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Uncommon Display of Vulnerability for Google: Search Giant Acknowledges Open Source AI Superiority in Confidential Memo

Google, widely acknowledged for its search engine dominance, now faces an unforeseen reality: its standing in the artificial intelligence (AI) race is no longer secure. In an internal memo that was leaked between executives, Google conceded that open source AI has surpassed both it and other closed-source systems, rendering competition futile.

As per the leaked memo, open source AI proves to be swifter, more adaptable, and generally superior in all aspects compared to Google’s, as well as OpenAI’s, proprietary AI.

These developments have prompted Google to reevaluate its strategies in order to maintain its foothold in the industry. There is now consideration of releasing projects on an open source basis, allowing them to retain control while still leveraging the benefits of open source technology.

So, what are the implications of this leaked Google memo for the future of AI, Google, and open source AI? Let’s delve into the insights offered by the memo.

It Was Not OpenAI, After All

The author of the memo, Luke Sernau, opened with this statement:

“The uncomfortable truth is, we aren’t positioned to win this arms race and neither is OpenAI.”

While Microsoft-backed OpenAI and Google engage in fierce competition within the AI domain, Sernau asserted that open source has outpaced them on multiple fronts, encompassing:

  • Mobile phone large language models (LLMs)
  • Multimodal capabilities
  • Responsible release
  • Scalable personal AI, akin to an open source AI chatbot

This trend initiated with the release of Meta’s LLaMA. In and of itself, LLaMA held no extraordinary attributes, merely constituting a very sizable language model. However, it was the inaugural openly released model of its kind.

This spurred others to pick up where Meta left off, catalyzing the open source revolution we witness today.

Sernau contended that this addresses a longstanding predicament of contemporary proprietary AIs: scalability. Meta’s LLaMA lowered the entry barrier to merely “one person, an evening, and a powerful laptop.”

And this is not the initial instance of major tech companies losing the open source versus closed source contest.

Sernau pointed out that the current state of large language models mirrors what transpired with the emergence of image generation. OpenAI introduced Dall-E as the premier AI image-generation tool in January 2021. Yet, its open source counterpart, Stable Diffusion, garnered myriad enhancements, including:

  • Marketplaces
  • User interfaces
  • Breakthroughs
  • Product integrations

The question remains whether the open source AI initiatives we currently witness will become Google’s pivotal “Stable Diffusion moment.” Nevertheless, as Sernau posited, “the fundamental structural elements align.” This implies that open source AI might represent Google’s most formidable AI challenge to date.

Faster, More Customizable, More Private

The memo also acknowledged the fundamental weakness of Google’s and major tech’s large language models: iterations are protracted and costly. In contrast, open source generative AI exhibits agility, high customizability, and cost-effectiveness.

Meta’s leaked LLM has already yielded improved iterations, encompassing:

  • Instruction tuning
  • Reinforced learning from human feedback (RLHF)
  • Quantization
  • Human evaluations

Remarkably, all these enhancements materialized within a single month of LLaMA’s leak. Sernau highlighted that this became viable through low-rank adaptation (LoRA) and scaling breakthroughs in image synthesis and large language models.

LoRA constitutes an open source technology that expedites and enhances the training of large language models to augment their precision. Concurrently, Chinchilla and latent diffusion are two methodologies employed to amplify neural networks for AI.

Regarding these technologies, the memo articulated:

“In both instances, access to a model of sufficiently high quality catalyzed a surge of ideas and refinement from individuals and institutions worldwide.”

Ultimately, colossal models impede the progress of major tech corporations. Ventures like an open source AI chatbot affirm that “the most effective models are those which undergo rapid iteration.” This is attributable to the fact that the open source community accomplishes far more with $100 and 13 billion parameters than Google can achieve with $10 million and 540 billion parameters. Notably, they achieve all this within weeks, not months.

Furthermore, Sernau emphasized that the disparity in quality between open source and closed source is so negligible that people are disinclined to pay for a restricted model that merely provides equivalent value to free alternatives.

A prime example of this phenomenon is the ascent of ChatGPT alternative projects, which adversely impact its paid version despite the latter being powered by GPT-4. While these open source chatbot alternatives do not operate on GPT-4, they receive an astounding number of iterations from the open source community, effectively narrowing the gap.

Open Source Vs Closed Source AI Models: What’s The Difference?

Though both rely on neural networks, the distinction between these two AI models lies in their approach to data interaction.

Closed source models are meticulously optimized and closely guarded intellectual property, impervious to external tweaking or enhancement. Their closed nature furnishes greater control and security for those who develop and use the technology.

Conversely, open source models proffer “greater transparency and accessibility, allowing for greater collaboration and innovation in the development process,” Taripe pointed out.

Unlike closed source AI, open source models benefit from a feedback loop with users, enabling them to learn from errors and refine the model iteratively.

Nonetheless, the leaked Google memo specifies three crucial areas where open source AI projects clearly outshine their existing counterparts.


In this context, scale bears different connotations for Google and the open source community. For Google, scale equates to substantial investments in LLMs and billions of parameters. Conversely, for the open source community, scaling pertains to “training on small, highly curated datasets” that are highly adaptable and swift in terms of improvement.

This implies that even if the open source community faces a size disadvantage, the “cumulative effects of all these fine tunings” more than compensate for it. As an illustration, there already exist ChatGPT alternatives and variants that are indistinguishable, functioning as open source chatbots. The scaling of open source AI projects far outperforms Google’s approaches in achieving desired outcomes.

Creation Process

As previously indicated, open source AI projects predominantly operate within LoRA, latent diffusion, or Chinchilla. These cost-effective methods empower engineers to iterate on prior work rather than starting from scratch, as Google does with their LLMs.

This expedites the development of robust projects like a ChatGPT alternative within a matter of weeks, without expending excessive resources and effort. Additionally, most open source AI projects facilitate collaboration with engineers globally.


Given that everyday individuals possess more insight into optimal AI applications within open source, the quality of their work surpasses what Google can achieve with their LLMs. This unlocks opportunities for novel and creative applications that were previously inaccessible.

“The fact that this technology exists is underexploited inside Google, even though it directly impacts some of our most ambitious projects,” Sernau emphasized in the memo.

Even if the fine-tunings in open source AI projects are considered “low rank,” their cumulative effect need not be, allowing comprehensive model updates to accrue over time. This implies that as superior datasets and tasks become available, the model can be cost-effectively kept up

 to date, without incurring the expense of a complete retraining, as Sernau outlined.

Conversely, Google’s generative AI models rely on recurrent retraining, pretraining, and discarding of iterative improvements, incurring costs in resources and time.

What’s The Future Of AI? Google Offers A Solution

According to Google’s perspective, the future of AI leans toward open source, but not exclusively OpenAI. Consequently, Sernau proposed that Google establish itself as a “thought leader and direction setter” in open source innovation, effectively “shaping narratives on ideas that are larger than itself.”

This approach allows them to essentially take ownership of the platform where most innovations transpire. This, however, entails a potentially uncomfortable shift towards relinquishing control over certain aspects of their proprietary AI, such as ULM variants and model weights.

Nonetheless, this strategy is not uncharted territory for Google, having previously navigated similar terrain with their Android OS and Chromium.

Google now finds itself in the distinctive position of leading yet another open source community, but this necessitates loosening their firm grasp on their models. In effect, Google anticipates that other open source alternatives will lose their allure, ultimately allowing Google to wield significant influence within the community.

This summarizes the comprehensive contents of the leaked Google memo.

What You Can Do: Three Tips From SEO Experts

Contrary to image generation, the ascent of generative AI holds profound implications for the future of SEO and marketing in general. While a wealth of information emerges from major tech entities like Anthropic and Google, how can one navigate this landscape effectively?

Stay Informed About Open Source Innovation

Begin by familiarizing yourself with the latest trends in open source AI, including GPT-4 and OpenAI’s recent advancements.

The leaked Google memo “underscores the rapid pace of innovation and the importance of staying abreast of new trends and technology, even if they may not have an immediate impact on SEO and digital marketing experts,” advised Taripe.

A reliable approach to staying informed is to follow reputable sources that provide updates on the latest news and breakthroughs. Some exemplary digital and search marketing resources encompass:

  • Search Engine Journal
  • Leadshouse
  • SEO Roundtable
  • Search Engine Land

These platforms offer invaluable insights into the current trends in SEO and open source AI. Keeping abreast of industry developments empowers you to make informed decisions regarding your franchise and business marketing strategies.

Anticipate Google’s Shift Towards Open Source

It is evident that Google is positioning itself to enter the open source community as a countermove against its chief big tech AI competitors, OpenAI and Microsoft.

With the support of Anthropic, Google aims to establish itself as a pioneer in responsible AI and is poised to become a significant contender in the open source AI arena.

Consequently, Taripe advises paying closer attention to open source programs and technologies, as they not only offer cost-effective and innovative alternatives that enhance work processes and outcomes, but also feature a robust community of developers and contributors that continually enhance and refine these programs.

Prepare for Google’s strong presence and industry-leading strategies as they introduce products into the open source AI domain. These strategies and tools may manifest as pay-per-click (PPC) solutions or a comprehensive platform for machine learning development.

Choose Your AI Solutions Wisely

The array of options for AI today may seem overwhelming, but that doesn’t mean you should make a choice arbitrarily.

If your needs involve frequent code modifications and access to a community of developers, open source AI is the way to go. Open source AI may be riskier because they depend on volunteer development.

This is why AI systems like Bard and ChatGPT, which provide better security, dependability and customer support, may be preferred by companies with sensitive data or those with less technical know-how.

While each business has distinct requirements, the use of proprietary AI is recommended due to the safeguards and security measures instituted by reputable companies such as Google and Microsoft.

Adhere to Current SEO and AI Best Practices and Guidelines

Much of the future of SEO and AI remains speculative. Thus, the most prudent course of action is to adhere to established SEO best practices and AI guidelines.

Google’s recent internal memo may have shed light on their intentions, but this does not imply that these will be their exclusive long-term strategies. Be attentive to shifts in Google’s algorithms and advancements in open source AI innovations.

Consequently, we recommend adhering to enduring practices like optimizing your website’s technical SEO to ensure that search engines comprehensively grasp your website’s purpose. For local businesses, optimizing for your geographical location is essential to enhance visibility to local clientele.

These optimizations remain efficacious irrespective of the proliferation of AI. After all, they constitute the bedrock of SEO and will continue to be pertinent no matter how sophisticated the technology becomes.

Expect an Influx of Open Source AI Products in the Market

Gruspe highlighted that “open source AI solutions are anticipated to expand both in development and application” as their advantages gain recognition among companies and professionals across various industries. “To stay abreast of open source AI development, major corporations like Google may adopt this trend and disseminate code as open source.”

As previously mentioned, keeping abreast of these advances equips you to stay ahead of the curve and allocate resources judiciously as new technologies emerge.

Forge Ahead in Digital Marketing With Leadshouse

The future of SEO and AI resides in the open source realm, and Google’s foray into this domain signals a shift in how we interact with technology. Much like an engine requires fuel to operate, AI necessitates data – but it also demands thoughtful consideration from digital marketers who are willing to stay abreast of industry trends and best practices.

With Leadshouse’s assistance, you can navigate the ever-evolving landscape of SEO and digital marketing with the knowledge to keep your strategies ahead of the curve.

Therefore, don’t lag behind: visit our website today and commence future-proofing your digital marketing strategies.


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