Building agents, brain-like chips, and tiny semiconductors
Welcome to The Short, IBM Research's weekly recap of the latest innovations in AI, quantum computing, semiconductors, and the cloud. If you're liking what you see here, be sure to sign up for earlier access on LinkedIn.
In this week's edition:
- These new IBM agents will give developers new ways to solve problems — and clear their backlog
- The chips of tomorrow may well take inspiration from the architecture of our brains
- IBM and Albany partners unlock new yield benchmarks for EUV patterning
- Bringing cloud-native AI supercomputing to a data center near you
- IBM Research History
For most software developers, working through their backlog of issues feels like a never-ending triage. But what if there were tools that could make finding bugs, suggesting fixes, and testing those ideas as easy as submitting an issue on GitHub? At TechXchange, researchers previewed IBM SWE-Agent 1.0, the first set of software engineering (SWE) agents of its kind that can autonomously resolve GitHub issues efficiently. Unlike any other SWE agents, this is powered by open LLMs. It has the potential to drastically reduce the time developers spend solving issues with their code.
To meet the growing energy and compute demands of AI, IBM research scientists are working on a new generation of computer chips inspired by the world's most efficient computing machine: the human brain. Neuromorphic or brain-inspired computing architecture can include merging memory and processing, as well as storing data in the same way neurons do, all to achieve greater performance than existing processors while using less energy.
IBM Research scientists have hit a new milestone in semiconductor manufacturing that will make it possible to reliably build even smaller transistors. Using High NA EUV (High Numerical-Aperture Extreme Ultraviolet), they've reliably achieved functional 28nm pitch in unbroken copper interconnects over a meter long. Shrinking these metal lines that link transistors will be a crucial step toward achieving ever smaller transistor nodes and closing in on the 1nm mark.
Over the last year, IBM Research has been developing a full-stack, on-premises system for cloud-native AI supercomputing. The architecture can scale from dozens to thousands of GPUs. It contains a flexible, scalable, and affordable network capable of supporting high-performance AI training and a high-performance storage system based on IBM Storage Scale — one of the industry’s fastest and most flexible file systems. IBM knows are partners all over the world are looking for scalable, fully integrated, and future-proofed solutions to enable innovation on their own timeframes. We’re working to unlock this by bringing the appropriate infrastructure and tools to where customers can most effectively use them — and for many, that’s in their own facilities, rather than public clouds.
On October 23, 1956, the IBM Research Laboratory in Zurich, Switzerland officially opened its doors. Today, the Zurich lab is the home to Nobel Prize-winning work, and talented researchers pioneering emerging industries.
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