Introduction to Artificial Intelligence

CT-AI · 45 questions

• A harbor office opens lock gates from a coded if-then timetable. A neighboring marina scores “likely delay” from years of tide and traffic logs and never wrote those rules. Which statement is correct?
• A compost-site scale house wants reject/accept to be identical every time the same truck weight and moisture reading arrive. Their vision sorter, given the same hopper photo twice, can emit slightly different grade labels. How should a tester classify those behaviors?
• A credit-union lending desk must tell a member why a small-business loan was declined. One option is a short decision tree on five application fields; the other is a many-layer network with millions of internal weights. Which option creates the black-box explainability problem for testers and auditors?
• A municipal snow-route office used to ship one fixed plow-priority table each November. The replacement system keeps changing those priorities as new storm telemetry arrives. What distinction should the tester recognize?
• A parks department hears three pitches: a coded irrigation timer, “any system that acts intelligently,” and a moisture predictor that improved only because it was fitted on historical soil logs. How should those three be nested?
• A ferry-queue estimator must cope with fog, late trains, and festival crowds that no one listed as coded exceptions. Stakeholders ask why the team did not just write more branches. Why is a probabilistic, pattern-based AI-based system chosen here?
• A kelp farm’s camera only estimates frond density and is marketed as “general intelligence for the whole marina.” How should a tester classify the deployed system?
• A fish hatchery’s count-from-video model is asked to start writing the weekly feed-purchase emails. Operations assumes last year’s vision work will “just handle words too.” What should the tester know?
• A foundation-model clerk’s assistant drafts ordinances and answers permit questions and is labeled “frontier” on the vendor slide. A councilor treats that label as proof of general AI. How should the tester place frontier AI?
• A city CIO claims the new assistant can perform most intellectual work any staffer can, across unfamiliar departments, without being prepared again for each desk. What claim is that, and does such a system exist today?
• A risk briefing describes an AI that keeps improving itself without human control, exceeds both human intellect and general AI, and — if the jump ever happens — is named as the technological singularity. Which term matches that description?
• A workshop argues that super AI is impossible unless the system is on the public internet. Another participant says a closed facility could still host it, though a network would widen its reach. Which statement is correct?
• A grain elevator wants a moisture-grade predictor that is not handed a written formula; it should form the mapping from labeled historical samples. Which technology is that?
• A vineyard night-shift board shows three pilots: nights labeled frost / no-frost for a fan controller, unlabeled cellar aroma readings grouped into clusters, and a lock-gate agent that earns a reward for fewer vessel waits. How should those three be classified?
• An orchard desk has still photos of leaf spots, a river desk has hourly gauge readings, and a permits desk has long statutes whose early clause changes a later one. Which deep-learning families match those data shapes?
• A community-radio archive wants volunteer show notes grouped by topic and named guests. A glacier desk wants crevasse photos flagged when the split widens. Which technologies match those two requests?
• A canal office uses a “somewhat high” water-level controller, a barge router that searches a lock network for a cheaper path, and a cheese-aging cellar that fires a coded knowledge base of if-thens. Which non-ML AI technologies are those?
• A warehouse robot chooses a pick path, replans when an aisle is blocked, and acts without waiting for a human step-list. A second system only labels a bin photo as “full” or “empty.” Which system is agentic AI?
• A QA kickoff slide lists linear regression, decision trees, support-vector machines, random forests, Bayesian models, and neural networks as candidate techniques for a hatchery grader. How should a tester treat those names?
• A tourism board wants paragraphs for a visitor guide and painted poster scenes from a short brief. A second vendor only sorts last year’s photos into “harbor / mountain / festival.” Which request is generative AI?
• A ceramics studio’s research bench has one network inventing extra kiln-defect pictures and a second network trying to spot which pictures are fabricated. Which generative approach is that?
• A print shop’s poster tool begins with a field of noise and step-by-step removes that noise until a festival illustration appears. Which generative approach is that?
• A municipal clerk’s drafting tool still respects a definition that appeared two pages earlier when it writes the closing clause. What mechanism should the tester tie to that long-range coherence?
• A harbor-authority communications desk worries about a fabricated video of a “channel closed” announcement spreading before any official notice. What GenAI societal risk should a tester be aware of?
• A county legal office sees first-draft ordinance language and routine medical-chart summaries being produced by a generative tool. Which syllabus societal concern should the tester recognize?
• A coastal-notice desk wants one system that reads tide charts and writes the public bulletin. Training that large multimodal stack burns a lot of electricity, and the vendor started from a broad pretrained base then specialized it. What should the tester connect?
• A trail-head kiosk transcribes hikers’ spoken reports on a low-power board, but the model was fitted for two weeks on a data-center cluster. How should a tester compare the hardware?
• A hatchery lab argues their office PCs “clock higher, so they must beat the graphics boards at fitting the grader.” What hardware comparison should the tester apply?
• A lighthouse edge box must cut the number of bits used for each arithmetic value so the chip stays cooler, cheaper, and less hungry for bandwidth. Which hardware trait is that?
• A river buoy carries a purpose-built AI chip (an ASIC or system-on-chip) that does in-memory, multi-core inference, while the model itself was fitted in a cloud hall. How should the tester place that hardware?
• A research pier is evaluating processors that abandon the usual stored-program layout and instead mimic neuron-like structures. Which hardware should a tester recognize?
• A small maritime museum can subscribe to a pretrained captioning service and go live next month, or fund a private model that obeys its accession rules but needs scarce specialists. What trade-off should the tester compare?
• A clinic wants to sketch a compact decision tree on a staff laptop so patient fields never leave the building, then later fit a larger network on a public cloud that already has GPUs and a usage bill. How should a tester compare those development options?
• A regional hospital keeps note-redaction and private-data prep on a private cloud, bursts the heavy fitting job onto a public cloud, and calls the mix hybrid. Which traits should the tester match?
• An allergy-alert model could run on clinic phones (privacy, no hosting fee, weak hardware), on a dedicated on-site server (up-front cost, more control), or on elastic public hosting. What is the tester comparing?
• A canal authority fitted a mid-size model on a rented cluster but now wants to host the running model on its own lock-house servers because of a new privacy rule. What should the tester conclude?
• A cooperative’s toolkit loads and cleans harvest logs, lets staff pick a tree versus a net, iteratively fits internal parameters, scores precision on unseen weeks, and exports a file a kiosk can run. Which five framework function groups are those?
• A junior analyst wants a high-level interface so a frost-fan prototype exists by Friday. A specialist wants a low-level interface so every layer and operation can be specified. What trade-off should the tester compare?
• A transit desk can adopt a general-purpose framework that covers several problem types, or a specialized framework aimed at spoken announcements. What should drive that selection?
• A lighthouse lab lists what it cares about: a gentle interface for a short prototype, room to configure a harder model later, the staff’s current skill, whether the result must run on a constrained buoy, and how active the user community is. How should a tester treat that list?
• A city council wants a human-centric, internationally cooperative baseline before it drafts a local AI ordinance. Which instruments should a tester recognize?
• A clinic’s triage assistant that can affect safety and fundamental rights is placed in a high-risk band of a risk-based statute. A festival chatbot that only writes slogans sits much lower. What should the tester explain?
• Counsel warns that a breach of the EU-style act can be charged as a share of worldwide turnover, while some governments outside that act prefer lighter rules to keep experiments moving. What should the tester contrast?
• A QA lead must show a regulator that the team used recognized guidance for testing AI-based systems. Which syllabus-named standards should the tester point to?
• A port authority asks why any of these rules exist, which quality-model number testers will meet next, and whether last year’s checklist is good forever. What should the tester answer?