Preferred Networks

Visit the PFN desk in the Microsoft Japan booth (A103, West 3) at #SusHiTechTokyo2026 today and tomorrow! PFN's global biz VP and MS Japan's CTO will be on Green Stage (1st floor) today at 17:15-18:00 to discuss integration of Azure between our PLaMo LLM sushitech-startup.metro.tokyo.lg.jp

Hiring now: MN-Core runtime software engineer open.talentio.com/r/1/c/preferre…

Hiring now: MN-Core compiler engineer open.talentio.com/r/1/c/preferre…

Hiring now: We started looking for engineers who can develop the LLM serving engine with us for our MN-Core™ L series of proprietary inference AI chip. See reply for other MN-Core-related positions👇 open.talentio.com/r/1/c/preferre…

Applications are now open for the our 2026 Summer Internship! We welcome students who want to create new technologies, products and services using machine learning and other computer science technologies. The application deadline is Sunday, April 19 JST. preferred.jp/en/careers/int…

Optuna can also be applied in material science. A blog post has been published detailing its use case in crystal structure prediction. tech.preferred.jp/en/blog/matlan…

PFN, IIJ and JAIST will start operating AImod, the direct liquid cooling modular data center built in IIJ's Shiroi DCC, in April 2026. We will jointly test the liquid cooling system and high-density integration of PFN's AI chips in the MN-Core™ series. preferred.jp/en/news/pr2026…

PFN Co-Founder and CEO Daisuke Okanohara @hillbig has been invited to speak at #ITFWorld2026, the annual forum to be held by the international nanoelectronics R&D hub Imec between May 19-20 in Antwerp, Belgium. The session theme will be announced soon! imecitf.com/world/speakers

Announcing CuPy v14! 🚀 🔹 NumPy v2 semantics 🔹 CUDA Pip Wheels support 🔹 bfloat16 & structured dtype 🔹 Enhanced NumPy/SciPy API coverage Read more on our blog for the full details! 👇

Discover unknown stable crystals at unprecedented speed. Introducing Matlantis CSP. 💎🚀 We are thrilled to announce the launch of Matlantis CSP (Crystal Structure Prediction), a new capability that rapidly identifies previously unknown stable crystal structures from the enormous search space of atomic configurations and compositions within a given elemental system. Materials R&D has long depended on repeated synthesis experiments, even when the likelihood of success is low. Matlantis CSP introduces a computational screening step earlier in the process to rule out what is physically implausible in advance. By combining Matlantis’ core technology—the universal machine learning potential PFP—with proprietary algorithms, Matlantis CSP enables you to: ✅ Screen out experimentally unviable configurations before experimentation. ✅ Explore complex composition spaces with approx. 3–6× greater efficiency than random search. ✅ Discover novel materials that do not exist in current databases. We are honored to have Honda R&D as an early adopter. “We have high expectations for CSP as a technology that will dramatically improve exploration efficiency in materials development,” said Mitsumoto Kawai, Chief Engineer, Device Process, Innovative Research Excellence, Honda R&D Co., Ltd. “Through CSP, crystal structure searches—including multi-component systems and metastable structures that were previously impractical—have become feasible. Being able to narrow down promising crystal structures and compositions with high confidence before experiments will not only increase the probability of realizing next-generation materials but also shorten development timelines.” Learn how Matlantis CSP can transform your materials discovery: 👇 matlantis.com/en/product/mtc… #Matlantis #CrystalStructurePrediction

Watch PFN co-founder @hillbig talk about AI in Japan as a guest lecturer at Columbia Business School Center on Japanese Economy and Business @ColumbiaCJEB in December last year youtube.com/watch?v=rsD9Qn…

PFN was selected as a partner for JICA's PoC for the National Bank of Cambodia🇰🇭. PFN will develop an AI model that forecasts the liquidity of the local currency to support Cambodia's Riel promotion efforts to achieve independent monetary policy. preferred.jp/en/news/pr2026…

Pre-register to our Summer 2026 Internship Program in Japan to receive invitations for applications from PFN! We welcome students who wish to take on technological challenges in algorithms, mathematics and implementation. preferred.jp/en/news/pr2026…

Here's our paper on PARC, a coding agent that can autonomously execute long-horizon tasks. PARC assesses its actions and outcomes by itself to detect and correct errors. We demonstrated its problem-solving capability in materials science and Kaggle tasks. arxiv.org/abs/2512.03549

PFN's Japanese translation-specific LLM Plamo™ Translate will be adopted by Japan's "Gennai" government AI project as a high-quality, Japan-made on-premise AI for supporting government employees. preferred.jp/en/news/pr2025…

Do you need some extra bandwidth (for LLM inference)? If you’re attending #SC25 in St. Louis, meet us at the booth 4311 and check out our MN-Core™︎ series of AI processors!

PFN will be at #SC25 in St. Louis between Nov 16-21! Meet us at the booth #4311 to learn about our MN-Core™ series of fast, powerful AI processors preferred.jp/en/news/pr2025…

What a week at #CIIE! We were thrilled to exhibit Matlantis at the L'Oréal BIG BANG BEAUTY TECH INNOVATION PROGRAM booth. A huge thank you to the L'Oréal team for this opportunity and to everyone who visited us! #CIIE #LorealBigBang

Optuna v4.6 has been released! 📊Optuna Dashboard LLM Integration 🚀Significant speedup of GPSampler 🦾Full support for multi-objective and constrained optimization in AutoSampler ⛏️Robust Bayesian Optimization Algorithms medium.com/optuna/announc…

PFN 2025 summer intern Sahoo Manish conducted a study on the automatic construction and optimization of pseudopotentials, which is crucial for accelerating DFT (Density Functional Theory) calculation. Read more: tech.preferred.jp/en/blog/automa…