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A version of Gemini, known as “nano”, was designed specifically for running on mobile devices and would be integrated into Google’s latest Pixel phones.
Introducing Gemini: our largest and most capable AI model
We’ve optimized Gemini 1.0, our first version, for three different sizes:
- Gemini Ultra — our largest and most capable model for highly complex tasks.
- Gemini Pro — our best model for scaling across a wide range of tasks.
- Gemini Nano — our most efficient model for on-device tasks.
With a score of 90.0%, Gemini Ultra is the first model to outperform human experts on MMLU (massive multitask language understanding), which uses a combination of 57 subjects such as math, physics, history, law, medicine and ethics for testing both world knowledge and problem-solving abilities.
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A general formula, on the other hand, might include the following components:
Dynamic Price = Base Price + Adjustment Factors
The dynamic price is calculated by adding the base price to various adjustment factors. These adjustment factors may be based on real-time data and may include:
- Demand Factor (DF) reflects the product or service's current demand.
- Time Factor (TF) considers the time of day, day of the week, or seasonality.
- Competitor Pricing Factor (CPF) takes into account the prices set by competitors.
- Customer Behavior Factor (CBF) considers a customer's purchase history, preferences, or other behavioral data.
Competitive Price = Competitor’s Price ± Adjustment Factor
The adjustment factor can consider various factors such as your product's quality in comparison to competitors, additional services or features, brand reputation, and other market differentiators.
How to Pick a Pricing Method
Pricing method selection is influenced by a variety of factors, including product characteristics, competitive landscape, target market, and overall business objectives. Here are some common scenarios and pricing method recommendations:
- Cost-Plus Pricing:
Scenario: Your company has a clear understanding of its production costs and wants to ensure that those costs are covered while maintaining a consistent profit margin.
Product Examples: Standardised or commoditized products with well-defined production costs.
- Competitive Pricing:
- Scenario: Your product is similar to others on the market, and you want to maintain or increase market share.
- Product Examples: Consumer goods, electronics, or other products with numerous competitors.
- Value-Based Pricing:
- Scenario: Your product has unique features, superior quality, or a strong brand reputation, allowing you to charge a premium based on perceived value.
- Product Examples: Luxury goods, high-end technology, premium services.
- Dynamic Pricing:
- Scenario: Your industry permits frequent price changes based on real-time market conditions, fluctuations in demand, or other dynamic factors.
- Product Examples: Airline tickets, hotel rooms, concert tickets.
- Customer Willingness to Pay:
- Scenario: Your product has a strong emotional or lifestyle appeal, and customers are willing to pay more for the perceived value.
- Product Examples: Products with a niche or specialized customer base.
- Psychological Pricing:
- Scenario: You want to use pricing strategies that have an impact on customer perceptions and behaviors.
- Product Examples: Retail items with prices set just below round numbers (for example, $9.99 instead of $10).
- Skimming or Penetration Pricing:
- Scenario: You are launching a new product and must decide whether to enter the market at a high or low initial price (skimming or penetration).
- Product Examples: Cutting-edge technology (skimming), new consumer goods (penetration).
- Freemium Pricing:
- Scenario: You provide a product or service with a free basic version and charge for premium features.
- Product Examples: Software applications, online services.
- Bundle Pricing:
- Scenario: You want to entice customers to buy multiple products by offering them at a discount when purchased in bulk.
- Product Examples: Fast-food meal deals, software suites.
- Geographic Pricing:
- Scenario: Your company operates in multiple regions, and you must account for varying costs and market conditions.
- Product Examples: Products with different shipping costs, considering regional economic factors.
Methods of Pricing Triangulation
Pricing triangulation is the practice of combining elements of common pricing models such as cost-based, value-based, and competition-based pricing to find the most effective pricing strategy for a product or service.
The following techniques aid in triangulating pricing models as effectively as possible:
- Market Dynamics Analysis: To effectively triangulate pricing methods, a thorough understanding of market dynamics is essential. Examine supply and demand, market trends, and economic conditions. For example, dynamic pricing may be more effective during high-demand periods, whereas value-based pricing may be a good strategy in a stable market.
- Competitor Pricing Analysis: Knowing what your competitors charge for comparable products provides useful benchmarks. If your product has unique features or superior quality, value-based pricing may allow you to justify a higher price. In contrast, if you're entering a price-sensitive market, a cost-plus strategy may be more appropriate.
- Customer Perceptions and Preferences Analysis: Understanding your target audience's perceptions and preferences is critical to pricing success. Conduct surveys, interviews, or focus groups to learn more about what influences their purchasing decisions. This data can help you implement psychological pricing or adjust your pricing strategy to better match customer expectations.
- Maintaining Cost-Effectiveness and Profit Margins: While customer-centric considerations are critical, it is also critical to ensure that your pricing covers production costs and provides a reasonable profit margin. Cost-plus pricing can serve as a foundation for adjustments based on market and customer analysis.
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A bronze sculpture of a Schiaparelli garment from 1936.
Schiaparelli and Chanel’s Feud Immortalized in New Exhibition
Sculptor Robyn Neild’s latest exhibition chronicles 40 of the designers' works in bronze.
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How generative AI is democratizing investing, reshaping business operations and altering market dynamics.
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Revealing emergent magnetic charge in an antiferromagnet with diamond quantum magnetometry
Tan, A.K.C., Jani, H., Högen, M. et al. Revealing emergent magnetic charge in an antiferromagnet with diamond quantum magnetometry. Nat. Mater. (2023). https://doi.org/10.1038/s41563-023-01737-4
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Merlin
卷积神经网络监测分析鸟类声音
here have been many other approaches to bird sound ID through the years, the result of engineering contests such as BirdClef and DCASE, among many others. Similar techniques have been used to monitor the activity of bats, as well as find patterns in whale songs.
Previous bird sound ID models have typically been trained using data with a coarser level of temporal resolution. For instance, a model might hear a 30 second recording of a White-breasted Nuthatch, but not be told when the nuthatch is singing in the recording. This can lead to problems: if other species are singing in the same recording, the model will erroneously call all species in the recording a White-breasted Nuthatch, leading to false predictions.
built a custom annotation tool that allows sound ID experts to listen to Macaulay Library recordings and annotate the precise moments when different bird species are vocalizing.
What’s next?
In building the model, we made a number of design decisions about how to handle our particular dataset, how to integrate predictions with information from eBird (a database of bird sightings shared by citizen scientists from around the world), and how to maximize the accuracy of Merlin Sound ID’s predictions in the field.
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Para
We recently launched Claude 2.1, our state-of-the-art model offering a 200K token context window - the equivalent of around 500 pages of information. Claude 2.1 excels at real-world retrieval tasks across longer contexts.
Claude 2.1 was trained using large amounts of feedback on long document tasks that our users find valuable, like summarizing an S-1 length document. This data included real tasks performed on real documents, with Claude being trained to make fewer mistakes and to avoid expressing unsupported claims.
Being trained on real-world, complex retrieval tasks is why Claude 2.1 shows a 30% reduction in incorrect answers compared with Claude 2.0, and a 3-4x lower rate of mistakenly stating that a document supports a claim when it does not.
Additionally, Claude's memory is improved over these very long contexts
Claude 2.1 的 200K 令牌上下文窗口功能强大，但也需要一些仔细的提示才能有效使用。
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世界回报 超线性 | 关注增长率 指数性增长 | 奖励曲线在远处上升得很陡峭 | 名气有其自身得超线性增长源泉
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Paul Graham
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Golden Building the world’sknowledge engine
We are automating the construction of the largest open knowledge graph of entities and topics.
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充电瓦特 融资
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be careful about the impact of DNA data breach
has AncestryService
biotechnology company
23andMe is updating its TOS to force binding arbitration with a limited opt-out window
In response to the cyberattack, rather than implementing robust security measures, 23andMe has opted for a legal shield, mandating binding arbitration for disputes.
23andMe, the personal genomics and biotechnology company, has been trying to contain a security breach that was first disclosed on October 6th. On October 19th, 23andMe disclosed another security breach by the same hacker who had initially claimed responsibility. The hacker said he had access to more than 4 million genetic profile records this time. And on December 4th, 23andMe confirmed that the total scope of the breach was 6.9 million users in total.
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Artificial-Intelligence-Terminology-Databas
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Dirck de Bray, Flowers in a Glass Vase, 1671 © Museum Associates / LACMA
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晶泰科技的主要业务有2个。一是药物发现解决方案，提供横跨药物发现及研究全过程中不同模块的解决方案；二是智能自动化解决方案，主要包括固态研发服务及自动化化学合成服务。
晶泰科技自身，从CRO企业的前瞻性指标合同负债来看，2020年-2022年公司合同负债分别为483.8万元、987.1万元、1551.9万元，2023年前6个月及前9个月合同负债分别为3583.5万元和3416.3万元，在本身基数较小的情况下首次出现下滑，公司未来的创收能力面临挑战。
从客户留存率来看，由于临床合作周期长且具连贯性，同时转换成本较高，客户通常不会轻易更换CRO合作机构，具备一定的粘性，留存率较高。而晶泰科技的客户留存率低于可比企业且持续走低。招股书显示，2020年、2021年及2022年以及截至2023年6月30日止六个月，晶泰科技客户留存率分别约为53.8%、67.5%、51.4%及51.4%。