The world of search is about to be turned upside down once again. Google, the undisputed leader in search for over two decades, is hard at work on a top secret initiative codenamed "Project Magi" that aims to radically transform how we search the web and interact with information online. Powered by the latest breakthroughs in artificial intelligence, Project Magi represents Google‘s boldest vision yet for the future of search – and it could change everything.
What We Know About Project Magi So Far
First revealed in a recent New York Times article, Project Magi is a mammoth effort currently involving over 160 Google engineers and executives. While still in the early stages of development, the goal is nothing short of reinventing search from the ground up to make it more personal, predictive, and conversational.
According to the NYT report, some of the key features and capabilities Google is working to build into Magi include:
- Personalized results tailored to each user‘s interests, search history, and needs
- Proactive suggestions and information based on anticipating what a user wants
- Engaging in back-and-forth dialogue to answer questions
- Providing intelligent, synthesized answers (not just links)
- Integrating ads and supporting transactions directly in search
In an interview with the NYT, Prabhakar Raghavan, SVP of Google Search, framed the Magi effort as part of Google‘s ongoing evolution in search:
"We‘re taking a step back to completely rearchitect our search engine, laying the foundation for the future," said Prabhakar Raghavan, SVP at Google Search. "Magi is a transformation of the search experience leveraging advanced AI models to understand users‘ intents better than ever before."
Under the Hood: How Magi Uses Advanced AI
At the heart of Project Magi is Google‘s cutting-edge work in AI, particularly in the field of natural language understanding and generation. Over the past few years, Google has made huge strides with systems like BERT, MUM, and LaMDA that can comprehend and generate human language with unprecedented fluency.
Magi aims to take this to the next level by integrating multiple AI breakthroughs into a unified search system:
- BERT (Bidirectional Encoder Representations from Transformers): A neural network-based NLP model pre-trained on a large text corpus that provides state-of-the-art query understanding. BERT allows Magi to better grasp the intent and context behind searches.
- MUM (Multitask Unified Model): A multimodal AI model capable of analyzing info across text, images, video, and audio to provide more comprehensive answers to complex queries. MUM is a key part of Magi‘s ability to synthesize knowledge.
- LaMDA (Language Model for Dialogue Applications): A large language model designed for open-ended conversations. Trained on dialogue data, LaMDA powers Magi‘s engaging conversational UI and ability to handle follow-up queries.
- Knowledge Graph: Google‘s massive framework of entities and relationships spanning the collective knowledge of the web. Magi can tap the Knowledge Graph to provide direct, factual answers to queries by understanding how entities relate to the query.
By integrating these different AI capabilities, Magi aims to understand queries more like a human expert. It can grasp nuances of language, draw insights from multiple sources, engage in thoughtful dialogue, and synthesize relevant knowledge into coherent answers.
The end goal is a search engine that feels less like typing keywords into a box, and more like having an insightful conversation with a knowledgeable assistant. Here‘s an example of how that could play out in Magi:
User: What are some good family cars with high safety ratings and decent gas mileage?
Magi: Here are 3 top family cars with excellent safety ratings and fuel efficiency:
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Honda Accord – NHTSA 5-Star overall safety rating, up to 38 MPG highway. Spacious interior and reliability make it a great family pick.
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Toyota Camry – IIHS Top Safety Pick+, up to 39 MPG highway. Comfortable ride, low cost of ownership.
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Subaru Outback – IIHS Top Safety Pick+, up to 33 MPG highway. Standard AWD great for all weather. Roomy interior with ample cargo space.
These models have repeatedly scored at the top of safety tests by the NHTSA and IIHS. You can expect a starting price in the $25K – $30K range. Let me know if you want to see detailed crash test ratings or compare specs side-by-side!
Rather than just a list of links, Magi provides a concise, actionable answer that directly addresses the key criteria (safety, mileage) with relevant supporting info (scores, specs, pricing). And the conversational prompt makes it easy to go deeper and compare options.
Magi vs. The Competition
To understand where Project Magi fits into the larger search landscape, it‘s helpful to compare its key capabilities to other major players:
| Feature | Google Search | Google Bard | Bing AI | ChatGPT |
|---|---|---|---|---|
| Personalized results | Some | No | Some | No |
| Proactive suggestions | Limited | No | No | No |
| Conversational UI | No | Yes | Yes | Yes |
| Synthesized answers | Some | Yes | Yes | Yes |
| Ads and transactions | Separate | No | Some | No |
| Knowledge breadth | Broad | Broad | Broad | Broad |
| Data freshness | Realtime | Recent | Realtime | Limited |
| Access to private data | Yes | No | Yes | No |
As you can see, Project Magi aims to combine the best elements of traditional search (personalization, realtime info, privacy) with the latest advances in conversational AI (chat UI, intelligent synthesis) in a unified experience.
Compared to a standalone chatbot like Bard or ChatGPT, Magi can tap your personal search history and the full breadth of the web to provide more relevant, up-to-date info. And with built-in ads and transactions, the goal is a seamless experience from query to conversion.
In short, Magi represents an evolution of Google Search that integrates its full platform capabilities with the latest AI to deliver a radically improved search experience tailored to each user‘s needs. As Raghavan explains in the NYT piece:
"Instead of iterating on our existing UI, we saw an opportunity to create something completely new leveraging the latest techniques in deep learning," said Raghavan. "The goal is a search experience that understands your context, can engage in real dialog, and that gets you the information you need as efficiently as possible."
What Magi Means for the Future of SEO
For SEOs and search marketers, the eventual arrival of Project Magi will bring both challenges and opportunities. Some key implications to consider:
Higher bar for quality and relevance
With Magi focused on directly synthesizing answers to queries, ranking will require having the most relevant, high-quality information on a topic. SEOs will need to go beyond keywords and basic optimization to create truly standout, authoritative content.
Some key tactics:
- Develop in-depth, well-researched content that addresses user needs from multiple angles
- Use clean page structure, headings, and formatting to facilitate info retrieval
- Leverage images, videos, and other media to provide additional context and value
- Build topical authority through consistent publishing and link building on core topics
Importance of user intent
To rank in Magi‘s results, content will need to closely align with the meaning and intent of queries, both for informational and transactional searches. Cookie-cutter, general-purpose content will have a harder time competing against Magi‘s own tailored responses.
To align with intent in a Magi world:
- Group and map target keywords by intent (know, go, do)
- Develop intent-focused content that directly addresses the user‘s need
- Optimize for long-tail, conversational keywords that Magi can easily parse
- Provide clear next steps for users in each stage of the funnel
Opportunities in dialogue
With conversational search a core part of the Magi experience, there will be new opportunities to engage users in ongoing dialogue. Content that provides hooks and prompts for users to dive deeper and have follow-up questions answered will have an advantage.
Some ways to optimize for dialogue:
- Identify common follow-up questions for your core topics and develop content to answer them
- Use conversational, question-based headers and copy to encourage engagement
- Implement chatbots or virtual assistants to provide interactive content experiences
- Leverage Q&A and FAQ structured data to help Magi identify relevant dialogues
Focus on structured data
Clean, well-structured content will be critical for Magi to accurately extract and synthesize relevant information for searchers. Implementing structured data like Schema.org markup will help Google better understand and use your content for richer features.
Key structured data considerations:
- Implement relevant schemas like FAQPage, HowTo, Rating, Product, Event, etc.
- Provide complete and accurate data for all required and recommended properties
- Keep structured data in sync with on-page content and update regularly
- Validate and test markup with Google‘s Rich Results Tool
Interactive content and experiences
With Magi focused on helping users complete tasks directly in search, interactive content that supports those goals will have a leg up. Tools, calculators, quizzes, and other experiences that provide utility and encourage engagement will be especially valuable.
Some interactive content ideas:
- Develop embeddable tools related to your industry (e.g. mortgage calculator, calorie counter)
- Create quizzes and assessments to help users make decisions or find recommendations
- Design interactive infographics, maps, and data visualizations to convey complex info
- Build virtual product tours or 360 experiences that showcase your offerings
Final Thoughts on Magi and the Future of Search
While many details about Project Magi are still unknown, it‘s clear that Google is betting big on AI as the key to search‘s future. By rebuilding its core search product around large language models and other cutting-edge technologies, the goal is to deliver a vastly improved user experience that‘s personalized, predictive, and conversational.
For search marketers, this means now is the time to start preparing for an AI-first future. By focusing on quality, intent, structure, and interactivity, you can begin to future-proof your content and strategies for a Magi world.
Of course, many open questions remain:
- How will Magi handle potential issues like bias, accuracy, and transparency in its AI-generated responses?
- What will paid search advertising look like with transactions and ads built into the core UI?
- Will a more closed-off search experience limit website traffic even if it improves user satisfaction?
- How will Google address the SEO challenges of a single "perfect answer" for some queries?
Google will need to address these concerns head-on to build trust in Magi. And search marketers will need to stay agile to adapt to the new realities and opportunities Magi creates.
But one thing is certain – a new era of search is on the horizon. Google has the resources and motivation to bring Magi to market quickly. And when it arrives, it has the potential to reshape user expectations and redefine search as we know it.
As Raghavan and the Magi team build towards that future, the rest of the search world will be watching – and preparing. Those that embrace the shift to AI will be well-positioned to thrive. It‘s an exciting time to be in search – a whole new frontier awaits.
