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Stone Soup AI (2024)
For some time, I’ve argued that a common conception of AI is misguided. This is the idea that AI systems like large language and vision models are individual intelligent agents, analogous to human agents. Instead, I’ve argued that these models are “cultural technologies” like writing, print, pictures, libraries…
933
George Eliot's reflections on AGI from 1879
Forgotten musings on the economics of AI, an intelligence explosion, and machine consciousness
934
Mistral Saba
The most powerful AI platform for enterprises. Customize, fine-tune, and deploy AI assistants, autonomous agents, and multimodal AI with open models.
935
AI vending machine was tricked into giving away everything
Anthropic installed an AI-powered vending machine in the WSJ office. The LLM, named Claudius, was responsible for autonomously purchasing inventory from wholesa
936
The Future of Compute: Nvidia's Crown Is Slipping
Demand consolidation, changing compute mix, custom silicon, and distributed training will hurt NVIDIA's pole position.
937
Sprinkling self-doubt on ChatGPT
I replaced my ChatGPT personalization settings with this prompt a few weeks ago and promptly forgot about it: Be extraordinarily skeptical of your own…
938
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The Bitter Lesson of LLM Extensions
From ChatGPT Plugins to Agent Skills, a look at how we've been trying (and failing) to extend LLMs for the last three years.
940
LLM Observability in the Wild – Why OpenTelemetry Should Be the Standard
LLM Observability breaks in wild today as new libraries like OpenInference don't adhere to OpenTelemetry standards leading to silos and suboptimal performance for users who want to tie LLM observability with rest of their observability stack
941
RustAssistant: Using LLMs to Fix Compilation Errors in Rust Code
The Rust programming language, with its safety guarantees, has established itself as a viable choice for low-level systems programming language over the traditional, unsafe alternatives like C/C++. These guarantees come from a strong ownership-based type system, as well as primitive support for features like closures…
942
Get an AI code review in 10 seconds
Personal Musings and Transcripts
943
Gemini 2.5 Pro reasons about task feasibility
... in which a surprisingly reflective AI tells me no (for good reasons) ...
944
Bot or human? Creating an invisible Turing test for the internet
Behavioral and cognitive patterns distinguish humans from bots. Explore interactive demos and a practical framework for invisible Proof of Human.
945
Detecting and countering misuse of AI
Anthropic's August 2025 threat intelligence report on AI cybercrime and other abuses.
946
A bubble that knows it's a bubble
Railway Mania, dot-com, AI. Technology bubbles follow a pattern older than any of them. What's different this time is that everyone knows the script.
947
Why Fei-Fei Li and Yann LeCun are both betting on "world models"
Gaussian splats, SIMA 2, JEPA and Genie 3 — and why “world model” now means three very different things at once.
948
If a Meta AI model can read a brain-wide signal, why wouldn't the brain?
In 2023, Meta researchers were able to decode images in thoughts from the brain's magnetic fields. What if that's how the brain coordinates it's own global state?
949
Claude Code vs. Codex: I built a sentiment dashboard from Reddit comments
I scraped hundreds of Reddit comments that compare Claude Code and Codex, and used Claude Haiku to build a sentiment analysis dashboard. The dashboard and my interpretations are shared here.
950
From LLM to AI Agent: What's the Real Journey Behind AI System Development?
Confused by LLMs, RAG, & AI Agents? We break down the spectrum of AI system design with a familiar resume-screening example to show the leap in capabilities (and complexity) at each level.
951
The Math Behind GANs (2020)
Generative Adversarial Networks refer to a family of generative models that seek to discover the underlying distribution behind a certain data generating process. This distribution is discovered through an adversarial competition between a generator and a discriminator. As we saw in an earlier introductory post on…
952
ChatGPT Saved My Life (no, seriously, I'm writing this from the ER)
How using AI as a bridge when doctors aren't available can improve patient-to-doctor communications in real time emergencies
953
LLMs tell bad jokes because they avoid surprises
LLMs suck at comedy, art, journalism, research, and science for the same fundamental reason
954
Grok 4.1
Grok 4.1 is now available to all users on grok.com, 𝕏, and the iOS and Android apps. It is rolling out immediately in Auto mode and can be selected explicitly as “Grok 4.1” in the model picker.
955
What's working for YC companies since the AI boom
The goal of this analysis was to understand what’s working for YC companies by looking at which ones have raised Series A rounds.
956
Is Lovable getting monetization wrong?
The current (and future) monetization strategies of "Shopify for SaaS"
957
No clicks, no content: The unsustainable future of AI search
AI companies are causing a content drought that will eventually starve them.
958
Why OpenAI's $157B valuation misreads AI's future (Oct 2024)
I break down the logic behind the company's towering price tag and why I think the most valuable AI companies have yet to be built.
959
Wasting Inferences with Aider
Auto-Fixing Bugs from Asana (for 9 cents!)
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Bitter Lesson is about AI agents
The Race for AI Progress In 2019, Richard Sutton, wrote his groundbreaking essay titled ‘The Bitter Lesson’. Simply put, the essay concludes that systems which get better with higher compute beat the systems that do not. Or specifically in AI: raw computing power consistently wins over intricate human-designed…