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AI Factory Glossary

1,106 technical terms and definitions

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setup time, production

Time to prepare tool for different process.

setup wafers, production

First wafers after recipe change.

seven points on one side, spc

Run indicating shift.

seven points trending, spc

Systematic trend.

seven wastes, manufacturing operations

Seven wastes are overproduction waiting transportation over-processing inventory motion and defects.

severity, manufacturing operations

Severity rates seriousness of failure effect on system or customer.

sf, SF, san francisco, san fran, bay area, silicon valley, ai ecosystem, artificial intelligence, openai, anthropic

# San Francisco # The Global Capital of Artificial Intelligence ## 1. Center of Artificial Intelligence Revolution San Francisco has emerged as the **undisputed epicenter** of the artificial intelligence revolution. The city hosts: - **83+ AI companies** leasing nearly 1 million sq ft of office space - **78.2%** of all US venture capital funding flowing to Bay Area companies - Projected **50,000+ AI workers** by 2030 - AI office space expected to grow from **5M to 21M sq ft** by 2030 ## 2. AI Titans — Frontier AI Labs ### 2.1 OpenAI - **Headquarters:** 3180 18th Street, San Francisco (Mission District) - **Expanded Campus:** 550 Terry A. Francois Blvd, Mission Bay (315,000 sq ft) - **Additional Space:** 1455 & 1515 Third St (486,600 sq ft, subleased from Uber) - **Total Raised:** $65.1B - **Key Products:** GPT-4, ChatGPT, DALL-E, Sora **Leadership:** - Sam Altman (CEO) - Greg Brockman (President) - Founding team included: Ilya Sutskever, Andrej Karpathy, Wojciech Zaremba ### 2.2 Anthropic - **Headquarters:** 548 Market Street, PMB 90375, San Francisco, CA 94104, USA. - **Key Products:** Claude AI (Opus, Sonnet, Haiku) **Leadership:** - Dario Amodei (CEO & Co-founder) - Daniela Amodei (President & Co-founder) - Founded: 2021 by former OpenAI researchers **Anthropic's AI Alley Location:** ``` - ┌─────────────────────────────────────┐ │ Salesforce Tower │ │ ↓ │ │ [300 Howard St] ← Planned HQ │ │ ↓ │ │ [500 Howard St] ← Current HQ │ │ ↓ │ │ [505 Howard St] ← Expansion │ └─────────────────────────────────────┘ ``` ### 2.3 xAI (Elon Musk) - **SF Office:** The Pioneer Building, 3180 18th St, San Francisco, CA. - **Memphis Data Center:** 3231 Riverport Rd, Memphis, TN 38109 (Colossus 1). - **Palo Alto Headquarters:** 1450 Page Mill Road, Palo Alto, CA 94304, USA (main research/leadership). - **Key Products:** Grok AI ### 2.4 Thinking Machines Lab - **Headquarters:** San Francisco - **Founded:** February 2025 - **Structure:** Public Benefit Corporation - **Funding:** $2B seed round (July 2025) at $12B valuation - **Lead Investor:** Andreessen Horowitz (a16z) **Founding Team:** - Mira Murati (CEO) — Former OpenAI CTO - John Schulman — OpenAI Co-founder - Lilian Weng - Andrew Tulloch - Barrett Zoph **Key Products:** Tinker API (LLM fine-tuning platform) ### 2.5 Safe Superintelligence Inc. (SSI) - **Mission:** Build safe superintelligence — nothing else - **Founded:** June 2024 - **Funding:** $1B from Sequoia, a16z, DST Global, SV Angel **Founding Team:** - Ilya Sutskever (Co-founder) — OpenAI Co-founder & former Chief Scientist - Daniel Gross - Daniel Levy ### 2.6 World Labs - **Headquarters:** San Francisco - **Founded:** 2023 - **Funding:** $230M from a16z, NEA, Radical Ventures, NVentures - **Valuation:** $1B+ (Unicorn) **Founding Team:** - Fei-Fei Li (CEO) — "Godmother of AI", Stanford HAI Co-Director - Justin Johnson - Christoph Lassner - Ben Mildenhall **Key Products:** Marble (3D world generation platform) ## 3. AI Infrastructure & Data Companies ### 3.1 Scale AI - **Headquarters:** 303 2nd Street, Floor 5, South Tower, San Francisco - **New Office:** 650 Townsend St (170,000-180,000 sq ft) — former Airbnb space - **Founded:** 2016 - **Total Raised:** $15.9B - **Employees:** 1,400+ **Services:** - Data labeling & annotation - Model evaluation - RLHF (Reinforcement Learning from Human Feedback) - Defense & government AI projects **Key Clients:** Meta, Microsoft, Google, OpenAI, US Army, DoD ### 3.2 Surge AI - **Headquarters:** 2193 Fillmore Street, San Francisco - **Founded:** 2020 - **Total Raised:** $25M (Series B) **Services:** - Data labeling for LLMs - RLHF training data - Content moderation - Search evaluation ### 3.3 Databricks - **New Headquarters:** One Sansome Street, San Francisco (150,000 sq ft) - **Previous HQ:** 160 Spear Street - **South Bay Office:** 200 West Washington, Sunnyvale (305,000 sq ft) - **Founded:** 2013 (UC Berkeley AMPLab) - **Investment in SF:** $1B+ over 3 years **Valuation History:** | Date | Valuation | Funding Round | |------|-----------|---------------| | Dec 2024 | $62B | Series J ($10B) | | Aug 2025 | $100B+ | Series K | | Dec 2025 | $134B | Series L ($4B+) | **Revenue:** $4.8B run-rate (55%+ YoY growth) **Key Products:** - Data Intelligence Platform - Agent Bricks (AI agents) - Lakebase (serverless Postgres) - Unity Catalog ### 3.4 Fireworks AI - **Headquarters:** 2317 Broadway St, Redwood City, CA - **Founded:** 2022 - **Total Raised:** $307M - **Valuation:** $4B (Oct 2025) - **Employees:** 148 **Founding Team:** - Lin Qiao (CEO) — Former Head of PyTorch at Meta - Benny Chen — Former Meta Ads Infrastructure Lead **Services:** - LLM inference optimization - Model fine-tuning - Low-latency AI deployment ## 4. Tech Giants — Gig Economy & Consumer Tech ### 4.1 Uber - **Global Headquarters:** 1655 & 1725 Third Street, San Francisco (Mission Bay) - **Real Estate:** JV with Alexandria Real Estate & Golden State Warriors - **Financing:** $500M refinancing (Feb 2025) ### 4.2 Lyft - **Headquarters:** 185 Berry Street, San Francisco (Mission Bay, near Oracle Park) - **Current Space:** 170,000 sq ft (renewed Dec 2024) - **Previous Space:** 419,000 sq ft (reduced post-pandemic) - **Founded:** 2007 (as Zimride) - **Employees:** 4,400+ ### 4.3 Instacart - **Headquarters:** 300 Mission Street, Financial District - **Current Space:** 60,000 sq ft (2 floors) - **Lease Term:** 9 years (through 2034) - **Previous Space:** 107,000 sq ft (expanded 2019, did not fully occupy) ## 5. Y Combinator & Startup Ecosystem ### 5.1 Y Combinator - **New Headquarters:** Pier 70, Dogpatch, San Francisco (moved 2024) - **Previous HQ:** Mountain View (17 years) - **Investment per Startup:** $500,000 **Leadership:** - Garry Tan (CEO & President since Jan 2023) - Co-founder of Initialized Capital - Co-founder of Posterous (YC S08) - Early employee at Palantir - Stanford BS in Computer Systems Engineering ### 5.2 YC AI Startup Stats - **AI Startups in SF Bay Area:** 819+ - **Currently Hiring:** 307+ - **Winter 2025 Batch Growth:** 10% per week aggregate - **AI Code Generation:** 95% of code is AI-generated for ~25% of startups ### 5.3 Notable YC Alumni (SF-based) | Company | Category | Notable Stats | |---------|----------|---------------| | Scale AI | Data/Infrastructure | $15.9B raised | | Instacart | Delivery | Public company | | Coinbase | Crypto | Public company | | Stripe | Fintech | $95B valuation | | DoorDash | Delivery | Public company | ## 6. Visionary Leaders & Talent ### 6.1 Dario Amodei (Anthropic CEO) - **Born:** 1983, San Francisco - **Education:** - Lowell High School (San Francisco) - Caltech (undergraduate, physics) - Stanford University (BA, physics) - Princeton University (PhD, biophysics) - **Career:** - Baidu (2014-2015) - Google Brain (2015-2016) - OpenAI (2016-2021) — VP of Research - Anthropic (2021-present) — CEO ### 6.2 Sam Altman (OpenAI CEO) - **Education:** Stanford University (dropped out) - **Career:** - Loopt (founder, 2005) - Y Combinator (President, 2014-2019) - OpenAI (CEO, 2019-present) - **Recognition:** TIME CEO of the Year 2023 ### 6.3 Ilya Sutskever (SSI Co-founder) - **Education:** - University of Toronto (PhD under Geoffrey Hinton) - **Career:** - Google Brain - OpenAI (Co-founder & Chief Scientist, 2015-2024) - Safe Superintelligence Inc. (Co-founder, 2024-present) ### 6.4 Andrej Karpathy (AI Researcher) - **Education:** - Stanford University (PhD, Computer Vision) - **Career:** - OpenAI (Co-founder, early team) - Tesla (Sr. Director of AI, 5 years) - Independent researcher - **Notable Quote:** AGI is "at least a decade away" ### 6.5 Fei-Fei Li (World Labs CEO) - **Titles:** - "Godmother of AI" - Stanford HAI Co-Director - Former Google Cloud AI Lead - **Contributions:** - ImageNet (revolutionary dataset) - Computer vision research - **Current:** World Labs CEO ### 6.6 Mira Murati (Thinking Machines Lab CEO) - **Previous:** - OpenAI CTO (resigned Oct 2024) - **Current:** - Thinking Machines Lab CEO & Co-founder - **Funding:** $2B seed at $12B valuation ### 6.7 Garry Tan (Y Combinator CEO) - **Born:** 1981 (Winnipeg, Canada) - **Education:** - American High School (Fremont, CA) - Stanford University (BS, Computer Systems Engineering) - **Career:** - Palantir (10th employee) - Posterous (co-founder, sold to Twitter) - Y Combinator (Partner 2011-2015, CEO 2023-present) - Initialized Capital (co-founder) ## 7. San Francisco Landmarks & Districts ### 7.1 Iconic Landmarks #### Golden Gate Bridge - **Opened:** 1937 - **Span:** 1.7 miles (2.7 km) - **Height:** 746 ft (227 m) - **Color:** International Orange - **Recognition:** Wonder of the Modern World #### Bay Bridge - **Connects:** San Francisco ↔ Oakland - **Opened:** 1936 - **Total Length:** 4.5 miles #### Pier 39 - **Size:** 45 acres - **Features:** - 90+ shops - 12 full-service restaurants - California sea lions on K-Dock - 300-berth marina - Views of Golden Gate Bridge, Bay Bridge, Alcatraz #### Salesforce Tower - **Height:** 1,070 ft (tallest in SF) - **Completed:** 2018 - **Location:** Financial District ### 7.2 Key Neighborhoods | Neighborhood | Notable Companies/Features | |--------------|---------------------------| | **SoMa (South of Market)** | Anthropic, Salesforce Tower, tech startups | | **Mission District** | OpenAI, xAI (Pioneer Building) | | **Mission Bay** | OpenAI campus, Uber HQ, Chase Center | | **Financial District** | Databricks (One Sansome), Instacart | | **Dogpatch** | Y Combinator (Pier 70) | | **Embarcadero** | Ferry Building, waterfront | | **Nob Hill** | Historic cable cars | | **Union Square** | Shopping, hotels | | **Chinatown** | Oldest Chinatown in North America | | **North Beach** | Italian heritage, Coit Tower | | **Fisherman's Wharf** | Tourism, Pier 39, Aquarium of the Bay | ### 7.3 Major Venues | Venue | Purpose | Capacity | |-------|---------|----------| | **Moscone Center** | Conventions (Dreamforce, Data+AI Summit) | 700,000 sq ft | | **Oracle Park** | SF Giants baseball | 41,915 | | **Chase Center** | Warriors basketball, concerts | 18,064 | | **Golden Gate Park** | Urban park | 1,017 acres | ### 7.4 Transportation - **BART:** Bay Area Rapid Transit (connects to East Bay, SFO) - **Caltrain:** Commuter rail to Silicon Valley - **MUNI:** SF public transit (buses, light rail, cable cars) - **Ferries:** To Sausalito, Oakland, Vallejo - **Cruise (Waymo):** Autonomous vehicles ## 8. Education & Research Institutions ### 8.1 UC Berkeley **Berkeley Artificial Intelligence Research Lab (BAIR)** - Computer vision - Machine learning - Natural language processing - Planning & control - Robotics **Notable Contributions:** - Apache Spark (Databricks foundation) - AMPLab (precursor to Databricks) - Ray (distributed computing) ### 8.2 UC Berkeley Extension **AI/ML Course Offerings:** | Course | Format | Topics | |--------|--------|--------| | Artificial Intelligence Foundations | Live Online | Deep learning, CNN, RNN, Keras, PyTorch | | Introduction to Machine Learning Using Python | Hybrid | ML concepts, algorithms, applications | | Machine Learning and Deep Learning | Online | Apache Spark, TensorFlow, neural networks | | Machine Learning with TensorFlow | Online | Data mining, forecasting, signal processing | **Professional Certificate:** Machine Learning and Artificial Intelligence (6-month program with UC Berkeley Executive Education) ### 8.3 Stanford University - **Stanford AI Lab (SAIL)** - **Stanford Institute for Human-Centered AI (HAI)** — Co-directed by Fei-Fei Li - Major source of AI talent for SF companies ### 8.4 UCSF (University of California, San Francisco) - Medical AI research - Health data science - Biotech AI applications ### 8.5 Academy of Art University (AAU) - Located in San Francisco - Design and technology programs - Digital media and animation ## 9. AI Market Analysis & Metrics ### 9.1 San Francisco AI Office Market ``` Current (2025): ████████████ 5M sq ft Projected (2030): ████████████████████████████████████████████ 21M sq ft Growth: +320% ``` ### 9.2 Venture Capital Flow **Bay Area Share of US AI VC Funding:** 78.2% **Major VC Firms Investing in SF AI:** - Andreessen Horowitz (a16z) - Sequoia Capital - Lightspeed Venture Partners - Founders Fund - Index Ventures - ICONIQ Capital - Thrive Capital - Khosla Ventures ### 9.3 AI Workforce Projections | Year | AI Workers in SF | Growth | |------|-----------------|--------| | 2024 | ~20,000 | Baseline | | 2025 | ~30,000 | +50% | | 2030 | 50,000+ | +150% | ### 9.4 Key AI Technologies **Large Language Models (LLMs):** - GPT-4/GPT-5 (OpenAI) - Claude 4.5 (Anthropic) - Llama 3 (Meta) - Grok (xAI) **Training Techniques:** - **Pre-training:** Large-scale unsupervised learning - **Fine-tuning:** Task-specific adaptation - **RLHF:** Reinforcement Learning from Human Feedback - **Constitutional AI:** Anthropic's safety approach **Model Architectures:** - Transformers - Mixture of Experts (MoE) - Reasoning models (o1-style) ## 10. Mathematical Modeling in AI ### 10.1 Transformer Architecture The self-attention mechanism is defined as: $$ \text{Attention}(Q, K, V) = \text{softmax}\left(\frac{QK^T}{\sqrt{d_k}}\right)V $$ Where: - $Q$ = Query matrix - $K$ = Key matrix - $V$ = Value matrix - $d_k$ = Dimension of keys ### 10.2 Multi-Head Attention $$ \text{MultiHead}(Q, K, V) = \text{Concat}(\text{head}_1, \ldots, \text{head}_h)W^O $$ Where each head is computed as: $$ \text{head}_i = \text{Attention}(QW_i^Q, KW_i^K, VW_i^V) $$ ### 10.3 Loss Functions **Cross-Entropy Loss (Language Modeling):** $$ \mathcal{L} = -\sum_{t=1}^{T} \log P(x_t | x_{

sfm, sfm, time series models

State Frequency Memory networks capture multiple time scales through frequency decomposition for forecasting.

sge, sge, infrastructure

Distributed resource management.

shadow board, manufacturing operations

Shadow boards outline tool locations enabling quick identification of missing items.

shadow deployment,mlops

Run new model alongside production model without affecting users.

shadow mode,parallel,compare

Shadow mode runs new model alongside old without affecting users. Compare outputs before switching.

shallow trench isolation (sti) stress,device physics

Mechanical stress from STI affects mobility.

shap (shapley additive explanations),shap,shapley additive explanations,explainable ai

Explain predictions by attributing importance to each input feature.

shap for feature importance, shap, data analysis

Explain which features matter most.

shap values, shap, interpretability

SHAP values use Shapley values from game theory to fairly attribute predictions to features.

shap-e, multimodal ai

Shap-E generates textured meshes and implicit functions from text or images.

shap,shapley,explanation

SHAP values are Shapley-based feature attributions. Game-theoretic. Popular for ML explanation.

shape bias, computer vision

Encourage models to use shape.

shape completion,computer vision

Predict complete shapes from partial observations.

shape correspondence,computer vision

Match points across different shapes.

shape generation,computer vision

Generate novel 3D shapes.

shape parameter, business & standards

Shape parameter characterizes failure distribution indicating infant mortality random or wear-out.

shapley value marl, reinforcement learning advanced

Shapley values in multi-agent RL fairly distribute rewards among agents based on their marginal contributions to team performance.

share,teach,community

Share learnings with community. Blog, talk, open source. Teaching deepens understanding. Give back.

shared expert in moe, moe

Expert used by all inputs.

shared memory agents, ai agents

Shared memory provides common workspace for multiple agents to coordinate.

shared memory, hardware

Fast on-chip memory shared by thread block.

shared memory,cache,scratchpad

GPU shared memory is fast on-chip scratchpad. Manually managed. Use for data reuse within thread block.

shared representations, multi-task learning

Common features across tasks.

sharegpt, training techniques

ShareGPT provides dataset of user conversations with ChatGPT for instruction tuning.

sharp minima, theory

High-curvature optima may generalize worse.

sharpening in self-supervised, self-supervised learning

Sharpen probability distributions.

sharpening, semi-supervised learning

Make probability distributions peaky.

sharpness-aware minimization, sam, optimization

Optimize toward flat minima.

shear test, quality

Test bond pad adhesion.

sheet resistance mapping, metrology

Measure resistance uniformity across wafer.

sheet resistance, yield enhancement

Sheet resistance characterizes thin film conductivity measured in ohms per square.

shelf life, quality

Storage time before use.

shell command,cli,generate

Generate shell commands from description. Complex pipes and flags.

shewhart chart,spc

Classic control chart for process monitoring.

shielding, reinforcement learning advanced

Shielding in safe RL uses separate safety controller to override unsafe actions from learning agent.

shielding,design

Guard signals with ground to reduce crosstalk.

shift detection, spc

Identify sudden level changes.

shift operation, model optimization

Shift operations move feature map regions spatially enabling mixing without parameters.

shift-reduce parsing, structured prediction

Shift-reduce parsing constructs parse trees using stack operations and reduce actions based on grammar rules for constituency parsing.

shift-to-shift variation, manufacturing

Differences between work shifts.

shifted window attention, computer vision

Windows shifted between layers (Swin).

shifted window, computer vision

Attention within shifted local windows.

shiftnet, model optimization

ShiftNet replaces spatial convolutions with shift operations dramatically reducing parameters.