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Nepal Architecture Archive

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Established in 2016, the Nepal Architecture Archive (NAA) is a unique repository of research conducted by national and international scholars and practitioners on the built landscape of Nepal across time.

The conceptual premise of our archive emerged from a spontaneous and spirited conversation – between Arun Saraf, Namita Saraf, Neils Gutschow and Eric Theofiled – at the Yak and Yeti bar, in 2009, which quickly morphed into a detailed restoration and documentation project. As the Saraf Foundation initiated the Taragaon restoration project, in parallel, we also began researching and acquiring documents on the nuanced histories of our landscape. Today, NAA consists of a comprehensive collection of sketches, photographs, indigenous architectural drawings, and detailed documents on the material culture of Nepal.

These archival documents are digitized – under the guidance of Eka Resources – and are now accessible to the public on written requests. As part of our objective on heritage preservation, the Saraf Foundation continues to work with locals and expatriates to collect and organize documents and archival material relevant to the region. Thus, archiving is an ongoing process at NAA, a spacethat also provides a secure and controlled environment with adequate material storage facilities for the acquired documents.

NAA receives diverse collections of materials regularly, which then undergo a digital scanning process, online references, and copyright adjustment according to international copyright standards. Thus, we play an integral role in ensuring that indigenous architecture and baatsukala – the understanding of traditional processes, materials, and designs – are preserved and rendered accessible to architects that lead renovation and restoration projects. After the earthquake of 2015, NAA provided authentic documents to the restoration team at Kasthamandap, and thus, it was rebuilt as per the original design and materials.

Scholars whose works feature at the NAA include: Niels Gutschow, Wolfgang Korn, Jørgen Rahbek Thomsen & Jens Wærum (Danish Architects team), John Harrison, Andreas Brandt, Robert Powell, Konstanty Gutschow, Thomas Kelly, Tiziano Terzani, Axel Weller, Klaus Kunzmann, Klaus Kette, Franz Frei, Ulrich Burscher, Thomas Turscher, Raimund Wuldz, and Peter Herrle amongst others.

Acquisitions

In 2013, as the Taragaon restoration project began, around 150 exhibits were collected from various renowned scholars who worked in Nepal. Over the years, this collection continued to grow, and by 2015, nearly 2000 archives were housed at the Saraf Foundation. Due to this tremendous response, we received an impetus to establish a physical archive – and thus NAA was conceptualized, designed, and launched in 2016, with the support of Neils Gutschow and his team.

The largest collections were received from a Danish group of architects, as well as Wolfgang Korn, Dr. Becker, Peace Corp. volunteers, Barbara Adams, and Neils Gutschow, who also supported the collection of wood carvings and pottery from Bhaktapur and old brick samples from various monuments.

Over the years, the Foundation has received different types of materials including: Architectural drawings, maps, sketches, photographs, slides, negatives, beta tapes, books, research documents, reference documents, proposals, feasibility studies, unpublished reports, diaries, manuscripts and digital materials.

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Please note you do not have access to teaching notes, rebuilding nepal: traditional and modern approaches, building or diminishing resilience.

International Journal of Disaster Resilience in the Built Environment

ISSN : 1759-5908

Article publication date: 11 June 2018

Issue publication date: 11 June 2018

The purpose of this paper is to highlight the importance of vernacular architecture and traditional knowledge to building resilience in Nepal and the impact of modernisation on that resilience and architectural diversity.

Design/methodology/approach

Using an action research approach, including field observations and discussions with local community members, artisans, architects, engineers and other international experts, the study examines the resilience of traditional building typologies to natural hazards in Nepal, including earthquake; the changes that have occurred over time leading to the failure and/or rejection of traditional construction; and a review of post-earthquake reconstruction options, both traditional and modern.

Although traditional approaches have been cyclically tested over time, this study found that changes in building materials, technologies, knowledge and skills, access to resources, maintenance practices, urban environments and societal aspirations have all contributed to the popular rejection of vernacular architecture following the earthquakes.

Research limitations/implications

The research is limited to traditional timber and masonry construction in the Kathmandu Valley and surrounding mountain areas.

Practical implications

To improve resilience the study identifies the need for capacity building in both traditional and modern construction technologies; adoption of approaches that use local materials, knowledge and skills, whilst addressing local timber shortages and access issues; a transparent construction certification system; good drainage; and regular maintenance.

Originality/value

The study critically evaluates the impact of technological, environmental, social and economic changes over time on the resilience of vernacular housing in Nepal.

• Architectural diversity
• Building resilience
• Changing construction technologies
• Impacts of modernization on resilience
• Vernacular architecture

Acknowledgements

This paper forms part of a special section “Invited papers from the International Conference on Building Resilience”, guest edited by Dilanthi Amaratunga and Richard Haigh.

Forbes, C. (2018), "Rebuilding Nepal: traditional and modern approaches, building or diminishing resilience?", International Journal of Disaster Resilience in the Built Environment , Vol. 9 No. 3, pp. 218-229. https://doi.org/10.1108/IJDRBE-01-2017-0001

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In This Article Expand or collapse the "in this article" section Buddhist Art and Architecture in Nepal

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Buddhist Art and Architecture in Nepal by Erberto Lo Bue LAST REVIEWED: 24 November 2020 LAST MODIFIED: 24 November 2020 DOI: 10.1093/obo/9780195393521-0079

The earliest evidence of the presence of Buddhism in the Nepal Valley belongs to the 5th century. According to inscriptions of the Licchavi dynasty, the Buddhist ruler Vrsadeva (fl. c.  400  CE ) founded a monastery at Svayambhu. Most Licchavi foundations have disappeared, but a few, such as the Gum monastery near Sankhu, have survived. The Buddhist pantheon in Nepal is obviously related to the Indian tradition, in which Buddhism and Hinduism coexisted and influenced each other through many centuries. Although the sophisticated artistic production in the Nepal Valley represents to some extent the continuation of the aesthetics prevailing in India under the Gupta, Pâla, and Sena dynasties, the art and architecture of its original inhabitants, the Newars, developed in a unique way. Even after their Buddhist tradition was cut off from its sources following the destruction of all Indian monastic universities by the 13th century, Newar artists continued to produce images for Buddhists not only in Nepal, but also in other countries, particularly Tibet. At least two Buddhist traditions and related styles may be distinguished in Nepal: the Newar ones of the Nepal Valley, where Buddhism followed its own local development; and the Tibetan ones, in areas inhabited by people of Tibetan stock and language, such as Lo (Mustang) and Dölpo, and in the Nepal Valley itself, where the number of Tibetan monasteries has increased significantly since the 1960s. That accounts for iconographic and stylistic differences in images produced even by the same artist, who traditionally can adapt easily to the requests of his client. The traditional style of architecture characterizing most of the 363 monasteries in the Nepal Valley, the earliest ones dating to the Licchavi dynasty, may be traced to Buddhist monastic structures such as those found at Sanchi, Ajanta, and Ellora, representing stone versions of now-lost Indian wooden architecture, but at the same time prototypes of the brick and wood monasteries of the Nepal Valley. Newar monasteries are characterized by three essential elements: the main shrine, a small stupa in the middle of the courtyard, and a tantric temple above the shrine. Their courtyards are surrounded by rooms that do not necessarily conform in their function to their Indian models, since, following the decline of Buddhism in the Nepal Valley, they have sometimes turned into residential buildings. Another feature deriving from Indian architecture is the tòrana , originally a decorated arch leading to a shrine, which in the Nepal Valley turned into a semicircular panel placed above the doors of shrines or gates.

There are no general overviews of Nepalese Buddhist art and architecture, both subjects being covered in works dealing also with Hindu art and architecture in Nepal. The first significant study of the art and sculpture of the Nepal Valley was produced by Pratapaditya Pal ( Pal 1974 , cited under Sculpture , and Pal 1978 , cited under Painting ), who has since published a series of catalogues on the subject, one of them being devoted exclusively to Newar art ( Pal 1985 , cited under Collections and Exhibitions ). Hutt, et al. 1994 provides an introduction to the art and architecture of the Nepal Valley, devoting sections of this work to Buddhist sites. Also, Slusser 1982 deals with Newar Buddhist art and architecture, placing them in their cultural and historical context. Buddhist monasteries and stupas are surveyed in Locke 1985 and Gutschow 1997 (both cited under Architecture ), whereas an inventory of sites and monuments in the Nepal Valley in the early 1970s was edited by Pruscha ( Pruscha 1975 ). The only serious guide recording Buddhist as well as Hindu sites and temples all over Nepal is written in French ( Rouvre 1975 ). Newar artists have been active not only in the Nepal Valley, but also in other parts of the Himalayas such as Lo (Mustang), Ladakh, and Bhutan ( Lo Bue 1985 ), and beyond, from Tibet ( Lo Bue 1988 ) to China ( Jing 1994 ). However, the finest wall paintings in Nepal are found in the culturally Tibetan former kingdom of Mustang ( Lo Bue 2010 ).

Hutt, Michael, David N. Gellner, and Shastri Indo-Canadian Institute. Nepal . A Guide to the Art and Architecture of the Kathmandu Valley . Gartmore, UK: Kiscadale, 1994.

An introduction to Newar art and architecture dealing also with Buddhist sites and images in the Nepal Valley, it is intended for a general readership. It includes pictures, some of them in color; maps and drawings; and, being based on authoritative sources, it is useful for students and travelers alike.

Jing, Anning. “The Portraits of Khubilai Khan and Chabi by Anige (1245–1306), a Nepali Artist at the Yuan Court.” Artibus Asiae 54.1–2 (1994): 40–86.

DOI: 10.2307/3250079

This essay affords much more than what is suggested by its title, since it documents the life story of the great Newar sculptor, painter, and architect Anige, exemplifying the important role played by the Buddhist artists of the Nepal Valley well beyond the Himalayas.

Lo Bue, Erberto F. “The Newar Artists of the Nepal Valley: A Historical Account of Their Activities in Neighbouring Areas with Particular Reference to Tibet.” Oriental Art 31.3 (1985): 262–277.

This essay, published in two parts, represents a first attempt to record the role played by sculptors and painters from the Nepal Valley in the production of images for Buddhist clients and monastic institutions in other Himalayan areas as well as Tibet and India from the 8th to the 20th century. Part 2 in Oriental Art 31.4 (1986): 409–420.

Lo Bue, Erberto F. “Cultural Exchange and Social Interaction between Tibetans and Newars from the Seventh to the Twentieth Century.” International Folklore Review 6 (1988): 86–114.

This essay deals with the relationship between Buddhist Newars and Tibetans both in Tibet and in the Nepal Valley, with particular reference to the Newars’ organization in Tibet and to their production of Buddhist images for Tibetan clients and institutions (pp. 91–110).

Lo Bue, Erberto F. Wonders of Lo: The Artistic Heritage of Mustang . Mumbai: Marg, 2010.

This monograph is devoted to Buddhist art and architecture in the culturally Tibetan former kingdom of Mustang, which maintained a degree of autonomy even after its inclusion in the Gorkha kingdom. Its authors deal with the most important and some hitherto unpublished sites in the region, with a special emphasis on painting.

Macdonald, Alexander W., and Anne Vergati Stahl. Newar Art: Nepalese Art during the Malla Period . Warminster, UK: Aris & Phillips, 1979.

This survey deals with Newar cultural history, architecture, and painting during the Malla dynasties (1200–1768). It includes a section on the Newar pantheon (pp. 38–60), which it illustrates with pictures of Hindu as well as Buddhist statues, one on Buddhist architecture (pp. 71–82), and a chapter on painting (pp. 119–150), some of it Buddhist.

Pruscha, Carl, ed. Kathmandu Valley: The Preservation of Physical Environment and Cultural Heritage : Protective Inventory . 2 vols. Vienna: Anton Schroll, 1975.

This inventory was meant to be a tool for the Nepalese government to preserve the cultural heritage and physical environment of the Nepal Valley. Although it failed in its purpose, it affords black-and-white pictures of and basic information on scores of Hindu and Buddhist sites all over the valley as they were in the early 1970s.

Rouvre, Évrard de. Népal . Paris: Robur, 1975.

This French travel guide, handy, conveniently arranged in alphabetical order, and based on authoritative sources, describes and illustrates in color the most important sites in Nepal, including Buddhist ones.

Slusser, Mary Shepherd. Nepal Mandala: A Cultural Study of the Kathmandu Valley . 2 vols. Princeton, NJ: Princeton University Press, 1982.

Because of the detailed treatment of its variously related subjects, this exhaustive and clearly written study, based on many references to scientific publications and indigenous sources, provides invaluable information on the Nepal Valley, including Buddhist art and architecture, and its reading is compulsory for a serious approach to those subjects.

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Nepal Architecture

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Vernacular architecture in the contemporary context in the outskirts of Kathmandu Valley is being undermined and is at the direct influences of modernization and globalization. This paper intends to explore the status quos, continuities and discontinuities of the vernacular architecture in the outskirts of the Kathmandu Valley in the contemporary context. Literatures were studied to comprehend the concepts of vernacular architecture and the practicing paradigms in the global context. These reviews were referenced to critically analyze the contexts in the contemporary outskirts of the Kathmandu Valley. Three different individuals were interviewed and a field observation in Ghumarchowk was conducted. Studies showed that the vernacular architecture practices in the outskirts are either being disregarded or are adulterated to fit in the contemporary modernity. At few instances of conservational approaches to promote and encourage vernacular architecture is also found but, is only constricted to a profit generating institutional mechanisms. The sustainable features of the vernacular architectural practices where, environment exploitation is discouraged and social cohesion and bonding is appreciated should not be undermined. The studies project the needs for proper strategies, policies, awareness and design skillsets for a rational continuity of the vernacular architecture where few values and norms of the vernacular architecture may have to be reconsidered.

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Vernacular settlement of the Magar community in the Taka village of East Rukum are still lively, and represent the society, cultural and history of the place, which reflects the sustainable living pattern of a rural community. This study of Taka village clearly defines the geography, settlement pattern, community groups, settlement cluster, social structure, construction of dwelling and rituals. It further identifies the dwelling types and construction technology on the basis of three features: 1. representation of each community, 2. representation of each locality, and 3. representation of variation in house form. The settlement pattern and dwelling form in a way represent the characteristics of social structure and life style in the sharing of spaces of the dwelling environment. The dwelling form, building materials and construction technology blends with the terrain profile and climate creating a harmonious settlement pattern with nature and society. There is also community awareness on the conservation of Taka rural settlement heritage which is the positive sign on maintaining the identity of the community and place.

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The sheer diversity and lively activity of Nepal geographies makes them difficult to ignore. From the continuous uplift of mountains and itinerant migration of river channels, to the feats of engineering on display in terraced fields and remarkable histories of migration and trade across mountain passes and floodplains, Nepal is a place where the “environment”—produced through intertwined social and biophysical processes—rarely recedes as passive “context.” Home to uniquely diverse and rapidly transforming bio-physical systems, geopolitical encounters and indigenous relations of knowledge and practice, Nepal has long offered a wealth of opportunities to advance nuanced geographical understandings of the co-production of socio-natural relations and affords rich grounds for transformative politics and intersectional modes of resistance.

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ArchI DosE NepaL

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List of thesis topic for architecture.

• Advanced Trauma Centre and Hospital,
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• Waterfront Development – Beach Convention and Exhibition Centre,
• Integrated Transportional Node,
• Architecture for Hills: A Site Responsive Settlement.
• Forest Research and Training Institute,
• Urban Entertainment Centre,
• Memorial Cancer Hospital and Research Centre,
• Aqua Marine Park,
• Archeological Survey of – Research and Training Institute
• Low Cost Housing,
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• Fashion Technology Park,
• Tribal Heritage Museum,
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• Houses -A Study in Contrast,
• Digital Morphogenesis and Its Implementation in Fairlie Center,
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LIST OF THESIS TOPIC TAKEN IN INDIA - part 1

List of thesis topic taken in india - part 2, 56 comments:.

Hey I am a final architecture student and doing my thesis this year. Please if i can get any help regarding television media centre given in the list will be of great help Email id - [email protected]

I am a final yr student of architecture n my thesis topic is Aquarium-Aqua display and Research Centre. If i cn get ne hlp regarding ds pls mail me at- [email protected]

hey i am doing masters, n ow its time for thesis.. please suggest me some topics under landscaping and sustainability

Hey I am a final architecture student and doing my thesis this year. Please if i can get any help/material regarding media center given in the list will be of great help or can get contact of the person done this topic Email id - [email protected]

Hey mine is school of media nd art..if u get any data plz mail me at [email protected]

hello can anybody help me with the proposed site for india islamic centre? where can i get it from?

Hiii ..its thesis time for this Sem..can anyone plzzz help me in the concerned topic DRUG DE-ADDICTION CENTRE with any data and mainly the Proposed site in india ..because i am not getting the proposed site for it ..it will be very grateful if anyone can mail be it ..email : [email protected]

Hey iv taken... School of arts and media as my thesis topic..if u could help me with its proposed site..tgen it will be great help of provide me wd any relevant data ..kindly mail me at [email protected]

hi can anyone help me with Rejuvenation Center For Addicts. i want to do this topic for my thesis.contact me [email protected]

hi can any one of help me in thesis topic..fashion school.contact me [email protected]

child labor treatment via architecture is my thesis topic any help

Polo retreat is my topic for thesis project please in need of guidance Mail [email protected]

hii friends my thesis topic is district jail pls help me by guidance and relevance data. [email protected]

hii friends my thesis topic is surat diamond bourse help me by guidance and relevance data. mail-arti28patel2gmail.com

Hi guys! Please help me out to choose my thesis topic. I'm 5th year student in Architecture. I'm still struggling to choose between rehabilitation center for PWD and school for PWD?

hi guys..im on my last year also. i would gladly ask some information about this topic mentioned above: Architecture for Hills: A Site Responsive Settlement

hi guys..im on my last year also. i would gladly ask some information about this topic mentioned above: Architecture for Hills: A Site Responsive Settlement.. [email protected]

hey guys my topic is tourist resort in jaisalmer can anyone help me with the relevant literature or case study ...

Insightful blog shared. One can also get the detail colleges of architecture in maharashtra . Thanks for sharing.

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Eleven from MIT awarded 2024 Fulbright fellowships

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Eleven MIT undergraduates, graduate students, and alumni have won Fulbright grants to embark on projects overseas in the 2024-25 grant cycle. Two other students were offered awards but declined them to pursue other opportunities.

Funded by the U.S. Department of State, the Fulbright U.S. Student Program offers year-long opportunities for American citizen students and recent alumni to conduct independent research, pursue graduate studies, or teach English in over 140 countries.

MIT has been a Fulbright Top-Producing Institution for five years in a row. MIT students and alumni interested in applying to the Fulbright U.S. Student Program should contact Julia Mongo, MIT Fulbright program advisor, in the Office of Distinguished Fellowships in Career Advising and Professional Development.

April Cheng is a junior studying physics with a minor in mathematics and is fast-tracked to graduate this spring. They will take their Fulbright research grant to the Max Planck Institute for Gravitational Physics in Potsdam, Germany, where they will study different statistical techniques to infer the expansion rate of the universe from gravitational waves. They first developed an interest in gravitational waves and black holes at the MIT LIGO and Caltech LIGO labs, but their research spans a wide range of topics in astrophysics, including cosmology and fast radio bursts. Cheng is passionate about physics education and is heavily involved in developing educational materials for high school Science Olympiads. At MIT, they are a member of the Physics Values Committee, the physics mentorship program, and the MIT Lion Dance team. After Fulbright, Cheng will pursue a PhD in astrophysics at Princeton University, where they have received the President’s Fellowship.

Grace McMillan is a senior majoring in literature and mechanical engineering with a concentration in Russian language. As a Fulbright English Teaching Assistant Award recipient, she will teach at a university in Kazakhstan. McMillan’s interest in Central Asia was sparked by a Russian language immersion program she participated in during her sophomore summer in Bishkek, Kyrgyzstan, funded by MIT International Science and Technology Initiatives (MISTI). She is excited to help her students learn English to foster integration into the global academic community. During her time at MIT, McMillan has conducted research with faculty in nuclear science; earth, atmospheric, and planetary sciences; and the Digital Humanities Lab. Outside of academics, she has been an active member of her sorority, Sigma Kappa, and has served on the MIT Health Consumers’ Advisory Council for two years. After Fulbright, McMillan hopes to attend law school, focusing on education reform.

Ryan McTigue will graduate this spring with a BS in physics and mathematics and a concentration in Spanish. With a Fulbright award to Spain, he will do research at the University of Valencia’s Institute of Molecular Science focusing on the physics of two-dimensional multiferroic nanodevices. He is looking forward to improving his Spanish and getting the opportunity to live abroad. At MIT, McTigue became interested in condensed matter physics research with the Checkelsky group, where he focused on engineering materials with flat bands that exhibited correlated electron effects. Outside of research, McTigue has been a mentor in the physics department’s mentoring program and a member of the heavyweight men’s crew team. After his Fulbright grant, McTigue will begin a PhD in physics at Princeton University.

Keith Murray ’22 graduated from MIT with a BS in computation and cognition and linguistics and philosophy. He will receive his MEng degree in computation and cognition this spring. As a Fulbright Hungary research grantee at the HUN-REN Wigner Research Centre for Physics, Murray will design generative AI models inspired by the primary visual cortex with the goal of making AI models more interpretable. At MIT, Murray’s research experiences spanned from training mice to perform navigation tasks in virtual reality to theorizing about how neurons might compute modular arithmetic. He was also a member of the men’s heavyweight crew team and the Phi Delta Theta fraternity. After Fulbright, Murray will pursue a PhD in neuroscience at Princeton University.

Maaya Prasad ’22 completed her undergraduate education at MIT with degrees in both electrical engineering and creative writing and will graduate this month with an MS in mechanical and ocean engineering. Her thesis research focuses on microplastic detection using optical sensing. Prasad’s Fulbright fellowship will take her to Mauritius, an East African island country located in the Indian Ocean. Here, she will continue her master’s research at the University of Mauritius and will work with local researchers to implement a microplastic survey system. While at MIT, Prasad joined the varsity sailing team with no prior experience. Her time spent on the water led her to pursue marine research at MIT Sea Grant, and she eventually earned an honorable mention to the 2023 All-American Sailing Team. After Fulbright, Prasad hopes to pursue a PhD in applied ocean engineering.

Anusha Puri is a senior majoring in biological engineering. Her Fulbright award will take her to Lausanne, Switzerland, where she will conduct cancer immunology research at the Swiss Institute for Experimental Cancer Research. At MIT, Puri’s work in the Weinberg Lab focused on understanding mechanisms that drive resistance of breast cancer to immunotherapy. On campus, she founded and serves as president of MIT’s premiere stand-up comedy group, Stand-Up CoMITy, leads MIT’s Bhangra dance team, and is the editor-in-chief of the MIT Undergraduate Research Journal . She looks forward to engaging with teaching outreach and practicing her French in Switzerland. After her Fulbright grant, she plans to pursue a PhD in biomedical science.

Olivia Rosenstein will graduate this spring with a BS in physics and a minor in French. Her Fulbright will take her to ENS Paris-Saclay in Palaiseau, France, where she’ll deepen her education in atomic, molecular, and optical (AMO) physics. At MIT, Rosenstein has worked in Professor Mark Vogelsberger’s group researching models of galaxy formation and the early universe, and in Professor Richard Fletcher’s group on an erbium-lithium experiment to investigate quantum many-body dynamics in a degenerate mixture. In France, she will expand on the skills she developed in Fletcher’s lab by contributing to a project using optical tweezer arrays to study dipolar interactions. After Fulbright, Rosenstein plans to return to the United States to pursue a PhD in experimental AMO at Caltech.

Jennifer Schug willreceive this spring an MEng degree in the Climate, Environment, and Sustainability track within the MIT Department of Civil and Environmental Engineering. During her Fulbright year in Italy, she will conduct research on carbon storage in the Venice lagoon at the University of Padua. Schug is excited to build upon her research with the Terrer Lab at MIT, where she is currently investigating the effectiveness of forestation as a carbon sequestration strategy. She also looks forward to improving her Italian language skills and learning about Italian history and culture. Before beginning Fulbright this fall, Schug will study ecological preservation in Sicily this summer through an MIT-Italy collaboration with the University of Catania. After Fulbright, she hopes to continue researching nature-based solutions as climate change mitigation strategies.

Vaibhavi Shah ’21 earned a BS in biological engineering and in science, technology, and society at MIT, where she was named a Goldwater Scholar. She is now a medical student at Stanford University. As a Fulbright-Fogarty Fellow in Public Health, Shah will use both her computational and humanities backgrounds to investigate sociocultural factors underlying traumatic surgical injuries in Nepal. While at MIT, she was on the executive board of GlobeMed and the Society of Women Engineers, and she hopes to use those experiences to amplify diverse voices in medicine while on her journey to becoming a neurosurgeon-scientist. After Fulbright, Shah will complete her final year of medical school.

Charvi Sharma is a senior studying computer science and molecular biology with a minor in theater arts. As a Fulbright English teaching assistant in Spain, she is excited to engage in cross-cultural exchange while furthering her skills as a teacher and as a leader. In addition to teaching, Sharma looks forward to immersing herself in the country’s vibrant traditions, improving her Spanish proficiency, and delving into the local arts and dance scene. At MIT, through Global Teaching Labs Spain and her roles as a dynaMIT mentor, an associate advisor, and a captain and president of her dance teams Mirchi and Nritya, Sharma has served as a teacher of both STEM and dance. Her passion for making a difference in her community is also evident through her work with Boston Medical Center’s Autism Program through the PKG Public Service Center and as an undergraduate cancer researcher in the Yaffe Lab. After Fulbright, Sharma plans to pursue an MD and, ultimately, a career as a clinician-scientist.

Isabella Witham is a senior majoring in biological engineering. As a recipient of the Fulbright U.S.-Korea Presidential STEM Initiative Award, she will conduct research at Seoul National University’s Biomimetic Materials and Stem Cell Engineering Lab. Her work will involve creating biomimetic scaffolds for pancreatic cell transplantation to treat type I diabetes. While in South Korea, Witham aims to improve her language skills and explore cultural sites and cities. At MIT, she worked in the Belcher Lab on nanoparticle formulations, was a tutor for MIT’s Women’s Technology Program, and volunteered as a Medlink. After her Fulbright fellowship, she plans to pursue a PhD in biological engineering.

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The road toward AI: Fundamentals

There's no question that artificial intelligence (AI) is the talk of the town these days, overshadowing almost everything else in the world of technology. In this series of articles, we'll explore the road toward AI (Figure 1 ) and how your organization can smoothly transition toward incorporating AI into its platforms and applications. 

Clean architecture isn't the only topic I cover, you know! So, welcome aboard as we steer our focus toward artificial intelligence and machine learning (for now, at least, as these principles will map on the domain of AI/ML as well). 

Don't worry if AI is still a bit of a mystery to you—we'll start right from scratch. Think of this series of posts as an inverted pyramid, with each post building upon the last (Figure 2). We'll kick things off by laying down the basics and gradually move toward more advanced topics. As we progress, the discussion will branch out into various aspects of AI, providing you with a comprehensive understanding of its applications and implications. So, fasten your seatbelts and get ready to explore the exciting world of AI with me!

Is it AI, ML, or DL?

AI is a broad field that includes many different techniques—machine learning is just one of them. 

Artificial intelligence

AI is about creating computer systems that can perform tasks that would normally require human intelligence. This could include things like understanding language, recognizing objects in images, or making decisions based on complex data.

For example, think about a virtual assistant like Siri or Alexa. These systems use AI to understand what you're saying, figure out what you want, and then provide you with the appropriate response. 

AI is often perceived as a cutting-edge innovation, but that's not entirely accurate. My thesis, completed back in 2011, delved into topics that now resonate with machine learning concepts (see Figure 3). I focused on enabling drones to fly autonomously and designing algorithms to efficiently locate packages within warehouses based on probabilities of their positions. However, at that time, these functionalities were implemented using traditional methods like if-else statements and heuristic algorithms such as the traveling salesman and ant colony optimization.

Taking a step further back, around 2002, we encounter the beginning of iRobot Roomba, marking a significant milestone in autonomous vacuuming technology. Yet the roots of AI stretch back even further. In 1955, John McCarthy organized a workshop at Dartmouth on "artificial intelligence," marking the first usage of the term and laying the groundwork for its popularization over the years. Reflecting on these historical points illustrates the evolution of AI from its early stages to the sophisticated technologies we see today.

Machine learning

Machine learning is like teaching a computer to learn from examples. Instead of giving the computer a set of rules to follow, you provide it with a bunch of data and let it figure out the patterns on its own. It's a bit like how you might learn to recognize different types of dogs by looking at pictures: you don't memorize a list of rules, but you start to recognize common features like floppy ears or wagging tails (i.e., pattern matching). Figure 4 shows an example of a person using their pattern-matching abilities to categorize objects.

For example, suppose you want to build a spam filter for your email. You could give the computer thousands of emails, some marked as spam and some as not spam. By analyzing the patterns in these emails, the computer can learn to recognize which ones are likely to be spam and which ones aren't (notice that manual labeling of the input/training data is a prerequisite for starting with machine learning).

Deep learning

Deep learning (DL) is a subset of machine learning that's inspired by the way the human brain works. It involves building neural networks, which are networks of interconnected nodes that are loosely modeled on the neurons in our brains (see Figure 5 for an artistic depiction of this). These networks are capable of learning increasingly complex representations of data by stacking layers of nodes on top of each other.

A classic example of deep learning in action is image recognition. By training a deep learning model on a large dataset of labeled images, the model can learn to recognize patterns like edges, shapes, and textures at different levels of abstraction. This allows it to accurately identify objects in new images, even ones it hasn't seen before. Figure 6 illustrates how in this process, a human being must first categorize the images in the dataset in order to then train the deep learning model on the appropriate information.

So, in summary, machine learning is about teaching computers to learn from data, AI is about creating systems that can perform tasks that would normally require human intelligence, and deep learning is a specific technique within machine learning that's inspired by the structure of the human brain.

Roadies and rock stars

In the context of discussing AI, we can draw a comparison to the dynamics of a concert. Imagine purchasing tickets to see your favorite band perform. More often than not, the focus lies in witnessing the rock stars take center stage, rather than appreciating the meticulous efforts of the roadies working behind the scenes. These unsung heroes are responsible for setting up the stage, orchestrating the lights and sound, and managing the PR and marketing efforts that make the concert possible. Figure 7 shows a few Red Hat "rock stars."

Similarly, within the landscape of AI/ML, a similar analogy can be drawn. The "rock stars" in this scenario are the models themselves, be it Gemini, GPT, LLaMa, Mistral, or others. These models capture our attention with their remarkable capabilities, such as generating text or recognizing images. However, their success is only made possible by the dedicated individuals working tirelessly behind the scenes.

These AI counterparts come in various roles: software developers, data scientists (sometimes regarded as rock stars themselves), platform engineers, product owners, and even the infrastructure. Much like the stage crew at a concert, they ensure the smooth operation of AI endeavors, from data collection and preprocessing to model training and deployment. Even the infrastructure quietly supports these AI models, though its significance may go unnoticed until a rare disruption, like a 502 error, brings it to our attention.

In essence, just as a rock concert thrives on collaboration between performers and the backstage crew, the success of AI and ML ventures relies on the collective efforts of both the models and the dedicated individuals who bring them to fruition.

Comparing AI/ML and gem mining

Before diving into the details of AI and ML processes, let's take a moment to draw parallels with the process of gem and gold mining. The gem mining process looks like this:

• Miners venture into the waters to collect nuggets, hoping to find valuable gems or crystals among the regular rocks.
• These nuggets are examined by gemologists or geologists who help identify the ones containing precious materials, filtering out the worthless rocks.
• Then, the valuable materials are extracted from the nuggets, leaving behind pure substances ready for further processing .
• Fourthly, craftsmen such as jewelers and goldsmiths transform these pure materials into sellable items like jewels or gold bars. 

Finally, the finished products are sold—but the process doesn't end there. Just as with any product, there's a quality assurance phase where any defects are addressed and fixed by the craftsmens.

Now, you might wonder, what does this have to do with AI? In the next section, we'll uncover the intriguing connections between these processes.

AI/ML process

Although the title of this section refers to AI/ML processes, the focus of this section will primarily be on the ML process. We'll delve into other AI processes in the next section. For now, let's keep things high level. Don't worry—we'll dive deeper into each step in future articles.

To kick off, let's draw parallels with the gem mining process described earlier. The full process is depicted in Figure 8.

Surprisingly, ML processes share striking similarities, as shown in Figure 9.

• Collecting nuggets from the water:  Just as miners gather raw nuggets from the water, collecting data from APIs and applications initiates the ML process. However, not all data is relevant, requiring data engineers to filter and manipulate it.
• Filtering out worthless rocks:  Similar to separating valuable nuggets from worthless rocks, data analysts and/or data engineers sift through data to identify which pieces contribute to valuable insights and predictions for businesses.
• Extraction of valuable materials:  Extracting valuable materials from nuggets aligns with isolating valuable data in statistical databases. The importance of this step will be elaborated on in subsequent posts.
• Crafting pure materials:  Just as craftsmen transform materials into pure forms, data scientists design and train neural networks or (pre-trained) ML models based on datasets. They then refine or train these models with training data.
• Selling jewels/gold bars:  Deploying the ML model for consumption by applications mirrors the selling of jewels or gold bars. Additionally, quality assurance involves testing for, detecting, and rectifying model drift, which we'll explore further in later posts.

By drawing parallels with gem mining, we can unravel the complexity of the ML process, laying the groundwork for a deeper understanding in the posts to come.

Road toward AI

As earlier noted, future articles will focus on how you can transition from zero to fully embedded AI/ML, highlighting every step along the way. A more general view on the road toward AI will look like this:

• Get your application platform mature.
• Implement structured data and day 1 intelligence.
• Introduce machine learning.

Step 1: Get your application platform mature

Data is the cornerstone of AI/ML initiatives, and the first step toward success lies in acquiring, refining, and managing your data effectively. This process begins with establishing a robust application platform , such as an event-driven architecture or microservices framework.

A solid application platform is crucial as it facilitates agile development and deployments. For instance, if a data engineer or analyst requires the integration of a new data field or API (e.g., a weather API), the platform should enable swift implementation within hours or days, not months.

Furthermore, the platform should support the replication of data in various formats and across different databases to cater to diverse analytical needs. We'll delve deeper into this aspect in subsequent posts.

By laying the groundwork with a solid application platform, organizations can ensure agility and responsiveness in managing and leveraging their data, setting the stage for successful AI/ML endeavors. See Figure 10 for an illustration of this process.

Step 2: Implement structured data and day 1 intelligence

Once your application platform is robust and agile, the next logical step is to implement a data platform. This platform serves as a structured data source for data engineers, data scientists, and business analysts. Beyond simply enabling structured data storage, it's crucial to consider implementing day-one intelligence capabilities. This intelligence acts as a shortcut toward developing ML models.

But what's the value in this approach? Well, traditionally, implementing machine learning requires vast amounts of data—terabytes or even petabytes—which may not be available from day one. However, leveraging tools like Spark and graph databases allows you to code basic intelligence into your platform using a limited dataset. This brings two significant benefits. Firstly, it provides intelligence from the very beginning, enhancing the platform's functionality and usefulness right from the start. Secondly, it helps validate the completeness of your dataset early on. Identifying missing data fields at an early stage allows you to address them promptly, preventing potential setbacks down the line.

This process introduces an AI flow into your platform. Even when incorporating ML in the future, this step remains relevant. While ML models operate as black boxes trained solely on patterns within the training data, the intelligence coded into the platform adds a layer of human logic to the predictions. This complementary approach (e.g., enabled with Kafka) ensures a more comprehensive and nuanced understanding of your data, ultimately enhancing the effectiveness of your AI and ML initiatives. Figure 11 depicts this step of the process.

Step 3: Introduce machine learning

Now that structured data is in place, your data analyst can begin exploring correlations, and/or data scientists can start implementing business requirements using ML models. At this stage, neural networks can be developed from scratch, or pre-trained models can serve as a baseline to speed up the design and training phases. However, it's essential to exercise caution when using pre-trained models, ensuring they align with data governance principles—more on this in future articles.

Once the model is designed and trained, it can be deployed, potentially alongside any shortcuts developed earlier, and seamlessly integrated into your applications or platform. However, the journey doesn't end here. Continuous testing and validation of the model's performance on new data are imperative. Detection of model drift, where the model's performance degrades over time due to changes in the data distribution, signals the need for retraining with the updated data.

Despite the allure of ML, adopting a MLOps approach requires consideration of CI/CD -like pipelines to streamline model development and deployment processes. We'll explore this further in forthcoming blog posts, diving deeper into the complexities of MLOps and its significance in maintaining model performance and reliability over time. Figure 12 illustrates a complete view of this entire process.

Now that we've outlined the basics of the AI/ML process, it's time to delve deeper and clear out the road toward AI. Stay tuned for updates as we progress further along this journey.

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