Is Google the Hottest New AI Company?

The world of artificial intelligence moves at a relentless pace, often feeling like a high-stakes chess match played out in hyperspeed.

Just when one player seems to claim the crown, another makes a move that reshapes the entire board.

For a time, it seemed like OpenAI, with its viral ChatGPT, had taken the lead, leaving even industry titans scrambling.

Google, a company synonymous with innovation, found itself in a rare position of playing catch-up, reportedly issuing a code red in December 2022 following ChatGPT’s overnight success (The New York Times, 2022).

Yet, the latest buzz suggests a new twist in this fast-changing AI race.

The question on everyone’s mind is no longer who’s next but rather, is the hottest new AI company Google?

Google’s Gemini 3 model and Tensor chips are shaking up the AI race, drawing notice from rivals like Nvidia and OpenAI, despite Google’s prior AI setbacks.

This resurgence positions Google as a formidable contender in the evolving landscape of generative AI.

Why This Matters Now: The Stakes of AI Leadership

When a tech behemoth like Google makes waves in AI, the ripple effects are enormous.

It is not just about bragging rights among Silicon Valley giants; it is about shaping the future of digital interaction, influencing technological infrastructure, and impacting investment portfolios from billionaires to 401k-holding retirees.

The question of which company, and thus which vision, comes out on top in the AI race affects nearly every aspect of modern life.

The market has certainly taken notice.

Following mounting buzz about Google’s Gemini 3 model and its proprietary Tensor chips, shares of Google were up nearly 8% in a recent week.

In contrast, Nvidia, a dominant player in AI hardware, saw its shares dip a little over 2% during the same period (CNN, 2023).

This shift in market sentiment underscores the profound impact that perceived leadership in artificial intelligence development can have on investor confidence and the broader tech economy.

The sheer scale of Google’s user base for its AI offerings, with Gemini app reaching 650 million monthly active users compared to ChatGPT’s 800 million weekly active users (CNN, 2023; OpenAI, 2023), further highlights the massive reach and potential influence of its advancements.

From Underdog to Contender: Google’s AI Journey

For a company that has integrated AI into core services like Search and Translate since the early 2000s, Google is hardly an AI underdog (CNN, 2023).

Its status as a hyperscaler—one of the few tech giants renting cloud-based computing resources on a massive scale—further solidifies its long-standing foundation in artificial intelligence and infrastructure (CNN, 2023).

Yet, the rapid emergence of OpenAI’s ChatGPT in 2022 caught many off guard, including Google itself.

The Moment of Code Red

The narrative often focuses on Google’s perceived stumble when ChatGPT first burst onto the scene.

Internal reports from December 2022 suggested a code red situation within Google management (The New York Times, 2022).

This initial scramble reflected the intense competitive pressure in the generative AI space.

This historical context is vital; it frames Google’s current advancements not merely as incremental updates, but as a deliberate and powerful resurgence, demonstrating resilience and a renewed focus on AI innovation.

Gemini 3 and Tensor Chips: Google’s Two-Pronged AI Strategy

Google’s recent push is not a singular event; it is a strategic, two-pronged approach focusing on both cutting-edge AI models and the custom hardware that powers them.

This strategy is now clearly paying dividends, drawing significant attention and even praise from rivals.

Gemini 3 is performing strongly in AI benchmarks for specific tasks, positioning it as a top contender.

For instance, Gemini 3, which debuted on November 18, is now at the top of benchmark leaderboards for tasks like text generation, image editing, image processing, and turning text into images, outperforming rivals such as ChatGPT, xAI’s Grok, and Anthropic’s Claude in these categories (CNN, 2023; Google, 2023).

This suggests that Google is rapidly regaining ground in the AI race, potentially shifting market dynamics and bolstering investor confidence.

Over one million users tried Gemini 3 in its first 24 hours, utilizing both Google’s AI coding program and tools for connecting digital services to other apps (Google, 2023).

This strong initial uptake further underscores its competitive potential.

Despite Nvidia’s market dominance, interest from Meta and Anthropic in Google’s Tensor chips suggests a move toward diversifying chip suppliers.

Meta is reportedly in talks with Google to purchase its Tensor chips (The Information, 2023), and Anthropic announced in October 2023 plans to significantly expand its use of Google’s technology (CNN, 2023).

This indicates that major companies may be seeking to reduce reliance on single vendors like Nvidia, fostering greater competition and potentially more specialized solutions in the AI chip market.

The acknowledgment of Google’s AI advancements by rival CEOs signifies its growing influence in the AI ecosystem.

Sam Altman, CEO of OpenAI, offered congratulations to Google on Gemini 3, stating it looked like a great model (OpenAI, 2023).

Salesforce CEO Marc Benioff went even further, expressing on X that the leap was insane, noting that reasoning, speed, images, and video were all sharper and faster, making it feel like the world had changed again after trying Google’s new model (Salesforce, 2023).

This highlights the highly competitive and interconnected nature of the AI industry, where major players closely monitor and react to competitors’ breakthroughs, validating Google’s resurgence.

Navigating the Evolving AI Landscape: Lessons from Google’s Resurgence

Google’s journey from a perceived setback to a strong contender offers crucial lessons for any business leader or investor navigating the complex world of artificial intelligence.

• First, prioritize vertical integration.

  Google’s investment in its own custom Tensor chips, started long before the recent AI boom, now provides a competitive edge.

  This suggests that controlling the full stack—from hardware to software—can offer significant advantages in performance and cost optimization.

  Businesses should evaluate where vertical integration could yield strategic benefits in their AI initiatives.

• Second, focus on differentiated performance.

  While Google’s Gemini 3 leads in specific benchmarks like text generation and image editing, experts note that people use different AI models for different purposes (CNN, 2023).

  Companies should identify specific use cases where they can achieve demonstrable leadership rather than aiming for a generic best AI.

  A targeted approach can secure market segments.

• Third, build a resilient supply chain.

  The interest from Meta and Anthropic in Google’s Tensor chips points to a broader industry desire to reduce reliance on a single AI hardware provider, like Nvidia.

  Businesses developing or deploying AI should actively explore diversifying their hardware and software partners to mitigate risks and foster flexibility.

• Fourth, embrace continuous innovation.

  Even after a perceived stumble with ChatGPT, Google’s continuous push for improvement led to Gemini 3’s success.

  The AI landscape is defined by constant innovation; organizations must foster agile development cycles and a culture that encourages rapid iteration and learning from setbacks.

• Finally, understand the ecosystem, not just individual players.

  As Angelo Zino, senior vice president and technology lead at CFRA, noted to CNN, Google is just another piece to this expanding AI ecosystem (CNN, 2023).

  A holistic understanding of the AI ecosystem, including specialized models (like xAI’s Grok or Perplexity for search) and diverse hardware solutions, is key to making informed strategic decisions.

The Nuance of Dominance: Challenges in the AI Chip Market

While Google’s Tensor chips are gaining traction, the AI chip market remains fiercely competitive, with Nvidia still holding a formidable lead.

Nvidia reported a staggering 62% year-over-year sales growth in a recent October quarter, with profits up 65% compared to a year ago (CNN, 2023).

This dominance is largely due to Nvidia’s Graphics Processing Units (GPUs), which offer broad versatility for complex calculations, and its comprehensive technology packages including networking chips and a robust software platform for developers (CNN, 2023).

Ted Mortonson, a technology desk sector strategist at Baird, emphasized that the magnitude of Nvidia’s offerings is unmatched (CNN, 2023).

Google’s Tensor chips are Application-Specific Integrated Circuits (ASICs), custom-made for specific purposes.

While both GPUs and ASICs can train and run AI models, Jacob Feldgoise, a senior data research analyst at Georgetown’s Center for Security and Emerging Technology, explained that ASICs are usually designed for narrower workloads than GPUs (CNN, 2023).

This means Google’s chips are unlikely to replace Nvidia’s offerings across the board anytime soon.

However, increased adoption of custom ASICs, combined with competition from AMD, signals a broader industry trend towards reducing reliance on a single vendor.

Ben Barringer, global head of technology research at investment firm Quilter Cheviot, suggests this evolving landscape represents a part of a balance in the AI ecosystem, where Google will be a competitor, but is unlikely to achieve Nvidia’s all-encompassing dominance (CNN, 2023).

Measuring AI’s Impact: Beyond Bragging Rights

For businesses investing heavily in AI, simply having the hottest model or chip is not enough; demonstrating tangible impact and value is crucial.

Measuring success in the AI race requires a nuanced approach, looking beyond simple benchmarks to real-world application and competitive positioning.

Key Performance Indicators (KPIs) to consider include user adoption and engagement, tracking metrics like monthly active users for AI applications (e.g., Google’s Gemini app boasts 650 million monthly active users, CNN, 2023) and new user acquisition (Gemini 3 saw one million users in its first 24 hours, Google, 2023).

Market share and competitive standing involve monitoring benchmark leaderboards for specific AI tasks where models excel (Gemini 3 leads in several categories, CNN, 2023) and observing how competitors acknowledge or react to advancements (Nvidia, OpenAI, Salesforce X posts, 2023).

Hardware adoption and diversification track the interest and adoption of proprietary AI chips by other industry players, signaling potential shifts in the underlying hardware market.

Financial performance observes stock performance (Google shares up 8%, CNN, 2023) and sales growth (Nvidia’s 62% year-over-year sales growth, CNN, 2023) as broader indicators of market confidence and revenue generation from AI initiatives.

A continuous review cadence, perhaps quarterly, involving both technical and business strategists, can help organizations remain agile and responsive in this dynamic AI landscape.

Glossary

• AI Race: The intense competition among technology companies to develop the most advanced and widely adopted artificial intelligence technologies.
• ASIC (Application-Specific Integrated Circuit): A microchip designed for a specific application, such as Google’s Tensor chips for AI workloads.
• Generative AI: A type of artificial intelligence that can create new content, such as text, images, or code.
• GPU (Graphics Processing Unit): A specialized electronic circuit designed to rapidly manipulate and alter memory to accelerate the creation of images, also highly effective for AI model training.
• Hyperscaler: A large cloud provider (like Google) that offers extensive computing resources to other companies on a massive scale.
• MLOps: (Machine Learning Operations) A set of practices for machine learning operations that aims to streamline the lifecycle of machine learning models, from development to deployment and maintenance.
• Tensor Chips: Google’s proprietary ASICs designed to power its artificial intelligence models.

FAQ

• How is Google’s Gemini 3 performing in the AI race? Gemini 3 is currently at the top of benchmark leaderboards for tasks like text generation, image editing, image processing, and turning text into images, surpassing rivals in these categories (CNN, 2023).
• What are Google’s Tensor chips and how do they compare to Nvidia’s GPUs? Google’s Tensor chips are Application-Specific Integrated Circuits (ASICs), custom-made for specific AI purposes.

  Nvidia’s GPUs are Graphics Processing Units, more versatile and capable of vast complex calculations, typically used for broader AI workloads (CNN, 2023).

• Did Google’s recent AI news impact its stock price? Yes, shares of Google were up nearly 8% in the week following the buzz about its Gemini 3 model and proprietary chips (CNN, 2023).
• Are Google’s AI advancements causing concern among competitors? Yes, OpenAI CEO Sam Altman and Salesforce CEO Marc Benioff praised Gemini 3 on X, while Nvidia acknowledged Google’s advances but emphasized its own GPU advantages, indicating close competitive monitoring (Nvidia, OpenAI, Salesforce X posts, 2023; CNN, 2023).

Conclusion

The AI race is not a sprint; it is an ultra-marathon punctuated by moments of explosive innovation.

Google’s journey, from a perceived code red to a strong contender with Gemini 3 and its Tensor chips, embodies this dynamic.

It reminds us that leadership is fluid, constantly challenged, and often reclaimed through relentless dedication to both foundational research and practical application.

While the hottest new AI company might be a title that shifts with each significant breakthrough, Google has certainly thrown its hat back into the ring with considerable force, proving that legacy and strategic innovation can still disrupt even the most established narratives.

In this ever-evolving landscape, staying informed and agile is not just an advantage; it is a necessity.

What move will you make next?

References

• CNN. (2023). News report.
• Google. (2023). Company statement on Gemini 3 users.
• Nvidia. (2023, November 25). X post.
• The Information. (2023). News report.
• The New York Times. (2022, December 1). The New York Times.
• OpenAI. (2023). Company statement on ChatGPT users.
• OpenAI. (2023, November 21). X post.
• Salesforce. (2023, November 21). X post.