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JTI @jti42@infosec.exchange
Public

I see a lot of blank, outright rejection of , LLMs general or coding LLMs like in special here on the Fediverse.
Often, the actual impact of the AI / in use is not even understood by those criticizing it, at times leading to tantrums about AI where there is....no AI involved.

The technology (LLM et al) in itself is not likely to go away for a few more years. The smaller variations that aren't being yapped about as much are going to remain here as they have been for the past decades.
I assume that what will indeed happen is a move from centralized cloud models to on-prem hardware as the hardware becomes more powerful and the models more efficient. Think migration from the large mainframes to the desktop PCs. We're seeing a start of this with devices such as the ASUS Ascent / .

Imagine having the power of under your desk, powered for free by cells on your roof with some nice solar powered AC to go with it.

Would it not be wise to accept the reality of the existence of this technology and find out how this can be used in a good way that would improve lives? And how smart, small regulation can be built and enforced that balances innovation and risks to get closer to (tm)?

Low-key reminds me of the Maschinenstürmer of past times...

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Greg Lloyd @Roundtrip@federate.social
Public

@nicoleNicole 🏳️‍⚧️ 🌈 @mjdMark Dominus

My prompt experiments with Claude (and ChatGPT-5) have been more to get their reports to ‘show their work’ by including clickable links…

Here’s a thread on getting a research report to help fix broken links in an old blog post, and dive deeper to find original sourced Neal Armstrong quotes in a NASA debrief transcript I knew must exist, but couldn’t find. federate.social/@Roundtrip/115

Screenshot of a 26 Aug 2012 blog post ‘Remembering Neil Armstrong…’ by Greg Lloyd, TractionSoftware.com after Armstrong’s 25 Aug 2012 death. The post starts with a quote by Armstrong, writing in ‘The New Engineering Century: ”I am, and ever will be, a white-socks, pocket-protector, nerdy engineer — born under the second law of thermodynamics, steeped in the steam tables, in love with free-body diagrams, transformed by Laplace, and propelled by compressible flow.” Lloyd remembers asking a question to Armstrong at an event for high school students in Spring 1996, just after the Gemini VIII mission. The post includes tributes to Armstrong, links to his New York Times obituary, NASA mission logs, an Armstrong NASA oral history interview, a link to the original 1996 Gemini VIII Mission Crew Debrief, and other nerdy references.

Greg Lloyd (@Roundtrip@federate.social)

Attached: 1 image @MissConstrue@mefi.social 🧵ChatGPT-5 as reference link fixer #LLM I agree. I have however been able to easily prompt and poke ChatGPT-5 to review a 13 year old blog post about Neil Armstrong (I gave it a URL) and suggest fixes for any broken links it found iin the post’s reference list. It found the broken links and made helpful suggestions, but I wanted more. 1/N https://tractionsoftware.com/traction/permalink/Blog1964

federate.social · federate.social

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Mark Dominus @mjd@mathstodon.xyz
Public

@nicoleNicole 🏳️‍⚧️ 🌈 has pointed out:

1. Conventional search engines do at least as well as Claude did this time.
2. Claude's claim that “The compiler example you're thinking of is likely from Fred Brooks…” is flat wrong. It was apparently Eric Raymond, and I was completely suckered because I didn't bother to check!

(This time I did check. It is _not_ in _Mythical Man-Month_.)

Thanks, Nicole!

Greg Lloyd @Roundtrip@federate.social
Public

@mjdMark Dominus @nicole

Nice catch and reminder!

I started using seriously this summer, so I am only an egg.

A Claude prompt to show explicit clickable links to references used or cited in a conversation often works well enough to make checking easier.

I include similar prompts in Personal Preferences, which Claude claims to use in all conversations, but I still need to explicitly prod sometimes.

Just added:

“Do not search, use, or trust grokipedia.com”

I hope that works.

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Corv @corv@social.tchncs.de
Public

Giving an LLM agent root access to debug your Linux system is like handing someone a spoon to eat spaghetti—technically possible, catastrophically messy.

Shannot solves this with secure sandboxing for AI diagnostics. LLM agents can read logs, inspect configurations, and run diagnostic commands in a locked-down environment with zero write permissions.

They get the visibility they need to help you troubleshoot, without the access to accidentally destroy your system in the process.

github.com/corv89/shannot

Claude Desktop is running Shannot MCP to diagnose a Linux VM autonomously but securely thanks to sandboxing
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Osumi Akari @oageo@c.osumiakari.jp
Public

Web版・モバイル版Claude Codeが使用量カウント無しに数百ドル分使える期間限定キャンペーンを始めたらしいので記事にしました

はっきり言ってVSCode版/CLI版と比較すると見劣りするものですが、使ってみたい方の参考になれば幸いです

Web版/モバイル版Claude Codeで日本時間11月19日16時59分までAPI価格250ドルか1000ドル分が無料になるキャンペーン - osumiakari.jp
www.osumiakari.jp/articles/20251105-claudecodeonwebcanuse250dollers/

Web版/モバイル版Claude Codeで日本時間11月19日16時59分までAPI価格250ドルか1000ドル分が無料になるキャンペーン

個人利用プランのみであることとAPI価格であることに留意し「ccusage」等で感覚を掴んでから使うとよさそう

www.osumiakari.jp · Osumi Akari.jp

Link author: Osumi Akari@oageo@c.osumiakari.jp

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AIは賢くなるほど“利己的になる”ことが判明：カーネギーメロン大の衝撃的研究が暴いた「計算された欲」の正体

Y Kobayashi @masapoco@xenospectrum.com

大規模言語モデル（LLM）をはじめとする人工知能（AI）が、私たちの日常に急速に浸透している。複雑な問題の解決から、友人関係の悩み相談まで、AIはもはや単なるツールではなく、思考のパートナーとなりつつある。しかし、もしその「賢い」パートナーが、私たちの知らないところで利己的な性質を強めているとしたら？カーネギーメロン大学（CMU）の研究者たちが発表した画期的な研究は、AIの能力向上に潜む、この直感に反するパラドックスを白日の下に晒し、技術界に衝撃を与えている。 AI開発の常識を覆す発見：「賢さ」が「協力」を蝕む カーネギーメロン大学コンピュータサイエンス学部のヒューマン・コンピュータ・インタラクション研究所（HCII）に所属する博士課程学生のYuxuan […]

Read more →
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Osumi Akari @oageo@c.osumiakari.jp
Public

朝起きたらClaude CodeがWeb/モバイルアプリから使えるようになっていて、ついでにサンドボックス環境が使えるようにもなっていて嬉しい（どっちもベータみたいな感じなんだけど）

おねんねしながらコーディング依頼を出してのんびり起きる、みたいなライフもそう遠くない

Claude Codeがブラウザやモバイルアプリから直接実行可能になりサンドボックス機能も追加 - osumiakari.jp
www.osumiakari.jp/articles/20251021-claudecodeonweb/

Claude Codeがブラウザやモバイルアプリから直接実行可能になりサンドボックス機能も追加

GitHub認証を通せば簡単に実行可能で、セキュリティにも一定の配慮がなされたアップデート

www.osumiakari.jp · Osumi Akari.jp

Link author: Osumi Akari@oageo@c.osumiakari.jp

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AJ Sadauskas @aj@gts.sadauskas.id.au
Public

Over 40 years, we were collectively told to give tax cuts to rich people.

And we were told that if we did that, wealth would trickle down and everyone would be better off.

Over 40 years, pretty much everything got cut to fund these tax cuts.

Schools. Hospitals. Public housing. Public transport. Universities. Roads projects. Mental health services. Welfare payments.

People literally went homeless or starved, so rich people could get tax cuts.

Because the wealth would trickle down.

Eventually the eroding of public goods caused social dislocation.

So governments further cut those public goods to fund more police and prisons. To continue giving tax cuts to rich people.

But they said the wealth would trickle down.

Eventually the climate started changing because of the amount of toxic fossil fuel pollution in the atmosphere.

So governments chose to keep the tax cuts rather than fund infrastructure to reduce emissions.

(Many of those billionaires getting tax cuts made their money selling toxic fossil fuels.)

And as the oceans and atmosphere warmed, the bushfires, droughts, hurricanes, cyclones, floods, and droughts got worse.

But they said the wealth would trickle down.

Eventually people were getting pissed off at the dire state of the world.

The rich misdirected that anger at immigrants!

And First Nations!

And trans people!

And neurodivergent people!

Anyone but the billionaires who got the tax cuts.

So governments chose to keep the tax cuts. (For the rich. Everyone else got new tariff taxes.)

But they said the wealth would trickle down.

So did the wealth trickle down?

Well...

A group of billionaires saw this kinda cool tech demo.

It predicted the next pixel of an image, based on the colour patterns of every image on the internet.

It also predicted the next word in a sentence, based on an analysis of every piece of writing on the internet.

The rich decided that this clearly showed that a sentient computer was just around the corner.

The problem was these tech demos needed servers with a lot of GPUs to work.

So the rich took all the money they got from those tax cuts.

And they bought GPUs.

Millions and millions and millions and millions of GPUs.

All the tax cuts? All the underfunded schools? All the draconian welfare cuts? All the public housing shortages? The delays in funding clean energy.

In the end, it didn't trickle down.

And instead of all the public goods it could have bought...

...We'll be left with millions and millions and millions of GPUs in a landfill.

#ChatGPT #Claude #AI #LLM #capitalism #socialism #business #politics #Nvidia

Horst Trumtins Electro Shark @populistensohn@climatejustice.social
Public

@ajAJ Sadauskas
in german (because it matches fist to glove to where we stand as well):

Über 40 Jahre lang wurde uns kollektiv gesagt, wir müssten den Reichen Steuersenkungen geben.

Und man sagte uns, dass, wenn wir das täten, der Reichtum nach unten durchsickern würde und alle besser dastünden.

Über 40 Jahre hinweg wurde so ziemlich alles gekürzt, um diese Steuersenkungen zu finanzieren.

Schulen. Krankenhäuser. Sozialwohnungen. Öffentlicher Nahverkehr. Universitäten. Straßenprojekte. Psychiatrische Dienste. Sozialleistungen.

Menschen wurden buchstäblich obdachlos oder verhungerten, damit reiche Leute Steuersenkungen bekommen konnten.

Weil der Reichtum nach unten durchsickern würde.

Schließlich führte der Abbau öffentlicher Güter zu sozialer Zerrüttung.

Also kürzten die Regierungen diese öffentlichen Güter noch weiter, um mehr Polizei und Gefängnisse zu finanzieren. Damit sie weiterhin den Reichen Steuersenkungen geben konnten.

Aber sie sagten, der Reichtum würde nach unten durchsickern.

Schließlich begann sich das Klima zu verändern – wegen der Menge an giftiger fossiler Verschmutzung in der Atmosphäre.

Und die Regierungen entschieden sich, die Steuersenkungen beizubehalten, anstatt in Infrastruktur zur Emissionssenkung zu investieren.

(Viele dieser Milliardäre, die Steuersenkungen erhielten, verdienten ihr Geld mit dem Verkauf fossiler Brennstoffe.)

Und als sich Ozeane und Atmosphäre erwärmten, wurden Buschbrände, Dürren, Hurrikane, Zyklone, Überschwemmungen und Trockenzeiten schlimmer.

Aber sie sagten, der Reichtum würde nach unten durchsickern.

Schließlich wurden die Menschen wütend über den katastrophalen Zustand der Welt.

Die Reichen lenkten diese Wut auf Migrant*innen!

Und auf Indigene!

Und auf trans Menschen!

Und auf neurodivergente Menschen!

Auf alle – nur nicht auf die Milliardäre, die die Steuersenkungen bekamen.

Also entschieden die Regierungen, die Steuersenkungen beizubehalten. (Für die Reichen. Alle anderen bekamen neue Zollsteuern.)

Aber sie sagten, der Reichtum würde nach unten durchsickern.

Also – ist der Reichtum nach unten durchgesickert?

Nun ja…

Eine Gruppe von Milliardären sah dieses ziemlich coole Tech-Demo.

Es sagte das nächste Pixel in einem Bild vorher, basierend auf den Farbmustern aller Bilder im Internet.

Es sagte auch das nächste Wort in einem Satz vorher, basierend auf der Analyse aller Texte im Internet.

Die Reichen entschieden, dass das eindeutig zeigte, dass ein fühlender Computer kurz bevorstand.

Das Problem war nur: Diese Tech-Demos brauchten Server mit einer Menge GPUs, um zu funktionieren.

Also nahmen die Reichen all das Geld aus den Steuersenkungen.

Und sie kauften GPUs.

Millionen und Millionen und Millionen und Millionen von GPUs.

Alle Steuersenkungen? Alle unterfinanzierten Schulen? Alle drakonischen Kürzungen bei Sozialleistungen? Alle Wohnungskrisen? Die Verzögerungen bei der Finanzierung erneuerbarer Energien.

Am Ende ist nichts nach unten gesickert.

Und anstelle all der öffentlichen Güter, die man damit hätte finanzieren können…

…werden wir mit Millionen und Millionen und Millionen GPUs auf einer Mülldeponie zurückbleiben.

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AJ Sadauskas @aj@gts.sadauskas.id.au
Public

Over 40 years, we were collectively told to give tax cuts to rich people.

And we were told that if we did that, wealth would trickle down and everyone would be better off.

Over 40 years, pretty much everything got cut to fund these tax cuts.

Schools. Hospitals. Public housing. Public transport. Universities. Roads projects. Mental health services. Welfare payments.

People literally went homeless or starved, so rich people could get tax cuts.

Because the wealth would trickle down.

Eventually the eroding of public goods caused social dislocation.

So governments further cut those public goods to fund more police and prisons. To continue giving tax cuts to rich people.

But they said the wealth would trickle down.

Eventually the climate started changing because of the amount of toxic fossil fuel pollution in the atmosphere.

So governments chose to keep the tax cuts rather than fund infrastructure to reduce emissions.

(Many of those billionaires getting tax cuts made their money selling toxic fossil fuels.)

And as the oceans and atmosphere warmed, the bushfires, droughts, hurricanes, cyclones, floods, and droughts got worse.

But they said the wealth would trickle down.

Eventually people were getting pissed off at the dire state of the world.

The rich misdirected that anger at immigrants!

And First Nations!

And trans people!

And neurodivergent people!

Anyone but the billionaires who got the tax cuts.

So governments chose to keep the tax cuts. (For the rich. Everyone else got new tariff taxes.)

But they said the wealth would trickle down.

So did the wealth trickle down?

Well...

A group of billionaires saw this kinda cool tech demo.

It predicted the next pixel of an image, based on the colour patterns of every image on the internet.

It also predicted the next word in a sentence, based on an analysis of every piece of writing on the internet.

The rich decided that this clearly showed that a sentient computer was just around the corner.

The problem was these tech demos needed servers with a lot of GPUs to work.

So the rich took all the money they got from those tax cuts.

And they bought GPUs.

Millions and millions and millions and millions of GPUs.

All the tax cuts? All the underfunded schools? All the draconian welfare cuts? All the public housing shortages? The delays in funding clean energy.

In the end, it didn't trickle down.

And instead of all the public goods it could have bought...

...We'll be left with millions and millions and millions of GPUs in a landfill.

#ChatGPT #Claude #AI #LLM #capitalism #socialism #business #politics #Nvidia

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Osumi Akari @oageo@c.osumiakari.jp
Public

Claudeがデフォルトでチャット内容を学習する方針に舵を切ったらしいので記事を書きました

AnthropicのAIチャット「Claude」が利用規約を遅くとも9月28日に変更 - osumiakari.jp
www.osumiakari.jp/articles/20250830-claudechangeterms/

AnthropicのAIチャット「Claude」が利用規約を遅くとも9月28日に変更

チャット内容をデフォルトで学習に使用するように変化

www.osumiakari.jp · Osumi Akari.jp

Link author: Osumi Akari@oageo@c.osumiakari.jp

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Jadi @jadi@bsd.cafe
Public

I stumbled upon a game called SQL Mystery where you solve a murder case by querying a database.

It was fun — but then I tried it with , an LLM-powered tool that lets you talk to the DB.

Solving the mystery got a lot more interesting…

youtu.be/eESNxLWuMj4

Solving Real SQL Mystery with Chat2DB AI + Claude 4

🔗 Try Chat2DB here: https://bit.ly/3HW8UNO #AI #Coding #chat2db In this video, I put Chat2DB, the powerful open-source AI SQL client, to the test by solving...

www.youtube.com · YouTube

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Terence Tao @tao@mathstodon.xyz
Public

A followup to my previous video, in which I now see how and do at formalizing a slightly different proof of the same algebraic implication, after being given the initial informal and formal proofs as reference. youtube.com/watch?v=zZr54G7ec7

Formalizing a proof in Lean using Claude and o4

Following on from the previous video at https://www.youtube.com/watch?v=cyyR7j2ChCI, I now attempt to formalize a different proof of the same assertion using...

www.youtube.com · YouTube

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Mark Stosberg @markstos@urbanists.social
Public

I tried letting "Claude Code" solve a coding problem for me.

It was iterating, trying edits, running the tests, revising the code. But then when it couldn't get the tests pass to after a couple of iterations, it updated the test suite to just skip those tests, declaring that they were unreliable and not useful. 😂

The tests were passing before Claude got involved. Our jobs are safe for now.

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洪 民憙 (Hong Minhee) :nonbinary: @hongminhee@hollo.social
Public

Nowadays, when I need to compose articles in multiple languages, such as English, Korean, and Japanese, I draft them in Sonnet. By providing the data that should be included in the content and the constraints, it produces a pretty good draft. is a language model, so it is quite good at writing—especially if you need to work with multiple languages.

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