Large Language Models (LLMs), Vision LMs and Multimodal Large Language Models (MLLMs) have shown impressive performance across various Natural Language Understanding and Multimodal Understanding tasks while improving physical/spatial intelligence tasks similar to/better than human performance. This work attempts to bring various alignment studies to find consensus about alignment/divergences that are desirable and not desirable. There are broadly two categories of alignment studies included-human-AI and human brain-AI representational alignment. The two categories may evaluate alignment/divergence on the basis of specific tasks, applications, evaluations and hypotheses while considering various types of data such as text, image, audio and video inputs across LLMs, VLMs and MLLMs. This attempt finds that the insights from the human brain-AI representational alignment may help with better human-centered design and human-AI alignment by also including potential research questions/directions. The key finding is that there is, however, a lack of sufficient consensus for alignment given the disagreements within and across the two categories due to both undesirable - divergences and alignment.

Finding Consensus from AI Alignment Studies: A Short Survey

Specialized computing infrastructure is undergoing rapid transformation driven by advances in artificial intelligence, quantum computing, and exascale systems. This paper analyzes the evolution of specialized computing architectures, communication networks, storage systems, and management frameworks. Through case studies and comparative analysis, we highlight emerging trends, challenges, and opportunities shaping the next generation of high-performance and domain-specific computing environments.

Evolution of Specialized Computing Infrastructure: From Traditional Data Centers to Specialized Supercomputing Architectures

ArEEG-Open-Access-Arabic-Inner-Speech-EEG-Dataset

ApplicativeDo tries to remove the monad binds where possible when desugaring Haskells' do-notation. It does this by looking at inter-statement dependencies and connecting them with applicative operations when possible; this introduces implicit parallelism in the code. Deciding which structure to generate is tricky, since many different are usually possible. Currently, this is solved with simple minimum cost analysis with an unit cost model, assuming each statement takes the same amount of time to evaluate. By extending the cost model inside the ApplicativeDo algorithm for variable evaluation costs, we perform smarter generation of code by prioritising parallelisation of heavy statements.

At Facebook, Marlow et al. developed Haxl, a data-fetching library that can use applicative structure in expressions for free parallelism. To our knowledge, it is the only library that can do automatic parallelism on applicative expressions. We observe significant wall-clock speedups in many cases when running benchmarks with Haxl, compared to the original ApplicativeDo-desugared programs, given relative costs of statements.

The ApplicativeDo extension is agnostic to the source of costs, but one way of providing them is investigated as optional weight annotations on do-statements. This works well when the relative costs are known, but this kind of run-time estimation is notoriously difficult, particularly in Haskell. We suggest different directions for future work relating to sources of costs.

Better Implicit Parallelism Improving ApplicativeDo Heuristics Through Weight Annotations MSc thesis in Computer Science: Algorithms, Language and Logic

Specialized computing infrastructure is undergoing a radical transformation driven by emerging technologies such as advanced artificial intelligence, quantum computing, and exascale computing. This comprehensive study examines recent developments in specialized computing infrastructure through mixed-methods analysis, focusing on architectural innovations, decentralized management protocols, and their applications in scientific and commercial domains. We analyze 15 specialized systems and present six detailed case studies demonstrating performance improvements of 10-100x over traditional infrastructure. Our research highlights the paradigm shift from general-purpose to workload-specific architectures, addressing critical challenges in interoperability, energy efficiency, and decentralized management. The findings contribute to the emerging field of decentralized scientific computing infrastructure, offering actionable recommendations for researchers, industry stakeholders, and policymakers in the Web3 science ecosystem.

Specialized computing infrastructure is undergoing a radical transformation driven by emerging technologies such as advanced artificial intelligence, quantum computing, and exascale computing. This work examines recent developments in specialized computing infrastructure, focusing on new architectural designs, management protocols, and their applications in scientific and commercial domains. We present a comprehensive analysis of emerging trends, challenges, and opportunities in this field.

The Moon represents a strategic cornerstone in the future of space exploration and technological development. Its role has evolved beyond scientific observation to become a platform for testing advanced engineering systems and building a sustainable space economy. This paper analyzes the growing importance of the Moon in technological innovation, space resource utilization, and infrastructure development for interplanetary missions. We discuss the technical, environmental, and geopolitical challenges associated with lunar settlement and propose future visions to enhance the effective use of the Moon in supporting human expansion beyond Earth. Our findings indicate that lunar resource utilization could reduce space mission costs by up to 60%, while the Moon's position as a testing ground significantly mitigates technical risks for Mars missions.

The Moon as a Strategic Platform for Space Technology Development and the Formation of a Global Space Economy

Questa ricerca si propone di introdurre ed analizzare l'antinomia dello specchio nverso, un paradosso psicologico del tutto nuovo che illustra come un investimento consapevole nella cura della propria bellezza possa portare ad una crescente difficoltà nel percepire autenticamente quella stessa bellezza. Attraverso un'analisi che unisce psicologia della percezione, fenomenologia dell'embodiment e teorie del sé, si dimostra come l'osservazione ripetuta ed analitica del proprio aspetto fisico generi tre fenomeni interconnessi: (1) una frammentazione percettiva che sostituisce la visione complessiva con un'attenzione eccessiva ai difetti; (2) una dissociazione tra il sé vissuto ed il sé osservato, che porta ad una depersonalizzazione estetica; (3) un bias cognitivo in cui l'esperienza personale porta ad una mancanza di piacere estetico invece di un apprezzamento maggiore. L'antinomia si presenta come un circolo vizioso che si autoalimenta: ogni atto di cura richiede di identificare imperfezioni, aumentando la consapevolezza cognitiva dei difetti percepiti ed alimentando ulteriore ansia estetica. Il paradosso raggiunge il suo culmine quando si considera che la consapevolezza estetica elimina proprio quella spontaneità ed autenticità che sono al centro dell'attrattiva interpersonale. Lo studio esplora le implicazioni cliniche di questo fenomeno, particolarmente importanti per comprendere il disturbo di dismorfismo corporeo ed i comportamenti compulsivi legati all'immagine, suggerendo che la bellezza umana esista fondamentalmente nell'incontro tra soggetti piuttosto che nell'analisi isolata del proprio aspetto.

ANTINOMIA DELLO SPECCHIO INVERSO

The Moon, Earth’s closest celestial neighbor, continues to inspire scientific exploration.
As a natural satellite, it offers a unique opportunity to study the formation and evolution
of the solar system. This research paper highlights the importance of lunar exploration,
reviewing key missions, technologies, and the scientific and strategic benefits of returning
to the Moon.
The study emphasizes how lunar geology contributes to understanding planetary ori
gins, and how the Moon serves as a testing ground for space technologies supporting
future missions to Mars and beyond. It also explores in-situ resource utilization (ISRU),
such as the presence of water ice in polar regions, and current efforts to develop sustain
able lunar habitats.
Despite major advances, challenges remain, including radiation, low gravity, and lo
gistical constraints. Through continuous innovation and international cooperation, the
Moon remains a vital gateway for deep space exploration and the future of human pres
ence beyond Earth.
Keywords: Moon, Lunar Exploration, Artemis, ISRU, Space Settlement, Mars Gate
way
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