Increasing global energy demand and renewable integration complexity have placed buildings at the center of sustainable energy management. We present a three-step reinforcement learning(RL)-based Building Energy Management System (BEMS) that combines clustering, forecasting, and constrained policy learning to address scalability, adaptability, and safety challenges. First, we cluster non-shiftable load profiles to identify common consumption patterns, enabling policy generalization and transfer without retraining for each new building. Next, we integrate an LSTM based forecasting module to anticipate future states, improving the RL agents' responsiveness to dynamic conditions. Lastly, domain-informed action masking ensures safe exploration and operation, preventing harmful decisions. Evaluated on real-world data, our approach reduces operating costs by up to 15% for certain building types, maintains stable environmental performance, and quickly classifies and optimizes new buildings with limited data. It also adapts to stochastic tariff changes without retraining. Overall, this framework delivers scalable, robust, and cost-effective building energy management.

Despite the huge progress in myriad generation tasks, pretrained language models (LMs) such as GPT2 still tend to generate repetitive texts with maximization-based decoding algorithms for open-ended generation. We attribute their overestimation of token-level repetition probabilities to the learning bias: LMs capture simple repetitive patterns faster with the MLE loss. We propose self-contrastive training to penalize the output of a premature checkpoint of the same model when it incorrectly predicts repetition, which is shown to mitigate repetition effectively while maintaining fluency on two datasets. Furthermore, we find that LMs use longer-range dependencies to predict repetitive tokens than non-repetitive ones, which may be the cause of sentence-level repetition loops.

Facebook's parent company, Meta, has used AI to develop a new way of creating concrete which it claims produces 40 per cent less carbon emissions than standard mixtures, and is already using it in its latest data centre. But experts say that concrete mixtures with similar emissions are already in use across Europe, and that constructing new buildings is incompatible with reducing carbon pollution. Meta is investing heavily in AI research, including building the world's most powerful AI-specific supercomputer. Its main aims are to develop better speech-recognition tools, automatically translate between different languages and help build a 3D virtual metaverse, but the company is also using AI to work on projects such as concrete production. The company says that this construction material is a major contributor to its carbon footprint as it builds data centres around the world for its online services.

The need for construction is more significant than ever. The projected 70% increase in urban population over the next 15 years will require many new buildings. Although the European Union anticipates that such a need will arise, builders still do not see this opportunity. So if you want to enter the construction industry or any other profession in this field, I have good news for you -- you are living in a hellish boom time! Unfortunately, this boom will lead to a climate catastrophe on a hitherto unknown scale.

Designers increasingly rely on procedural generation for automatic generation of content in various industries. These techniques require extensive knowledge of the desired content, and about how to actually implement such procedural methods. Algorithms for learning interpretable generative models from example content could alleviate both difficulties. We propose SIGI, a novel method for inferring shapes and inducing a shape grammar from grid-based 3D building examples. This interpretable grammar is well-suited for co-creative design. Applied to Minecraft buildings, we show how the shape grammar can be used to automatically generate new buildings in a similar style.

Last fall, the MIT Stephen A. Schwarzman College of Computing embarked on a project to design and construct a new building on Vassar Street in Cambridge, at the former site of Building 44. Working with Skidmore, Owings & Merrill (SOM), the design for the new building is taking shape, with plans for the exterior façade now complete. The proposed project will establish a home for the MIT Schwarzman College of Computing, providing state-of-the-art space for computing research and education. The building's central location in the Vassar Street block between Main Street and Massachusetts Avenue will help form a new cluster of connectivity, and will enable the space to have a multifaceted role. The project has been reviewed extensively with city planning staff and will be presented to the Cambridge Planning Board for review and approval.

Chief Justice of India, Sharad Arvind Bobde on Saturday hinted at the possibility of Artificial Intelligence being developed for the court system while making it clear that it will never replace human discretion. Speaking at an event here, Bobde said, "We have a possibility of developing Artificial Intelligence for the court system. Only for the purpose of ensuring that the undue delay in justice is prevented." "I must make it clear at the outset as there are times when even judges have asked this. AI is not going to replace human judges or human discretion", he added.

Chief Justice of India, Sharad Arvind Bobde on Saturday hinted at the possibility of Artificial Intelligence being developed for the court system while making it clear that it will never replace human discretion. Speaking at an event in Bengaluru, Bobde said, "We have a possibility of developing Artificial Intelligence for the court system. Only for the purpose of ensuring that the undue delay in justice is prevented." "I must make it clear at the outset as there are times when even judges have asked this. AI is not going to replace human judges or human discretion", he added.

MIT announced today that it is massively doubling down on the future of computer science with the launch of a new college of computing. The university is committing $1 billion in resources to the new school, and the university received a $350 million donation from Stephen A. Schwarzman, who will be the naming donor. MIT said that its commitment is the largest of a university yet to the discipline. The university is already one of the leaders in computer science, with a famed department located in the School of Engineering. The new initiative will see computer science, artificial intelligence, and data science placed in the new school, complete with a new dean and around 50 new faculty positions according to the university.

"The Max Planck Society has created a scientific beacon of light here which beams far and wide, attracting both emerging and established scientists from all over the world," remarked Max Planck President Martin Stratmann. The new building, which houses all three of the Institute's departments, was constructed between September 2014 and March 2017. It was funded by the federal state of Baden-Württemberg's government which places great emphasis on research into intelligent systems: "With its Institute for Intelligent Systems in Tübingen and Stuttgart, the Max Planck Society has firmly established one of the key research fields in the digital transformation in Baden-Württemberg," indicated Minister-President Winfried Kretschmann. "The federal state has contributed € 41 million to the new building in Tübingen – this represents a sound investment which will help ensure that Baden-Württemberg remains a leading centre of research on artificial intelligence." The new building provides scientists with an outstanding environment in which to advance their theoretical and experimental research.