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Vic | funclosure

Vic | funclosure

@funclosure

@SouldaYoda of @Soulda16Club | iOS Dev | Husband | Everyone needs closure and I need a fun closure An ENFP who tested as ESFP but essentially is an introvert

nowhere 参加日 Mayıs 2020
2.2K フォロー中833 フォロワー
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Trust Wallet
Trust Wallet@TrustWallet·
Last week, AI got eyes on crypto. Today, it gets hands 🤖👐 Trust Wallet Agent Kit is live ↓🧵 portal.trustwallet.com
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Salio
Salio@Mr_Salio·
@bcherny every day now... After you joined
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Boris Cherny
Boris Cherny@bcherny·
Little known fact, the Anthropic Labs team (the team I joined Anthropic to be on) shipped: - MCP - Skills - Claude Desktop app - Claude Code It was just a few of us, shipping fast, trying to keep pace with what the model was capable of. Those early Desktop computer use prototypes, back in the Sonnet 3.6 days, felt clunky and slow. But it was easy to squint and imagine all the ways people might use it once it got really good. Fast forward to today. I am so excited to release full computer use in Cowork and Dispatch. Really excited to see what you do with it!
Claude@claudeai

You can now enable Claude to use your computer to complete tasks. It opens your apps, navigates your browser, fills in spreadsheets—anything you'd do sitting at your desk. Research preview in Claude Cowork and Claude Code, macOS only.

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Andrej Karpathy
Andrej Karpathy@karpathy·
Thank you Sarah, my pleasure to come on the pod! And happy to do some more Q&A in the replies.
sarah guo@saranormous

Caught up with @karpathy for a new @NoPriorsPod: on the phase shift in engineering, AI psychosis, claws, AutoResearch, the opportunity for a SETI-at-Home like movement in AI, the model landscape, and second order effects 02:55 - What Capability Limits Remain? 06:15 - What Mastery of Coding Agents Looks Like 11:16 - Second Order Effects of Coding Agents 15:51 - Why AutoResearch 22:45 - Relevant Skills in the AI Era 28:25 - Model Speciation 32:30 - Collaboration Surfaces for Humans and AI 37:28 - Analysis of Jobs Market Data 48:25 - Open vs. Closed Source Models 53:51 - Autonomous Robotics and Atoms 1:00:59 - MicroGPT and Agentic Education 1:05:40 - End Thoughts

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Vic | funclosure@funclosure·
很讚的interview!
张小珺 Xiaojun Zhang@zhang_benita

@sainingxie 一起挑战7小时播客!他刚和Yann LeCun踏上“世界模型”的创业旅程(AMI Labs)。这是他第一次Podcast、第一次访谈。 2026年2月雪后的一天,我们在纽约布鲁克林,从下午2点,开启了一场始料未及的马拉松式访谈,直到凌晨时分散去。 这篇访谈的中文标题叫做《逃出硅谷》,但他又不厌其烦地枚举了影响他学术生涯的每一个人,并反反复复口头描摹这些人的人物特征(侯晓迪、何恺明、杨立昆、李飞飞…)正是这些,让这篇“逃出硅谷”的对话充斥着人性的温度。 By the way, 下面是访谈的YouTube版本,我们提供了中英字幕。 And yes, 我们是在用播客给这个世界建模😎 A 7-hour podcast with Saining Xie. He has just begun a new journey on world models with Yann LeCun at AMI Labs. This was his first podcast appearance and his first long-form interview. A day after the snowfall in February 2026, in Brooklyn, New York, we started recording at 2 p.m. What followed became an unexpected marathon conversation that lasted until the early hours of the morning. The Chinese title of the interview is “Escaping Silicon Valley.” Yet throughout the conversation, he patiently listed the people who shaped his academic life, repeatedly sketching their personalities in vivid detail: Hou Xiaodi, Kaiming He, Yann LeCun, Fei-Fei Li, and others. These portraits are what give this “escape from Silicon Valley” conversation its human warmth. By the way, the YouTube version of the interview is below, with Chinese and English subtitles. And yes, we are using podcasts to model the world 😎 A 7-hour marathon interview with Saining Xie: World Models, AMI Labs, Ya... youtu.be/rIwgZWzUKm8?si… 来自 @YouTube

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Thariq
Thariq@trq212·
we need a better word than vibe coding man, Claude can create the most beautiful things
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Alejandro
Alejandro@acamposuribe·
🥁🥁 Presenting... 🥁🥁 p5.brush 2.0.0 Unlock custom brushes, natural fill effects and intuitive hatching. I'm finally adding compatibility with @p5xjs 2.0+, and - Modularity for easier open-source contributing - Better performance - Simpler usage, inheriting p5 state 🔗👇
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Alejandro@acamposuribe

🥁🥁 Presenting... 🥁🥁 p5.brush Unlock custom brushes, natural fill effects and intuitive hatching in @p5xjs! With p5.brush.js, I’m open sourcing part of my toolbox, which I’ve developed and used since the start of my coding practice. p5-brush.cargo.site Read below 🧵👇

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Claude
Claude@claudeai·
We're launching Claude Community Ambassadors. Lead local meetups, bring builders together, and partner with our team. Open to any background, anywhere in the world. Apply: claude.com/community/amba…
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Paul Hudson
Paul Hudson@twostraws·
Today I'm pleased to release an all-new agent skill for SwiftUI 🔥 It builds upon the success of the AGENTS file I released previously, adding a wider range of tips and more details too. On GitHub now! github.com/twostraws/Swif…
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Ahmad Awais
Ahmad Awais@MrAhmadAwais·
Introducing chartli 📊 CLI that turns plain numbers into terminal charts. ascii, spark, bars, columns, heatmap, unicode, braille, svg. $ 𝚗𝚙𝚡 𝚌𝚑𝚊𝚛𝚝𝚕𝚒 I wanted terminal charts with zero setup. No browser, no Python env, no matplotlib. Pipe numbers in, get a chart out. Again built using Command Code with my CLI taste. $ npx chartli data.txt -t ascii -w 24 -h 8 8 chart types spanning a fun range of Unicode density: - ascii (line charts with ○◇◆● markers) - spark (▁▂▃▄▅▆▇█ sparklines, one row per series) - bars (horizontal, ░▒▓█ shading per series) - columns (vertical grouped bars) - heatmap (2D grid, ░▒▓█ intensity mapping) - unicode (grouped bars with ▁▂▃▄▅▆▇█ sub-cell resolution) - braille (⠁⠂⠃ 2×4 dot matrix, highest density) - svg (vector output, circles or polylines) Input format is dead simple: rows of space-separated numbers. Multiple columns = multiple series. 0.0 0.1 0.1 0.1 0.2 0.4 0.2 0.4 0.3 0.2 0.4 0.2 Composes with pipes: $ cat metrics.txt | chartli -t spark S1 ▁▂▃▄▅▆ S2 ▁▄▂▇▅█ S3 ▁▂▄▃▆▅ S4 ▁▄▂▇▂▇ The braille renderer is my fav. Each braille character encodes a 2×4 dot grid, so a 16-wide chart gives you 32 pixels of horizontal resolution. Free anti-aliasing from Unicode. The bars renderer uses 4 shading levels (░▒▓█) to visually separate series without color. Works on any terminal, any font. Heatmap maps values to a 5-step intensity scale across a row×column grid, so you can spot patterns in tabular data at a glance. SVG mode has 2 render paths: circles (scatter plot) and lines (polylines). Output is valid XML you can pipe straight to a file or into another tool. Zero config by default, every dimension overridable (-w width, -h height, -m SVG mode). No config files. No themes. No dashboards. $ 𝚗𝚙𝚡 𝚌𝚑𝚊𝚛𝚝𝚕𝚒 Or global install it. $ npm i -g chartli # Skill for your agents $ npx skills add ahmadawais/chartli If you work in terminals and want quick data visualization without leaving your workflow, try it. ⌘ let's go!!
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Thariq
Thariq@trq212·
Today we're launching local scheduled tasks in Claude Code desktop. Create a schedule for tasks that you want to run regularly. They'll run as long as your computer is awake.
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Mattt
Mattt@mattt·
sosumi.ai now has a CLI ``` npx @nshipster/sosumi fetch /documentation/swift/array ``` This lets you fetch and render  Developer content directly into LLM-readable Markdown, without connecting to a remote MCP server.
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Kat ⊷ the Poet Engineer
Kat ⊷ the Poet Engineer@poetengineer__·
all my obsidian notes are now a living, digital garden 🌿🌸 each plant is a notes from a tag: older ones on the trunk, newer ones as leaves. i wanted to create a sense of tending your garden, so scrubbing the timeline lets you watch your notes grow chronologically.
Kat ⊷ the Poet Engineer@poetengineer__

i want to grow my ideas like a garden. a conceptual prototype inspired by this thread of tweets.

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Lex Fridman
Lex Fridman@lexfridman·
The power of AI agents comes from: 1. intelligence of the underlying model 2. how much access you give it to all your data 3. how much freedom & power you give it to act on your behalf I think for 2 & 3, security is the biggest problem. And very soon, if not already, security will become THE bottleneck for effectiveness and usefulness of AI agents as a whole (1-3), since intelligence is still rapidly scaling and is no-longer an obvious bottleneck for many use-cases. The more data & control you give to the AI agent: (A) the more it can help you AND (B) the more it can hurt you. A lot of tech-savvy folks are in yolo mode right now and optimizing for the former (A - usefulness) over the the latter (B - pain of cyber attacks, leaked data, etc). I think solving the AI agent security problem is the big blocker for broad adoption. And of course, this is a specific near-term instance of the broader AI safety problem. All that said, this is a super exciting time to be alive for developers. I constantly have agent loops running on programming & non-programming tasks. I'm actively using Claude Code, Codex, Cursor, and very carefully experimenting with OpenClaw. The only down-side is lack of sleep, and an anxious feeling that everyone feels of always being behind of latest state-of-the-art. But other than that, I'm walking around with a big smile on my face, loving life 🔥❤️ PS: By the way, if your intuition about any of the above is different, please lay out your thoughts on it. And if there are cool projects/approaches I should check out, let me know. I'm in full explore/experiment mode.
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Mitchell Hashimoto
Mitchell Hashimoto@mitchellh·
Ghostty will now auto-generate a full, cohesive 256-color theme from just the base 16-color palette. This makes it significantly easier to make custom themes that are beautiful (just define 16 colors). See the demo below showing multiple themes fully generated. Thanks to Jake Stewart who contributed this to Ghostty and made a nice write-up explaining the background and approach: gist.github.com/jake-stewart/0…
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Rob Zolkos
Rob Zolkos@robzolkos·
Major Claude Code policy clear up from Anthropic: "Using OAuth tokens obtained through Claude Free, Pro, or Max accounts in any other product, tool, or service — including the Agent SDK — is not permitted"
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Point-Free
Point-Free@pointfreeco·
We are hard at work on our next video series where we break down some of Swift’s most advanced features: isolation, ~Copyable, and ~Escapable. You will learn how to write code that enforces correctness and improves performance. Stay tuned!
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Joon Sung Park
Joon Sung Park@joon_s_pk·
Introducing Simile. Simulating human behavior is one of the most consequential and technically difficult problems of our time. We raised $100M from Index, Hanabi, A* BCV, @karpathy @drfeifei @adamdangelo @rauchg @scottbelsky among others.
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