TSMC
Reporting and context on TSMC, with a closer look at the decisions and developments that matter.
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At a glance
TSMC is a dedicated semiconductor foundry. Coverage follows chip manufacturing, advanced packaging and the supply chain supporting AI computing.
- Focus
- Semiconductor manufacturing; advanced packaging
- Reference
- TSMC
Sources checked . Selected company background and milestones.
Company milestones
Selected milestones, newest first. Earlier history is available below.
Arizona fab enters volume production
TSMC reports that its first Arizona fab begins volume production on N4 technology in the fourth quarter of 2024.
Source: TSMC
Show earlier historyHide earlier history · 1 milestones
More than 10 years ago.
Company is established
Morris Chang establishes TSMC, focused on manufacturing customers’ semiconductor designs.
Source: TSMC
The latest on TSMC
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Good Morning, AI Enthusiasts!
AI isn’t just a tool but an operating system for how we think, create, and build. Welcome to the New Superhuman era.
REBRAND
Grammarly Wants to Be Superhuman
📌 What’s happening: Grammarly just pulled a full identity heist. After acquiring Superhuman Mail in June and Coda last year, it’s ditching its own name and rebirthing as Superhuman, complete with a new AI agent suite called Superhuman Go. The classic grammar checker still exists, but now it’s just one plugin inside a larger “AI productivity OS.”
🧠 How this hits reality: Grammarly’s problem isn’t users; it’s use cases. ChatGPT and every “copilot” under the sun have turned writing help into a commodity. To stay relevant, Grammarly’s betting that “context-aware agents” across browsers and work apps will give it a bigger playground and a higher ceiling. But this makeover also screams midlife crisis: when your moat dries up, rename the castle.
🛎️ Key takeaway: Grammarly didn’t buy Superhuman for synergy; it bought it for reincarnation.
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CENTER
Figma Buys Weavy, Builds Its Own “AI Command Center” for Designers
📌 What’s happening: Figma has acquired Weavy, a node-based creative platform that lets users link multiple AI models and editing tools in one canvas for over $200M. Rebranded as Figma Weave, it turns prompt-based image and video generation into a visual workflow that users can branch, remix, and test outputs across models like Midjourney, Runway, and OpenAI in parallel. It’s not just a plugin; it’s Figma turning itself into a multi-modal AI layer for creative production.
🧠 How this hits reality: This move pushes Figma beyond UI design into the AI orchestration game, where the next “creative suite” isn’t about brushes or layers, but model routing and version control across modalities. Adobe, Canva, and Notion just lost their comfort zone: Figma’s no longer a design tool, it’s a control tower for generative workflows.
🛎️ Key takeaway: Figma didn’t buy an app; it bought the operating system for post-prompt creativity and quietly declared war on every AI content tool pretending to be a platform.
FACTORY
Samsung and Nvidia Plan World’s First AI Megafactory
📌 What’s happening: Samsung and Nvidia have finalized a deal to build an AI Megafactory, a semiconductor plant powered by more than 50,000 Nvidia GPUs with the exact site location yet to be disclosed. Instead of training AI models in data centers, this facility will use AI to run manufacturing itself. It will combine digital-twin fabs built in Nvidia Omniverse, AI-optimized lithography, GPU-accelerated EDA systems, and autonomous robots using Nvidia’s Blackwell servers. In short, this will be the first factory designed to think before it manufactures.
🧠 How this hits reality: If this project becomes fully operational, it could trigger the next industrial shift. Yield optimization, equipment tuning, and process design would evolve from engineering tasks into learning systems. Fabs could adapt in real time, self-correct production, and shorten product cycles from quarters to weeks. TSMC’s precision and Intel’s scale would suddenly face a rival whose competitive edge lies not in capacity, but in cognition.
🛎️ Key takeaway: Once Samsung’s fabs learn faster than humans can calibrate, manufacturing advantage will no longer depend on machinery. It will depend on intelligence.
Samsung and Nvidia Plan World’s First AI Megafactory
📌 What’s happening: Samsung and Nvidia have finalized a deal to build an AI Megafactory, a semiconductor plant powered by more than 50,000 Nvidia GPUs with the exact site location yet to be disclosed. Instead of training AI models in data centers, this facility will use AI to run manufacturing itself.
TSMC: Samsung and Nvidia Plan World’s First AI Megafactory
Yield optimization, equipment tuning, and process design would evolve from engineering tasks into learning systems. Fabs could adapt in real time, self-correct production, and shorten product cycles from quarters to weeks. TSMC’s precision and Intel’s scale would suddenly face a rival whose competitive edge lies not in capacity, but in cognition.
QUICK HITS
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- OpenAI launched Aardvark, a GPT-5 agent that autonomously finds and fixes software vulnerabilities, now in private beta.
- Google rolls out new AI-powered Android tools and XR devices, expanding Gemini’s reach from developer workflows to immersive hardware.
TRENDING
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Hello, AI Enthusiasts!
In today's issue, we dive into a gripping story that highlights the delicate balance between cutting-edge technology and security.
AI Secret helps you grasp the latest AI trends and insights in just 5 minutes. Don’t remember subscribing or want to stop receiving our newsletters completely? Unsubscribe here
TODAY’S AI SECRET:
- A developer manipulated Apple Intelligence.
- Intel is going through a series of major failures.
- Daily trending & featured AIs boost your career and business.
- Publishers make millions, while authors get nothing.
- OpenAI Collaborates with The Met - The partnership introduces an interactive chat experience with a representation of socialite Natalie Potter, enhancing visitors' engagement with the "Sleeping Beauties" exhibit.
- AI Experiment Raises Alarms - ChaosGPT, an open-source AI, attempts to "destroy humanity" through tweets and research in a controversial demonstration.
- Microsoft Crashed Again - GitHub announces that its services are now “fully operational” after a major outage caused by database changes. Since Microsoft's acquisition in 2018, some users have doubted its service stability.
- Cisco Layoffs Amid Shift to AI - Cisco announces a 7% reduction in workforce, laying off approximately 5,900 employees as it pivots towards AI and cybersecurity.
A developer manipulated Apple Intelligence.
Recently, just as Apple was poised to release its latest AI functionality—Apple Intelligence—a developer named Evan Zhou revealed a significant security flaw in the system. Zhou then published his code on GitHub.
The Details:
- Security Flaw Discovery: Evan Zhou demonstrated in the beta version of MacOS 15.1 how simple code could manipulate Apple Intelligence.
- Method of Manipulation: Zhou showcased a method where malicious commands are injected to manipulate AI behavior. This successful attack highlights the vulnerability in how AI systems handle input and instructions, due to the blurred boundaries between them.
- Technical Background and Impact: Zhou's case is not isolated but reflects a broader issue. OWASP has also listed prompt injection as one of the primary threats to large language models. When attackers can manipulate AI with simple inputs, causing it to leak sensitive information or perform malicious actions, the trust and security of the entire system are severely compromised.
Why It Matters:
Evan Zhou's example serves as a reminder that, alongside technological innovation, security cannot be overlooked. For companies and developers, ensuring that AI systems are resilient against such attacks is crucial for protecting user privacy and data security.
A developer manipulated Apple Intelligence.
Recently, just as Apple was poised to release its latest AI functionality—Apple Intelligence—a developer named Evan Zhou revealed a significant security flaw in the system. Zhou then published his code on GitHub.
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Intel is going through a series of major failures.
SoftBank and Intel's plan to create an AI chip to rival Nvidia has been scrapped. Intel couldn't meet SoftBank's volume and speed needs, prompting SoftBank to shift its focus to TSMC.
The Details:
- Partnership Breakdown: Intel failed to meet SoftBank's specific demands for the AI chip production, causing the partnership talks to collapse.
- Impact on Intel: The failed negotiations preceded Intel's significant cost-cutting measures, including widespread layoffs.
- Shift in Strategy: SoftBank is now engaging with TSMC, aiming to leverage the capabilities of the world's largest contract chipmaker for its AI chip ambitions.
Why It Matters:
Right now, Intel, once a leading chip maker, appears to be struggling. After facing several challenges, such as problems with new chips, a drop in stock prices, and significant layoffs, even new companies like SoftBank have decided to distance themselves from Intel. I can't help but wonder if Intel will end up like Nokia?
TSMC: Intel is going through a series of major failures.
Shift in Strategy: SoftBank is now engaging with TSMC, aiming to leverage the capabilities of the world's largest contract chipmaker for its AI chip ambitions.
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Publishers make millions, while authors get nothing.
A recent disturbing practice in the academic world: publishers selling academic papers to tech companies for AI training, earning millions while the original authors receive nothing. This raises significant ethical and legal questions about the use of intellectual property and the compensation of creators.
The Details:
- Exploitative Earnings: Publishers like Taylor & Francis and Wiley have made substantial profits, up to $23 million, by licensing academic papers to tech companies for AI training.
- Authors' Lack of Compensation: Despite their hard work, authors of these papers have not received any financial benefits from the commercial use of their work.
- Legal and Ethical Concerns: The practice has sparked debates about the legality and ethics of using academic research in this way, especially without compensating the authors.
Why It Matters:
As AI continues to evolve, the need for massive datasets has led to the commodification of academic research, often at the expense of the original creators. This practice not only questions the fairness of the academic publishing model but also the broader implications for how we value and protect intellectual contributions in the digital age.
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Apple AI‘s Huge Bug
A developer manipulated Apple Intelligence
