Lucas wang

Think Python Book for FREE! To get your copy, do the following. - Like and Repost - Comment "Python" - Follow me so that I can DM you.

@python_spaces python

Lowk apple notes and notion is like the GOAT in managing a good personal system

@seungkwonson @michaelbaum @hoomanrenezhad @khawajasn @gustai hey i m interested could I dm you further details?

Thanks @michaelbaum, @hoomanrenezhad, @khawajasn, @gustai for helping put this together.

Launching the Alive Prize. $100K to build what makes you come alive. I've been fixated on a quote from Howard Thurman lately: "Don’t ask what the world needs. Ask what makes you come alive, and go do it. Because what the world needs is people who have come alive." We want to help more people find that feeling. aliveprize.com

Should I post weekly or daily, give some opinions.

@XiangruTang 有多大的吗？

小红书上的北美教授红黑榜 #heading=h.6pyxgqw8wy3" target="_blank" rel="nofollow noopener">docs.google.com/document/d/1-A… 其实没有绝对的红和绝对的黑 读phd不容易 做教授也不容易 大家应该互相理解 找到平衡，找到适合自己的组才是最重要的

@rohanthmarem @vercel @v0 @teenbuilders_ Count me in

hosting a @vercel @v0 build night this friday 4 hour build night use v0 platform to create something agentic free credits + merch happening at stan hq, downtown toronto reply or dm if you want in

@rohanthmarem @vercel @v0 @teenbuilders_ Yooo bet

@DevGohi79892783 I agree, like I have several projects to work on but I tend be over emotional at times with the progress so I avoid work by consuming social media content

@SystemsWang That’s interesting, I’ve noticed the same thing. People think they’re productive because they consume a lot, but very little actually turns into something real. I’ve been building in that space too and it really changes how you think about what actually matters.

In today's world, our wants are magnified - especially with social media exposure - but action is misaligned. This is why I'm starting on X to officially document my journey of building a startup and a few cool projects.

@sid_srk @melanimaheswar1 Is there a sign up link

Toronto. 2 weeks, in-person. Pick a domain you don't know, learn it and build something with it. $250 to spend on whatever enables you to learn and create. 10 others doing the same beside you. Only real constraint is you have to understand what you create and share interested?

Want to break into VC? Entrepreneurs First (EF) has supported 3k+ founders of startups worth $16B+ EF is now recruiting Investment Fellows I joined the first cohort and ran Toronto events with hundreds of attendees If you want to do the same, reply/DM

@KrishivThakuria Dm

🫱 Introducing 𝐍𝐞𝐮𝐫𝐚𝐥 𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫s: 𝐰𝐡𝐚𝐭 𝐢𝐟 𝐀𝐈 𝐝𝐨𝐞𝐬 𝐧𝐨𝐭 𝐣𝐮𝐬𝐭 𝐮𝐬𝐞 𝐜𝐨𝐦𝐩𝐮𝐭𝐞𝐫𝐬 𝐛𝐞𝐭𝐭𝐞𝐫, 𝐛𝐮𝐭 𝐛𝐞𝐠𝐢𝐧𝐬 𝐭𝐨 𝐛𝐞𝐜𝐨𝐦𝐞 𝐭𝐡𝐞 𝐫𝐮𝐧𝐧𝐢𝐧𝐠 𝐜𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐢𝐭𝐬𝐞𝐥𝐟? Beyond today's conventional computers, agents, and world models, Neural Computers (NCs) are new frontiers where computation, memory, and I/O move into a learned runtime state. We ask: whether parts of runtime can move inward into the learning system itself. This is our first step toward the Completely Neural Computer (CNC): a general-purpose neural computer with stable execution, explicit reprogramming, and durable capability reuse. Work done with Mingchen Zhuge (@MingchenZhuge), Changsheng Zhao, Haozhe Liu (@HaoZhe65347 ), Zijian Zhou (@ZijianZhou524 ), Shuming Liu (@shuming96 ), Wenyi Wang (@Wenyi_AI_Wang ), Ernie Chang (@erniecyc ), Gael Le Lan, Junjie Fei, Wenxuan Zhang, Zhipeng Cai (@cai_zhipeng ), Zechun Liu (@zechunliu ), Yunyang Xiong (@YoungXiong1 ), Yining Yang, Yuandong Tian (@tydsh ), Yangyang Shi, Vikas Chandra (@vikasc), Juergen Schmidhuber (@SchmidhuberAI)

@Zukoife @nestymee But let’s connect

@nestymee Guys who also got rejected to Canopy? Let's connect!

guys who is also got accepted to Canopy? let's connect!

@Zukoife @nestymee Recently just got rejected lol

NEW paper from Meta. (bookmark this one) What if the model wasn't just using the computer, but became the computer? New research from Meta AI and KAUST makes a serious case for Neural Computers (NCs). The paper proposes NCs as learned runtimes where computation, memory, and I/O live inside a single latent state. Their first prototypes use video models to roll out terminal and GUI interfaces from prompts, pixels, and user actions. Why does it matter? Today's agents still depend on external computers to store state, execute actions, and enforce system contracts. Neural Computers point to a different machine form: one where interface dynamics, working memory, and execution are learned together. The early results are promising but grounded. CLI rendering improves, GUI cursor control reaches 98.7% with explicit visual supervision, and reprompting boosts arithmetic-probe accuracy from 4% to 83%. But symbolic reliability, stable reuse, and runtime governance remain open. This is less "agents got better" and more "what comes after agents as a computing substrate?" Paper: arxiv.org/abs/2604.06425 Learn to build effective AI agents in our academy: academy.dair.ai

@CiprianiRanieri Let’s connect and I think it would be great opportunity

I'm 28. -325 followers on x -950+ connections on linkedin -8929 subscribers on youtube (12M+ total views) -1263 followers on tiktok - Shipped 10+ projects with Lovable / Claude Code & antigravity Trust the process, and show up each day. If you are into: Ai, tech, start-ups, reply & lets connect.

One of the most though provoking points Karpathy made during the Dwarkesh podcast is that humans learn mostly from “synthetic” self generated data, ie replaying, distilling, processing recent experience.

@austinjian_ Bro is locked out