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25
Part of the State of AI 2023 report.2023 Air Street Capital The State of AI Report 2023 · Air Street Capital
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26
The slide highlights the shift from 'more data/parameters' to 'better data' in LLM training, specifically referencing the 'phi' model series.2023 Air Street Capital The State of AI Report 2023 · Air Street Capital
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27
The slide uses a visual comparison (meme vs. truth) to explain the shift from dense models to Mixture of Experts (MoE) architectures.2023 Air Street Capital The State of AI Report 2023 · Air Street Capital
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The slide uses three separate line charts to illustrate data exhaustion timelines for different data types.2023 Air Street Capital The State of AI Report 2023 · Air Street Capital
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29
The chart shows Top-1 Accuracy vs Parameters (M) for models trained on 'Real' vs 'Real + Generated' data, indicating performance gains.2023 Air Street Capital The State of AI Report 2023 · Air Street Capital
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Includes logos of University of Maryland, Google, Google DeepMind, ETH Zurich, and Princeton.2023 Air Street Capital The State of AI Report 2023 · Air Street Capital
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31
Discusses the trade-off between training epochs, model size, and overfitting.2023 Air Street Capital The State of AI Report 2023 · Air Street Capital
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45
Features official Nobel Prize announcement graphics for John J. Hopfield, Geoffrey E. Hinton, David Baker, Demis Hassabis, and John M. Jumper.2024 Air Street Capital The State of AI Report 2024 · Air Street Capital
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46
Includes a technical architecture diagram and a bar chart comparing success rates of AF3 against baselines.2024 Air Street Capital The State of AI Report 2024 · Air Street Capital
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47
The slide uses a bar chart to compare performance metrics of different AI models (Chai-1, AF3, RosettaFold) across different datasets.2024 Air Street Capital The State of AI Report 2024 · Air Street Capital
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48
The slide highlights the importance of in silico filtering in protein design and compares AlphaProteo's performance against previous methods across various targets.2024 Air Street Capital The State of AI Report 2024 · Air Street Capital
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49
Discusses the transition from specialized equivariant models to domain-agnostic diffusion models in molecular modeling.2024 Air Street Capital The State of AI Report 2024 · Air Street Capital
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50
The slide explains the transition from Meta's research to the independent EvolutionaryScale company and the technical innovation of ESM3.2024 Air Street Capital The State of AI Report 2024 · Air Street Capital
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51
Includes a process diagram of the model training/inference and bar charts showing editing performance.2024 Air Street Capital The State of AI Report 2024 · Air Street Capital
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52
Includes logos of PoseCheck, PoseBusters, Polaris, and Inductive Bio at the bottom.2024 Air Street Capital The State of AI Report 2024 · Air Street Capital
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53
The slide uses a hub-and-spoke diagram to illustrate how the MACE-MP-0 model integrates various material types.2024 Air Street Capital The State of AI Report 2024 · Air Street Capital
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54
The slide presents a technical case study on protein structure generation using AI models.2024 Air Street Capital The State of AI Report 2024 · Air Street Capital
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55
The slide illustrates the pipeline from data collection (UK Biobank/HCP) to model training (BrainLM) and downstream clinical prediction tasks.2024 Air Street Capital The State of AI Report 2024 · Air Street Capital
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The slide details the architecture and performance benefits of the Aurora model compared to traditional numerical weather prediction.2024 Air Street Capital The State of AI Report 2024 · Air Street Capital
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57
The slide explains a technical process for brain-to-image reconstruction using a specific neural architecture.2024 Air Street Capital The State of AI Report 2024 · Air Street Capital
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58
The slide highlights a medical application of AI/neural decoding, featuring a photo of the patient's interface and a line chart showing error rate reduction.2024 Air Street Capital The State of AI Report 2024 · Air Street Capital
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13
The slide highlights the shift towards inference-time scaling (test-time compute) as a key driver for AI reasoning capabilities.2025 Air Street Capital The State of AI Report 2025 · Air Street Capital
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14
The slide uses a line chart to show scaling laws and a bar chart for comparative performance on AIME 2024.2025 Air Street Capital The State of AI Report 2025 · Air Street Capital
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Includes a bar chart comparing model performance and a line chart showing AIME accuracy improvement during training.2025 Air Street Capital The State of AI Report 2025 · Air Street Capital
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16
The slide highlights the architectural shift to DeepSeek Sparse Attention (DSA) in V3.2-Exp to reduce cost and latency.2025 Air Street Capital The State of AI Report 2025 · Air Street Capital
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17
Discusses technical advancements in LLM inference strategies.2025 Air Street Capital The State of AI Report 2025 · Air Street Capital
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2025 Air Street Capital The State of AI Report 20252025 Air Street Capital The State of AI Report 2025 · Air Street Capital
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19
Slide compares longitudinal performance trends (left) with a static ranking of current models (right).2025 Air Street Capital The State of AI Report 2025 · Air Street Capital
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20
The chart shows 'Reported vs Measured Results' and 'Variance DS-R1-1.5B' to demonstrate that performance swings are often due to variance rather than actual model improvement.2025 Air Street Capital The State of AI Report 2025 · Air Street Capital
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21
The slide presents a debate regarding the performance of reasoning models (LRMs) versus standard LLMs across different complexity levels.2025 Air Street Capital The State of AI Report 2025 · Air Street Capital
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