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Perplexity CEO: AI Success Depends On Energy Efficiency

Perplexity CEO Aravind Srinivas said AI companies that generate the most economic value from the least amount of computing power will be best positioned to succeed as competition intensifies across the sector. Speaking to CNBC’s Elaine Yu, Srinivas argued that maximizing “token value per watt per user” will become a key metric for evaluating AI businesses.

Balancing Accuracy, Latency, Cost And Privacy

Srinivas explained that every AI token, the basic unit of data processed by a model, consumes energy. Companies that can optimize the relationship between energy use and economic output, he said, will have a significant advantage. “Whoever is able to maximize this particular objective by balancing accuracy, latency, cost, privacy and intelligence really will win in the long term,” Srinivas said. His comments reflect a growing focus within the AI industry on efficiency as companies face rising infrastructure and computing costs.

Advancing Agentic AI With A Platform-Agnostic Approach

Perplexity continues to expand its work in agentic AI, systems designed to complete complex tasks rather than respond to individual prompts. In February, the company introduced Perplexity Computer, an AI agent capable of handling multi-step tasks over extended periods. While Perplexity develops its own models, its products also incorporate technology from companies including Anthropic.

The company recently launched Personal Computer, an orchestration layer that routes queries to the most appropriate processing resource. Srinivas described the shift as a move toward bringing more AI capabilities directly onto personal devices rather than relying exclusively on centralized data centres. According to Srinivas, this approach can reduce energy consumption while improving privacy and security.

Integration Across Leading Platforms And Growing Competition

Personal Computer is currently available on Apple’s Mac devices and is expected to expand to Microsoft’s Windows platform. The system is designed to work across applications, including Word and Outlook. The strategy also differentiates Perplexity from competitors such as OpenAI, Anthropic and Google, which are building increasingly integrated AI ecosystems around their own models and platforms.

Despite rapid growth among rivals, Srinivas said Perplexity’s focus remains on creating a system that works across different models, chips and operating systems. “We believe we’re building the most versatile operating system by making it work across different models, chips, and operating systems,” he said.

Future Outlook: Sustainable And Enduring Advantage

Perplexity’s approach allows the company to incorporate advances from multiple AI providers rather than relying on a single model ecosystem. The strategy has coincided with strong business growth. According to Srinivas, the company’s annualized revenue has tripled since the beginning of the year. As competition intensifies across the AI sector, efficiency, infrastructure costs and cross-platform integration are becoming increasingly important factors for companies seeking to scale their products and services.

A New Twitter-Inspired Social Network Is Taking Shape

A new social network called Twitter.now is entering the market, with a founding team that includes former Twitter trademark counsel Stephen Coates. The service is being developed by startup Operation Bluebird.

As Ars Technica reported, X sued the company last year and asked a Delaware judge to block the launch. Operation Bluebird argued in a petition that X had abandoned trademarks including “Twitter” and “Tweet.”

Coates has said the project is not an attempt to recreate the original Twitter. In a LinkedIn post, he described the platform as a new public space focused on trust, transparency and user choice.

AI System To Rate Posts

Twitter.now is currently being tested, with early access priced at $20. Its main feature is VERA, an AI system designed to evaluate posts, verify claims and provide sources and context.

Posts receive a trust score, with users eventually able to set a minimum score to filter their feeds. The company says this approach will give people more control over what they see instead of leaving those decisions entirely to an algorithm.

Moderation Remains A Challenge

Scaling moderation will be one of the platform’s biggest tests. Social networks have repeatedly struggled with content moderation as their communities grow, and newer platforms such as Bluesky have faced similar criticism.

Operation Bluebird says VERA will form the basis of its moderation and verification system. A second version is already planned, with expanded tools that would let users set a specific trust threshold for the posts appearing in their feeds.

For now, Twitter.now remains in an early testing phase, combining the familiarity of the Twitter name with an AI-driven approach to evaluating online information.

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