Yes, It Is • AI User + Usage + CapEx Growth = Unprecedented • AI Model Compute Costs High / Rising + Inference Costs Per Token Falling = Performance Converging + Developer Usage Rising • AI Usage + 15% 0% Details on Page 293 USA – LLM #1 China USA – LLM #2 AI Model Compute Costs High / Rising + Inference Costs Per Token Falling = Performance Converging + Developer Usage Rising 3 Cost of Relative to Launch Year % of Original Price By Year (Indexed to Year 0) Note: Per-token inference costs shown. Source: Richard Hirsh; John McCallum; OpenAI Details on Page 138 0 Years 72 Years Electric

chart of accounts. • Custom Time Periods - a master list to display or setup financial periods • Costs - a master list of any cost calculations to be used for assets or tasks • Payment Method Type - a quarters) • VAT / GST Periods • Sales Periods Costs A business is designed to be profi table. This means that you need to be able to track all the costs involved in your business to ensure that you are Some example costs that you may want to setup and track are as follows: • Raw Materials Costs • Labour Costs • Rental Costs • Electricity Costs • Quality Assurance or Regulatory Costs Direct and Indirect

includes an IT Box model for Information Systems (IS). The policy applies to programs with software costs over $15M and with COTS or Government off-the-Shelf (GOTS) hardware installation or technology refresh monitor the contract for cost control assurance  Less incentive for contractor to control costs thus risk of a cost growth that could exceed budget or stakeholder commitments Time-and-Material government  Requires close government monitoring  Contractor is not incentivized to control costs increasing the risk of a cost growth that could exceed budget or stakeholder commitments The

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 9.9.3. Costs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . be credited back to the Customer. 4. Taxes credited to taxing authorities must be reversed. 5. Costs for shipping, handling, perhaps re-shelving, must all be accounted for. 6. Possible replacement of chart of accounts. • Custom Time Periods - a master list to display or setup financial periods • Costs - a master list of any cost calculations to be used for assets or tasks • Payment Method Type - a

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 8.9.3. Costs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . be credited back to the Customer. 4. Taxes credited to taxing authorities must be reversed. 5. Costs for shipping, handling, perhaps re-shelving, must all be accounted for. 6. Possible replacement of chart of accounts. • Custom Time Periods - a master list to display or setup financial periods • Costs - a master list of any cost calculations to be used for assets or tasks • Payment Method Type - a

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 8.9.3. Costs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . be credited back to the Customer. 4. Taxes credited to taxing authorities must be reversed. 5. Costs for shipping, handling, perhaps re-shelving, must all be accounted for. 6. Possible replacement of chart of accounts. • Custom Time Periods - a master list to display or setup financial periods • Costs - a master list of any cost calculations to be used for assets or tasks • Payment Method Type - a

67B, DeepSeek-V2 achieves significantly stronger performance, and meanwhile saves 42.5% of training costs, reduces the KV cache by 93.3%, and boosts the maximum generation throughput to 5.76 times. We pretrain Family (a) 0 50 100 150 200 250 300 DeepSeek-V2 DeepSeek 67B saving 42.5% of training costs Training Costs (K GPU Hours/T Tokens) 0 100 200 300 400 DeepSeek-V2 DeepSeek 67B reducing KV cache by 1 | (a) MMLU accuracy vs. activated parameters, among different open-source models. (b) Training costs and inference efficiency of DeepSeek 67B (Dense) and DeepSeek-V2. Contents 1 Introduction 4 2 Architecture

DPUDirect feature significantly reduces service offloading costs in DPU scenarios, simplifies O&M, and significantly reduces subsequent maintenance costs. Challenges iNICs are gradually evolving into DPUs/IPUs ensure software compatibility and evolving services, as well as reducing component maintenance costs. Features The figure illustrates the architecture of DPU management plane seamless offload framework implemented HPCRunner, an HPC deployment tuning assistant that significantly reduces deployment costs and improves optimization efficiency. Project Introduction HPCRunner is composed of two parts: HPC

the task such that they follow the guidelines correctly while labeling, which further adds to the costs. In many cases, to reduce the chances of mislabeling due to human error, data is labeled by multiple multiple human labelers and the label that wins the consensus is assigned to the example. Given all the costs involved, it is imperative to utilize all the training data available to us, as efficiently as possible sample and label efficiencies. Both sample and label efficiency techniques help us reduce training costs. Assuming we do have a sample efficient and/or label efficient training setup, can we exchange some