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Labs
9 records Generated from this page's data. Click a name to open its panel on the Places: South East page. Records resting on one source are tagged "one source".| Record | What it is | Place | Links | Confidence |
|---|---|---|---|---|
| AIFS ENS (ECMWF machine-learned ensemble forecast)Chips, models and products | ECMWF's machine-learned ensemble forecast: 51 stochastic forecasts per run from a 229-million-parameter model trained on reanalysis and operational analyses. operationalKey facts 229m parameters; about 30 km; 50 perturbed members plus 1 control; trained on 38 years of ERA5 (1979–2017) and 8 years of IFS operational analyses (2016–2023); up to 25% better than IFS ENS, mainly upper-air variables; authors Simon Lang and Linus Magnusson (ECMWF Newsletter 185)Made by European Centre for Medium-Range Weather Forecasts (ECMWF): machine-learned forecasting (AIFS) · 2025-10-28 (newsletter date; start date not given) | Reading | ecmwf.int/en/newsletter/185/earth-system-science | one source |
| AIFS Single (ECMWF Artificial Intelligence Forecasting System)Chips, models and products | ECMWF's first operational machine-learned weather model, run alongside its physics-based forecasts and trained on past weather data. operationalKey facts Operational 25 Feb 2025; up to 20% gains on many measures incl. tropical cyclone tracks; about 1,000 times less energy per forecast; 28 km grid (ECMWF, 25 Feb 2025); AIFS v1.1 operational since Feb 2025; AIFS v2 fine-tuned with prototype 50r1 data, operational date not stated (ECMWF blog, 11 May 2026)Made by European Centre for Medium-Range Weather Forecasts (ECMWF): machine-learned forecasting (AIFS) · 2025-02-25 | Reading | ecmwf.int/en/about/media-centre/news/2025/ecmwfs · ecmwf.int/en/about/media-centre/aifs-blog/2026/f | lab's own pages |
| Anemoi (open-source machine-learning weather framework)Chips, models and products | Open-source framework for building machine-learned weather models, first developed at ECMWF and now co-developed with European national weather services. in use (open source)Key facts Covers dataset curation, model training, graph selection and inference; used in ECMWF's Machine Learning Project with 17 national weather services, led by MET Norway and MeteoSwiss, launched 2024 under EUMETNET E-AI (ECMWF blog, 14 Jul 2026)Made by European Centre for Medium-Range Weather Forecasts (ECMWF): machine-learned forecasting (AIFS) · 2026-07-14 | Reading | ecmwf.int/en/about/media-centre/aifs-blog/2026/b | one source |
| European Centre for Medium-Range Weather Forecasts (ECMWF): machine-learned forecasting (AIFS)Networks, bodies, events and media | European weather centre hosted in Reading, UK, that trains and runs its own machine-learned forecasting models, AIFS Single and AIFS ENS.Key facts AIFS Single operational 25 Feb 2025: gains of up to 20% on many measures, about 1,000 times less energy per forecast, 28 km grid (ECMWF); AIFS ENS: 229m parameters, up to 25% better than the physics-based IFS ENS mainly for upper-air variables (ECMWF Newsletter 185, Oct 2025); 11 May 2026: stopped real-time runs of four external ML models (Pangu-Weather, GraphCast, Aurora, FourCastNet) with IFS Cycle 50r1; AIFS v2 fine-tuned on prototype 50r1 data; ML project with 17 national weather services (ECMWF blog, 14 Jul 2026); 2025–2034 Strategy approved Dec 2024Models and products (3)
| Reading | ecmwf.int/en/about/media-centre/news/2025/ecmwfs · ecmwf.int/en/about/media-centre/news/2025/new-10 | verified |
| Ochre BioCompanies | Oxford liver-disease biotech that combines machine learning with large human liver datasets to find RNA drug targets.Key facts HQ Oxford; labs in New York (Alexandria Center, relocated 2025-07-21) and Taipei; partnerships with Boehringer Ingelheim (2024-04-22) and GSK (AI pact 2024-06-12; research phase complete 2025-11-18); proprietary OBELiX software; says it has "invested over $20m" in human liver datasets; Clinical Translation Board announced 2026-10-07 | Oxford | Companies House · ochre-bio.com/2025/11/18/ochre-bio-completes-hum · ochre-bio.com/ | one source |
| Oxford Drug DesignCompanies | Oxford University spin-out using its own machine-learning platform to design cancer drugs, first for lung and bowel cancer. unknown — latest source May 2022Key facts £2.2m ($2.7m) bridge round May 2022 from ACF Investors, o2h Ventures, Meltwind Advisory and US-based R42 Group; oncology focus (lung and colorectal) | Oxford (HQ not stated in sources) | Companies House · businesscloud.co.uk/news/cancer-fighting-spinout · startupsmagazine.co.uk/article-oxford-drug-desig | one source |
| TokaMind (fusion plasma foundation model)Chips, models and products | Open-source foundation model for fusion plasma, trained on data from UKAEA's MAST tokamak by IBM Research, UKAEA and the Hartree Centre. released (open source)Key facts Base 9,324,382 and tiny 5,293,854 parameters; pre-trained on public MAST data; TokaMark benchmark of 14 tasks, 11,573 shots, 39 signals (arXiv v1, 16 Feb 2026); did better than a traditional machine-learning model on nearly all 14 tasks; MAST ran 1999–2013 (IBM Research blog, 23 Apr 2026); code at github.com/UKAEA-IBM-STFC-Fusion-FMs/tokamindMade by Hartree Centre · 2026-02-16 | Abingdon | arxiv.org/html/2602.15084v1 · research.ibm.com/blog/fusion-plasma-ai-model | lab's own pages |
| UK Atomic Energy Authority (UKAEA) fusion AI and computing programmeNetworks, bodies, events and media | The UK Atomic Energy Authority trains AI models on fusion experiment data, including TokaMind, a plasma foundation model built with IBM and Hartree.Key facts TokaMind posted 16 Feb 2026 (base 9,324,382 parameters; tiny 5,293,854), trained on MAST tokamak data (arXiv); 14 Sep 2026: declaration of intent with US PPPL to link SUNRISE (backed by £45m UK government money) and STELLAR-AI and train the same AI models on MAST Upgrade and NSTX-U data, long-term aim a shared foundation model for spherical tokamaks (WNN, 15 Sep 2026); 14 Jan 2026: digiLab models let UKAEA explore reactor designs around 100,000 times faster (company figure; channellife)Models and products (1)
| Abingdon (arXiv author affiliation) | arxiv.org/html/2602.15084v1 · world-nuclear-news.org/articles/uk-usa-enhance-c | verified |
| XymeCompanies | Oxford company founded in 2024 by Exscientia founder Andrew Hopkins that designs new enzymes with AI and quantum chemistry.Key facts Founded 2024; combines AI, quantum chemistry and lab experiments; took 5,600 sq ft at Inventa, Oxford West End (reported 2025-05-30) | Oxford | Companies House · cambridgenetwork.co.uk/index.php/news/mission-st · find-and-update.company-information.service.gov. | one source |