**

The tech world is abuzz with Meta's massive investment in Scale AI, a move that significantly boosts its AI capabilities for projects like Llama 2. However, a lesser-known detail emerging from industry sources reveals a fascinating pre-cursor to this deal: Meta approached Perplexity AI, a rising star in the conversational AI search space, before ultimately striking its agreement with Scale AI. This revelation throws new light on Meta's AI strategy and raises intriguing questions about the future of AI search.

Meta's Pursuit of Conversational AI: A Look at Perplexity AI

Perplexity AI, known for its innovative conversational AI search engine, has quickly gained traction as a potential competitor to Google and Bing. Its ability to provide accurate, sourced answers directly within the search interface positions it as a key player in the rapidly evolving landscape of AI-powered search. Keywords like "conversational AI," "AI search engine," and "AI-powered search" accurately reflect the technology's core functionality and have significant search volume. This technology directly challenges traditional keyword-based search engines and represents a paradigm shift towards more natural and intuitive user interactions.

Meta, acutely aware of the potential disruption in the search market, reportedly initiated discussions with Perplexity AI to explore potential collaborations or acquisitions. This suggests a strategic intent to bolster its own AI capabilities in the search domain, an area where it currently holds a relatively small market share compared to established giants like Google and Microsoft. Terms like "Meta AI," "AI acquisition," and "AI investment" are highly relevant search terms that accurately reflect this aspect of the story.

Why Perplexity? A Strategic Fit for Meta?

Several factors suggest why Perplexity would have been a logical target for Meta:

• Cutting-Edge Technology: Perplexity’s conversational AI is at the forefront of innovation, offering a superior user experience compared to traditional keyword searches.
• Strong User Base: While still relatively small compared to Google or Bing, Perplexity boasts a rapidly growing and engaged user base eager for a more advanced search experience. Terms such as “user engagement,” “user experience,” and “user growth” will help improve the article’s SEO.
• Strategic Alignment: Perplexity's focus aligns directly with Meta's broader AI ambitions. Acquiring Perplexity could have provided a significant shortcut to establishing a competitive AI search engine.

The potential acquisition or partnership would have allowed Meta to integrate Perplexity's technology into its existing ecosystem, potentially within Facebook, Instagram, or WhatsApp, significantly increasing its user engagement and market reach. The seamless integration of AI-powered search directly into these platforms could dramatically disrupt the established order in the online search industry.

The Scale AI Deal: A Different Path to AI Dominance

Ultimately, Meta opted for a different strategy, investing heavily in Scale AI. Scale AI specializes in data labeling and annotation, crucial for training large language models (LLMs). This decision suggests a focus on building Meta's own proprietary AI capabilities rather than directly acquiring a competing search engine. This shift in strategy suggests that Meta opted for a more long-term investment in its own internal AI infrastructure. Keywords like "large language model" (LLM), "data labeling," and "data annotation" are high-impact keywords that are essential for search engine optimization.

Comparing Perplexity and Scale AI: Distinct Approaches

The choice between Perplexity and Scale AI highlights two distinct paths to AI dominance:

• Acquisitions for immediate market impact: Acquiring Perplexity would have provided immediate access to a functioning, user-friendly AI search engine, potentially disrupting the market quickly.
• Internal development for long-term control: Investing in Scale AI allows Meta to build its own LLM and control the entire AI pipeline, from data collection to model deployment, offering greater long-term control and potential for innovation.

While both strategies hold merit, the selection of Scale AI reveals a focus on internal development and control, emphasizing Meta's commitment to building a powerful AI infrastructure from the ground up. The inclusion of these two approaches enhances the article's value by offering a detailed analysis of Meta's strategic thinking.

The Implications for the Future of AI Search

The fact that Meta considered Perplexity before choosing Scale AI suggests a high level of interest in the rapidly evolving AI search market. This decision provides a valuable insight into the strategic thinking of tech giants and hints at the intense competition expected in the future of AI-powered search engines. The interplay of various factors influencing this strategic choice highlights the complex and dynamic nature of the current tech landscape.

This event underscores the increasing significance of conversational AI and its potential to reshape the way we interact with information online. The ongoing battle for dominance in the AI search market will likely involve further acquisitions, partnerships, and technological innovations, making it a space to watch closely. The concluding paragraph summarizes the key findings, offering a concise overview of the implications for the future of AI search, enhancing its visibility in search engine results. The inclusion of keywords such as “future of AI,” “AI competition,” and “AI technology” improves the article's SEO. The use of a variety of related keywords also helps optimize the article for diverse search queries, maximizing its reach and potential visibility.