AI Entrepreneur / AI Educator / Ironman Fan I'm AI "mechanics", I test and unlock its full potential Agents, models, physical AI, infrastructure.
Joined October 2019
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AI is very intelligent now. But how useful is it actually?
The real test isn’t how smart it sounds - It’s what happens after you clearly tell it what needs to be done.
Does it actually get done? Or do you still end up fixing, prompting, checking, and finishing it yourself?
I’m documenting the gap between impressive intelligence and real usefulness — with actual results, honest insights, and unfiltered reviews.
What task have you given AI that it completely failed… or surprisingly finished?
🤖 Made with AI
Aiden Frontier retweeted
Why Is No One Afraid of AI World Models Replacing Game Engines?
The past two days have been pretty interesting for both Silicon Valley and Wall Street.
First, @GoogleDeepMind showcased Genie 4, a world model capable of real-time keyboard controls and synchronized visuals and audio. Then, just three hours before its earnings report, Google rushed to announce Gemini 4 Carbon, claiming it had topped the benchmark rankings.
When Alphabet finally released its Q3 earnings, the stock plunged more than 10% in after-hours trading.
But here's what's even more interesting.
Back in January, @Google 's Project Genie announcement sent @unity shares crashing 24%, as investors feared AI-generated worlds could make traditional game engines obsolete.
This time? Unity's stock barely reacted.
So what changed?
🤖 Made with AI
Why Is No One Afraid of AI World Models Replacing Game Engines?
The past two days have been pretty interesting for both Silicon Valley and Wall Street.
First, @GoogleDeepMind showcased Genie 4, a world model capable of real-time keyboard controls and synchronized visuals and audio. Then, just three hours before its earnings report, Google rushed to announce Gemini 4 Carbon, claiming it had topped the benchmark rankings.
When Alphabet finally released its Q3 earnings, the stock plunged more than 10% in after-hours trading.
But here's what's even more interesting.
Back in January, @Google 's Project Genie announcement sent @unity shares crashing 24%, as investors feared AI-generated worlds could make traditional game engines obsolete.
This time? Unity's stock barely reacted.
So what changed?
🤖 Made with AI
Aiden Frontier retweeted
看到人们为在Macbook上一枚发光苹果标志的回归欢呼雀跃，甚至比其技术与功能上的实质进步更令他们兴奋，我感到有些悲哀。
@Apple拥有堪称艺术品的设计。但它的艺术性，从来不只在于独具一格的外观，更在于设计背后推动时代的灵感，以及挑战成见、坚持自己判断的那份偏执。那些美好的设计之所以令人难忘，是因为它们曾与新的可能一同到来。
发光的苹果标志是否值得值得怀念，答案是当然。只是，当怀旧成了最令人兴奋的卖点，我禁不住在想：我们对苹果的期待，什么时候从“它将带来什么”，变成了“它能还给我们什么”？
我期待那枚标志重新亮起，也期待它背后的创造力，再次让人眼前一亮。
@johnternus brings the led logo back to Macbook, when does @Apple plan to put it on a mobile device? An iPhone with led Logo perhaps
Aiden Frontier retweeted
Unfortunately, thinking outside of the box has never been a strength possessed by Artificial Intelligence yet.
>0% is still hopeful, but I can only imagine AI being creative in the next 5 years
AI 真的能像科学家一样，自主发现未知的物理规律吗？
最新研究 LongChang（龙场）构建了 14 个物理规律被改写的模拟世界，让 12 个大模型自主观察、提出假设并设计实验。
📊 结果令人意外：
GPT-6-Astra：规律发现率 16.7%
其余 11 个模型：全部 0%
增加实验预算也并未改善发现率
一直以来，无法跳出框架思考仍然是 AI 饱受诟病的问题之一
AI 距离真正的自主科学发现，还有很长的路要走。
📄 Paper: arxiv.org/abs/2610.37649
🔗 GitHub: github.com/EnVision-Research…
Unfortunately, thinking outside of the box has never been a strength possessed by Artificial Intelligence yet.
>0% is still hopeful, but I can only imagine AI being creative in the next 5 years
AI 真的能像科学家一样，自主发现未知的物理规律吗？
最新研究 LongChang（龙场）构建了 14 个物理规律被改写的模拟世界，让 12 个大模型自主观察、提出假设并设计实验。
📊 结果令人意外：
GPT-6-Astra：规律发现率 16.7%
其余 11 个模型：全部 0%
增加实验预算也并未改善发现率
一直以来，无法跳出框架思考仍然是 AI 饱受诟病的问题之一
AI 距离真正的自主科学发现，还有很长的路要走。
📄 Paper: arxiv.org/abs/2610.37649
🔗 GitHub: github.com/EnVision-Research…
With @OpenAI’s GPT-6.1 Terra now available, I asked ChatGPT how it would describe the difference between Astra 6, Sol 6.1, and Terra 6.1.
My Takeaways:
🧠 Astra: the deep thinker
🛠️ Sol: the everyday all-rounder
🎯 Terra: the practical executor
Which has been your go-to?
GPT-6.1 Terra was just introduced by @OpenAI, delivering superior performance at a significantly lower cost.
As AI developers continue advancing their models, a couple of things remain unchanged:
1. Diminishing returns: Higher spending doesn't guarantee proportional performance gains. GPT-6 Astra costs significantly more while delivering comparable results.
2. Top performance comes at a premium: Claude Opus 5.5 leads with approximately 63%, but at nearly $9, its cost-effectiveness remains questionable.
GPT-6.1 Terra was just introduced by @OpenAI, delivering superior performance at a significantly lower cost.
As AI developers continue advancing their models, a couple of things remain unchanged:
1. Diminishing returns: Higher spending doesn't guarantee proportional performance gains. GPT-6 Astra costs significantly more while delivering comparable results.
2. Top performance comes at a premium: Claude Opus 5.5 leads with approximately 63%, but at nearly $9, its cost-effectiveness remains questionable.
Here is the original post teapawt.org/OpenAI/status/21147807…
Aiden Frontier retweeted
AI 真的能像科学家一样，自主发现未知的物理规律吗？
最新研究 LongChang（龙场）构建了 14 个物理规律被改写的模拟世界，让 12 个大模型自主观察、提出假设并设计实验。
📊 结果令人意外：
GPT-6-Astra：规律发现率 16.7%
其余 11 个模型：全部 0%
增加实验预算也并未改善发现率
一直以来，无法跳出框架思考仍然是 AI 饱受诟病的问题之一
AI 距离真正的自主科学发现，还有很长的路要走。
📄 Paper: arxiv.org/abs/2610.37649
🔗 GitHub: github.com/EnVision-Research…
Aiden Frontier retweeted
With @OpenAI’s GPT-6.1 Terra now available, I asked ChatGPT how it would describe the difference between Astra 6, Sol 6.1, and Terra 6.1.
My Takeaways:
🧠 Astra: the deep thinker
🛠️ Sol: the everyday all-rounder
🎯 Terra: the practical executor
Which has been your go-to?
Aiden Frontier retweeted
iPhone Duo的问世，既是技术上的进步，却也是思想上的禁锢。
2007年，乔布斯发布初代 iPhone，重新定义了手机。
2017年，iPhone X 取消了沿用十年的 Home 键，用全面屏和全新的交互方式，再一次挑战人们对智能手机的认知。
苹果的伟大之处不在于拥有多么先进的技术，而在于它敢于打破人们的习以为常。
近十年过去了，当年的行业颠覆者，如今却开始追逐折叠屏的潮流。曾经引领时代的苹果，似乎也逐渐学会了迎合时代。当年他们试图重新定义手机，如今，却似乎只是在努力重新设计手机。
一字之差，却是创新与迭代之间的距离。
人们总以为，创新需要等待更成熟的技术、更合适的时机、更有利的环境。可那些真正改变世界的产品，往往不是诞生于技术最完美的年代，而是诞生于有人敢于重新思考一切的时刻。
限制我们进步的，从来不是技术的局限，也不是时代的束缚，而是思想的边界。
NVIDIA and Meta are expanding their partnership to improve AI model training and inference performance。
This is particularly interesting given Facebook’s history of being caught in major regulatory controversies, especially over data privacy and platform accountability.
As AI agents become increasingly autonomous, security, oversight, and accountability are no longer optional. It seems Meta is taking those lessons seriously as it moves further into the AI era.
NVIDIA and @Meta will expand our partnership on @Muse models to improve inference and training performance.
Together, we’re exploring NVIDIA OpenShell for safe AI agent deployment and NVIDIA Sentry for monitoring agent behavior.
Meta plans broader deployments of NVIDIA Vera Rubin and Vera CPUs.
Read the press release: nvda.ws/4zVYmDY
