The Google Cloud Platform (GCP) is one of the world’s top three public cloud services. Besides Amazon Web Services (AWS) and Microsoft Azure (MS Azure), GCP is the other leader in this technology market. In fact, Statista reports that GCP held 10% of the global cloud infrastructure market at the end of 2022.
Though AWS and Azure held 32% and 23% respectively, Google’s extensive product suite makes it an “unrivalled titan”. Further Tiago Bianchia writes for Statista that, “The California-based multinational internet company provides digital products and services such as online search and advertising, cloud computing, and software.” Hence our GCP product discussion needs to incorporate how all of these offerings are delivering value in the AI age and beyond.
For that reason, this A3logics guide explores how Artificial Intelligence (AI) technology use is revolutionized through the Google Cloud Platform. Accordingly, we’ll now explore these important points so existing GCP customers and interested businesses can plan investing in GCP services.
To begin, we’ll review the Google Cloud Platform product offering. Since 2008, their cloud computing suite has incorporated an extensive range of modular cloud services. Currently GCP has an annual revenue of USD$26 billion or equal to almost 10% of Google’s total revenue.
Because of its colossal market reach, GCP is considered to be user-friendly and generally very easy to use. Specifically GCP’s retention of familiar Google product architecture, like Gmail and YouTube, creates a seamless user experience (UX). Undeniably GCP can be characterized for how it offers users an effortlessness in their onboarding, daily use, and navigation.
To explain, many businesses may already be using Google Cloud products through Google Drive and Gmail. Primarily Ray Fernandez writes for TechRepublic, “Google Cloud is a broad term usually used to refer to all of Google’s cloud computing services.” Specifically, “This includes GCP and those that are associated with Google products that are ready to use and available worldwide, such as Google Workspace and Google Maps Platform.”
When we are talking about GCP, this is Google’s comprehensive suite of cloud computing services. These, Fernandez says are, “…mostly used in the industry to describe the suite of cloud computing services available for end users and companies who want to build their own digital cloud infrastructures.” Significantly leading Google products that are a household name like YouTube and Gmail actually run on GCP. Moreover, Google’s Bard chatbot that we’ll discuss more below also runs on GCP. For the purposes of this article, we are talking about the full GCP suite.
Now that we’ve reviewed the GCP product, we’ll discuss current AI innovations. After all, the last 12 months — starting in November 2022 — have been an extraordinary period for AI advancement. For the most part, especially when we consider developments throughout 2023, it seems likely that momentum will sustain into 2024.
Presently, Google reports that their GCP product is being developed with extensive AI infrastructure and functionalities. Primarily Fernandez writes, “The company rapidly integrates and incorporates the latest innovations of value, including AI, ML, generative AI, large language models and small LLMs.” So what we know is that AI is an integral part of the GCP suite and updates are ongoing. Also the GCP value proposition intends businesses to benefit from AI functionalities in their enterprise operations. Accordingly, the official GCP business page says, “You’re ready for AI, but is your cloud?”
Thereafter the GCP suite is massively advancing in the AI space with the following AI products available to enterprise customers:
Across this AI product suite, Google emphasizes a commitment to GenAI, Data Science, and Responsible AI. Since Google has been developing its AI technologies for a long time, it’s expected that this is only the beginning. Subsequently it’s likely updates to existing technologies along with new AI product launches for GCP, and Google, continue into 2024.
So now let’s look at the leading ways AI is transforming the GCP product and why this revolutionizes AI use.
As far back as 2001, Google was using ML in its search engine for spellcheck and to improve user searches. Since then Google launched TensorFlow in 2015, an open-source machine learning framework, that’s used for natural language processing (NLP). It’s also usable for image recognition like with their image-to-search product Google Lens.
Overall Google is on track with major contributions to the LLM market. Google Research product LaMDA conversational LLM was released in 2021. This made a huge contribution to the emerging GenAI market. Following this, they released their PaLM 2 model in 2023 is that’s multilingual and has reasoning and coding capabilities. Google’s GenAI chatbot Bard is built on LaMDA and PaLM 2. Additionally Gemini has already been announced as a new model being worked on.
Following the launch of Google’s Transformer for language understanding in 2017. Its use for translation and search engines has had a groundbreaking impact. Since then, in 2019, their next advancement in this space was the Bidirectional Encoder Representations from Transformers, or BERT for short. Not only does this enable better search query sentence understanding but also search engines can now understand words in context.
Firstly, Google’s GenAI chatbot Google Bard was built using their LaMDA model. The chatbot can be used as an API with the GCP suite for countless tasks: customer service, translation, and research. Accordingly this is a highly effective virtual assistant with conversational capabilities that works with text, voice, and image prompts.
Secondly, the Duet AI product is trained on the cloud for cloud use. Though the “AI-powered collaborator” is currently in preview, it’s promising to be a robust tool for cloud services. For instance, Duet AI can handle a range of cloud-centric tasks. Whether for AI-powered code assistance or safe and responsible AI, Duet AI leverages the Vertex AI platform and LLMs. Basically Duet AI is an AI product purpose-built for enterprises to be more productive in GCP.
Thirdly, Google has a range of foundation models including:
These models can be used to handle a range of prompts whether for generative image functionalities or checking coding.
At present Imagen can be used for image generation and editing models. Concurrently, Pathways Autoregressive Text-to-Image model (Parti) and Muse also offer high-quality and photorealistic image generation. Lastly Codey fulfils a range of software development tasks for over 20 coding languages and is built on PaLM 2. In summary, these models are all integrated across the GCP’s unified ML platform Vertex AI.
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Explicitly, “Google Cloud is ready to help organizations build a new way forward in an increasingly AI-driven world.” Hence GCP now has full integration with Google’s comprehensive AI product range. What’s more Google envisions that GCP is the go-to tool for digital transformation. This means that AI functionalities can help businesses in all areas and at all times: operations, creativity, service, security, innovation.
All workload management is improved through AI automation. Accordingly this also applies to industry adaptability as GCP is designed for use across all businesses and industries. Furthermore AI can work in over 135 languages.
Data can be run anywhere and everywhere — cloud, on-premises, and in the field — so businesses constantly gain real insights. At the same time, the AI models are parsing business data to provide reports, make assessments, and flag issues.
Whether for business activities or developing, AI maintains the highest security standard for GCP ever. Because security is built-in, the defensive protocols are dynamic and combine analytics, threat intelligence, and incident review. Then this builds an ongoing security lifecycle that’s maturing in real-time through ML and AI.
All systems are designed to work anywhere with consistent performance. Global infrastructure brings teams together so that everyone is collaborating at all times no matter their language or location.
The AI-enriched GCP is designed to manage resources with intelligence-based insights for cheaper yet more powerful systems. Consequently businesses can reduce their carbon footprint and maintain sustainable operations.
Evidently it’s possible that Google’s AI may be much more wide-reaching and robust than the AWS and Azure functionalities. Comparatively MS Azure runs using OpenAI’s AI models (including ChatGPT) and AWS has their own AI along with Stability AI. Being that each of these companies are largely committed to open-source AI research, the core differences may be applications.
One key fact about GCP is that it has the smallest market share of the leading three public cloud providers. On the one hand, GCP has fewer products in their cloud range than these two competitors. Additionally it’s considered that GCP is less aligned with enterprise customers. On the other hand, GCP is working to become more integrated with enterprise IT teams. Generally GCP is considered to be focused on making their cloud model available to software developers. Though each platform has its own strengths and weaknesses, each is suitable for business customers. In particular, Statista writer Lionel Sujay Vailshery asserts, “All in all, the Google Cloud offers many different industry-specific solutions via the cloud that work towards accelerating organizations’ digitization.”
Obviously AI is becoming a default part of not just GCP but all cloud solutions. Even so, GCP products are clearly at the cutting-edge of this technology because of end-to-end AI integration. Statista actually reports that, “Notably, GCP is strong in artificial intelligence (AI) and machine learning (ML) in the sector, leveraging these technologies for applications.” Whether for building and deploying products or using in-built AI functionalities like conversational chatbots, GCP makes AI technology accessible. Therefore in this final section, we’ll review the ways their growing multimodal AI range revolutionizes all business areas.
At this point, one extraordinary advantage of accurate and lifelike AI is how it advances customer service. For stakeholders, this means round-the-clock responses with chatbots and greater scope for recommendation and response. Additionally this also means more personalized customer insights through data systems, reviewing past activities, and eliminating silos across GCP products.
All in all, a global advantage of robust AI is how inclusive and wide-reaching it promises to be. In this case, accessibility extends to all areas of user needs — from communication to freedom of location. For example, Google Translate was launched as an ML product nearly 20 years ago. Now it translates over 135 languages and can automatically detect different languages which means growing accessibility irrespective of language. At the same time, serverless GCP mean businesses and individuals aren’t limited by location. Simultaneously AI features can support them where they are if they issues so they don’t need costly in-person engineers.
Though IT personnel still have an incredibly important role in the GCP — and business — day-to-day, AI streamlines operations. Moreover it also encourages greater automation so that IT can focus on higher-order tasks from security to developing products. Additionally the in-built developer and support AI tools for IT team members ensures they can consistently progress in tasks. Accordingly non-IT team members can also turn to AI support for low-level resolutions or recommendations which reduces workload.
One of the most exciting advancements of GenAI is how it aids product development. For instance, the Bard chatbot can help users review code and detect problems. Additionally the Codey LLM is purpose-built for developers to manage high-level coding. All in all this promises the most exciting era of AI and technology yet.
GCP has an extraordinary scope of storage and data centers that free businesses to focus on their operations. Not only does this reduce latency in systems — key for businesses of all kinds — but also it supports scaling. Businesses can keep progressing in their roadmap strategy for growth and innovation with the knowledge GCP is ready to go. Further to this, AI can flag if there are any system issues that affect efficiency so work pace is maintained.
Altogether every business is concerned about security and rightly so. At present, attacks are a matter of when — not if. With its newest AI functionalities, Google is revolutionizing security in all areas of the cloud. Following their acquisition of Mandiant integrated with Google AI, their security environment becomes entirely intelligent. This rapid lifecycle is constantly scanning threats and data to deliver a 360-degree picture of security across the cloud.
Using AI, applications are the most-connected they’ve ever been. Their Cross-Cloud Network connects applications across multiple clouds irrespective of providers. This equips businesses to seamlessly operate no matter the product and encourages greater productivity. Google’s ML technology keeps the multi-cloud secure so that businesses can maximize functionalities.
All areas of GCP data processing have AI integration so businesses are gaining ongoing and wide-reaching insights. Both for evaluating opportunities through to projecting outcomes, the Google novel analytics use AI and ML for robust functionalities. What’s more, Google data centers are all over the world so businesses have almost water-tight data access.
Another phenomenal leap Google makes with AI in GCP is just how multimodal the technology is now. Whether building and deploying AI models or using the in-built pre-trained ML APIs like vision or NLP API. Overall the Google AI principles are founded on open-access so businesses can feel confident about access and technical innovation. What’s more the AI functionalities mean that marketing team members as much as IT team members can be using tools. For instance, users can give GCP voice prompts and receive a high-quality image mockup. Another option is other team members using Google App Engine (GAE) for cloud-native development.
Finally, GCP equips businesses to achieve new heights in how they operate, their products, and how their team works. Enhanced productivity, digital transformation, cutting-edge tools, qualitative and quantitative data insights, and reliable automation are core features of GCP with AI. Therefore businesses can confidently work towards a roadmap strategy for pivoting into new markets or bringing in new talent. Furthermore because GCP works everywhere, they’re no longer limited to a local recruitment pool. With AI accessibility functionalities for language and access, the best workers are just an internet connection away.
Additionally GCP is designed to be scaled so businesses can keep adding new products as they grow. For example, they can bring add on newly-launched programs through to delving into AI insights. As they advance, their GCP is ready for them to keep advancing and they won’t get left behind.
In conclusion, GCP will likely remain at the forefront of public cloud solutions as we progress further into the 2020s. Unquestionably Google has demonstrated the scope and intelligence of its products for over two decades. Though it’s possible that the market will shift dramatically as AI diversifies in the global market, cloud infrastructure is immovable.
In order to support businesses to receive end-to-end GCP solutions, the A3Logics software development team are platform specialists. When businesses are ready to start planning their GCP migration or even a hybrid-cloud solution, A3Logics unlocks Google’s power. Beginning with a comprehensive consultation, businesses can see how a GCP migration, integration, and security advance their strategic growth. Overall, working with software development experts ensures that businesses hit the ground running with GCP and maximize product functionalities.
Though Google Cloud is also a cloud product, Google Cloud Platform (GCP) is its own suite of cloud products. In fact, sometimes Google uses the terms interchangeably when discussing other free Google products like Google Drive and Gmail. Nevertheless GCP is its own product range and despite some products being free, it is an enterprise-level cloud offering.
A software development company will always have an important role in businesses deriving the most technical and financial cloud value. Because these software development teams will have experience with the chosen cloud solution their objective is businesses comprehensively leveraging products. Therefore they’ll actually help businesses through evaluating needs then making product recommendations and end-to-end solution design. Accordingly they will oversee configuration, migration, deployment, and Google Managed Services. Furthermore their GCP product suite certifications result in devising and delivering solutions for high-volume production environments. It’s important to remember that these certifications equip them to achieve this whereas normal IT team members can’t do this. Start with an A3Logics software development team consultation where they’ll discuss your business and what your aims for GCP are.
Currently AI functionalities are already being introduced or scheduled for integration to the GCP product suite. Accordingly this means conversational and GenAI features in databases through to text-to-image AI in creative programs. Undeniably Google’s vision of making AI available across the entire GCP range contributes massively to digital transformation. Not only can businesses access this technology now but also it means the AI is being rapidly finessed.
At present GCP reports that over 70% of GenAI unicorns are Google customers. Currently, major customers include Goldman Sachs and Spotify — two massive global brands with dynamic business models. Because Google’s technical expertise, long-term contributions to machine learning and AI, and an integrated business model are so user-oriented, they’re continually the go-to with businesses of all sizes.
