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The History of AI: From Ancient Ideas to Expert Systems and Foundation Models

Before you build on foundation models, it helps to know where they came from. Today’s generative AI looks like a sudden arrival, but it sits on top of roughly 70 years of research, two major collapses in funding and enthusiasm, and a much older dream: machines that reason. This post walks through that history, from the philosophical ancestors of AI to expert systems and the road to modern deep learning, and ends by connecting the old ideas to the services you will meet on AWS. 1. The ancestors: ideas before computers The wish to build artificial minds is ancient. Greek myths described Talos, a bronze guardian, and Jewish folklore told of the golem. These were stories, not science, but the real groundwork came from people who tried to turn thinking itself into something mechanical. Ramon Llull (13th century): designed paper wheels that combined concepts mechanically to generate statements, an early attempt to produce knowledge by procedure. Blaise Pascal and Gottfried Leibniz (17...
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Which AWS Certifications Exist for AI? A Practical Map

 If you want to prove you can work with AI on AWS, the certification catalog can feel crowded. This post gives you a map: which credentials are aimed at AI, who each one is for, what the exams look like, and in which order a sensible person would take them. Every figure below comes from the official AWS certification pages as they stood on 25 October 2026, so always double-check the live pages before you book anything. The short version Two certifications are built squarely around AI on AWS, and they sit at opposite ends of the difficulty scale: AWS Certified AI Practitioner (AIF-C01) is the foundational, concept-level exam. AWS Certified Generative AI Developer – Professional (AIP-C01) is the advanced, build-it-in-production exam. Around them sits a ring of neighbouring certifications that make good stepping stones, plus a newer business-focused AI credential and a set of hands-on "Demonstrated" credentials. At a glance Detail AI Practitioner GenAI Developer ...
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NLI (Natural Language Inferencing)

  "…when you have eliminated the impossible, whatever remains, however improbable, must be the truth"    Sir Arthur Conan Doyle Our brains process the meaning of a sentence like this rather quickly. We're able to surmise: Some things to be true: "You can find the right answer through the process of elimination.” Others that may have the truth: "Ideas that are improbable are not impossible!" And some claims are clearly contradictory: "Things that you have ruled out as impossible are where the truth lies." Natural language processing (NLP) has grown increasingly elaborate over the past few years. Machine learning models tackle question answering, text extraction, sentence generation, and many other complex tasks. But, can machines determine the relationships between sentences, or is that still left to humans? If NLP can be applied between sentences, this could have profound implications for fact-checking, identifying fake news, analyzing text, and m...
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Project: Heartbeat computing

In computer science, a heartbeat is a periodic signal generated by hardware or software to indicate normal operation or to synchronize other parts of a computer system. Usually, a heartbeat is sent between machines at a regular interval in the order of seconds; a heartbeat message. If the endpoint does not receive a heartbeat for a time—usually a few heartbeat intervals—the machine that should have sent the heartbeat is assumed to have failed. Heartbeat messages are typically sent non-stop on a periodic or recurring basis from the originator's start-up until the originator's shutdown. When the destination identifies a lack of heartbeat messages during an anticipated arrival period, the destination may determine that the originator has failed, shutdown, or is generally no longer available. Heartbeat messages may be used for high-availability and fault-tolerance purposes.
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Project: Face Detection in Images

Face detection is a computer technology being used in a variety of applications that identifies human faces in digital images. Face detection also refers to the psychological process by which humans locate and attend to faces in a visual scene. Face detection can be regarded as a specific case of object-class detection. In object-class detection, the task is to find the locations and sizes of all objects in an image that belongs to a given class. Examples include upper torsos, pedestrians, and cars. Face-detection algorithms focus on the detection of frontal human faces. It is analogous to image detection in which the image of a person is matched bit by bit. Image matches with the image stores in the database. Any facial feature changes in the database will invalidate the matching process. A reliable face-detection approach based on the genetic algorithm and the eigen-face technique: Firstly, the possible human eye regions are detected by testing all the valley regions in t...
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Project: GIS with Folium

A geographic information system (GIS) is a conceptualized framework that provides the ability to capture and analyze spatial and geographic data. GIS applications (or GIS apps) are computer-based tools, that allow the user to create interactive queries (user-created searches), analyze spatial information output, edit data presented within maps, and visually share the results of these operations. Geographic information science (or, GIScience)—the scientific study of geographic concepts, applications, and systems—is commonly initialized as GIS, as well. Geographic information systems are utilized in multiple technologies, processes, techniques, and methods. It is attached to various operations and numerous applications, that relate to engineering, planning, management, transport/logistics, insurance, telecommunications, and business. For this reason, GIS and location intelligence applications are at the foundation of location-enabled services, that rely on geographic ana...
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tf-idf

In information retrieval, tf–idf or TFIDF, short for term frequency–inverse document frequency, is a numerical statistic that is intended to reflect how important a word is to a document in a collection or corpus. It is often used as a weighting factor in searches of information retrieval, text mining, and user modeling. The tf–idf value increases proportionally to the number of times a word appears in the document and is offset by the number of documents in the corpus that contain the word, which helps to adjust for the fact that some words appear more frequently in general. tf–idf is one of the most popular term-weighting schemes today. A survey conducted in 2015 showed that 83% of text-based recommender systems in digital libraries use tf–idf. Variations of the tf–idf weighting scheme are often used by search engines as a central tool in scoring and ranking a document's relevance given a user query. tf–idf can be successfully used for stop-words filtering in various subjec...
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