Harnessing Machine Learning to Make Complex Systems More … – Lawrence Berkeley National Laboratory (.gov)
Getting something for nothing doesnt work in physics. But it turns out that, by thinking like a strategic gamer, and with some help from a demon, improved energy efficiency for complex systems like data centers might be possible.
In computer simulations, Stephen Whitelam of the Department of Energys Lawrence Berkeley National Laboratory (Berkeley Lab) used neural networks (a type of machine learning model that mimics human brain processes) to train nanosystems, which are tiny machines about the size of molecules, to work with greater energy efficiency.
Whats more, the simulations showed that learned protocols could draw heat from the systems by virtue of constantly measuring them to find the most energy efficient operations.
We can get energy out of the system, or we can store work in the system, Whitelam said.
Its an insight that could prove valuable, for example, in operating very large systems like computer data centers. Banks of computers produce enormous amounts of heat that must be extracted using still more energy to prevent damage to the sensitive electronics.
We can get energy out of the system, or we can store work in the system.
Stephen Whitelam
Whitelam conducted the research at the Molecular Foundry, a DOE Office of Science user facility at Berkeley Lab. His work is described in a paper published in Physical Review X.
Asked about the origin of his ideas, Whitelam said, People had used techniques in the machine learning literature to play Atari video games that seemed naturally suited to materials science.
In a video game like Pac Man, he explained, the aim with machine learning would be to choose a particular time for an action up, down, left, right, and so on to be performed. Over time, the machine learning algorithms will learn the best moves to make, and when, to achieve high scores. The same algorithms can work for nanoscale systems.
Whitelams simulations are also something of an answer to an old thought experiment in physics called Maxwells Demon. Briefly, in 1867, physicist James Clerk Maxwell proposed a box filled with a gas, and in the middle of the box there would be a massless demon controlling a trap door. The demon would open the door to allow faster molecules of the gas to move to one side of the box and slower molecules to the opposite side.
Eventually, with all molecules so segregated, the slow side of the box would be cold and the fast side would be hot, matching the energy of the molecules.
The system would constitute a heat engine, Whitelam said. Importantly, however, Maxwells Demon doesnt violate the laws of thermodynamics getting something for nothing because information is equivalent to energy. Measuring the position and speed of molecules in the box costs more energy than that derived from the resulting heat engine.
And heat engines can be useful things. Refrigerators provide a good analogy, Whitelam said. As the system runs, food inside stays cold the desired outcome even though the back of the fridge gets hot as a product of work done by the refrigerators motor.
In Whitelams simulations, the machine learning protocol can be thought of as the demon. In the process of optimization, it converts information drawn from the system modeled into energy as heat.
In one simulation, Whitelam optimized the process of dragging a nanoscale bead through water. He modeled a so-called optical trap in which laser beams, acting like tweezers of light, can hold and move a bead around.
The name of the game is: Go from here to there with as little work done on the system as possible, Whitelam said. The bead jiggles under natural fluctuations called Brownian motion as water molecules are bombarding it. Whitelam showed that if these fluctuations can be measured, moving the bead can then be done at the most energy efficient moment.
Here were showing that we can train a neural-network demon to do something similar to Maxwells thought experiment but with an optical trap, he said.
Whitelam extended the idea to microelectronics and computation. He used the machine learning protocol to simulate flipping the state of a nanomagnetic bit between 0 and 1, which is a basic information-erasure/information-copying operation in computing.
Do this again, and again. Eventually, your demon will learn how to flip the bit so as to absorb heat from the surroundings, he said. He comes back to the refrigerator analogy. You could make a computer that cools down as it runs, with the heat being sent somewhere else in your data center.
Whitelam said the simulations are like a testbed for understanding concepts and ideas. And here the idea is just showing that you can perform these protocols, either with little energy expense, or energy sucked in at the cost of going somewhere else, using measurements that could apply in a real-life experiment, he said.
This research was supported by the Department of Energys Office of Science.
# # #
Founded in 1931 on the belief that the biggest scientific challenges are best addressed by teams, Lawrence Berkeley National Laboratory and its scientists have been recognized with 16 Nobel Prizes. Today, Berkeley Lab researchers develop sustainable energy and environmental solutions, create useful new materials, advance the frontiers of computing, and probe the mysteries of life, matter, and the universe. Scientists from around the world rely on the Labs facilities for their own discovery science. Berkeley Lab is a multiprogram national laboratory, managed by the University of California for the U.S. Department of Energys Office of Science.
DOEs Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.
- Machine Learning in Drug Discovery Market to Witness Exponential Growth: Key Players, $250M Eli Lilly Deal & Regional Insights for 2025-2034 -... - July 18th, 2025 [July 18th, 2025]
- Automated seafood freshness detection and preservation analysis using machine learning and paper-based pH sensors - Nature - July 18th, 2025 [July 18th, 2025]
- Do You Know What It Means To Train a Machine Learning Model? - LSU - July 18th, 2025 [July 18th, 2025]
- Establishment of an interpretable MRI radiomics-based machine learning model capable of predicting axillary lymph node metastasis in invasive breast... - July 18th, 2025 [July 18th, 2025]
- A Machine Learning-Reconstructed Dataset of River Discharge, Temperature, and Heat Flux into the Arctic Ocean - Nature - July 18th, 2025 [July 18th, 2025]
- Leveraging computational linguistics and machine learning for detection of ultra-high risk of mental health disorders in youths | Schizophrenia -... - July 18th, 2025 [July 18th, 2025]
- Development and validation of machine learning-based diagnostic models using blood transcriptomics for early childhood diabetes prediction - Frontiers - July 18th, 2025 [July 18th, 2025]
- Fatigue and stamina prediction of athletic person on track using thermal facial biomarkers and optimized machine learning algorithm - Nature - July 18th, 2025 [July 18th, 2025]
- Identifying the crucial oncogenic mechanisms of DDX56 based on a machine learning-based integration model of RNA-binding proteins - Nature - July 18th, 2025 [July 18th, 2025]
- AI and Machine Learning Skills Are Make or Break for Developers: 71% of Tech Leaders Wont Hire Without Them - Yahoo Finance - July 18th, 2025 [July 18th, 2025]
- Developing an explainable machine learning and fog computing-based visual rating scale for the prediction of dementia progression - Nature - July 18th, 2025 [July 18th, 2025]
- Prognosis of air quality index and air pollution using machine learning techniques - Nature - July 18th, 2025 [July 18th, 2025]
- Integrating vision transformer-based deep learning model with kernel extreme learning machine for non-invasive diagnosis of neonatal jaundice using... - July 18th, 2025 [July 18th, 2025]
- PlayStation 6 Likely to Feature 24 GB RAM for Advanced Ray Tracing and Machine Learning Without Raising Costs - Wccftech - July 18th, 2025 [July 18th, 2025]
- Machine Learning-Assisted Iterative Screening for Efficient Detection of Drug Discovery Starting Points - ACS Publications - July 16th, 2025 [July 16th, 2025]
- 2025 IT Camp on AI & Machine Learning for Beginners to be held August 5 - Southeastern Oklahoma State University - July 16th, 2025 [July 16th, 2025]
- Utilizing machine learning to predict MRI signal outputs from iron oxide nanoparticles through the PSLG algorithm - Nature - July 16th, 2025 [July 16th, 2025]
- Developing a machine-learning model to enable treatment selection for neoadjuvant chemotherapy for esophageal cancer - Nature - July 16th, 2025 [July 16th, 2025]
- Advancing crop recommendation system with supervised machine learning and explainable artificial intelligence - Nature - July 16th, 2025 [July 16th, 2025]
- Predicting clozapine-induced adverse drug reaction biomarkers using machine learning - Nature - July 16th, 2025 [July 16th, 2025]
- Postoperative complication severity prediction in penile prosthesis implantation: a machine learning-based predictive modeling study - Nature - July 16th, 2025 [July 16th, 2025]
- The Future of AI & Machine Learning: Perspective on Shaping Tomorrows Business Landscape - Vocal - July 16th, 2025 [July 16th, 2025]
- Machine Learning: Your Ticket to a Thriving Career in the Tech World - The Impressive Times - July 14th, 2025 [July 14th, 2025]
- Integrative analysis of multi-omics data and gut microbiota composition reveals prognostic subtypes and predicts immunotherapy response in colorectal... - July 14th, 2025 [July 14th, 2025]
- Comprehensive multi-omics and machine learning framework for glioma subtyping and precision therapeutics - Nature - July 14th, 2025 [July 14th, 2025]
- Development and validation of a machine learning-based nomogram for survival prediction of patients with hilar cholangiocarcinoma after... - July 12th, 2025 [July 12th, 2025]
- Geochemical-integrated machine learning approach predicts the distribution of cadmium speciation in European and Chinese topsoils - Nature - July 12th, 2025 [July 12th, 2025]
- Machine learning-based construction of a programmed cell death-related model reveals prognosis and immune infiltration in pancreatic adenocarcinoma... - July 12th, 2025 [July 12th, 2025]
- Application of supervised machine learning and unsupervised data compression models for pore pressure prediction employing drilling, petrophysical,... - July 12th, 2025 [July 12th, 2025]
- Machine learning identifies lipid-associated genes and constructs diagnostic and prognostic models for idiopathic pulmonary fibrosis - Orphanet... - July 12th, 2025 [July 12th, 2025]
- An evaluation methodology for machine learning-based tandem mass spectra similarity prediction - BMC Bioinformatics - July 12th, 2025 [July 12th, 2025]
- The Rise of AI in Trading: Machine Learning and the Stock Market - Disruption Banking - July 12th, 2025 [July 12th, 2025]
- Integrative analysis identifies IL-6/JUN/MMP-9 pathway destroyed blood-brain-barrier in autism mice via machine learning and bioinformatic analysis -... - July 12th, 2025 [July 12th, 2025]
- Interpretive prediction of hyperuricemia and gout patients via machine learning analysis of human gut microbiome - BMC Microbiology - July 10th, 2025 [July 10th, 2025]
- Machine learning-based identification of key factors and spatial heterogeneity analysis of urban flooding: a case study of the central urban area of... - July 10th, 2025 [July 10th, 2025]
- Developing machine learning frameworks to predict mechanical properties of ultra-high performance concrete mixed with various industrial byproducts -... - July 10th, 2025 [July 10th, 2025]
- Small Drones Market Trend Analysis and Forecast Report 2025-2034 | AI and Machine Learning Revolutionizing Autonomous Operations, Trade Tariffs Push... - July 10th, 2025 [July 10th, 2025]
- When a model touches millions: Hatim Kagalwala on accuracy accountability, and applied machine learning - Dataconomy - July 10th, 2025 [July 10th, 2025]
- New Study Uses Gait Data and Machine Learning for Early Detection of Anxiety and Depression - AZoSensors - July 10th, 2025 [July 10th, 2025]
- Machine Learning and the Evolution of Mobile Apps - CIO Applications - July 10th, 2025 [July 10th, 2025]
- Artificial Intelligence, Machine Learning, and Big Data in Thailand: Legal and Regulatory Developments 2025 - Lexology - July 10th, 2025 [July 10th, 2025]
- Karen Hao on how the AI boom became a new imperial frontier - Machine Learning Week 2025 - July 8th, 2025 [July 8th, 2025]
- Machine Learning and AI in Enhancing Image Analysis of 3D Samples - Drug Target Review - July 8th, 2025 [July 8th, 2025]
- Gartner Predicts Over 40% of Agentic AI Projects Will Be Canceled by End of 2027 - Machine Learning Week 2025 - July 8th, 2025 [July 8th, 2025]
- Explainable machine learning model for predicting the transarterial chemoembolization response and subtypes of hepatocellular carcinoma patients - BMC... - July 8th, 2025 [July 8th, 2025]
- Identification and validation of glucocorticoid receptor and programmed cell death-related genes in spinal cord injury using machine learning - Nature - July 8th, 2025 [July 8th, 2025]
- Multiclass leukemia cell classification using hybrid deep learning and machine learning with CNN-based feature extraction - Nature - July 6th, 2025 [July 6th, 2025]
- Predictive modeling and machine learning show poor performance of clinical, morphological, and hemodynamic parameters for small intracranial aneurysm... - July 6th, 2025 [July 6th, 2025]
- A robust machine learning approach to predicting remission and stratifying risk in rheumatoid arthritis patients treated with bDMARDs - Nature - July 6th, 2025 [July 6th, 2025]
- Ultrabroadband and band-selective thermal meta-emitters by machine learning - Nature - July 4th, 2025 [July 4th, 2025]
- Machine Learning is Surprisingly Good at Simulating the Universe - Universe Today - July 4th, 2025 [July 4th, 2025]
- Machine learning-assisted multi-dimensional transcriptomic analysis of cytoskeleton-related molecules and their relationship with prognosis in... - July 4th, 2025 [July 4th, 2025]
- Machine learning combined with multi-omics to identify immune-related LncRNA signature as biomarkers for predicting breast cancer prognosis - Nature - July 4th, 2025 [July 4th, 2025]
- Comprehensive machine learning analysis of PANoptosis signatures in multiple myeloma identifies prognostic and immunotherapy biomarkers - Nature - July 4th, 2025 [July 4th, 2025]
- Enhancing game outcome prediction in the Chinese basketball league through a machine learning framework based on performance data - Nature - July 4th, 2025 [July 4th, 2025]
- A novel double machine learning approach for detecting early breast cancer using advanced feature selection and dimensionality reduction techniques -... - July 4th, 2025 [July 4th, 2025]
- Machine learning for Parkinsons disease: a comprehensive review of datasets, algorithms, and challenges - Nature - July 4th, 2025 [July 4th, 2025]
- Cervical cancer prediction using machine learning models based on routine blood analysis - Nature - July 4th, 2025 [July 4th, 2025]
- Enhancing anomaly detection in IoT-driven factories using Logistic Boosting, Random Forest, and SVM: A comparative machine learning approach - Nature - July 4th, 2025 [July 4th, 2025]
- Predicting car accident severity in Northwest Ethiopia: a machine learning approach leveraging driver, environmental, and road conditions - Nature - July 4th, 2025 [July 4th, 2025]
- Sensormatic Solutions Adds Machine Learning to Shrink Analyzer - Ink World magazine - July 4th, 2025 [July 4th, 2025]
- Exploring the link between the ZJU index and sarcopenia in adults aged 2059 using NHANES and machine learning - Nature - July 4th, 2025 [July 4th, 2025]
- Combining multi-parametric MRI radiomics features with tumor abnormal protein to construct a machine learning-based predictive model for prostate... - July 2nd, 2025 [July 2nd, 2025]
- New insight into viscosity prediction of imidazolium-based ionic liquids and their mixtures with machine learning models - Nature - July 2nd, 2025 [July 2nd, 2025]
- Implementing partial least squares and machine learning regressive models for prediction of drug release in targeted drug delivery application -... - July 2nd, 2025 [July 2nd, 2025]
- Advanced analysis of defect clusters in nuclear reactors using machine learning techniques - Nature - July 2nd, 2025 [July 2nd, 2025]
- Machine learning analysis of kinematic movement features during functional tasks to discriminate chronic neck pain patients from asymptomatic controls... - July 2nd, 2025 [July 2nd, 2025]
- Enhanced machine learning models for predicting three-year mortality in Non-STEMI patients aged 75 and above - BMC Geriatrics - July 2nd, 2025 [July 2nd, 2025]
- Modeling seawater intrusion along the Alabama coastline using physical and machine learning models to evaluate the effects of multiscale natural and... - July 2nd, 2025 [July 2nd, 2025]
- A comprehensive study based on machine learning models for early identification Mycoplasma pneumoniae infection in segmental/lobar pneumonia - Nature - July 2nd, 2025 [July 2nd, 2025]
- Identifying ovarian cancer with machine learning DNA methylation pattern analysis - Nature - July 2nd, 2025 [July 2nd, 2025]
- High-isolation dual-band MIMO antenna for next-generation 5G wireless networks at 28/38 GHz with machine learning-based gain prediction - Nature - July 2nd, 2025 [July 2nd, 2025]
- Sony and AMD want to focus on machine learning for the PS6 - Instant Gaming News - July 2nd, 2025 [July 2nd, 2025]
- How Machine Learning is Reshaping the Future of Sports Betting? - London Daily News - July 2nd, 2025 [July 2nd, 2025]
- An interpretable machine learning model for predicting depression in middle-aged and elderly cancer patients in China: a study based on the CHARLS... - July 2nd, 2025 [July 2nd, 2025]
- These Eight Projects Showcase the Power of Machine Learning on the Edge - Hackster.io - June 29th, 2025 [June 29th, 2025]
- Build Custom AI Tools for Your AI Agents that Combine Machine Learning and Statistical Analysis - MarkTechPost - June 29th, 2025 [June 29th, 2025]
- Check out these essential tips and trends for SEO in 2025 as AI and machine learning loom large - EdTech Innovation Hub - June 29th, 2025 [June 29th, 2025]
- Using machine learning to predict the severity of salmonella infection - Open Access Government - June 28th, 2025 [June 28th, 2025]
- How AI and machine learning are transforming drug discovery - Pharmaceutical Technology - June 28th, 2025 [June 28th, 2025]