[海伦]2024年以AI为中心的企业增长的11个数据预测

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2023 年是采用生成式人工智能和基础模型的一年。

然而，随着组织竞相将人工智能引入其工作流程的前沿和中心，他们意识到让数据事务井然有序是多么重要。

虽然公司始终了解高质量数据在业务成功中的作用，但新一代人工智能的兴起增强了其价值，确保它成为每个人的焦点。

现在，随着我们进入 2024 年，这将带来更大的新一代人工智能故事，领先的行业专家和供应商分享了他们对未来几个月数据生态系统不同方面如何发展的预测。

1.关系型将摆脱SQL

“无论是利用现代边缘、物联网智能应用程序还是生成式人工智能来发展业务，企业在 2024 年都不乏大胆的计划。所有这些计划都依赖于对企业数据的安全访问。

数据库基础设施将不断发展以支持新一代应用程序。

对于操作应用程序来说，虽然 SQL 数据库的使用仍然很流行，但现代应用程序的动态特性将鼓励开发人员寻找替代方案。

符合现代开发人员 CICD 工作流程并支持严格序列化事务以及跨集合的关系连接的文档关系数据库将成为许多项目的卓越解决方案。

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在分析方面，很明显大型语言模型需要详细的上下文才能高精度运行。

基于矢量数据库的检索增强生成 (RAG) 将在 2024 年成为主流。此外，业务概念和复杂文档将被构建为知识图，以提供人工智能解决方案所需的上下文。

到 2024 年，关系知识图谱将作为一种新的数据库架构来支持这一点。”

– Bob Muglia，Fauna 执行主席、Snowflake 前首席执行官

2.矢量数据库将成为最抢手的技术

“In 2024, vector databases will become the most sought-after technology to acquire. In an era where data-driven insights fuel innovation, vector databases have swiftly gained prominence due to their prowess in handling high-dimensional data and facilitating complex similarity searches. Whether for recommendation systems, image recognition, natural language processing, financial forecasting, or other AI-driven ventures, understanding the top vector databases will be critical for software development across industries.”

“As new applications get built from the ground up with AI …, vector databases will play an increasingly important role in the tech stack, just as application databases have in the past. Teams will need scalable, easy-to-use and operationally simple vector data storage as they seek to create AI-enabled products with new LLM-powered capabilities.”

– Ratnesh Singh Parihar, principal architect at Talentica Software, and Avthar Sewrathan, GM for AI and vector at Timescale

3. Fishing for LLM gold in enterprise data lakes

“There’s no shortage of statistics on how much information the average enterprise stores — it can be anywhere in the high hundreds of petabytes for large corporations. Yet many companies report that they’re mining less than half that information (largely structured data) for actionable insights. In 2024, businesses will begin using generative AI to make use of that untamed data by putting it to work building and customizing LLMs. With AI-powered supercomputing, businesses will begin mining their unstructured data — including chats, videos and code — to expand their generative AI development into training multimodal models. This leap beyond the ability to mine tables and other structured data will let companies deliver more specific answers to questions and find new opportunities. That includes helping detect anomalies on health scans, uncovering emerging trends in retail and making business operations safer.”

– Charlie Boyle, vice president of DGX Systems, Nvidia

4. Companies without sophisticated enough automation to power AI will feel the burn

“As businesses implement AI to maintain their competitive edge, many will feel the effects of their disorganized data infrastructure more acutely. The effects of bad data (or not enough data) will be compounded when the stakes are raised from simply serving up bad information on a dashboard to potentially automating the wrong decisions and behaviors based on that data. It’s only a matter of time before someone without strong data infrastructure and governance puts generative AI in a mission-critical context and suffers from a loss in accuracy.”

– Sean Knapp, CEO of Ascend.io

5. Cloud FinOps teams will optimize their data pipelines

“Confronted with the reality of run-away spending in the cloud this year, in 2024, true cross-organization partnerships will be required to identify unnecessary spending, with both finance and engineering teams playing critical roles. In Ascend’s annual research, 48% of respondents cited plans to optimize their data pipelines to reduce cloud computing costs, with 89% of those respondents expecting the number of pipelines to grow in the next 12 months. It will be imperative next year to leverage platforms that pinpoint where extra spending is occurring in data pipelines and push back with rapid demonstrations of cost optimizations to avoid misguided mandates from above.”

– Sean Knapp, CEO of Ascend.io

6. Intent data will become a must-have for go-to-market teams

“In 2024, intent data will no longer be a ‘nice-to-have’ for go-to-market