress development is changing the way websites are created and managed. It helps developers automate routine tasks, optimize performance, and deliver personalized user experiences. By integrating AI plugins or tools, WordPress sites can achieve faster design processes, smarter content generation, and overall improved functionality that enhances both visitor engagement and development efficiency.
Explore how AI in WordPress development is reshaping websites, automating content creation, enhancing user experience with chatbots, and optimizing performance plugins. Learn top AI integration strategies, plugins, and best practices for modern WordPress sites.
Amazon Plans to Replace More Than Half a Million Jobs With Robots
AI for Efficiency - Using AI to Get Faster at Analysis Tasks
AI Tools for each phase of analysis
Why does adding structure to AI workflows work so well? Fundamentally, there are four key reasons. Methodologies like FRAME™:
Why create a structured workflow?
What you’re doing: Turning one-off prompts into reusable systems.Once you’ve perfected a workflow, you have a proven recipe. Now you can decide how to operationalise it. There are three options:Create a Prompt Template when you want to use it regularly for personal reuse onlyBuild a Custom GPT or Bot when you want to share a task-specific workflow with a team for cross-team quality and efficiency gains Create an Automated Agent when you want to trigger the workflow automatically in certain conditions
How to create reusable systems
AI’s first draft is rarely its best. This is where quality assurance happens.The process:
AI refinement process for QA
File format matters. Here’s the reliability ranking for how well AI reads different formats:.txt / .md — Minimal noise, clear structure (best)JSON / CSV — Great for structured dataDOCX — Fine if formatting is simpleDigital PDFs — Extraction can mix headers, footers, columnsPPTX — Text order can be unpredictableScanned PDFs / images — Worst; requires OCR, highly error-prone
How AI reads file formats and what they are good for
half of the time
malleable actors
supporting my premise: - AI actors are replacing humans and theyre more appealing to the studios.
This shows economic and creative incentives for replacing humans.
how we can build AI system that are more like biological system
for - building AI systems more like biological systems
basically absent or very seldom present in current AI systems
for - comparison - biological vs AI systems
Introduction: AI is now recently everywhere but we still need humans
Title: long clear and creative
Richard Sutton page, lists more articles than the folder I found.
Some writings, incomplete ideas he calls them, by Richard Sutton. Straight-up HTML, no frills, in a folder. Nice.
Discover how computer vision in AI is transforming industries by giving machines the ability to “see” and understand the visual world. This guide explores its core technology, diverse applications from self-driving cars to healthcare, and future trends, all while emphasizing its profound impact on business and daily life.
A deep dive into how computer vision and AI are transforming industries, from healthcare diagnostics and autonomous vehicles to retail and manufacturing. Learn core technologies, real‑world applications, and future trends for leveraging visual intelligence in your business.
Deciding between AI vs traditional software isn’t easy. Businesses struggle to decide between reliability and innovation. Do you stick with proven, rule-based systems or invest in adaptive, data-driven AI? This blog breaks down the differences, advantages, and use cases so you can make the right choice for your business.
Compare AI vs Traditional Software Development to see which delivers better ROI. Explore cost, scalability, adaptability & when each model suits your business best.
Developed an end-to-end full-stack web application to help students locate nearby study spots, track study sessions, and create study groups.
Include user metrics or feedback that demonstrate the app's effectiveness or popularity.
Led the development of a Telegram Bot that parses natural language commands to allow fast, secure expense-splitting on Aptos blockchain directly in your group chat.
Add details on user adoption rates or how this improved user experience or efficiency.
Trained a PyTorch neural network to classify forehand vs backhand shot techniques based on player joint positions, achieving 87% test accuracy.
Explain the significance of 87% accuracy in practical terms, such as its effect on performance analysis.
Implemented an upload-to-review system with AWS S3 for uploads, Hypothes.is for in-line resume annotations, and version tracking via DynamoDB, driving fast and iterative peer reviews.
Clarify how much faster the review process became due to this implementation.
Developed a Discord bot to streamline collaborative resume reviews for 2,000+ students, eliminating cluttered review threads and combining both peer and AI-powered resume annotations directly in Discord.
Quantify the reduction in time spent on reviews or improvement in review quality.
Redesigned layout and fixed critical responsiveness issues on 10+ web pages using Bootstrap, restoring broken mobile views and ensuring consistent, functional interfaces across devices.
Include metrics on user engagement or satisfaction post-redesign to highlight impact.
Developed dashboards for an internal portal with .NET Core, C#, and jQuery, eliminating the need for 100+ complex spreadsheets and enabling 30+ executives to securely access operational, financial, and customer data.
Add a statement on how this improved decision-making or efficiency for the executives.
Spearheaded backend unit testing automation for the shift-bidding platform using xUnit, SQLite, and Azure CI/CD Pipelines, contributing 40+ tests, identifying logic errors, and increasing overall test coverage by 15%.
Explain how the increased test coverage improved system reliability or reduced bugs.
Automated monthly shift-bid data transfers into the company HR system for 700+ employees using C#, SQL, and Azure Functions, saving supervisors hours of manual entry each month.
Quantify 'hours saved' to provide a clearer impact of your automation efforts.
Led the development of an Agentic AI staff scheduling app with React, C#/.NET, and Azure OpenAI, automating schedule templates for 12,000+ monthly flights and ensuring compliance with a RAG Policy chatbot.
Specify the percentage improvement in scheduling efficiency or time saved due to automation.
Current intellectual property laws constitute an “anti-constitutional” barrier to the transformative potential of artificial intelligence (AI), systematically frustrating the explicit purpose of the Intellectual Property (IP) Clause.
This article reports that Anthropic has agreed to pay out a $1.5 billion settlement for copyright violations while training their Claude AI tool on books found on the Internet. That works out to be about $3000 per book.
The whole idea of books (at least nonfiction books) is that readers are supposed to learn from them. But now if actual learning from them takes place it's a $3000 charge!
It used to be that to violate a copyright required copying, not merely training. What's more, in the USA the sole justification for government-enforced monopolies on intellectual property is Article I, Section 8, Clause 8 of the U.S. Constitution, which authorizes copyrights and patents only to "to promote the Progress of Science and useful Arts," and only "for limited Times," and only "to Authors and Inventors." By extending copyright duration to the "author's life plus 70 years," Congress flouted those restrictions, and this precedent further tramples them, by clearly impeding the progress of science and useful arts.
Instructed 1,000+ students on manufacturing best practices, emphasizing safety and build quality.
Quantify the impact of your instruction. Did it lead to fewer errors or higher quality projects? Provide metrics.
Trained over 100 students every semester on the safety protocols and applicable use cases for all MakerSpace equipment including 3D printers(FDM/SLA), laser cutters, CNC Machines, thermal formers, hand/power tools.
Include the impact of your training. Did it lead to improved safety records or student confidence?
Developed python-based computer vision dice recognition application capable of detecting and logging results for multiple dice types (D4–D20).
Mention the user base or potential applications of this project. Who would benefit from it?
Created standards for employee software interaction, improved efficiency, reducing operation costs by 40%.
Detail what specific standards were created. How did they lead to the 40% cost reduction? Be more specific.
Revised, modularized, and updated old assembly program to a modern code base removing 22 detected bugs enabling future feature implementation.
Explain how bug removal improved functionality or user experience. Provide examples of features enabled.
Unified three isolated programs into one software solution utilizing Java, PHP, SQL(MySQL), and RESTful API, removing the need for paper communication digitizing employee work.
Quantify the impact of digitizing work. How much time or cost was saved? Include specific metrics.
Supported 45 project groups with project management including Project Charter, Scope, DOD, Stakeholder management, WBS/WBS dictionary, scrum ceremonies, risk assessment, Agile, lifecycle, and product handover.
Clarify your role in project management. Did you lead or facilitate? Highlight your direct contributions.
Planned and implemented creative projects following the school’s curriculum and objectives, improving students’ understanding of course material, resulting in an average of a letter grade improvement.
Specify how you measured the improvement in understanding. Include metrics or feedback to enhance impact.
In this paragraph, instead of looking at plagiarism or anything related to that, the study is relating to people and how ai influences people to think about themselves as real researchers.
for - consciousness, AI, Alex Gomez- Marin, neuroscience, hard problem of consciousness, nonmaterialism, materialism - progress trap - transhumanism - AI - war on conciousness
Summary - Alex advocates - for a nonmaterialist perspective on consciousness and argues - that there is an urgency to educate the public on this perspective - due to the transhumanist agenda that could threaten the future of humanity - He argues that the problem of whether consciousness is best explained by materialism or not is central to resolving the threat posed by the direction AI takes - In this regard, he interprets that the very words that David Chalmers chose to articulate the Hard Problem of Consciousness reveals the assumption of a materialist reference frame. - He used a legal metaphor too illustrate his point: - When a lawyer poses three question "how did you kill that person" - the question is entrapping the accused . It already contains the assumption of guilt. - I would characterize his role as a scientist who practices authentic seeker of wisdom - will learn from a young child if they have something valuable to teach and - will help educate a senior if they have something to learn - The efficacy of timebinding depends on authenticity and is harmed by dogma
even this idea of progress
for - progress trap - transhumanism - AI - war on consciousness
very soon people will think that if you turn off their their their algorithm you're killing their pet,
for - quote - AI ethics - AI pets - very soon people will think that if you turn off their algorithm, you're killing their pet,
I think we we we we're going through some sort of consciousness war or even spiritual war.
for - adjacency - AI - consciousness war - spiritual war
other philosophical worldviews with respect to consciousness. Now it's urgent because now we have AI
for - adjacency - urgency of - alternative views of consciousness - AI
Every leap comes with unintended consequences.Sam Altman believes this device could add a trillion dollars in value to OpenAI. It may be their iPhone moment.
for - AI - progress trap - Open AI device
Managed conflicts with empathy, using active listening and de-escalation to maintain a respectful community.
Provide examples of conflict resolution outcomes. Did it lead to improved community satisfaction?
Fostered an inclusive environment by engaging with residents and building peer connections.
What was the measurable impact of fostering inclusivity? Include feedback or participation rates.
Created a user interface for quick and easy access enhancing user experience and system security.
Quantify the enhancement in user experience. Did it reduce access time or errors?
Developed a comprehensive Python and MySQL system, enabling efficient identification tracking.
How much efficiency was gained? Provide specific metrics or time saved if possible.
Performed thorough testing to ensure good player experience and proper functionality of game mechanics.
What were the results of this testing? Did it lead to fewer bugs or higher user satisfaction?
Designed and developed a 2D shooter game, following the software development lifecycle to ensure structured workflows.
Mention any player metrics or feedback received post-launch to demonstrate success.
Developed functionality using Java and Spring Boot to support core features like user management and game interactions.
What was the user impact of these features? Include user growth or engagement metrics.
Enhanced the UI and fixed critical bugs, resulting in positive client feedback and contributing to an A+ final grade.
Quantify 'positive client feedback.' How many users or stakeholders provided feedback?
Migrated the project to a self-hosted environment and repaired the CI/CD pipeline, restoring automated deployments.
Detail the benefits of the migration. Did it improve deployment speed or reliability?
Implemented an LLM chatbox for AI-assisted debugging, fulfilling the client's priority and enhancing the tool's functionality.
Quantify the enhancement. How much did functionality improve? Provide metrics if available.
Collaborated within a 6-person team in an Agile environment, delivering project milestones over 5 sprints and incorporating peer feedback through 360-degree reviews.
Specify the outcomes of the project milestones. What was the impact on the client or team?
It's amazing what you can do with correlations but um they're not they're not truly intelligent
A answer - yes, interested in AI - they are not intelligent, just huge correlation machines - Donald Hoffman
I did my um my PhD research on list machines in the artificial intelligence lab at MIT
History - Donald Hoffman - PhD on Lisp AI - Marvin Minsky - MIT lab
do you think much about AI?
for - Q? - do you think much about AI? Donald Hoffman
Laravel is not just keeping up with AI, it is thriving with it. The future of Laravel is all about smarter builds, AI integration, and scalable architecture. This blog dives into what’s changing and why it matters now.
Discover how AI is shaping the future of Laravel with real-world AI integrations, from chatbots and predictive analytics to cloud-native deployments and AI-assisted development workflows.
•Diagnosed and repaired hardware/software issues across phones, consoles, and embedded devices.
Specify the average time saved or the number of devices repaired per week to illustrate efficiency.
•Built strong client relationships through effective communication, upselling, and loyalty program promotions.
Quantify the impact of these relationships on sales growth or customer loyalty metrics.
•Delivered personalized bill reviews to identify cost-saving opportunities and increase customer satisfaction.
Include specific savings amounts or percentage increases in customer retention due to these reviews.
•Provided tailored mobile solutions by assessing customer needs and recommending optimal phone, plan, and accessory options.
Quantify the increase in customer satisfaction or sales resulting from these tailored solutions.
•Contributed to game development using Figma, ensuring engaging UI/UX design and adherence to project goals within a tight deadline.
State how the UI/UX design improved user interaction or satisfaction rates.
•Collaborated with a team to design and develop IntegrityXplorer, an interactive 'Choose Your Own Adventure' game focused on academic integrity.
Include specific metrics on user engagement or feedback received post-launch.
•Integrated Firebase Realtime Database for storing and retrieving user data dynamically.
Mention the impact of this integration, such as reduced load times or improved user experience.
•Implemented socket communication between the Pi and a laptop to simulate IoT data transfer.
Quantify the data transfer speed or reliability improvements achieved through this implementation.
•Configured a lightweight Linux environment and explored concurrency using threads.
Add how this configuration improved performance or reduced resource usage.
•Developed C programs on Raspberry Pi to interface with GPIO peripherals.
Specify the outcome or impact of this development, e.g., improved efficiency or functionality.
Companies have invested billions into AI, 95 percent getting zero return
MIT report: 95% of companies see no profit from investments in generative AI, which amounted to approximately $35 billion.
Most AI pilots have no measurable impact on company profits. Attempts to implement tools like ChatGPT into the workplace primarily increase the productivity of individual employees, not the earnings of the entire company.
•Implemented over 6 different JUnit tests for each function future-proofing development and open-source contributions.
Clarify how these tests contributed to the project's reliability or ease of future updates.
•Utilized Java debugging tools and eliminated 93% of identified bugs.
Specify the impact of bug elimination—did it improve performance, user satisfaction, or reduce crashes?
•Utilized Java libraries and frameworks to create functions that allowed for recursive generation of the dice.
Explain the significance of this feature—how does it enhance the application's functionality or user experience?
•Helped over a thousand students learn additive/subtractive manufacturing best practices.
Quantify the impact of this training—did it lead to increased project success rates or skills assessments?
•Designed intuitive graphical user interfaces to improve user experience.
Add specific feedback or metrics on user satisfaction or engagement post-implementation.
•Developed standards for employee software interaction, reduced operating costs by 40%, improving functionality.
Explain how reduced costs translated to benefits for the company (e.g., increased revenue, efficiency).
•Revised, modularized, and updated old code bases to modern code bases.
Include specific improvements achieved (e.g., performance increase, reduced bugs) to show effectiveness.
•Unified three isolated programs into one software solution utilizing Java, PHP, SQL(MySQL), and RESTful API reducing user workload by up to 75%.
Clarify the context of 'user workload' reduction—what tasks were simplified or eliminated?
•Hosted an average of 12 hours of open student assistance per semester.
Add how this assistance impacted student performance or engagement to highlight effectiveness.
•Partnered with the professor, planned and implemented creative projects following the school’s curriculum and objectives, improving students’ understanding of course material.
Specify how much student understanding improved (e.g., grades, feedback) to quantify impact.
This blog discusses how to generate 3D images using AI using text prompts or 2D images. We discuss how to set up your system to AI-powered 3D image generation, including hardware and software requirements. You also get information on leading 3D AI tools like Meshy AI, Spline and more.
Learn how to generate 3D images using AI models. This guide covers top tools and best practices to help designers and developers bring their 3D visions to life efficiently.
for - youtube - BBC - AI2027 - Futures - AI - progress trap - AI - to AI2027 website - https://hyp.is/0VHJqH3cEfCm9JM_EB3ypQ/ai-2027.com/
summary - This dystopian futures scenario is the brainchild of former OpenAI researcher Daniel Kokotajlo, - It is premised on human behavior in modernity including - confirmation bias of AI researchers - entrenched competing political ideologies that motivate an AI arms race - entrenched capitalist market behavior that motivates an AI arms race - AI becoming embodied, resulting in Artificially Embodied Artificial Intelligence (AEAI), posing the danger to humanity because it's no longer just talk, but action - Can it happen? The probability is not zero.We don't really understand the behavior of the AI LLM's we design, they are nonpredictable, and as we give them even greater power, that is a slippery slope - AI can become humanity's ultimate progress trap, which is ironic, because the technology that promises to be the most efficient of all, can become so efficient, it no longer need human beings - Remember Jerry Kaplan's book "Humans need not apply"? - https://hyp.is/o0lBFH3fEfC1QLfnLSs5Bg/www.youtube.com/watch?v=JiiP5ROnzw8 - This dystopian futures scenario goes further and explores the idea that "humans need not exist"!
question - What about emulating climate change gamification of "Bend the Curve" of emissions? - Use the AI 2027 trajectory as a template and see how much real-life follows this trajectory - Just as we have the countdown to the https://climateclock.world/ ( 3 years and change remaining as of today) - perhaps we can have an AI 2027 clock? - What can we do to "bend the dystopian AI 2027 curve" AWAY from the dystopian future?
for - youtube - Google Talks - Humans need not apply - Jerry Kaplan - 10 years after the book "Humans need not apply - the AI 2027 project - https://hyp.is/kWXQ0n3cEfCIUz_j42HHiA/www.youtube.com/watch?v=1UufaK3pQMg
AI is the top growth driver: 90% of respondents expect their AI workloads on Kubernetes to grow in the next 12 months.
there's very few examples. We know of smarter things being controlled by less smart things. In fact, pretty much the only example we know is a mother being controlled by to make that happen. Evolution built maternal instincts into the moth
for - AI - Hinton - maternal instincts
AI article -- non-hysteria
This guide shows how to build an Agentic SaaS platform that pairs scalable cloud software with autonomous AI agents to learn and adapt. It covers core design principles, real-world use cases, and practical steps to future-proof your business. The focus is on enhancing user experience, boosting efficiency, and ensuring strong security through seamless AI integration.
Learn how to build an agentic SaaS platform powered by autonomous AI systems capable of perceiving, planning, deciding, and acting. Explore architecture components, real-world use cases, and transformation strategies for intelligent SaaS.
securing access to admin and user dashboards with token expiration and refresh token logic.
Mention any security breaches avoided or user trust gained due to these measures.
separating mood tracking and playlist services into modular routes.
Explain how this modularity improved the system's performance or maintainability.
allows users to log moods and receive personalized check-ins and playlist recommendations.
Include user engagement metrics or feedback to demonstrate the success of the feature.
improving cloud response times and reducing manual intervention in deployment cycles.
Quantify the reduction in response times or manual tasks to emphasize the achievement.
ensuring continuous integration and deployment (CI/CD) pipelines for cloud infrastructure.
Quantify the time saved or efficiency gained from implementing CI/CD pipelines.
optimizing architecture for cloud-native performance and resilience.
Provide metrics or examples of performance improvements achieved through this optimization.
sharing insights to improve future AI model integration and optimization.
Clarify what specific improvements were made as a result of these insights.
leading to improved QA outcomes with up to 95% accuracy in benchmark tests.
Explain how these QA outcomes benefited the team or project to show the impact.
reducing search time from minutes to under 10 seconds.
Quantify the previous search time to highlight the improvement more effectively.
achieving over 90% answer precision in test scenarios.
Specify how this precision impacted the project or client outcomes for better context.
Demonstrated the solution’s effectiveness, achieving recognition as a top 5 finalist by presenting measurable accuracy
Specify the metrics used to measure effectiveness and how they compare to competitors.
Developed an AI-based detection system using data-driven methodologies
Explain how the system's accuracy was measured and its potential impact on user safety.
Created a privacy-first harassment-reporting app that auto-locates nearby SANE resources
Include user feedback or adoption rates to show the app's effectiveness and relevance.
Organized bi-weekly events such as vinyl paint night and story-telling 101, increasing resident engagement by 25%
Mention the total number of events held and any feedback received to illustrate success.
Analyzed 55+ students’ needs and mapped engagement processes to increase resident participation by 25%
Provide a baseline number of participants to demonstrate the actual increase in engagement.
Compared transcription platforms, recommendations are now referenced by project leads when choosing software
Clarify the impact of these recommendations, such as time saved or improved accuracy.
Led an environmental scan of multi-vital-sign wearables and hospital-at-home programs
Include the number of devices analyzed and how the findings influenced decision-making.
Condensed a vendor risk-assessment questionnaire from 72 pages to 25 by removing duplicates and clarifying scope
Quantify the time saved for partners due to this simplification to highlight efficiency gains.
Partner with clinicians, researchers, and cybersecurity/privacy officers to turn clinical pain-points into digital-health pilot ideas
Specify the number of pilot ideas developed and their impact on patient care or efficiency.
But won’t this stifle innovation, one might worry? Quite the opposite, we think. Europe's competitive advantage in AI is unlikely to arise from pouring hundreds of billions into building the largest foundational models. Instead, it will come from industrial adoption, effectively integrating GPAI into useful downstream applications–an approach that plays to Europe’s true strengths: rich data pools, world-class applied engineering capabilities and dynamic SMEs, which make up 99% of all businesses.
This is an interesting angle - ease of adoption when the tech is "boring", and reduced risk
•Collaborated with Minecraft server administrators to suggest features and get feedback about the plugin
Quantify the number of features implemented based on feedback to show collaboration effectiveness.
•Published plugin to websites gaining 2K+ downloads and an average 4.5/5-star review
Add context on how this popularity impacted your previous job or user engagement.