← Back to AI Factory Chat

AI Factory Glossary

1,106 technical terms and definitions

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Showing page 4 of 23 (1,106 entries)

screening test, business & standards

Screening tests eliminate weak devices through stress reducing infant mortality in field.

screenplay writing,content creation

Generate movie scripts.

scribble conditioning, multimodal ai

Scribble conditioning interprets rough sketches as spatial guidance for generation.

scribble control, generative models

Condition on rough sketches.

scribe line test structures, metrology

Tests in kerf between dies.

scribe line, yield enhancement

Scribe lines are narrow spaces between die used for wafer dicing and test structures.

scribe line,manufacturing

Region between dies containing alignment marks test structures.

script learning,nlp

Learn typical event sequences.

script normalization, nlp

Standardize different scripts.

scrolls, scrolls, evaluation

Benchmark for long-context NLP.

scrubber system, environmental & sustainability

Scrubber systems remove hazardous gases from process tool exhaust through chemical reaction or adsorption before atmospheric release.

scu,santa clara university

# Santa Clara University ## Overview Santa Clara University (SCU) is a **private Jesuit Catholic university** located in Santa Clara, California, USA. ## Key Statistics | Metric | Value | |--------|-------| | Founded | 1851 | | Type | Private, Jesuit Catholic | | Endowment | approx USD 1.5 billion | | Total Enrollment | $\approx 9{,}000$ students | | Undergraduate | $\approx 5{,}500$ students | | Graduate | $\approx 3{,}500$ students | | Student-Faculty Ratio | $11:1$ | | Campus Size | $106 \text{ acres}$ | | NCAA Division | Division I (West Coast Conference) | ## Historical Timeline - **1777** — Mission Santa Clara de Asís founded (8th California mission) - **1851** — Santa Clara University established - Oldest operating higher education institution in California - Founded by the Society of Jesus (Jesuits) - **1912** — School of Engineering established - **1923** — School of Law established - **1961** — Women admitted as undergraduates - **1985** — Leavey School of Business named after Thomas and Dorothy Leavey ## Academic Schools & Colleges ### Undergraduate Schools - **College of Arts and Sciences** - Humanities - Natural Sciences - Social Sciences - Fine Arts - **Leavey School of Business** - Accounting - Finance - Management - Marketing - Business Analytics - **School of Engineering** - Bioengineering - Civil Engineering - Computer Science & Engineering - Electrical & Computer Engineering - Mechanical Engineering ### Graduate & Professional Schools - **School of Law** (JD, LLM programs) - **Jesuit School of Theology** (Graduate theology) - **School of Education and Counseling Psychology** - **Graduate Business Programs** (MBA, MS programs) ## Acceptance Rate Formula The acceptance rate can be expressed as: $$ \text{Acceptance Rate} = \frac{\text{Number of Admitted Students}}{\text{Total Applications}} \times 100\% $$ For SCU (approximate recent data): $$ \text{Acceptance Rate} \approx \frac{8{,}500}{17{,}000} \times 100\% \approx 50\% $$ ## Tuition & Cost Analysis ### Annual Cost Breakdown (Approximate) - **Tuition**: USD 59,000 - **Room & Board**: USD 18,000 - **Books & Supplies**: USD 1,200 - **Personal Expenses**: USD 2,500 ### Total Cost of Attendance $$ \text{Total Annual Cost} = 59{,}000\,\text{ USD} + 18{,}000\,\text{ USD} + 1{,}200\,\text{ USD} + 2{,}500\,\text{ USD} = 80{,}700\,\text{ USD} $$ ### Four-Year Cost (Without Aid) $$ \text{4-Year Cost} = 4 \times 80{,}700\,\text{ USD} = 322{,}800\,\text{ USD} $$ ### Net Price with Financial Aid If average financial aid package $= 35{,}000\,\text{ USD}$: $$ \text{Net Annual Cost} = 80{,}700\,\text{ USD} - 35{,}000\,\text{ USD} = 45{,}700\,\text{ USD} $$ ## Geographic Coordinates $$ \text{Latitude} = 37.3496° \, \text{N} $$ $$ \text{Longitude} = 121.9390° \, \text{W} $$ ### Distance from Major Tech Companies | Company | Distance (miles) | Distance (km) | |---------|------------------|---------------| | Apple HQ | $\approx 3.5$ | $\approx 5.6$ | | Google HQ | $\approx 8.0$ | $\approx 12.9$ | | Intel HQ | $\approx 2.0$ | $\approx 3.2$ | | Meta HQ | $\approx 15.0$ | $\approx 24.1$ | | Netflix HQ | $\approx 12.0$ | $\approx 19.3$ | ## Rankings & Metrics ### U.S. News Rankings (Regional Universities West) $$ \text{Rank} \in [1, 5] \quad \text{(consistently top 5)} $$ ### Graduate Employment Rate $$ P(\text{Employed within 6 months}) \approx 0.94 = 94\% $$ ### Return on Investment (ROI) $$ \text{ROI} = \frac{\text{Career Earnings} - \text{Total Education Cost}}{\text{Total Education Cost}} \times 100\% $$ ## Jesuit Educational Values The Ignatian pedagogical paradigm follows five key elements: 1. **Context** — Understanding the student's background 2. **Experience** — Engaging the whole person 3. **Reflection** — Critical analysis of meaning 4. **Action** — Informed decision-making 5. **Evaluation** — Assessing growth and progress ### Mission Statement Components - Pursuit of **faith** and **reason** - Commitment to **social justice** - Education of the **whole person** (*cura personalis*) - Service to **others** (*men and women for others*) ## Notable Alumni & Achievements ### Business Leaders - **Steve Nash** — NBA Hall of Famer (attended briefly) - **Leon Panetta** — Former CIA Director & Secretary of Defense - **Gavin Newsom** — Governor of California - **Brandi Chastain** — U.S. Women's Soccer Champion - **Janet Napolitano** — Former Secretary of Homeland Security ### Alumni Network Size $$ N_{\text{alumni}} \approx 100{,}000+ $$ ## Athletics ### Varsity Sports Programs **Men's Sports:** - Baseball - Basketball - Cross Country - Golf - Rowing - Soccer - Tennis - Track & Field - Water Polo **Women's Sports:** - Basketball - Beach Volleyball - Cross Country - Golf - Rowing - Soccer - Softball - Tennis - Track & Field - Volleyball - Water Polo ### Historical Soccer Success $$ \text{NCAA Men's Soccer Championships} = 1989 $$ ## Campus Facilities ### Key Buildings & Landmarks - **Mission Santa Clara de Asís** — Historic church (rebuilt 1928) - **Leavey Center** — Business school building - **Sobrato Campus for Discovery and Innovation** — STEM facilities - **Malley Fitness & Recreation Center** - **de Saisset Museum** — Art and history museum - **Harrington Learning Commons** — Main library ### Library Holdings $$ \text{Total Volumes} \approx 1{,}000{,}000+ $$ $$ \text{Electronic Resources} \approx 500{,}000+ $$ ## Research & Innovation ### Research Expenditures $$ R_{\text{annual}} \approx 25{,}000{,}000\,\text{ USD} $$ ### Key Research Areas - **Silicon Valley Ethics** — Tech ethics and AI responsibility - **Sustainability** — Environmental engineering - **Social Entrepreneurship** — Miller Center for Social Entrepreneurship - **Frugal Innovation** — Low-cost solutions for developing regions ### Miller Center Impact Formula $$ \text{Social Impact} = \sum_{i=1}^{n} (\text{Lives Improved}_i \times \text{Impact Factor}_i) $$ ## Sustainability Initiatives ### Carbon Footprint Goals $$ \text{Target: Carbon Neutral by } 2029 $$ ### Current Progress $$ \text{Emissions Reduction} = \frac{E_{2010} - E_{\text{current}}}{E_{2010}} \times 100\% $$ ### Sustainability Features - Solar panel installations: $\approx 1.5 \text{ MW capacity}$ - LEED-certified buildings: $\geq 10$ - Water recycling systems - Campus-wide composting program ## Admission Requirements ### Standardized Testing (Test-Optional) $$ \text{SAT Range (Middle 50\%)} = [1280, 1450] $$ $$ \text{ACT Range (Middle 50\%)} = [28, 33] $$ ### GPA Requirements $$ \text{Average Admitted GPA} \approx 3.7 $$ ### Application Components - Common Application or Coalition Application - High School Transcript - Letters of Recommendation (2) - Personal Essay - Application Fee: USD 70 - SAT/ACT Scores (Optional) ## Contact Information ``` Santa Clara University 500 El Camino Real Santa Clara, CA 95053 United States Phone: (408) 554-4000 Website: https://www.scu.edu ``` ## Quick Reference Formulas ### GPA Calculation $$ \text{GPA} = \frac{\sum_{i=1}^{n} (\text{Grade Points}_i \times \text{Credit Hours}_i)}{\sum_{i=1}^{n} \text{Credit Hours}_i} $$ ### Student-Faculty Ratio $$ \text{Ratio} = \frac{N_{\text{students}}}{N_{\text{faculty}}} = \frac{9{,}000}{818} \approx 11:1 $$ ### Graduation Rate $$ P(\text{Graduate in 4 years}) \approx 0.85 = 85\% $$ $$ P(\text{Graduate in 6 years}) \approx 0.91 = 91\% $$ ## Summary *"Santa Clara University combines the academic rigor of a top-tier institution with the values-centered education of the Jesuit tradition, all within the innovation ecosystem of Silicon Valley."*

sd upscale, sd, generative models

Stable Diffusion upscaling.

sdr, sdr, failure analysis advanced

Soft Defect Localization uses stimulation and imaging techniques to reveal intermittent or parametric failures.

se transformer, se(3), graph neural networks

SE(3) Transformer processes 3D point clouds and molecular structures with equivariance to rotation and translation through spherical harmonics.

se-transformers, scientific ml

Transformers with 3D symmetries.

se3-equivariant gnn, graph neural networks

SE(3)-equivariant GNNs process molecular geometries maintaining equivariance to rotations translations and reflections.

seaborn,statistical,visualization

Seaborn is statistical visualization. Built on matplotlib.

seam,cvd

Discontinuity where two growth fronts meet can cause defects.

seamless tiling, generative models

Generate seamlessly tileable images.

search space design, neural architecture search

Search space design determines the set of possible architectures balancing expressiveness with search efficiency.

search,retrieval,ranking

Search systems retrieve and rank relevant items. Embeddings for semantic search. BM25 for keyword.

searchqa, evaluation

QA using web search.

seasonal state space, time series models

Seasonal state space models represent seasonality through trigonometric or dummy variable state equations.

seasoning wafer requirements, production

Number of wafers to stabilize tool.

seasoning wafers, production

Stabilize tool after maintenance.

seasoning,process

Run dummy wafers after PM to stabilize chamber conditions.

secondary ion mass spectrometry depth profile, sims, metrology

Elemental depth profiling.

secrets detection,security

Find leaked credentials in code or outputs.

secs/gem protocol,automation

Communication standard between tools and fab host as mentioned earlier.

secure aggregation, privacy

Aggregate model updates without revealing individual contributions.

secure aggregation, recommendation systems

Secure aggregation enables federated learning by computing model updates without revealing individual user data.

secure aggregation, training techniques

Secure aggregation computes collective statistics without revealing individual contributions.

secure aggregation,encryption,mpc

Secure aggregation encrypts gradients in federated learning. Server learns only aggregate. MPC-based.

secure enclaves for inference, privacy

Hardware-protected inference.

secure multi-party computation, privacy

Cryptographic protocols for private computation.

secure multi-party computation,privacy

Compute on encrypted data from multiple parties.

secure multi-party, training techniques

Secure multi-party computation allows joint computation without revealing private inputs.

security,auth,oauth,keys

For auth and security basics I can explain API keys, tokens, OAuth flows, and good practices for secret management.

seebeck effect fa, failure analysis advanced

Seebeck effect imaging detects voltage gradients from thermal variations revealing resistive defects and current paths.

seed layer for electroplating,beol

Conductive layer for plating.

seed layer,pvd

Initial thin metal layer for subsequent electroplating.

seeds yield model, yield enhancement

Seeds yield model accounts for systematic and random defects with separate density and clustering parameters.

segment-level recurrence, llm architecture

Process segments recurrently.

segmentation control, generative models

Condition on semantic maps.

segmentation,mask,pixel

Segmentation classifies each pixel. Semantic, instance, panoptic. SAM for general segmentation.

segregate, production

Isolate questionable material.

seldon core,kubernetes,deploy

Seldon Core deploys ML on Kubernetes. Enterprise features.

selection-inference,reasoning

Separate selecting relevant info from making inference.

selective activation recomputation, optimization

Checkpoint strategically.