What AI is best at now? Improving products you already own
AI isn’t magic, but can it be ‘Agentic’?
Sequoia Capital bets big on AI apps
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What AI is best at now? Improving products you already own
The hype surrounding artificial intelligence has long touted it as a game-changing technology poised to revolutionize the world. However, recent developments suggest that AI is instead becoming a powerful tool to enhance existing products and services, rather than a standalone application.
Announcements from tech giants Apple and Google have highlighted AI's potential as a feature to upgrade and streamline the gadgets and software we already use. While AI-powered bots may have initially captured the public's imagination, the integration of AI into everyday systems is proving to be a more practical and exciting application.
This "agentic" AI, which enables machines to not only provide instructions but also take action, is being hailed as a significant breakthrough. By seamlessly integrating AI into existing software and systems, users can enjoy enhanced efficiency and productivity.
According to an OpenAI spokesman, the key to unlocking AI's potential lies in meeting users where they are. "AI is a very powerful general-purpose capability," the spokesman explained. "Our partnership with Apple, for example, is critical in imbuing use cases with AI, rather than people thinking of AI as just a chatbot or an app." This shift in focus is poised to make AI a ubiquitous and indispensable part of our daily lives.….
Read the original in The Wall Street Journal
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AI isn’t magic, but can it be ‘Agentic’?
In the rapidly evolving world of artificial intelligence, a new term has emerged: "agentic AI." This concept refers to AI systems that can operate independently, without the need for human input or oversight. The idea is that these systems can take on complex tasks, such as predicting maintenance needs for factory machines or booking travel arrangements, and complete them automatically.
However, the reality is that most agentic AI is still in its infancy, existing more in the realm of possibility than practical application. The term itself was popularized by Andrew Ng, a prominent AI researcher, as a way to sidestep debates over what constitutes a true "agent" in the world of AI. Ng's definition of agentic AI is broad, encompassing technologies that exhibit agent-like qualities, even if they don't strictly meet the definition of an autonomous agent.
Despite the hype surrounding agentic AI, some experts are sounding a note of caution. Zoe Weinberg, a venture capital investor who focuses on privacy- and security-focused agentic tech, points out the irony of using a term that originated from human agency to describe technology that operates with little to no human oversight….
Read the original in The New York Times
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Sequoia Capital bets big on AI apps
Sequoia Capital, one of the most prominent venture capital firms, is making significant bets on AI applications rather than focusing solely on foundational models.
Sequoia Capital believes that the majority of billion-dollar companies in artificial intelligence will emerge from application development rather than model creation. The firm is investing significantly more capital in AI applications compared to foundational models, despite the current lower revenue generation in the application layer.
Sequoia has invested approximately $150 million in companies building foundation models, such as OpenAI, Safe Superintelligence Inc., and xAI. The firm has allocated "an order of magnitude more dollars" to the AI application layer, indicating a much larger investment in this area. Sequoia expects the application layer to produce the largest number of billion-dollar-plus companies in the AI sector.
Good AI application startups carefully design their products on top of existing models, adding significant value through packaging and user experience. Sequoia is focusing on applications that solve real problems rather than investing based on the "cool factor" of AI technology.
There's a shift from investing heavily in GenAI platforms and large language models (LLMs) towards vertical-specific applications of existing models. This trend is reflected in both venture capital and corporate venture capital flow. By focusing on AI applications, Sequoia Capital is positioning itself to capitalize on the practical implementation of AI technologies across various industries….