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  2. Business model canvas - Wikipedia

    en.wikipedia.org/wiki/Business_Model_Canvas

    The business model canvas is a strategic management template that is used for developing new business models and documenting existing ones. [2] [3] It offers a visual chart with elements describing a firm's or product's value proposition, [4] infrastructure, customers, and finances, [1] assisting businesses to align their activities by illustrating potential trade-offs.

  3. Cost breakdown analysis - Wikipedia

    en.wikipedia.org/wiki/Cost_breakdown_analysis

    The cost breakdown analysis is a popular cost reduction strategy and a viable opportunity for businesses. [1] [2] [3] The price of a product or service is defined as cost plus profit, whereas cost can be broken down further into direct cost and indirect cost. [1] As a business has virtually no influence on indirect cost, a cost reduction ...

  4. Adobe rolls out AI features, plans for price hikes and payouts

    www.aol.com/news/adobe-rolls-ai-features-plans...

    Adobe customers will get a certain number of "credits" toward using generative AI features. After those credits are used up, users can pay for more or keep using the features but at slower speeds.

  5. Automated planning and scheduling - Wikipedia

    en.wikipedia.org/wiki/Automated_planning_and...

    Given a description of the possible initial states of the world, a description of the desired goals, and a description of a set of possible actions, the planning problem is to synthesize a plan that is guaranteed (when applied to any of the initial states) to generate a state which contains the desired goals (such a state is called a goal state).

  6. The cost of training AI could soon become too much to bear - AOL

    www.aol.com/finance/cost-training-ai-could-soon...

    Here’s Epoch AI’s projection of the hardware cost involved in training the most expensive AI models, through 2030. This excludes AI researchers’ salaries, which are considerable these days.

  7. Algorithmic pricing - Wikipedia

    en.wikipedia.org/wiki/Algorithmic_pricing

    Dynamic pricing algorithms usually rely on one or more of the following data. Probabilistic and statistical information on potential buyers; see Bayesian-optimal pricing. Prices of competitors. E.g., a seller of an item may automatically detect the lowest price currently offered for that item, and suggest a price within $1 of that price. [1] [2 ...