The Archive

Just curious, any one have insight on Dario Amodei's leadership style. Obviously countless things have been written about Musk's style (as well as other founders like Bezos and what not) but given Anthropic being the first to reach profitability out of the AI providers, I am curious to hear about how he got there. I am playing around with different management styles in my head but wanted to know more about Dario's method, given that he also was able to build Anthropic in a more ethical way. I feel like a lot of the 'win at all cost' CEOs get more attention so I want to hear more about othe...

Provided in both Safetensors and GGUFs. Safetensors, llmfan46/Gemma-4-Harmonia-31B-it-uncensored-heretic: [https://huggingface.co/llmfan46/Gemma-4-Harmonia-31B-uncensored-heretic](https://huggingface.co/llmfan46/Gemma-4-Harmonia-31B-uncensored-heretic) GGUFs, llmfan46/Gemma-4-Harmonia-31B-it-uncensored-heretic-GGUF: [https://huggingface.co/llmfan46/Gemma-4-Harmonia-31B-uncensored-heretic-GGUF](https://huggingface.co/llmfan46/Gemma-4-Harmonia-31B-uncensored-heretic-GGUF) Comes with benchmark too. Find all my models here: [HuggingFace-LLMFan46](https://huggingface.co/llmfan46/models) The o...

Worth taking a look to see if this affects any of you. Surprised nobody has posted it yet.

From the website, it touts: * Contamination free: Tasks are written from scratch, not adapted from existing commits or PRs, so no model has seen the solution during pretraining. * High diversity: Tasks span a broad pool of 91 repositories across 5 languages. * Real-world complexity: Prompts are ~half the length of SWE-bench Pro's, yet solutions require 5.5x more code and ~2x more output tokens. * Reliable verification: Verifiers are hand-written to test software behavior rather than implementation details. And the scores match more with actual experiences when using an LLM to do real codin...

Link: deepswe.datacurve.ai

Google is embarrassing itself, again.

Discover how AI supports business intelligence, key enterprise use cases, and what teams should consider before adopting AI-powered BI tools.

A specialized translation model leverages RWS’ global language and cultural expertise and Cohere’s Command A+ model to power the new Language Weaver Pro.

Delivers advanced reasoning with a minimal compute footprint. Command A+ offers full data sovereignty for governments and regulated industries worldwide.

Explore common AI governance challenges and how enterprises can maintain visibility, accountability, and control as AI adoption expands.

Learn how Model Context Protocol works and how enterprises can use MCP to connect AI applications to data, tools, and business systems.

MUFG uses ChatGPT Enterprise to build an AI-native organization, improve workflows, and deliver new AI-powered financial services at scale.

Explore OpenAI’s Frontier Governance Framework and how our AI safety, security, and risk practices align with emerging EU and California regulations.

sqlite AGENTS.md SQLite gained an AGENTS.md file five days ago - but it's not intended for their own development, it's presumably aimed at people who are pointing agents at the SQLite codebase. It includes: SQLite does not accept pull requests without prior agreement and/or accompanying legal paperwork that places the pull request in the public domain. However, the human SQLite developers will review a concise and well-written pull request as a proof-of-concept prior to reimplementing the changes themselves. SQLite does not accept agentic code. However the project will accept agentic bug repo...

I met Katrin from Squeez Labs at an event hosted by Pathway AI (the team behind Baby Dragon Hatchling) where she told me about CrankGPT, a literally hand-cranked device for running local LLMs. It's apparently real. It's appearently launched. It's apparently glorious. Check it out at [https://crankgpt.com/](https://crankgpt.com/) \- if anyone from Squeez Labs posts here and I'm stealing their thunder, I'll take the post down! But I've been really excited about this. So local you gotta squeez it with yer own armz. ;) [https://www.youtube.com/watch?v=HSapdLYpmWY](https://www.youtube.com/watch?...

The cold-start problem In production inference deployments, demand fluctuates over time, requiring inference replicas to scale elastically. However,... In production inference deployments, demand fluctuates over time, requiring inference replicas to scale elastically. However, cold-starting inference workloads on Kubernetes can take several minutes. During that time, GPUs are allocated but idle, generating no tokens and serving no requests. This delay increases the risk of service level agreement (SLA) violations during traffic spikes… Source

I had an essay prepared that I was going to share with you all but I think I just want to be honest and speak from my heart and personal experience. The first time I got black out drunk, I was 17 years old. I was at home and feeling isolated and lonely and not good enough, as teenagers sometimes do. My parents weren't home, so I went to the kitchen and grabbed a bottle of wine, and drank it all. I don't drink alcohol often, but I still have a drinking problem because I am someone who has, for most of my life, used alcohol to drown my bad days and my bad feelings. Earlier this year, I was at...

The weekly usage of Claude Design was too small, so I think this is a good thing.

With the OS I can ask Claude "what did I spend on coffee in 2022" and get back "$847 across 213 transactions, mostly Blue Bottle and Verve". Name me one expense tracking SaaS that can do that! And its not just my financials, my OS contains everything about my life in one place so Claude can reason about it. I've been building this incrementally for a few months. Its just a small web app on Cloudflare that holds my entire life: * bank transactions from Chase, Apple Card, BoA business * every receipt out of Gmail going back to 2019 * legal filings for my green card (I-140 still pending lol),...

no more separate usage limits.

We're opening a new office in Milan, our sixth in Europe.

This was super fun to build and I love watching as I slowly eat away at my quota. Just a simple Raspberry Pi 3 + 3D printed case + 640x480 LCD and some pygame code and you too can have a little dashboard on your desk to watch your tokenmaxxing progress (or lack there off like me). [https://github.com/fuziontech/claude-quota-display](https://github.com/fuziontech/claude-quota-display)

Link: global.fujitsu

Posted this to r/MachineLearning a couple weeks ago (30K views, 100+ upvotes) and have been meaning to share it here where the fine-tuning angle is more directly relevant. I spent years building and processing a complete Usenet corpus from 1980 to 2013. Here’s why it might matter for local model work specifically: Zero AI contamination. Every post predates LLMs by decades. Training on this won’t bake in GPT mannerisms, refusal patterns, or RLHF artifacts. It’s raw human writing - argumentative, unfiltered, stylistically diverse across 33 years. Pre-SEO, pre-algorithm internet. People wrot...

Anthropic recently published an incredibly deep breakdown analyzing millions of real human-agent tool calls across their public API, and they shared a breakdown of where these agents are being deployed. They said “Software engineering makes up roughly 50% of all agentic activity on their platform”. Everything else: sales, marketing, finance, legal is sitting down in the single digits. A lot of the initial commentary around this has been along the lines of: *"Oh, look, AI agents only work for coding. They haven't cracked the rest of the enterprise yet."* But if you’ve tried to build and dep...

Snowflake has signed a new, enormous five-year deal with Amazon to secure chips for AI usage. Nvidia is once again being put on notice.

Large language models (LLMs) are revolutionizing the financial trading landscape by enabling sophisticated analysis of vast amounts of unstructured data to... Large language models (LLMs) are revolutionizing the financial trading landscape by enabling sophisticated analysis of vast amounts of unstructured data to generate actionable trading insights. These advanced AI systems can process financial news, social media sentiment, earnings reports, and market data to predict stock price movements and automate investment strategies with unprecedented… Source

Nvidia will invest $150 billion a year to make Taiwan an AI “epicenter.”

A while back I wrote a post on r/wallstreetbets about why Anthropic's revenue story doesn't hold up the way the headlines suggest. It got removed because you can't take positions in a private company. But the core argument is playing out now, so I want to share it here for discussion. URL of the removed post: [https://www.reddit.com/r/wallstreetbets/comments/1sxdjt5/if\_anthropic\_goes\_public\_this\_year\_its\_gonna\_be](https://www.reddit.com/r/wallstreetbets/comments/1sxdjt5/if_anthropic_goes_public_this_year_its_gonna_be) The thesis was simple: From my circles in tech scene in Berlin...

Payroll service provider Remote recently surpassed $300 million in annual recurring revenue (ARR) and became cash-flow positive, thanks to a 50% increase in revenue per employee resulting from AI adoption.