omniomni/omni-engineering huggingface dataset:
Doosan Robotics. Doosan Robotics () is a South Korean robotics company founded in 2015. It mainly manufactures cobots and has a global market share of 5th place as of 2022.

History 
In July 2015, it was selected as a new growth engine for Doosan Group and established as a subsidiary. It went into mass production for the first time in 2018. As of 2024, it has a total of 13 product groups.

In October 2023, it was listed on the KOSPI stock market.

Location 
In May 2022, Doosan Robotics America, a U.S. corporation, was established in Plano, Texas.

In May 2024, a European branch was established in Düsseldorf, Germany, and a service center was built in Heerhugowaard, the Netherlands, to provide after-sales service such as installation and recovery of cobots and replacement of parts.

Products 
As of 2022, the product sales volume is approximately 1,400 units, and the company's sales in North America and Europe account for 70% of the total. It ranks first in the domestic collaborative robot market share in South Korea. As of 2022, it holds approximately 72% of the global cobot market share for payloads of 20kg or more.

The company's other product lines are service robots, including camera robots, modular robot cafes, ice cream robots, and medical assistance robots. The camera robot also won a 2022 Consumer Electronics Show Innovation Award.

The company's cobot lineup can be largely categorized into the M, A, H, E, and P series: The E series is a model specialized for the Food and Beverage industry that was released in April 2023. The P series is a model unveiled at Automate 2024 in May 2024, and is specialized for palletizing with a payload of 30kg.

References

External link 
 

Robotics companies of South Korea
Electronics companies of South Korea
Industrial robotics
Companies based in Suwon
Electronics companies established in 2015
South Korean companies established in 2015
Companies established in 2015
Industrial robotics companies
Pages with unreviewed translations
36Kr. 36Kr () is a publicly listed Chinese media company that focuses on technology and financial news. It also is a data provider for entrepreneurs and investors. 

It has been referred to as China's equivalent of TechCrunch.

Background 

The origins of 36Kr can be traced to the new apps and gadgets tech blog written by Liu Chengcheng (), who was then a college student majoring in communication engineering at the Beijing University of Posts and Telecommunications. He then attended the University of the Chinese Academy of Sciences for a master's program in data mining.

By late 2010, 19 writers were regularly contributing to Liu's blog. It was then that Liu met Wang Xiao, one of the founders of Baidu, at a university alumni party. Wang offered to invest 300,000 yuan in his blog with Liu eventually accepting the money.

That year, Liu Chengcheng established 36Kr. Liu is a fan of Superman, who is from the planet Krypton. The element Krypton has the atomic number 36. Hence the company's name is named 36Kr.

In July 2011, 36kr launched 36tr which is a database which collected entrepreneurial projects. A few exclusive investors could access the database. Throughout 2012 more than 1,000 projects were put on 36tr.

36kr also launched 36kr+, a service platform that could provide resources to entrepreneurs.

In 2014, 36Kr launched Kr Space, a business incubator which later became a provider of co-working spaces. It drew comparisons to WeWork. In 2016, Kr Space was spun off as an independent business.

36Kr quickly expanded as more startups and investors went to the 36Kr site for news. In 2015, 36Kr launched a financing platform that connected entrepreneurs and investors. In 2016, 36Kr launched Jing Data, a subscription-based venture capital and private equity database.As 36Kr gained exposure, it obtained funding from investors such as Alibaba Group, Matrix Partners and e.ventures 36Kr was described as a sort of LinkedIn for Chinese startups.

By the end of 2017, 36Kr had amassed a global readership of more than 150 million and published a total of 50,000 stories online.

On 8 November 2019, 36Kr held its initial public offering by becoming a listed company on the Nasdaq raising $20 million. On its first day trading debut, its shares dropped 10%.

In March 2022, Ant Group, an affiliate of Alibaba Group which held 15.1% in 36Kr sold its entire stake in the company.

References

External links
 

2010 establishments in China
2019 initial public offerings
Companies based in Beijing
Companies listed on the Nasdaq
Online publishing companies
Technology blogs
Technology websites
Heat coloring of metals. Heat coloring of metals is a relatively simple process that, in principle, produces interference colors on the surface of the metal . The colors depend on the temperature to which the metal is heated. The most obvious example is thermally produced colors on steel, of which blue coloring is most commonly used. In addition to steel, by heat produced colors can also be produced on copper and its alloys, nickel, chromium, titanium, and tantalum.

Heat coloring of metals can also include procedures for obtaining brown or black color by gradually heating objects made of gilt copper (also known as vernis brun) or steel coated with linseed oil to 300 - 400 C.

This process also includes the Bower-Barf process, and related processes, in which the steel is heated to 800 C and exposed to highly heated steam.

History
Heat coloring of metals is probably the oldest method of coloring metal objects.

Examples

Heat coloring of iron and steel

straw yellow/232 C brown/265 C purple red/277 C light blue/288 C dark blue/293 C

Heat coloring of stainless steel

light yellow/290 C brown/390 C magenta/450 C blue/540 C dark blue/600 C

Heat coloring of titanium

pale gold straw/385 C purple/412 C deep blue /440 C red purple/565 C light green/510 C brown gray/648 C green blue/925 C

Heat coloring of copper and its alloys

Heating to a temperature of 161-341 C produces various interference colors

Literature

References

External links
Lewton Brain, C.: Patinas for small studios (pdf-file), 1985
Budija, G.: Collection of formulas for the chemical,electrochemical and heat colouring of metals, the cyanide free immersion plating and electroplating ( pdf file), Zagreb 2025
Heat tinting stainless steel

Hr:Termičko bojenje metala
Metalworking
Artworks in metal
Bashir Gwandu. Bashir Gwandu is a Nigerian engineer, technologist, and the former Executive Vice Chairman (EVC) of the National Agency for Science and Engineering Infrastructure (NASENI). Gwandu assumed office as the EVC of NASENI in May 2023, after being appointed to the position by former President Muhammadu Buhari.

Early life and education 
Bashir Gwandu was born and raised in Kebbi State, Nigeria. He completed his higher education in the field of engineering, where he acquired expertise that later informed his work in scientific and technological research. Gwandu holds various academic qualifications in engineering and technology management.

Career

Leadership at NASENI 
Gwandu's career at NASENI spans over a significant period, culminating in his appointment as the Executive Vice Chairman (EVC) in May 2023. During this time, he has been instrumental in driving the agency's mandate to promote scientific research, technological innovation, and engineering infrastructure in Nigeria.

As the head of NASENI, Gwandu has worked on initiatives aimed at improving the technological landscape of Nigeria. His leadership is focused on reducing Nigeria's dependence on foreign technology and ensuring that the country becomes self-sufficient in critical areas such as renewable energy, engineering, and manufacturing. He was sacked by President Bola Ahmed Tinubu and was replaced by Khalil Halilu.

Personal life 
Details about Gwandu's personal life remain relatively private, though he is known to be deeply passionate about scientific development and technological innovation.

References 

Living people
Nigerian chief executives
People from Kano
Nigerian politicians
Businesspeople in software
Nigerian Muslims
Benzotrifuroxan. Benzotrifuroxan is a heterocyclic organic compound that is related to 1,2,5-oxadioles. The high-energy compound is explosive.

History 
The compound was first synthesized in 1924 by O. Turek as hexanitrosobenzene. In addition to the hexanitroso structure, symmetric polycyclic structures could also be formulated.

Characteristics

Physical properties 
Benzotrifuroxan is a crystalline solid that melts at 195 °C.  The compound crystallizes in an orthorhombic crystal lattice with the space group Pna21.  The molar enthalpy of formation is 606 kJ·mol−1, the enthalpy of combustion is −2967 kJ·mol−1.

Chemical properties 
Benzotrifuroxan can decompose explosively. The heat of explosion is 5903 kJ·kg −1, the detonation speed is 8.61 km·s −1.  The compound is sensitive to impact. 

Benzotrifuroxan forms stable complexes with aromatic hydrocarbons such as naphthalene, 1-phenylnaphthalene, 2-phenylnaphthalene and tetrahydronaphthalene. Recrystallization in benzene yields a 1:1 complex with the solvent, whereby the benzene can only be removed at 100 °C in vacuum.

Synthesis 
Benzotrifuroxan can be obtained by thermal degradation of 1,3,5-triazido-2,4,6-trinitrobenzene.

A further synthesis can be carried out by reacting 5,7-dichloro-4,6-dinitronbenzofuroxan with sodium azide.

Uses 
In combination with TNT, the compound can be used to produce nanodiamonds using detonation shock waves.

References 

attribution translated from the German article :de:Benzotrifuroxan
Heterocyclic compounds with 4 rings
Benzoxadiazoles
Orthorhombic crystals
Explosive chemicals
Fatma Özcan. Fatma Özcan is a Turkish-American computer scientist who works as a principal software engineer for Google, where her work concerns infrastructure such as MapReduce for the analysis of big data.

Education and career
özcan has an undergraduate degree from Middle East Technical University in Ankara. She completed her Ph.D. in 2001 at the University of Maryland, College Park, with the dissertation Improving the performance of heterogeneous databases and agents, supervised by V. S. Subrahmanian.

On completing her Ph.D., Özcan joined the IBM Research Almaden Research Center in San Jose, California, where her first project involved integrating XML with the IBM Db2 database, a feature that later became known as pureXML. She moved from IBM to Google in 2020.

Recognition
Özcan received the 2022 VLDB Women in Database Research Award of the Very Large Data Bases Endowment, given "for two decades of research in query languages and query processing, and her development of new technologies that have had significant impact on widely-used data management products". She was named as an ACM Fellow, in the 2024 class of fellows, "for contributions to the field of scalable data management systems".

References

External links

Year of birth missing (living people)
Living people
Turkish emigrants to the United States
Turkish computer scientists
American software engineers
American women computer scientists
Database researchers
Middle East Technical University alumni
University of Maryland, College Park alumni
IBM Research computer scientists
Google employees
2024 fellows of the Association for Computing Machinery
Hamish Dewar. Hamish Dewar (September 19, 1937, in Dumfries - April 9, 2024, in Edinburgh) was a lecturer and a researcher at the University of Edinburgh. He is credited with creating the first known Quine program written in Atlas Autocode at Edinburgh in the 1960s. He is also credited with creating the Edinburgh Compatible Context Editor and the Edinburgh IMP around the same time.

References 

1937 births
2024 deaths
Academics of the University of Edinburgh
AI/ML Development Platform. AI/ML development platforms, such as  PyTorch and Hugging Face, are software ecosystems designed to facilitate the creation, training, deployment, and management of artificial intelligence (AI) and machine learning (ML) models. These platforms provide tools, frameworks, and infrastructure to streamline workflows for developers, data scientists, and researchers working on AI-driven solutions.

Overview 
AI/ML development platforms serve as comprehensive environments for building AI systems, ranging from simple predictive models to complex large language models (LLMs). They abstract technical complexities (e.g., distributed computing, hyperparameter tuning) while offering modular components for customization. Key users include:

 Developers: Building applications powered by AI/ML.
 Data scientists: Experimenting with algorithms and data pipelines.
 Researchers: Advancing state-of-the-art AI capabilities.

Key features 
Modern AI/ML platforms typically include:

 End-to-end workflow support:
 Data preparation: Tools for cleaning, labeling, and augmenting datasets.
 Model building: Libraries for designing neural networks (e.g., PyTorch, TensorFlow integrations).
 Training & Optimization: Distributed training, hyperparameter tuning, and AutoML.
 Deployment: Exporting models to production environments (APIs, edge devices, cloud services).
 Scalability: Support for multi-GPU/TPU training and cloud-native infrastructure (e.g., Kubernetes).
 Pre-built models & templates: Repositories of pre-trained models (e.g., Hugging Face’s Model Hub) for tasks like natural language processing (NLP), computer vision, or speech recognition.
 Collaboration tools: Version control, experiment tracking (e.g., MLflow), and team project management.
 Ethical AI tools: Bias detection, explainability frameworks (e.g., SHAP, LIME), and compliance with regulations like GDPR.

Examples of platforms

Applications 
AI/ML development platforms underpin innovations in:

 Health care: Drug discovery, medical imaging analysis.
 Finance: Fraud detection, algorithmic trading.
 Natural language processing (NLP): Chatbots, translation systems.
 Autonomous systems: Self-driving cars, robotics.

Challenges 

 Computational costs: Training LLMs requires massive GPU/TPU resources.
 Data privacy: Balancing model performance with GDPR/CCPA compliance.
 Skill gaps: High barrier to entry for non-experts.
 Bias and fairness: Mitigating skewed outcomes in sensitive applications.

Future trends 
 Democratization: Low-code/no-code platforms (e.g., Google AutoML, DataRobot).
 Ethical AI integration: Tools for bias mitigation and transparency.
 Federated learning: Training models on decentralized data.
 Quantum machine learning: Hybrid platforms leveraging quantum computing.

See also 
 Automated machine learning
 Large language model

References

External links 
 MLflow Official Website – Open-source platform for the machine learning lifecycle.
 Hugging Face – Community and tools for NLP models.
 TensorFlow – Google's machine learning framework.
 Google AI Research – Publications on AI/ML advancements.

Machine learning
Living Intelligence. Living Intelligence is the convergence of artificial intelligence, biotechnology, and advanced sensors.

Overview 
 
The conceptual framework of Living Intelligence was introduced in 2024 with a report published by Amy Webb and Sam Jordan from Future Today Institute. The report described it as a convergence of three technologies (artificial intelligence, biotechnology, and advanced sensors) for systems capable of sensing, learning, adapting, and evolving.
 
Living Intelligence relies on the interaction between AI systems (such as Large Action Models), sensor networks that collect and transmit data, and biological engineering applications which include generative biology.

Applications 
 
Living Intelligence can be used in a variety of industries, including business and education. In education, it focuses on human cognition to personalize learning experiences. It can also assist in training AI models with empathy for applications of customer service and healthcare.
 
Notable early developments in Living Intelligence include DishBrain, a biological computer created by Cortical Labs using brain cells, and various applications of generative biology by companies like Ginkgo Bioworks and Google DeepMind's AlphaProteo project.

References 

Artificial intelligence
Bhavin J. Shastri. Bhavin J. Shastri is a Canadian academic, specializing in nanophotonics, photonic integrated circuits, and neuromorphic computing. He holds the Canada Research Chair in neuromorphic photonic computing and is a researcher at Queen's University at Kingston.
 
Shastri is a Member of the College of the Royal Society of Canada and holds a cross-appointment in Electrical and Computer Engineering at Queen's University. He also serves as the co-director of NUCLEUS, a pan-Canadian photonic computing program funded by NSERC CREATE.

Early life and education
Bhavin J. Shastri was born in Nairobi, Kenya, in 1981. He attended McGill University, where he earned a B.Eng. with distinction in electrical engineering in 2005, followed by an M.Eng. in 2007, and a Ph.D. in 2012, all specializing in photonics.

Career
From 2014 to 2016, Shastri was a Banting Postdoctoral Fellow and from 2012 to 2014 he was an NSERC Postdoctoral Fellow at Princeton University, where he worked under the guidance of Paul Prucnal. He then served as an Associate Research Scholar at Princeton from May 2016 to June 2018 and continues to serve as a Visiting Research Collaborator since July 2018.

In December 2020, Shastri became a faculty affiliate at the Vector Institute.

In 2024, Shastri was appointed as the scientific co-director of the NUCLEUS CREATE Program under NSERC. He was also appointed to the Canada Research Chair in Neuromorphic Photonic Computing, in the same year.

In September 2024, Shastri was inducted into the Royal Society of Canada.

Research
Shastri is recognized as a pioneer in the field of neuromorphic photonics, a term he co-coined.

Books
 P. R. Prucnal and B. J. Shastri, Neuromorphic Photonics, CRC Press, Taylor & Francis, Boca Raton, Florida (2017).

Selected awards and recognition
 2020: IUPAP Young Scientist Prize in Optics 
 2022: SPIE Early Career Achievement Award
 2022: iCANX Young Scientist Award
 2024: Science News (SN) 10 Scientist to Watch
 2024: Member of the College, The Royal Society of Canada

References

Living people
1981 births
Canadian academics
Academic staff of Queen's University at Kingston
Rainbow Robotics. Rainbow Robotics () is a South Korean robotics company founded in 2011 by Professor Oh Jun-ho of the HUBO Lab at the KAIST.

History 
Oh Jun-ho, Professor of KAIST, founded Rainbow in 2011 with students at the KAIST Humanoid Robot Research Center. The company produced 15 units of the mass-produced model of HUBO-2, HUBO-2 Plus, by 2012, exporting four units to domestic humanoid research teams and 11 units to overseas research teams in the United States, Japan, Singapore, and China.

Location 
The headquarters is located in the Daedeok Innopolis in Yuseong District, Daejeon. In 2023, a local corporation with a dedicated collaborative robot sales and customer management organization was established in Schaumburg, Illinois, and a branch office was subsequently established in the United States.

Product 
The flagship product, HUBO, is the first bipedal humanoid robot developed by KAIST. DDRC-HUBO, an exoskeleton-type disaster relief robot, is the winning model in the 2015 DARPA Robotics Challenge. It has an original actuator cooling system and a wheeled driving mode. HUBO-2 is the world's first commercialized humanoid robot platform and is a humanoid robot with a size similar to an actual person. It applies a cable-driven adaptive five-finger hand, and the fingers can close according to the shape of the object, allowing it to grasp objects of various shapes.

Other products include astronomy mount system, media service robot, medical laser robot toning system, cocktail and barista robot, cobot, mobile robot, and quadruped robot.

See also 
 Humanoid robot
 HUBO

References

External links 
 

Robotics companies of South Korea
Electronics companies of South Korea
Companies based in Daejeon
Companies listed on the Korea Exchange
Electronics companies established in 2011
South Korean companies established in 2011
Companies established in 2011
Industrial Museum (London). The Industrial Museum (later the Industrial Health and Safety Centre or Safety, Health and Welfare Museum) was a museum at the junction of Horseferry Road and Elverton Street in the City of Westminster, London, run by the factory department of the Home Office. It was designed by the Office of Works and was due to open in 1914, but the outbreak of the First World War meant it was instead used for social and educational events by Australian troops, an Anti-Aircraft Signal Company and the Metropolitan Police until 1925.

It took until December 1927 for it to be re-opened as a museum, with a catalogue produced in 1934. The Factory Department and the Museum were transferred to the Ministry of Labour and National Service for the duration of the Second World War and by 1943 staffing shortages had forced the Museum to close for the duration. It hosted the 1951 Manpower Exhibition and on 22 March 1955 was renamed the Industrial Health and Safety Centre. 

It closed in 1980 after an cost-benefit study by the Health and Safety Executive found that (in the words of the Secretary of State for Employment) "the cost per head for visitors was higher than for comparable methods of bringing relevant information to the public". Its building was demolished and in 1985 the drill hall of the London Scottish was built on the site.

References

Museums established in 1927
Museums disestablished in 1980
Defunct museums in London
1914 establishments in England
1927 establishments in England
1980 disestablishments in England
Home Office (United Kingdom)
Metropolitan Police buildings