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TSMC: Ecosystem for 2nm Chip Development Is Nearing Completion

Speaking to partners last week as part of their annual Open Innovation Platform forum in Europe, a big portion of TSMC’s roadshow was dedicated to the next generation of the company’s foundry technology. TSMC’s 2 nm-class N2, N2P, and N2X process technologies are set to introduce multiple innovations, including nanosheet gate-all-around (GAA) transistors, backside power delivery, and super-high-performance metal-insulator-metal (SHPMIM) capacitor over the next few years. But in order to take advantage of these innovations, TSMC warns, chip designers will need to use all-new electronic design automation (EDA), simulation, and verification tools as well as IP. And while making such a big shift is never an easy task, TSMC is bringing some good news to chip designers early-on: even with N2 still a couple of years out, many of the major EDA tools, verification tools, foundation IP, and even analog IP for N2 are already available for use.

“For N2 we could be working with them two years in advance already because nanosheet is different,” said Dan Kochpatcharin, Head of Design Infrastructure Management at TSMC, at the OIP 2023 conference in Amsterdam. “[EDA] tools have to be ready, so what the OIP did is to work with them early. We have a huge engineering team to work with the EDA partners, IP partners, [and other] partners.”

*Chip density published by TSMC reflects ‘mixed’ chip density consisting of 50% logic, 30% SRAM, and 20% analog.

ChatGPT-like tool to advance scientific studies is in the making

This might be a game-changing tool for accelerating scientific research.

An international group of scientists has begun work on developing a ChatGPT-like tool to accelerate scientific discovery. In recent years, scientists have been leveraging artificial intelligence (AI) for the purpose of advancing scientific research and exploration.

AI’s capability to analyze extensive datasets, simulate complex phenomena, and aid researchers in modeling and comprehending intricate systems has the potential to be a game-changer in various fields, including but not limited to medicine, astronomy, climate science, and materials research.


Laurence Dutton/iStock.

In recent years, scientists have been leveraging artificial intelligence (AI) for the purpose of advancing scientific research and exploration.

New algorithm may allow robots to move in crowded places

It is. based on reinforcement learning algorithms (RL) to allow for quick robot movement.

Robotic dogs have a massive hurdle in autonomous navigation in crowded spaces. Robot navigation in crowds has applications in various fields, including shopping mall service robots, transportation, healthcare, etc.

To facilitate rapid and efficient movement, developing new methods is crucial to enable robots to navigate crowded spaces and obstacles safely.


ILexx/iStock.

Robot navigation in crowds has applications in various fields, including shopping mall service robots, transportation, healthcare, etc.

OpenAI has quietly changed its ‘core values’

Putting a greater emphasis on the development of AGI — artificial general intelligence. CEO Sam Altman has described AGI as “the equivalent of a median human that you could hire as a co-worker.”


The AI startup says its singular goal is to build “safe, beneficial” artificial general intelligence, noting that anything else is “out of scope.”

Will Artificial Intelligence become the Stethoscope of the 21st Century?

In the realm of healthcare, change has always been met with resistance. It took considerable time for the medical community to accept the stethoscope as a valuable tool in patient care. Similarly, it will take a while for Artificial Intelligence (AI) to be recognized as a full-fledged health tool, despite its immense potential to revolutionize the healthcare industry. However, when A.I. eventually takes its rightful place in healthcare, it will displace the stethoscope as its symbol. Let’s dive into how AI is poised to transform the way we approach healthcare.