Unlocking Economic Potential: Generative AI as the Next Productivity Frontier

Preventing these 30,000 secrets from entering the code could save tens of millions of dollars, depending on the nature of the tokens. Future projections include AI-driven suggestions and auto-completions for secure coding practices, reshaping how security is embedded in the development lifecycle. We viewed with interest that IBM closed the acquisition of Manta Software Inc. for data lineage around the same time that it took the wraps off watsonx.governance for AI governance. Although IBM’s timing was coincidental, we hope that it will eventually take advantage of this serendipitous opportunity. The disconnect in data governance triggered the discussion over data mesh, which was about reconciling data ownership with responsibility for data products over their full lifecycle. There is scant appetite for new database startups in a landscape that still counts hundreds of engines, but shows the top 10 most popular ones remaining largely stable.

Over the last couple of years, we’ve seen a new wave of AI applications built on top of or incorporating large foundation models. This trend is commonly referred to as generative AI, because the models are used to generate content (image, text, audio, etc.), or simply as large foundation models, because the underlying technologies can be adapted to tasks beyond just content generation. The AI mediocrity spiral is not fatal, though, and you can indeed build sizable public companies from it.

Artificial Intelligence

In addition, generative AI can change the structure of the labor market, on the one hand, by expanding the capabilities of individual employees by automating processes, and on the other hand, by abolishing certain professions. AI-driven automation is powerful due to the ability of AI to understand natural language, which is required to complete 25% of all work tasks. More than 75% of all possible use cases are in four areas – customer operations, marketing software development and R&D. Among the tasks that generative AI can handle are interacting with customers, creating content, writing computer code based on natural language prompts.

Ultimately, AI technologies must be embraced as tools that can enhance, rather than undermine, human potential and ingenuity. Large language models (LLMs) like GPT-3, the underlying technology behind OpenAI’s immensely popular ChatGPT, are smarter by several orders of magnitude than their predecessors. These technological leaps democratize access to automated decision making in an unprecedented fashion, marking a new chapter in the rise of applied artificial intelligence (AI). These models are faster, cheaper, and more accurate than previous AI systems, with the potential to spur a massive innovation cycle, boosting productivity and powering a whole new set of applications and tools.

Products and services

Our Technology, Media and Telecom Conference highlights industry trends in generative AI, data observability, supercomputing and software. The same AI technology that creates convincingly fake images, audio and videos can also be used to identify content that isn’t real. The industry is in the early stages of using AI and machine learning to drive new revenue and boost efficiency.

Generative AI finds versatile applications in FinTech, ranging from enhancing chatbot conversations and ensuring customer satisfaction to generating synthetic data, detecting fraud, predicting trading outcomes, and modeling risk factors. FinTechs, from InsurTech to PayTech, can unlock significant business benefits by adopting generative AI. This technology has the power to revolutionize customer service, personalize recommendations, and scale marketing efforts. By the time the company is ready for growth-level investment, it has already built out an entire organization around hiring and operationalizing humans in the loop, and it’s too difficult to unwind. The result is a business that can show relatively high initial growth, but maintains a low margin and, over time, becomes difficult to scale. The pace of the AI policy response remains too slow given the speed at which the technology is developing.

Unlocking Economic Potential: Generative AI as the Next Productivity Frontier

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