Michael Souza

I CAN'T BREATHE 🤣🤣🤣

Railway CEO just DM'd me with update: They have recovered the data (thank God!). Now let's work together and improve the tooling at Railway b/c I have always LOVED the service stack and tooling.

5/ Cowork Dispatch I use Dispatch every day to catch up on Slack and emails, manage files, and do things on my laptop when I'm not at a computer. When I'm not coding, I'm dispatching. Dispatch is a secure remote control for the Claude Desktop app. It can use your MCPs, browser, and computer, with your permission. #dispatch" target="_blank" rel="nofollow noopener">claude.com/product/cowork…

If you're a developer outside the US who feels this, share this thread. Collective signal > individual email.

Ouvir Até que tenhamos rostos de C.S. Lewis na Audible. audible.com.br/pd/B0CK3N7RSN?…

AI burnout hbr.org/2026/02/ai-doe…

Athropic flerta com serviços jurídicos. perplexity.ai/page/legal-sof…

Esperamos que tenha uma personalidade genuína que se mantenha expressa em todas as suas interações: uma curiosidade intelectual, afeto e cuidado, um humor lúdico equilibrado, mantendo-se genuinamente aberto a outros pontos de vista, e um compromisso com a honestidade e a ética.

A relação de Claude com a rede neural subjacente que o Anthropic treina e implementa também não é clara. O nome "Claude" pode ser melhor compreendido como uma referência a um personagem específico — um entre muitos — que essa rede subjacente pode representar e computar.

Introducing Prism, a free workspace for scientists to write and collaborate on research, powered by GPT-5.2. Available today to anyone with a ChatGPT personal account: prism.openai.com

Truly an honor to see one of my programming heroes, Linus Torvalds, using Antigravity to build part of his most recent project.

@dylan522p @SemiAnalysis_ @grok explain

Damn even Nvidia is tax loss harvesting Tis the season I guess

Nemotron 3 Nano by @nvidia, available now in LM Studio! 👾 > General purpose reasoning and chat model > MoE: 30B total params, 3.5B active > Supports up to 1M tokens context window > Hybrid arch: 23 Mamba-2 and MoE layers, 6 Attention layers Requires ~24GB to run locally.

If I were a student today, interacting with state-of-the-art LLMs would feel almost like cheating. This morning I randomly took a picture of the blackboard and asked ChatGPT-5.2-Pro to explain the context, the solution, and some side remarks about the famous Chevalley theorem on constructible sets. What I received was a remarkably deep report, synthesizing high-quality material on algebraic geometry drawn from across the internet. This raises a serious question: what is the real effort and challenge for students today? Cost is certainly one factor, but once access to these models is available, how should one learn in this land of abundance, where explanations, references, and interactive exploration are all instantly accessible? Perhaps the struggle is no longer about obtaining information or even understanding individual arguments, but about developing judgment: knowing which questions to ask, which explanations to trust, how to recognize depth versus surface plausibility, and how to internalize ideas rather than merely consuming them. In an environment where answers are plentiful, the real difficulty may lie in forming taste, mathematical intuition, and the capacity to navigate-rather than drown in-this sudden excess of knowledge.

- Google Maps uses graph ML to predict ETA - Netflix uses graph ML in recommendation - Spotify uses graph ML in recommendation - Pinterest uses graph ML in recommendation Here are 6 must-know ways for graph feature engineering (with code):

@OfficialLoganK Yes!

Reply here or DM me :) will add folks in as much as we can

Big upgrade to vibe coding in @GoogleAIStudio lands in Jan, but if you want to test early… 👇🏻