CEO @323Works Experienced Technology Entrepreneur. I love helping people use technology to grow their business. I'm blessed with a fantastic family.
Charleston, WV
Joined August 2007
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- Following7.3K
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Paul Helmick retweeted
They did it! SpaceX has just caught their Starship rocket for the first time ever, marking the first recovery of a conventional orbital rocket upper stage in history!
This is one of the greatest engineering achievements in history. Congrats to the entire @SpaceX team! 🚀
Paul Helmick retweeted
There are 5 levels of owning a business, decide which level you’re building toward:
Level 1 - it makes sales
Level 2 - it makes a profit
Level 3 - it pays you well
Level 4 - it pays you well w/o constant stress
Level 5 - it runs so well someone pays to buy it
Paul Helmick retweeted
“Goals are for people who care about winning once.
Systems are for people who care about winning repeatedly.”
— James Clear
Paul Helmick retweeted
这一条我建议你收藏😋
你刷到的那些 AI 大新闻，很多都不是官号先发的，而是这 20 个人先发的 🔥🔥🔥
想比别人早一步知道御三家又憋了什么大招，下面这些号直接关注！
OpenAI
Tibo 哥，做 Codex 和 ChatGPT，Codex 额度、以前的 Reset 按钮掌控者
👉 teapaw.org/thsottiaux
Alexander Embiricos，也在做 Codex，新功能和背后的产品思路他会讲得很细
👉 teapaw.org/embirico
Cat姐，以前做 Claude Code，现在跳到 OpenAI 做核心产品，两家产品动向都能从她这里看到
👉 teapaw.org/_catwu
Sam Altman，大版本发布和公司级消息基本是他先放
👉 teapaw.org/sama
Greg Brockman，OpenAI 总裁，发布当天常常补技术细节
👉 teapaw.org/gdb
Anthropic
Boris Cherny，做 Claude Code 的核心人物，新功能会第一时间转发加讲解
👉 teapaw.org/bcherny
Noah Zweben，Claude Code 产品经理，新功能和集成有问题找他答疑最快
👉 teapaw.org/noahzweben
Ado，管 Claude 开发者社区，天天发新功能演示和用法技巧
👉 teapaw.org/adocomplete
Alex Albert，在 Anthropic 做研究，经常预告模型和产品动向
👉 teapaw.org/alexalbert__
Sholto Douglas，做强化学习规模化的研究员，想知道模型能力往哪走就看他
👉 teapaw.org/_sholtodouglas
Google
Varun Mohan，Windsurf 创始人，现在带 Antigravity，功能问题他会直接回
👉 teapaw.org/_mohansolo
Kevin Hou，Antigravity 产品工程负责人，新版本新功能第一手发
👉 teapaw.org/kevinhou22
Logan Kilpatrick，管 Gemini API 和 AI Studio，新模型基本先从他这里冒出来
👉 teapaw.org/OfficialLoganK
Josh Woodward，Gemini App 和 Google Labs 的 VP，App 新功能和 Labs 实验品他先预告
👉 teapaw.org/joshwoodward
Demis Hassabis，DeepMind 联合创始人，大模型发布他会亲自下场
👉 teapaw.org/demishassabis
爆料和汇总
TestingCatalog，专扒灰度中、还没上线的功能，爆料量最大
👉 teapaw.org/testingcatalog
Tibor Blaho，从 ChatGPT 和 Claude 的网页和 App 代码里扒新功能
👉 teapaw.org/btibor91
Lumina，爆模型代号，也跑基准测试
👉 teapaw.org/LuminaBench
Legit，常扒 API 里藏的模型代号
👉 teapaw.org/legit_api
Chubby，高频汇总号，懒得一个个关注就关他一个
👉 teapaw.org/kimmonismus
先 mark 住，下次看到大新闻就知道源头在哪了
Paul Helmick retweeted
Real wealth is having time for the people you love, and the energy to enjoy it.
Paul Helmick retweeted
All employees come in 5 levels, choose wisely:
Level 1 - tells you there's a problem
Level 2 - tells you there's a problem and what caused it
Level 3 - tells you there's a problem, what caused it, and options to fix it
Level 4 - tells you there's a problem, what caused it, options to fix it, and which one they'd pick
Level 5 - tells you there was a problem, what caused it, how they fixed it, and future proof’d it
Paul Helmick retweeted
OpenAI's computer-using agents can now operate almost any app the way a person does, clicking and typing through software that never got an API, and the team building them says they're close to beating expert humans on speed.
Ari Weinstein works on OpenAI's consumer computer use products, and James Sun works on the enterprise side. Both were startup founders before joining OpenAI.
They join a16z's Seema Amble and Fabrizio Serafini to discuss what OpenAI's Astra model changed for computer use, the controls enterprises need for agents they can no longer watch, why computer use works as a universal API for legacy ERPs and finance systems, and why they think cheap software will push UI to get better and more personal.
0:50 What Astra changed for computer use
3:23 Consumer vs. enterprise computer use
5:43 How James runs his workday with Dots
8:06 When computer use becomes superhuman
10:01 How much autonomy to give agents
11:36 What agents mean for ad-supported sites
13:51 Computer use as the universal API
17:21 Getting enterprises to trust agents
20:22 Why the best use cases are the boring ones
25:37 Why UI isn't going away
32:38 Advice for founders building on agents
37:31 Making computer use feel coherent
40:57 Computer use's scaling moment
YouTube: youtu.be/9v42ZOdiBJY
@AriX @JamesZmSun @OpenAI @seema_amble @fabserafini
Paul Helmick retweeted
11 million volunteers have unknowingly built one of the world’s most valuable AI datasets.
Most people think of OpenStreetMap as a free alternative to Google Maps. A new paper in Scientific Reports argues it has become something much bigger: the shared geographic layer that multiple AI systems can build on.
The researchers combined OpenStreetMap with satellite imagery, demographic data and environmental records to tackle four completely different urban planning problems. They classified land use, detected buildings, predicted traffic and forecast air quality, all within a single framework.
Instead of forcing one large model to do everything, they used specialist models for each task. A CNN classified land use, a U-Net mapped building footprints, an LSTM predicted traffic, and a hybrid CNN-RNN forecast air pollution. The common thread wasn’t the models. It was the map underneath them.
The results were strong. Land use classification reached 91.6% accuracy, building detection reached 94.0%, traffic prediction achieved an error of just 3.6 vehicles per hour, and air quality forecasts were within 2.3 µg/m³.
What’s pretty remarkable is where that map came from.
OpenStreetMap wasn’t built by a government agency or a technology company. More than 11 million volunteers have spent years mapping roads, buildings, footpaths, parks, bus stops and cycle lanes. Every edit adds another piece of structured geographic data that AI systems can learn from.
That changes the economics of urban AI. Instead of relying on expensive proprietary mapping databases that are updated on commercial schedules, researchers can build on a living dataset that evolves every day as contributors map the world around them.
The study focused on Krasnodar, but the framework was designed to transfer to other cities with different layouts and data quality. The individual models may change over time. The shared geographic foundation is likely to remain.
People often describe foundation models as systems trained on text, images or code. Geography may deserve a place on that list.
As more of the physical world becomes machine-readable, maps stop being navigation tools, and become infrastructure for AI.
Link to full paper: nature.com/articles/s41598-0…
Paul Helmick retweeted
The End of the Internet
The old Internet, where anyone could host a server is over, but it’s just the final blow in an ending that has been coming for years. The future, though, is brighter than it appears.
stratechery.com/2026/the-end…
Paul Helmick retweeted
Data center developers have announced more than 100 GW of their own power plants. That's equivalent to the power demand of 10 New York Cities.
The growth of this trend forced our team at Cleanview to rethink how we track them.
Our original plan was to publish a quarterly report on this topic. But we soon realized this was too infrequent given the speed at which this trend was evolving.
To illustrate what I mean, consider a few data points:
- The amount of operating behind-the-meter capacity has nearly doubled since we published our last report.
- Capacity under construction has roughly quadrupled.
- Anthropic has gone from an insignificant buyer of behind-the-meter gas power to one of the largest.
So we decided to scrap our original plan and build something much better. Today we’re excited to announce Cleanview's live behind-the-meter gas plant tracker. It covers more than 100 gas plants built to power data centers, and we update it every day.
Over the coming weeks, I plan to share insights from this growing dataset. In the meantime, if you’d like to see the new product or connect with our team, send us a note.
Paul Helmick retweeted
Your mindset is one of the most powerful tools you possess.
When you know your worth, have clarity about your goals, and believe in what's possible, you begin to see opportunities where others are very likely to see obstacles.
Paul Helmick retweeted
I wish I were 18 today... If you ARE young and reading this, the most accomplished people alive envy your starting position. The tools are becoming free, the problems are enormous, and this time you don't need to ask for permission.
Go change the world!
Paul Helmick retweeted
Jamie Dimon calls AI an unstoppable industrial revolution moving like a "tsunami," and says it can now do things that were unimaginable five weeks ago
“Oh, definitely the equivalent of the Industrial Revolution. It’s not even close. It’s very fast.
“You had the Industrial Revolution, electricity, steam engines and cars. Those took years. You had the internet. It took years to come in, to actually have the capital, the fiber and the computers. It took years to invent the iPhone.
“This is really fast. This is doing stuff today that no one would have imagined was possible literally five weeks ago. It’s going at that pace, so it’s more like a tsunami. It’s rolling through the system, and you can’t stop some of it.
“So it isn’t like even the regulators said, or the government said, ‘No more.’ I hate to tell you, there are hundreds of these things out there. They’re on your computer tops. There’s open source, there’s closed source, there’s open-source models. China’s doing it. A bunch of other countries are doing it.
“You can’t stop it. You just have to manage the hell out of it.”
Jamie Dimon reveals Anthropic’s Mythos increased JPMorgan’s biggest risk tenfold
“Oh, yeah. That’s what I’m saying. Mythos—whatever you thought it was before—when I published my chairman’s letter, I said cyber was our biggest risk, and they hadn’t published Mythos yet. I would say that went up tenfold after Mythos.”